{"as_of":"2026-08-11T07:16:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:fbe5314e4761fc2eea5e0af63cd281dc37b389b12527b66486f1dfab6774d254","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T18:25:09.218457Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-11T21:01:13.131227Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2409.18812","last_updated":"2024-09-27T15:04:39Z","snapshot_observed_at":"2026-08-11T01:10:02.189297Z","submitted_at":"2024-09-27T15:04:39Z","title":"LLMs4Synthesis: Leveraging Large Language Models for Scientific Synthesis","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.18812","snapshot_observed_at":"2026-08-08T18:25:09.218457Z","title":"B., D'Souza, J., and Auer, S","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.15745","last_updated":"2025-02-08T20:37:21Z","snapshot_observed_at":"2026-08-10T11:07:26.239905Z","submitted_at":"2025-02-08T20:37:21Z","title":"On the Effectiveness of Large Language Models in Automating Categorization of Scientific Texts","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-08T18:25:09.218457Z"},"links":{"cited_paper":"/paper/2409.18812","citing_paper":"/paper/2502.15745"},"observation_digest":"sha256:9aacb55b209e92df62a9835c9459ddcc5427340c3a42a3de8075256dc47848ea","observation_id":"7cdb4e3b-c661-47aa-b589-59e9c6351552","resolution":{"observed_at":"2026-08-08T18:25:09.218457Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.18812","last_updated":"2024-09-27T15:04:39Z","snapshot_observed_at":"2026-08-11T01:10:02.189297Z","submitted_at":"2024-09-27T15:04:39Z","title":"LLMs4Synthesis: Leveraging Large Language Models for Scientific Synthesis","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.18812","snapshot_observed_at":"2026-08-02T23:27:38.335219Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2602.13812","last_updated":"2026-05-29T15:27:31Z","snapshot_observed_at":"2026-08-10T06:52:14.249722Z","submitted_at":"2026-02-14T14:52:36Z","title":"DTBench: A Synthetic Benchmark for Document-to-Table Extraction","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-02T23:27:38.335219Z"},"links":{"cited_paper":"/paper/2409.18812","citing_paper":"/paper/2602.13812"},"observation_digest":"sha256:ca09d8b19e26da2336087060e1934b21bb24931b2dc6589fa7a0065c9526d640","observation_id":"abedef3f-27d3-4738-8f91-205dc5605373","resolution":{"observed_at":"2026-08-02T23:27:38.335219Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.18812","last_updated":"2024-09-27T15:04:39Z","snapshot_observed_at":"2026-08-11T01:10:02.189297Z","submitted_at":"2024-09-27T15:04:39Z","title":"LLMs4Synthesis: Leveraging Large Language Models for Scientific Synthesis","version":1},"cited_work":{"arxiv_id":"2409.18812","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.18812","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2409.18812 (2024) Automating Categorization of Scientific Texts using LLMs 23","venue":null,"work_id":"ed8b96ef-231f-4a89-a857-1c6b092bbe5b","year":2024},"citing_paper":{"arxiv_id":"2604.23430","last_updated":"2026-04-25T19:52:21Z","snapshot_observed_at":"2026-07-06T23:09:38.799345Z","submitted_at":"2026-04-25T19:52:21Z","title":"Automating Categorization of Scientific Texts with In-Context Learning and Prompt-Chaining in Large Language Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-08T07:18:25.902898Z"},"links":{"cited_paper":"/paper/2409.18812","citing_paper":"/paper/2604.23430"},"observation_digest":"sha256:2ed3f4993d78eaa61976db40b9089578439b8af833bb291adcbe94f52ce77b32","observation_id":"8214d901-3d1e-47bf-8210-77a789570c8d","resolution":{"observed_at":"2026-05-11T21:01:13.139347Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2409.18812/citation-record","integrity":"/paper/2409.18812/integrity","json":"/paper/2409.18812/citation-record.json","paper":"/paper/2409.18812"},"outbound":[],"paper":{"arxiv_id":"2409.18812","last_updated":"2024-09-27T15:04:39Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-11T01:10:02.189297Z","submitted_at":"2024-09-27T15:04:39Z","title":"LLMs4Synthesis: Leveraging Large Language Models for Scientific Synthesis"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2409.18812."}