{"as_of":"2026-07-31T10:42:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4fac0d0270844894d5736eb437e5304193308d7f02a2fda93c7633da55be73be","coverage":[{"denominator":64,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":64,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-07T16:20:50.111108Z","state":"measured"},{"denominator":64,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":64,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-07-31T06:34:12.847434+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/2604.25665/citation-record","integrity":"/paper/2604.25665/integrity","json":"/paper/2604.25665/citation-record.json","paper":"/paper/2604.25665"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A systematic survey of text summarization: From statistical methods to large language models","venue":null,"work_id":"f8b36ae4-9013-46da-a704-797aa58a3d4d","year":2025},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:92e8d40ad9436ac87c7fa136c40aab79e1fa6aaaab5971eddfe85835898cdf03","observation_id":"700b3251-0700-4b84-9e83-646f4860ac7d","resolution":{"observed_at":"2026-05-27T02:18:41.170435Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"A survey on biomedical automatic text summarization with large language models","venue":null,"work_id":"bb76c8a5-d786-47ec-88c0-adfb57236539","year":2025},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:36d4a69923ebf166008fdd0f7d0c572e4f61ba39b703413b094ece8de45a39c6","observation_id":"198765a6-ec37-4605-8b77-397101dd4b8f","resolution":{"observed_at":"2026-05-27T02:18:41.192722Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"A comprehensive survey of abstractive text summarization based on deep learning","venue":null,"work_id":"fea33207-13a9-4db5-9f75-8a020336d09b","year":2022},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:0f1e1dde88cd6488995d1ffade86c497137b57f243069529c6347a753ad2009b","observation_id":"e4b79ff3-f9ce-4318-8fd8-64989b023206","resolution":{"observed_at":"2026-05-27T02:18:41.198600Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.02554","last_updated":"2023-04-05T16:17:32Z","snapshot_observed_at":"2026-07-06T15:12:33.847206Z","submitted_at":"2023-04-05T16:17:32Z","title":"Human-like Summarization Evaluation with ChatGPT","version":1},"cited_work":{"arxiv_id":"2304.02554","doi":"10.48550/arxiv.2304.02554","metadata_source":"arxiv_reference","pith_arxiv_id":"2304.02554","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Human-like summarization evaluation with chatgpt","venue":null,"work_id":"80c135c0-8668-4b8c-b6a3-5a848cee4ed0","year":2023},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"cited_paper":"/paper/2304.02554","citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:ec8c7e8ec50e72787508914c4c6c63c3df557cb965bdbac6ad9620797be9bd14","observation_id":"0dfd8e45-4b92-4d8b-b3ce-17fc499899f5","resolution":{"observed_at":"2026-05-11T23:46:37.680608Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Summeval: Re-evaluating summarization evaluation","venue":null,"work_id":"c64836be-2e0f-41c4-b4d2-b530be51f96a","year":2021},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:be1840c388b9c41ea9ebe229490e5df5032d9029351e252011a450d8406f31df","observation_id":"215bd481-d14e-4618-89ea-74f3bc35dbb3","resolution":{"observed_at":"2026-05-27T02:18:41.188518Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Quality evaluation of summarization models for patent documents","venue":null,"work_id":"a7d1ff15-e728-4fcc-b29a-13a51e011e20","year":2023},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:5331213cd8b4b2856119e624c9899e6c2f4e1e85d00dffff126ab190816b3824","observation_id":"f08a9ffa-3d8d-477f-be59-5a90d81592c1","resolution":{"observed_at":"2026-05-27T02:18:41.204560Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Text summarization using topic- based vector space model and semantic measure","venue":null,"work_id":"9ceaa98b-fa9d-4b55-aabb-0893d99e672f","year":2021},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:22da94cbb49a3ec62d69d5e4c56828a1542d373845d79f3a7004130947d1fc99","observation_id":"0453c651-559f-4b22-b725-0b236c7057f2","resolution":{"observed_at":"2026-05-27T02:18:41.182526Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Candidate sentence selection for extractive text summarization","venue":null,"work_id":"45377191-daf1-4c1d-9db5-a354fa17d3d8","year":2020},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:b617765b2e7ed1cd0afb710e56186328d78885e2c2dc1f84098b5ed25f8e6d72","observation_id":"a67a9cc5-2fe7-401a-9e98-3c77f93640a9","resolution":{"observed_at":"2026-05-27T02:18:41.234859Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Bertscore: Evaluating text generation with