{"as_of":"2026-08-13T11:22:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e2c87d758edbbecdf429d87d3ef4ad381d1e286378728d04a5f8b74658dae8b7","coverage":[{"denominator":120,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T05:46:59.066791Z","state":"measured"},{"denominator":100,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":100,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2412.17165/citation-record","integrity":"/paper/2412.17165/integrity","json":"/paper/2412.17165/citation-record.json","paper":"/paper/2412.17165"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.684048Z","title":"Text summarization sota experiment","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.684048Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:27800d89dfab4db8c0f2a33b563a4444961c0713ce216a620b6b60664ed9a664","observation_id":"353231dd-18ea-4722-a2c9-59d894fc315a","resolution":{"observed_at":"2026-08-11T05:46:58.684048Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.688723Z","title":"World report: Citable documents, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.688723Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:7a666b1407a088f7eb1223204d9e1f5e08f826739465e91eb929359c74787660","observation_id":"5a1da1fb-5e8d-4924-a828-1dc01d793f75","resolution":{"observed_at":"2026-08-11T05:46:58.688723Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.692860Z","title":"Report of all scientific articles on covid published from 2015 to 2024","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.692860Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:72148838a5530f24379ba72e3e0fce36ce96e5ee56e65ab612665dd502e1f6c0","observation_id":"bd32f8e7-5efe-498c-9d2e-32c45ba1d366","resolution":{"observed_at":"2026-08-11T05:46:58.692860Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.697196Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.697196Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:d32338245613c8ef275d8558900fe00509ddcb47df9d8213269a54313d16309e","observation_id":"22a9bd21-1b1c-428d-96c0-30afb1130e3a","resolution":{"observed_at":"2026-08-11T05:46:58.697196Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.701251Z","title":null,"venue":null,"work_id":null,"year":1958},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.701251Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:b66e0521721ffebe7d35e55bc9c3d37f0b39128da75286144e026972c1090748","observation_id":"4742749e-deb2-44b5-b3d0-d619ff364423","resolution":{"observed_at":"2026-08-11T05:46:58.701251Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.706018Z","title":"Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.706018Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:3e8e4eab78d253233e5a3766d23f1df0a982eb70addf063a453a66b328d0f178","observation_id":"2e8f6691-8639-4baf-8b22-4e26404e3d8a","resolution":{"observed_at":"2026-08-11T05:46:58.706018Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.710277Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.710277Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:865b26543f923279dd4848202e386933e96f9b2de40096f9b3d4698b46a103a4","observation_id":"e0c746e8-c07d-4777-832b-8e7c3fe49345","resolution":{"observed_at":"2026-08-11T05:46:58.710277Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.714039Z","title":"Peters, and Arman Cohan","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.714039Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:f28a60c6e4504de3d69177c7d13d48f4443008375d620b1efae44a7d06e96daa","observation_id":"26e2a130-9d0b-493a-8fd3-69e4e7b83f93","resolution":{"observed_at":"2026-08-11T05:46:58.714039Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.717448Z","title":"Big bird: Transformers for longer sequences","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.717448Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:88c79d8f6855e26ca9346e35c6da22330637d1fe00ef4dc9c725a07bb24dace7","observation_id":"f19ba97d-c80c-4b78-80d8-c0c6a83dd579","resolution":{"observed_at":"2026-08-11T05:46:58.717448Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.720986Z","title":"Longt5: Efficient text-to-text transformer for long sequences","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.720986Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:0c22fd0a21ab8e6870f7eb667ccc9f32bbb122902e4686122c1a8238046c62bc","observation_id":"25c02cc3-2cf0-4078-a110-7175eec2cb21","resolution":{"observed_at":"2026-08-11T05:46:58.720986Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.725599Z","title":"Gomez, Łukasz Kaiser, and Illia Polosukhin","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.725599Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:096918da5ff7ec053df23327f9d289ffdb742e870b8b3c56490eb28096b17ebd","observation_id":"150ac847-3624-4354-adcf-d7e43041103f","resolution":{"observed_at":"2026-08-11T05:46:58.725599Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.729669Z","title":"Bert: Pre-training of deep bidirectional transformers for language understanding","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.729669Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:af93bdad4ded1997d5d65d0bea0a64d5a7bd671c6325bba1262ce2484d24cb8b","observation_id":"896e0915-5384-4fdd-a0e3-259ff1cd3565","resolution":{"observed_at":"2026-08-11T05:46:58.729669Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.733379Z","title":"Primera: Pyramid-based masked sentence pre-training for multi-document summarization","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.733379Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:754bd675fc85d44adad77a125502d3f1716467561f0fa9209034465d9541c35e","observation_id":"df267f3f-03c4-4faa-942b-a9eb5090057d","resolution":{"observed_at":"2026-08-11T05:46:58.733379Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.737083Z","title":"Antognini and B","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.737083Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:7a73eb4656d8999e4e2804d3968a03e828258d98a33a9af23afdd680d7b304f9","observation_id":"cf33f31b-16aa-48dd-84d5-219badd09329","resolution":{"observed_at":"2026-08-11T05:46:58.737083Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.740991Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.740991Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:7920b3e663ea0dad7e65bb7b46b7cf29e5339391a185bf818cd549298968d26a","observation_id":"21bf5a07-dd94-4677-8f44-3ac6a935849f","resolution":{"observed_at":"2026-08-11T05:46:58.740991Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.744799Z","title":"Yasunaga, R","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.744799Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:0e73f4649c5ec1f8f0a9106392b4465c8c392be1c7a592bc9b8aba8b0707ab16","observation_id":"825e47cd-398f-41dc-a4c8-8098d15bce00","resolution":{"observed_at":"2026-08-11T05:46:58.744799Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.748327Z","title":"Song, Y .-S","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.748327Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:1677b76fd6bb547148101b726f7309374835e2befc0b2ba229b05d2e3b803202","observation_id":"488db030-195c-4083-b508-b7af7ed980ee","resolution":{"observed_at":"2026-08-11T05:46:58.748327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.752076Z","title":"Efficiently summarizing text and graph encodings of multi-document clusters","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.752076Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:75a43cb17bcf62b14acab9653f40c27e99df0f7340ef89009cbcd6dd381769b7","observation_id":"ae528bdd-9041-4223-abf4-9a7d961747b3","resolution":{"observed_at":"2026-08-11T05:46:58.752076Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.755626Z","title":"Learning to extract coherent summary via deep reinforcement learning","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.755626Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:84e4ebb8e0448d5e96ccc045c855f448bf86a85fcc163b4a8df92080dd65cbc2","observation_id":"f5239014-4a20-4f3b-9b7e-8c4c921a8f17","resolution":{"observed_at":"2026-08-11T05:46:58.755626Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.759348Z","title":"Banditsum: Extractive summarization as a contextual bandit","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.759348Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:1b337c91574a1f64a4b641b8205a06cfbd064ce036325c4276d6ed2e1536baac","observation_id":"625b1f4e-4d3a-4c29-bdd2-849879a61516","resolution":{"observed_at":"2026-08-11T05:46:58.759348Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.762932Z","title":"Neural document summa- rization by jointly learning to score and select sentences","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.762932Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:05820cbadc91987792aefb886f93180241ea3239e0640db46a47bad447015e52","observation_id":"6bb241cd-0f54-4a45-aa59-6f4e9cf9f0fd","resolution":{"observed_at":"2026-08-11T05:46:58.762932Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.770290Z","title":"Neural latent extractive document summarization","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.770290Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:8c71b1a5190c9ac5ee23a19c716bb821a96bdc1cc6925c12c6626ae1d4ac977a","observation_id":"fff0fa95-ec67-4b4d-b923-5191c7741a51","resolution":{"observed_at":"2026-08-11T05:46:58.770290Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.773807Z","title":"Cohen, and Mirella Lapata","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.773807Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:32baa058773d4cef9648ede379f04241a1bcfa25a967e2ccf2d0174bcc6f7bd5","observation_id":"86627f57-8de4-42c8-85bb-e8f812ae17ba","resolution":{"observed_at":"2026-08-11T05:46:58.773807Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.777349Z","title":"Williams","venue":null,"work_id":null,"year":1992},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.777349Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:e578c616666be2ed1b1496daff1c793b39481d28a7fdb3a67e9754ffc197ab39","observation_id":"91bb26c8-5f0a-4be8-aaa0-aefaaf7fd90a","resolution":{"observed_at":"2026-08-11T05:46:58.777349Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.780822Z","title":"Neural extractive text summarization with syntactic compression","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.780822Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:e73a7788767db0f726540feb7672aa08b248ae8dbb96a7d95185135da8d5d09c","observation_id":"fa489f2c-27f5-4384-8577-334198b0f70f","resolution":{"observed_at":"2026-08-11T05:46:58.780822Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.784495Z","title":"Strass: A light and effective method for extractive summarization based on sentence embeddings","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.784495Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:a544783c0420a07151ab37ed4db325c91de3db9ff7cff974234b3a5cfc6498a0","observation_id":"a307b5bf-2c63-4be1-88fb-877281063fcb","resolution":{"observed_at":"2026-08-11T05:46:58.784495Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.788263Z","title":"A novel extractive multi-document text summarization system using quantum-inspired genetic algorithm: Mtsqiga","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.788263Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:94189aa9095a7d0fb7205d391cc7789d62720226b1a97ed9d3be936b26293d61","observation_id":"9f4f8761-da18-4bb5-94be-11e8d5d3b66b","resolution":{"observed_at":"2026-08-11T05:46:58.788263Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.791897Z","title":"Alguliev, R.M","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.791897Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:0d359f876d0b7e309a9c4514bd2cc8a5128d89113f778aed0e34491d08d367b8","observation_id":"68c58e78-13d9-4bff-9bae-4919a5b73869","resolution":{"observed_at":"2026-08-11T05:46:58.791897Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.795586Z","title":"Alguliyev, R","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.795586Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:feaa12fa62abf75c3bd8eef102e456b8128d2d333d6792641f2636be2686511c","observation_id":"d33e32c5-c0f1-49aa-b50d-556512afef9e","resolution":{"observed_at":"2026-08-11T05:46:58.795586Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.799122Z","title":"Alguliyev, R","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.799122Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:df44ddc5fdc03882ed931cde7f3a8c90caba3bf57996678186eaafe064924cf8","observation_id":"76b21e75-5eac-4db9-9f1d-70c44ec7716a","resolution":{"observed_at":"2026-08-11T05:46:58.799122Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.803068Z","title":null,"venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.803068Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:964149082c4472f4b6c22d45e2eaa723b1295fa4c4b3abed48f2c270a62131ab","observation_id":"98bd759a-adee-4cb5-8b42-ae6152adfce4","resolution":{"observed_at":"2026-08-11T05:46:58.803068Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.806946Z","title":"Alguliyev, R","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.806946Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:8bb75d81d10bce01f238f4a2b5ecc4ed8a82158bc291631b4315459117877525","observation_id":"64be9a48-9fdf-45f1-ac5c-920fa49ff951","resolution":{"observed_at":"2026-08-11T05:46:58.806946Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.810711Z","title":"Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.810711Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:bdfeb7952afc4c5d5944fa351a1e624d1d30c0197c9a0fd4cc7e5898e9c28e2d","observation_id":"fd499467-b5e0-4fe0-a29a-7720561f68e6","resolution":{"observed_at":"2026-08-11T05:46:58.810711Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.814330Z","title":"Abstractive text summarization using sequence-to-sequence rnns and beyond","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.814330Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:59f72dacd58ac65b518e7e12a279f325bc367d81ff4b9d1b6f79ae35c5036159","observation_id":"d6eb8714-3b2e-48a6-807e-24377d58ead6","resolution":{"observed_at":"2026-08-11T05:46:58.814330Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.818734Z","title":"Newsroom: A dataset of 1.3 million summaries with diverse extractive strategies","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.818734Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:e55cfa1ab06172d8497200154d3c8b20d1998d45a9834f124b8e65287a58bbbc","observation_id":"cc09e84c-8982-4488-be40-07a74e2f5325","resolution":{"observed_at":"2026-08-11T05:46:58.818734Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.822615Z","title":"Narayan, S","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.822615Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:8839c8742bda3c1dfc72c3247447350e25bdd3c9ddc10e3c91193d7b3ef6ab89","observation_id":"aeefb43b-950f-48aa-83bd-f98d2478b6cb","resolution":{"observed_at":"2026-08-11T05:46:58.822615Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.826454Z","title":"An entity-driven framework for abstractive summarization","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.826454Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:588abea881d7923bf0cb01022a2fa399a5445f51983e4bd3e0ba8841fb834ea3","observation_id":"e4c2ea52-6884-476c-9ac0-ab0056262555","resolution":{"observed_at":"2026-08-11T05:46:58.826454Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.829947Z","title":"Hierarchical transformers for multi-document summarization","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.829947Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:169193fcd04d686c828d21d5d956f34cbfbe8e165d348fd999e94516e31ce287","observation_id":"d544e580-3dd8-46e6-88ce-4dd60d6410c4","resolution":{"observed_at":"2026-08-11T05:46:58.829947Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.833695Z","title":"Text summarization with pretrained encoders","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.833695Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:02a8242184ba5978ddc609c4fa73207d1dbb9ad1e4f1132af954efcb8397d1ed","observation_id":"e42b3dc7-c547-4836-837c-932972dd9bf3","resolution":{"observed_at":"2026-08-11T05:46:58.833695Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:47:00.125848Z","title":"Liu, and Christopher D","venue":null,"work_id":"15635d0c-c705-4ecf-b522-84e30fcc6c8c","year":2017},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.837270Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:230c9e2b871c2b9160ffb1b720c733c957880ee80134d954cfd66e2d21c17e08","observation_id":"16b3f720-a8e5-46e3-94ef-16830c5638ed","resolution":{"observed_at":"2026-08-11T05:47:00.130058Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:47:00.113619Z","title":"Cohan, F","venue":null,"work_id":"d85f1027-2c48-49aa-b8d5-62c8fcc6f9ed","year":2018},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.840781Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:67749d27dc11ffe05d377791c66214e5cb7dc3f72eefdec39602d934c8c52b71","observation_id":"453d4c9b-005b-434d-848c-09b1141ed9e5","resolution":{"observed_at":"2026-08-11T05:47:00.118129Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:47:00.101258Z","title":"Soft layer-specific multi-task summarization with entailment and question generation","venue":null,"work_id":"4d04a418-00a9-423d-819b-88f011107579","year":2018},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.844290Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:e951e7b74b626979525e611f2be4f6c86577c7c861ed832c15d9dd90878a8b58","observation_id":"c250905f-9a5c-430f-9151-b50d720a775e","resolution":{"observed_at":"2026-08-11T05:47:00.105549Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:47:00.089507Z","title":"Improving abstraction in text summarization","venue":null,"work_id":"a753e6cb-2892-47b1-9c76-0e88bf874e6b","year":2018},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.848035Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:50beaa4aed8be29bd1c14afc66ba2864a25b1aa1eac80a357c7ef0da0b016e6d","observation_id":"40fb2390-20a9-418d-876d-57c7d67dad90","resolution":{"observed_at":"2026-08-11T05:47:00.093653Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:47:00.075936Z","title":"Raffel, N","venue":null,"work_id":"d8558a1f-73fd-404e-8117-4cd14618403f","year":2023},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.851407Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:eadba547f9ea932cf9d09d3e1d5a20b32950a976f8ff1cbd3c8c984e5619a730","observation_id":"fed40d47-fbd9-40e3-b07d-1c9c9add38cf","resolution":{"observed_at":"2026-08-11T05:47:00.080291Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:47:00.061383Z","title":"Distillation knowledge applied on pegasus for summarization, 2019–2020","venue":null,"work_id":"22423ac1-4873-47ab-820c-f0ec26636c8e","year":2019},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.854886Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:ba1e291b148e10d61a1fff866abd0524febb206ec88e671d73e79c4d1d7de9ab","observation_id":"5ec93ba8-311e-44bc-a484-d392cdac4c4f","resolution":{"observed_at":"2026-08-11T05:47:00.066680Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:47:00.046437Z","title":"Faithful to the original: Fact aware neural abstractive summarization","venue":null,"work_id":"fb7d97f4-4f35-4c93-82d4-5f6699904d93","year":2018},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.858325Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:93b8e63c0d30ff7647b3a62f3e347ae3bc392c88ad079e85107db71955510fdf","observation_id":"315d0e98-09b8-4bd1-b49c-57e95b47eb6a","resolution":{"observed_at":"2026-08-11T05:47:00.052738Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:47:00.028952Z","title":"Liu, and Mohammad Saleh","venue":null,"work_id":"1cf1b96e-cd89-4c65-b3c7-c1310c789a11","year":2019},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.861676Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:5c64b0523f211de36b423a5dff2fdbe4ad9ca32071558c4da5ca73579a38868d","observation_id":"64c412e2-92af-408e-adb3-07c9c896dc1b","resolution":{"observed_at":"2026-08-11T05:47:00.034772Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:47:00.011230Z","title":null,"venue":null,"work_id":"0099ef23-dea6-4cdc-86db-a08379b0c754","year":2019},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.864862Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:e78e9114715f9fe6498202ef891ee63e4a59f639ba8e3a0da861b5196fb727e0","observation_id":"794e48dd-26b9-46dd-852f-54ad1f373e46","resolution":{"observed_at":"2026-08-11T05:47:00.016138Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.994130Z","title":"Neural text summarization: A critical evaluation","venue":null,"work_id":"aeb3ce71-2c1d-4ac1-b2e0-c22b3dc6db60","year":2019},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.868377Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:d8abe1ad7306ac15be743416c094d74a7883726f2309a43248e4d56c14038a1d","observation_id":"a7cd131b-9b07-4a85-8cc5-1b50ee5f21b3","resolution":{"observed_at":"2026-08-11T05:46:59.998779Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.871763Z","title":"Long short-term memory","venue":null,"work_id":null,"year":1997},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.871763Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:47b9f044f0937e12b8c440a5e30f92228158e2f2399ff21b1157ba73ba965a9f","observation_id":"f954d62f-2f72-4465-87dc-6a867c818ce6","resolution":{"observed_at":"2026-08-11T05:46:58.871763Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.974525Z","title":"Review summarization with pointer gen and bert, 2020","venue":null,"work_id":"9959eaaa-2949-498f-8e84-668efe07c95f","year":2020},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.875556Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:14332519ba07e4ef95fe030e60d0925cfdda6bbb46c262cd33fd87e04f479f41","observation_id":"12b07d45-9069-465b-a2e7-9d1e46fdad8f","resolution":{"observed_at":"2026-08-11T05:46:59.978753Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1705.04304","last_updated":"2017-11-13T20:11:26Z","snapshot_observed_at":"2026-08-09T04:03:30.544666Z","submitted_at":"2017-05-11T17:39:35Z","title":"A Deep Reinforced Model for Abstractive Summarization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1705.04304","snapshot_observed_at":"2026-08-11T05:46:58.879109Z","title":"A deep reinforced model for abstractive summarization","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.879109Z"},"links":{"cited_paper":"/paper/1705.04304","citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:9052514741b941c451c36e814384d0a42b7ce231f367fa04597127e9d4b8c256","observation_id":"a8f46f5e-ceba-4781-ba92-007f4ac36cb0","resolution":{"observed_at":"2026-08-11T05:46:58.879109Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.962790Z","title":"Multi-reward reinforced summarization with saliency and entailment","venue":null,"work_id":"7e041e93-584a-469a-baf9-f0684f684a4a","year":2018},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.883213Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:32455136a6713725bf77482747ff5aae61db88d02092b81d6f2e197f650dc758","observation_id":"34e09012-850f-4417-abc8-f11ce0e9e264","resolution":{"observed_at":"2026-08-11T05:46:59.966906Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.950830Z","title":"Closed-book training to improve summarization encoder memory","venue":null,"work_id":"ed28dbb5-9e7c-48f1-bbd2-18553ea686b9","year":2018},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.886794Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:3b8427d5f478333e8bec66bbc8daab56fad062ea4a45b38050ce22bf523221c4","observation_id":"badc18f7-fb6f-4580-a0a7-22a66d5ec0cb","resolution":{"observed_at":"2026-08-11T05:46:59.955000Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.938542Z","title":"Ziegler, Nisan Stiennon, Jeffrey Wu, Tom B","venue":null,"work_id":"a05ce457-1163-461c-b3de-7ecb07ccd4f6","year":2020},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.890457Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:f98e7fb2cfe066ceef8c422351519453ccb66504c5f58c5844fb2bd595d4665b","observation_id":"79b06991-64bd-4b2c-8ba5-951aab5e35c4","resolution":{"observed_at":"2026-08-11T05:46:59.943316Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.926578Z","title":"Unified language model pre-training for natural language understanding and generation","venue":null,"work_id":"43cb526d-597b-4f0b-bea1-a135886c91bf","year":2019},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.893911Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:885775681f0b42da8e1da2fcaca0eb22d318d109c65622a78d17656cd9ddb1c1","observation_id":"f946c8cd-3fb3-4cfe-a2e2-080deb282c38","resolution":{"observed_at":"2026-08-11T05:46:59.930802Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.914899Z","title":"Deep communicating agents for abstractive summarization","venue":null,"work_id":"47ba315c-1e74-41f3-a4e2-67d331a56a8b","year":2018},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.897457Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:b3f175dd2e25cc2e1735b3afaae3a2f4dec15f4cb67ede2fbb4ba860cf059545","observation_id":"c1521ceb-1803-4344-9bce-007a53ca07f7","resolution":{"observed_at":"2026-08-11T05:46:59.918901Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.902407Z","title":null,"venue":null,"work_id":"904ff83b-44b4-48e0-836d-493633a7aa4d","year":2020},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.901030Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:8acae30f40b7abbb7775abb7d73515014e72eb090b25d3bc3231c68c4ac98eba","observation_id":"beabc8a4-6d47-49fb-8e82-d6c16a4d5c8a","resolution":{"observed_at":"2026-08-11T05:46:59.906250Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.891514Z","title":"Fast abstractive summarization with reinforce-selected sentence rewriting","venue":null,"work_id":"a08311d5-670d-48d5-bf07-c631100c0273","year":2018},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.904995Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:6c941c069974823912712491932774c6896ceed35067d8fc6133bc8a4eb32313","observation_id":"a9af3755-6123-488d-8ce5-b2084edb7727","resolution":{"observed_at":"2026-08-11T05:46:59.895146Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.880577Z","title":null,"venue":null,"work_id":"bd1d36c4-c66d-4d44-80c6-226fbdd9f473","year":2018},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.908719Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:2c9b3a7b61289efedf223c8f018fab25e7498319094395ffd99304651bf071ca","observation_id":"6c9cfd59-bf29-4ed3-97db-cb680dfa3ae6","resolution":{"observed_at":"2026-08-11T05:46:59.884210Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.867878Z","title":"A unified model for extractive and abstractive summarization using inconsistency loss","venue":null,"work_id":"bad3512f-7259-44d9-84da-1a0a08de23ce","year":2018},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.912460Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:b9606dc0805728691648543503e3dc1871eb8d1396d948e77d132c277663e88e","observation_id":"9bad44f4-faaf-4c85-90dc-e6273e13b67c","resolution":{"observed_at":"2026-08-11T05:46:59.872702Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.855608Z","title":"Improving multi-document summarization through referenced flexible extraction with credit-awareness","venue":null,"work_id":"5a8180a5-0931-47d1-b1cf-f1b97d0046f6","year":2022},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.916279Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:f35b63359fa7de814cd4cfe92a9dfc98ebcb7f698ae363d93ef703f5a0772ed7","observation_id":"20cfca97-fd87-467a-804f-3bf04c4fb08b","resolution":{"observed_at":"2026-08-11T05:46:59.859897Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.843908Z","title":null,"venue":null,"work_id":"05853a43-444e-4175-b280-45c1f61f1951","year":2020},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.922230Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:e2ae21cbc0a282d2d49e5f5ef68ac1e43b4ed51cabee5e436c8402d41705af8b","observation_id":"51823c6a-dec6-48ad-84c0-9a92b5fa28a9","resolution":{"observed_at":"2026-08-11T05:46:59.848024Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.831598Z","title":"Efficient estimation of word representations in vector space","venue":null,"work_id":"d418981f-166f-4ae2-88fc-fe1955693447","year":2013},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.926554Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:0c88fc4eccfc0799a328179dc708c73e561e7672f56907c8586aef83b83acc00","observation_id":"0e330c01-e826-47f7-b68f-ff78e5e16235","resolution":{"observed_at":"2026-08-11T05:46:59.836135Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.819697Z","title":null,"venue":null,"work_id":"c0ca9ca3-2b47-4ab1-940b-c90480357e3d","year":2014},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.930328Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:b6d8e4f4310eea6e1c9be77df2299f6605c2b501aacdf17b45ce7aaec4e49451","observation_id":"2d95a7a4-6c93-41d0-a24e-7562bde86a43","resolution":{"observed_at":"2026-08-11T05:46:59.823890Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.807154Z","title":"An introduction to convolutional neural networks","venue":null,"work_id":"90573281-0a01-415b-b47f-e3ec8df728cc","year":2015},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.934186Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:284628d0ba6521560194653d3da5b80543ebca5b351b65a20d33c708370ae705","observation_id":"34bb39cd-0bdd-42d5-a92a-3fdabbc11277","resolution":{"observed_at":"2026-08-11T05:46:59.811981Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.938434Z","title":null,"venue":null,"work_id":null,"year":1997},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.938434Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:af79bd3c1acdfb7acba2f1b43910188d49cb22fcdadc53f6520fda81f2da5224","observation_id":"d43505cf-6357-40f4-ba16-6b2c37db1820","resolution":{"observed_at":"2026-08-11T05:46:58.938434Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.789537Z","title":"Huggingface","venue":null,"work_id":"025c0746-3940-4d33-8266-dd77e7fbbbf5","year":2024},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.942763Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:190dc1bd559665c44d5d09d47918a072e0d3a77d4c5b76bbdfb55e54486f7fca","observation_id":"14607ad7-ea88-4787-a7ad-c1aceacffd35","resolution":{"observed_at":"2026-08-11T05:46:59.793686Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1703.09902","last_updated":"2018-01-29T16:09:38Z","snapshot_observed_at":"2026-07-06T05:35:39.527105Z","submitted_at":"2017-03-29T06:51:00Z","title":"Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1703.09902","snapshot_observed_at":"2026-08-11T05:46:58.946747Z","title":"Survey of the state of the art in natural language generation: Core tasks, applications and evaluation","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.946747Z"},"links":{"cited_paper":"/paper/1703.09902","citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:16aabf58b8301308fcb4eef517b8bad2eb8dd9091177a94204b76c1a0c19457a","observation_id":"ecd6bc2f-5b25-4cef-b4ac-6d771b91c21d","resolution":{"observed_at":"2026-08-11T05:46:58.946747Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:58.951006Z","title":"Rouge: A package for automatic evaluation of summaries, 2004","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.951006Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:54ec2295d5bc74b0257af0e5cb8397e590e6255ffd50956cc3e143ec5c55ca05","observation_id":"a2be189f-1b86-49bb-b862-c85e63d98910","resolution":{"observed_at":"2026-08-11T05:46:58.951006Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.771535Z","title":"Learning to score system summaries for better content selection evaluation","venue":null,"work_id":"4b77cd4f-cfbd-4d5f-80bf-a69ba4e6c35b","year":2017},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.954904Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:c9b40ed29c99323046ee045666b297a9cafe8bfbd59e314468d83d6db44cbf76","observation_id":"1e79026e-9ce9-427a-aeb8-291b34dfba46","resolution":{"observed_at":"2026-08-11T05:46:59.775540Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1904.09675","last_updated":"2020-02-24T18:59:28Z","snapshot_observed_at":"2026-07-29T15:42:51.774083Z","submitted_at":"2019-04-21T23:08:53Z","title":"BERTScore: Evaluating Text Generation with BERT","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1904.09675","snapshot_observed_at":"2026-08-11T05:46:58.958699Z","title":"Weinberger, and Yoav Artzi","venue":null,"work_id":null,"year":1904},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.958699Z"},"links":{"cited_paper":"/paper/1904.09675","citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:39cec0e1f331e9533aa64399438dbea2751aef6c2dfb2b7a7ef2cc83921e7d74","observation_id":"3b2f3b31-8855-4220-b130-7572027e40e9","resolution":{"observed_at":"2026-08-11T05:46:58.958699Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.760618Z","title":"Meyer, and Steffen Eger","venue":null,"work_id":"4a247495-9ffb-4dc6-ba17-686bb541a9a6","year":2019},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.963340Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:f6f1289ae17893d9831ffc8678d6b43aad376d8f8944268db60f63a537be47b8","observation_id":"c99c3467-77d6-408c-b947-4c3360fa89e5","resolution":{"observed_at":"2026-08-11T05:46:59.764420Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.749335Z","title":"Speeding up word mover’s distance and its variants via properties of distances between embeddings, 12 2019","venue":null,"work_id":"4211007e-dc2c-45ac-a5cc-0513dd18ba7f","year":2019},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.967073Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:6f50664070d7fa6f7524346c571911efe4ddc28111c54b0799be869aeec9a220","observation_id":"10758d3e-05b0-4205-a2d6-43a09cdf36c7","resolution":{"observed_at":"2026-08-11T05:46:59.753511Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.738356Z","title":null,"venue":null,"work_id":"e924cc81-7902-458d-909a-e3ce3a76d2c1","year":2019},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.970968Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:d69d581b4c187b87d43e3688de041d19ab82ec60dc0fdd75a2a3ac62b1bc67aa","observation_id":"ab309c0d-ffb3-4cd0-be90-13190ce929c9","resolution":{"observed_at":"2026-08-11T05:46:59.742129Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.727634Z","title":"Answers unite! unsupervised metrics for reinforced summarization models","venue":null,"work_id":"65a57c3a-28b1-4a8d-9c13-d720a8f322ba","year":2019},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.974536Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:25a4fa8b577f134e25dc14ce68eecebbdedaa273f907dedcd3a9a94dbd9d785a","observation_id":"fa25e71b-f424-44eb-a8df-7331c3b2ea1a","resolution":{"observed_at":"2026-08-11T05:46:59.731562Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2002.09836","last_updated":"2020-11-11T20:09:36Z","snapshot_observed_at":"2026-08-13T01:39:59.785431Z","submitted_at":"2020-02-23T06:21:43Z","title":"Fill in the BLANC: Human-free quality estimation of document summaries","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2002.09836","snapshot_observed_at":"2026-08-11T05:46:58.978075Z","title":"Vasilyev, Vedant Dharnidharka, and John Bohannon","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.978075Z"},"links":{"cited_paper":"/paper/2002.09836","citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:d1f5392140335f8f80345f8b9edf41666c64d01894d4d6122f3e0bec8567171f","observation_id":"c5550f85-0f36-45e4-8260-f013da18b150","resolution":{"observed_at":"2026-08-11T05:46:58.978075Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.716624Z","title":"Supert: towards new frontiers in unsupervised evaluation metrics for multi document summarization","venue":null,"work_id":"a83fab6a-cbdc-4820-8601-148818a5132c","year":2020},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.982129Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:5c591e402a5ca73a1995d509d77d0da231e8a9e4c68df40ca53c5237b4421f86","observation_id":"01c8e5ae-4ebf-4a50-9511-d7f825c7799c","resolution":{"observed_at":"2026-08-11T05:46:59.720655Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.705226Z","title":"Bleu: a method for automatic evaluation of machine translation","venue":null,"work_id":"afc5f02a-0a1a-43a9-904b-10d88e61af8e","year":2002},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.985839Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:d3a859ee7759bb39c6b12b28e1ac0a37c01401ba0e1ea6be0d1d68c16d5bbade","observation_id":"753e29ba-24e1-49e9-a5df-1a50271d0049","resolution":{"observed_at":"2026-08-11T05:46:59.709378Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.693878Z","title":"Chrf: Character n-gram f-score for automatic mt evaluation","venue":null,"work_id":"ca2a5486-da97-4392-aeb1-1dcf0a157e87","year":2015},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.989302Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:e0d8b5d4cd9dcdc74fa14f689abe7d69540350ac1a16421a0d2585cc000a1367","observation_id":"a1808f9b-794a-4a4d-b193-9dbd8b4c2aa4","resolution":{"observed_at":"2026-08-11T05:46:59.697920Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.682831Z","title":"Meteor: An automatic metric for mt evaluation with high levels of correlation with human judgments","venue":null,"work_id":"85c7363e-554a-4185-98c5-492d14bea195","year":2007},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.992870Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:d3c00a57d3b0a56b5cebd7aebf8e4e50480c9cb2ff7050a73141f935a9845524","observation_id":"a89eadb1-52b8-44ea-ba81-421b63855013","resolution":{"observed_at":"2026-08-11T05:46:59.686705Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.671195Z","title":"Lawrence Zitnick, and Devi Parikh","venue":null,"work_id":"2ca7b048-42d5-4088-ba12-ffb3177f5e48","year":2015},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:58.996467Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:7f09976511d077d803d9faa734e913c14106979d2ccf7e7510d1f862f9eee174","observation_id":"51ebb77b-33f0-4b7d-a475-34c6d06e90b1","resolution":{"observed_at":"2026-08-11T05:46:59.675154Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.660213Z","title":"Evaluating the factual consistency of abstractive text summarization","venue":null,"work_id":"b98182e6-e5b6-4e93-8ab3-019d5e7fdcf8","year":2020},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:59.000607Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:1f81882faf325d8a071cb8c3bad8198ca43bc66525584db7228541d48da03bc2","observation_id":"eba0a1df-22b2-44eb-a86f-59918b470948","resolution":{"observed_at":"2026-08-11T05:46:59.664006Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.648965Z","title":"Entity-level factual consistency of abstractive text summarization","venue":null,"work_id":"536c9dab-8104-436e-8bdc-353ed0af49ab","year":2021},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:59.004259Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:5a1fc3a8eb216c5032f799a78979fde0e82c309c63f62905e4804da6366881e4","observation_id":"e4f3e728-7efd-430f-a5b4-5e48f3ca4493","resolution":{"observed_at":"2026-08-11T05:46:59.652994Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.636685Z","title":"Fact-checking","venue":null,"work_id":"b912d9e0-9dc5-46dc-ae49-beab2e6913a4","year":2021},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:59.008224Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:ba085280fed345c6d2131453385f75155ef4d4950cf62e7441c035081e4eee47","observation_id":"34ee355a-ddf5-4d5e-9db9-05ebeb95c43b","resolution":{"observed_at":"2026-08-11T05:46:59.640968Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.624797Z","title":"Fabbri, Wojciech Kry´sci´nski, Bryan McCann, Caiming Xiong, Richard Socher, and Dragomir Radev","venue":null,"work_id":"e268f307-660b-4e5a-b6e5-f55644af0325","year":2021},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:59.012003Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:061cd3bb644daae8b00e3780ff7f5a9a7a685d90670aeafed2e09a423975cfd3","observation_id":"eb253ff8-8fda-4d98-812c-8efb9820e87b","resolution":{"observed_at":"2026-08-11T05:46:59.628845Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2001.09386","last_updated":"2020-04-13T21:47:52Z","snapshot_observed_at":"2026-08-09T23:25:17.078828Z","submitted_at":"2020-01-26T02:08:22Z","title":"Generating Representative Headlines for News Stories","version":4},"cited_work":{"arxiv_id":"2001.09386","doi":null,"metadata_source":"pith","pith_arxiv_id":"2001.09386","snapshot_observed_at":"2026-08-11T05:46:59.266961Z","title":"Generating Representative Headlines for News Stories","venue":"cs.CL","work_id":"df70e9a5-964d-4c95-99fb-c58434b2d219","year":2020},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:59.015526Z"},"links":{"cited_paper":"/paper/2001.09386","citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:1e7b8a5ee57b80dc691c983acbf23f563578c1438f5100d43420aace76471cd7","observation_id":"0f4c6382-a8ca-498f-9d56-960939735722","resolution":{"observed_at":"2026-08-11T05:46:59.271592Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.612798Z","title":null,"venue":null,"work_id":"7ca5bb57-d78c-4260-a4aa-48f721102b28","year":2015},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:59.019665Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:11f0b72b275ef13f2c22d9f7b25495746e962dc886b25ba0f8bf0de8cd2697e1","observation_id":"62785ebf-8006-4648-937b-dd71027d8c1e","resolution":{"observed_at":"2026-08-11T05:46:59.616723Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.601946Z","title":"Newsroom: A dataset of 1.3 million summaries with diverse extractive strategies","venue":null,"work_id":"e37855b4-7923-45fc-9ca4-c02f8a5eadf4","year":2018},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:59.023519Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:9f727e3d82080d3a16896823bceff98a25fa61a36a5ead7a985eceff746d27a3","observation_id":"3367d8c9-55d6-48b1-b110-ec5d0c7d6746","resolution":{"observed_at":"2026-08-11T05:46:59.605675Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.591656Z","title":null,"venue":null,"work_id":"4662373d-e50e-4f71-b2f0-b684a68f46e3","year":2015},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:59.027140Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:e052513371af0da1f25315ebc0bdc59dc1f7da928d8c106606592e9b440da46f","observation_id":"cd59e727-86ae-47ef-bcc5-0e0926a51eab","resolution":{"observed_at":"2026-08-11T05:46:59.595186Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.580446Z","title":"Graff, J","venue":null,"work_id":"a82aeec1-dc50-40af-8581-0ec47bc053f0","year":2003},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:59.031077Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:290bb16ae5b2510203335660c37081c7959fae1160c1d7276a7e736b65672905","observation_id":"2a820a03-ed89-4523-b9b8-89b94b14cae7","resolution":{"observed_at":"2026-08-11T05:46:59.584493Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.569287Z","title":"Sharma, C","venue":null,"work_id":"721c8b64-03a4-44cd-bb28-67708d802353","year":2019},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:59.034919Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:2d709d0e92bbe7396ab6ca0f92603293c8edb66fe484e70de355f97ea72a9587","observation_id":"d6fc6dda-c77d-4403-835f-574161680697","resolution":{"observed_at":"2026-08-11T05:46:59.573101Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1810.09305","last_updated":"2018-10-18T05:29:41Z","snapshot_observed_at":"2026-08-12T08:14:30.190326Z","submitted_at":"2018-10-18T05:29:41Z","title":"WikiHow: A Large Scale Text Summarization Dataset","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.09305","snapshot_observed_at":"2026-08-11T05:46:59.038766Z","title":"Koupaee and W","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:59.038766Z"},"links":{"cited_paper":"/paper/1810.09305","citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:a69a1fb5169b6fe296a122947c2e5c7c071cb28d040437d59e2e30408313a731","observation_id":"9e1a8548-6f0c-4e9a-b41d-d7550234f816","resolution":{"observed_at":"2026-08-11T05:46:59.038766Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.551756Z","title":null,"venue":null,"work_id":"f7b8aabe-2619-4235-90ce-853d64cc728b","year":2019},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:59.043366Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:317474a141a552901f2f7e345456a243ff9d965373c788369468bfd749f9f756","observation_id":"95f43f94-87c7-4dc4-9f81-9c2918bec38e","resolution":{"observed_at":"2026-08-11T05:46:59.561199Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.540237Z","title":"Zhang and J","venue":null,"work_id":"c6def5a5-2749-482a-aad9-5ce97f1a5584","year":2019},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:59.047242Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:bf77216ccde5f533a4a95a1e1dc47004ebb98249af14d8d29ffd943d439b107d","observation_id":"e076b283-07d8-4bb4-9841-cba582478775","resolution":{"observed_at":"2026-08-11T05:46:59.544068Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.527243Z","title":"The enron corpus: A new dataset for email classification research","venue":null,"work_id":"733e4cd5-2d96-4cd4-a9a9-8620a2cf2518","year":2004},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:59.051714Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:4a04afbb59129bb8b3a7836d8345f179a809751e08c90f2e3788bc2cf0dcd90b","observation_id":"d27ed675-d7ba-4264-9307-3774d3f22944","resolution":{"observed_at":"2026-08-11T05:46:59.531171Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.515556Z","title":"Kornilova and V","venue":null,"work_id":"8fc6da04-96eb-455b-bbd5-3b50113020ad","year":2019},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":97,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:59.055326Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:7e1f41b26a47a99cb1952050df8e9fc90218fc342e83f4d46e751afc418d9b5c","observation_id":"d11ce5a1-07d9-44cb-b8ac-4e5cd298d8e3","resolution":{"observed_at":"2026-08-11T05:46:59.519378Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2105.08209","last_updated":"2022-12-06T19:19:35Z","snapshot_observed_at":"2026-08-13T03:28:47.490673Z","submitted_at":"2021-05-18T00:22:46Z","title":"BookSum: A Collection of Datasets for Long-form Narrative Summarization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2105.08209","snapshot_observed_at":"2026-08-11T05:46:59.058964Z","title":"Booksum: A collection of datasets for long-form narrative summarization","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":98,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:59.058964Z"},"links":{"cited_paper":"/paper/2105.08209","citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:c2045f47c9ac733e4708da78a357fd6e225082352de18435764d5f37b9402cb3","observation_id":"ad65ca52-ea6e-40c1-84d8-ead6ce34d98b","resolution":{"observed_at":"2026-08-11T05:46:59.058964Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.503427Z","title":"Efficient attentions for long document summarization","venue":null,"work_id":"63238f80-2271-490c-b6be-b9344a2a308d","year":2021},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":99,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:59.063088Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:3c624daeea8a0590dc8310291bc889d3d060cd88fe522cac44971f7da03b8d0d","observation_id":"0b7d7ce2-dc84-46ac-b407-cc74648724f6","resolution":{"observed_at":"2026-08-11T05:46:59.507650Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:46:59.491359Z","title":"Multi-lexsum: Real-world summaries of civil rights lawsuits at multiple granularities, 06 2022","venue":null,"work_id":"5aec8f0a-e9c6-4d6e-b2e5-a0efc5066d24","year":2022},"citing_paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","version":1},"reference_index":100,"source":"pdf_text","source_observed_at":"2026-08-11T05:46:59.066791Z"},"links":{"citing_paper":"/paper/2412.17165"},"observation_digest":"sha256:0f3f8cb426536cf3ab3aa560453c685d7d7ad7900c1bcd2a616ddee992f6fb83","observation_id":"b681b70d-7443-483a-b87a-b7b028ddd8fb","resolution":{"observed_at":"2026-08-11T05:46:59.495342Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.17165","last_updated":"2024-12-22T21:18:40Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-12T15:03:13.497286Z","submitted_at":"2024-12-22T21:18:40Z","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":57,"verified_exact":1,"verified_fuzzy":42},"total_outbound_references":120},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 100 of 120 outbound references and 0 inbound Pith citation observations for arXiv:2412.17165."}