bert","venue":null,"work_id":"009218bd-a94a-4b1a-bc30-820afb269464","year":2020},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:788d8470c74ba9a32b61ccb6b3a3ba6196e9ea2b93a95db5768a64602f0e31c2","observation_id":"9ad09f76-aef7-40c3-ba2c-6a70d2e8bba5","resolution":{"observed_at":"2026-05-27T02:18:41.195709Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"A structured review of the validity of bleu","venue":null,"work_id":"6e518e8f-638c-4f38-b60a-0e67f1b1fd80","year":2018},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:a40cfe0086406d05536f44980d1dc294f944d9032e427a94e3f019e15ab2c854","observation_id":"ce774a5f-69fc-42fc-a307-2e3665731f18","resolution":{"observed_at":"2026-05-27T02:18:41.182787Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.12356","last_updated":"2023-05-23T22:52:18Z","snapshot_observed_at":"2026-07-06T13:56:07.502556Z","submitted_at":"2022-09-26T01:04:52Z","title":"News Summarization and Evaluation in the Era of GPT-3","version":2},"cited_work":{"arxiv_id":"2209.12356","doi":"10.48550/arxiv.2209.12356","metadata_source":"arxiv_reference","pith_arxiv_id":"2209.12356","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"J.; and Durrett, G","venue":null,"work_id":"ec749274-c88c-461b-8bea-cc527ad5c047","year":2022},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"cited_paper":"/paper/2209.12356","citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:893b96b239702a7d7ed836c78e84585f69988f88c0978f6c4f400709071b5d29","observation_id":"9f9c09c5-3315-46f4-be12-fc9f5800c2ed","resolution":{"observed_at":"2026-05-11T23:46:38.147101Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Evaluation of question-answering based text summarization using llm invited paper","venue":null,"work_id":"86f81224-975a-41b1-a090-ba341f14def1","year":2024},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:f0282b73634b82de623640f1bb781789e1a5bae0444376b63af6629f372f9c87","observation_id":"81b57119-ace7-483c-a292-52f28322e044","resolution":{"observed_at":"2026-05-27T02:18:41.189670Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.00747","last_updated":"2024-06-30T16:12:37Z","snapshot_observed_at":"2026-07-06T18:39:07.595367Z","submitted_at":"2024-06-30T16:12:37Z","title":"A Comparative Study of Quality Evaluation Methods for Text Summarization","version":1},"cited_work":{"arxiv_id":"2407.00747","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2407.00747","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A Comparative Study of Quality Evaluation Methods for Text Summarization, June 2024","venue":null,"work_id":"15cd69d1-49b8-4b3a-803a-f6067a4711a4","year":2024},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"cited_paper":"/paper/2407.00747","citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:5ea8bc20d9e8fe63f28ea4fb9c013d737be98d91054eacbd948a76ba16610d53","observation_id":"0f63aeba-ef28-44a0-b6cd-1f708121574e","resolution":{"observed_at":"2026-05-11T23:46:38.498781Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.15621","last_updated":"2023-04-13T10:59:39Z","snapshot_observed_at":"2026-07-06T15:08:41.430154Z","submitted_at":"2023-03-27T22:30:39Z","title":"ChatGPT as a Factual Inconsistency Evaluator for Text Summarization","version":2},"cited_work":{"arxiv_id":"2303.15621","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2303.15621","snapshot_observed_at":"2026-07-03T10:37:57.047047Z","title":"Fangrui Lv, Kaixiong Gong, Jian Liang, Xinyu Pang, and Changshui Zhang","venue":null,"work_id":"75a45abd-5fd5-49ee-a177-c3210bca0717","year":2024},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"cited_paper":"/paper/2303.15621","citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:8a5e96eb45ccf94cb36c892996c5e2f3b0d4bdb122e19fa3914f3af41e5e547a","observation_id":"a2af7649-3e4b-4284-91ec-ed5872c8affa","resolution":{"observed_at":"2026-05-11T23:46:39.201774Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-07-05T06:40:46.094093Z","title":"G-eval: Nlg evaluation using gpt-4 with better human alignment","venue":null,"work_id":"c1abbb0e-601e-4547-a3db-a624c25e9cd1","year":2023},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:d0ef4fa3d8bc8987e8d61def9b79ae2875a9a57a4cf7588a4859fe4aa9a647d3","observation_id":"7872ce79-8d75-41e8-b26b-f3b980ad8a0f","resolution":{"observed_at":"2026-05-27T02:18:41.279382Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Causal keyword driven reliable text classification with large language model feedback","venue":null,"work_id":"87df80c5-4cd7-487a-8d41-0750ce92a14c","year":2025},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:b2730006c4ff10cfd47233c5c2dcfd4c4b0e26ef974a4103371274aaa3e5916e","observation_id":"5a35f6db-955a-42c1-be65-0eac73450c43","resolution":{"observed_at":"2026-05-27T02:18:41.285819Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"A comprehen- sive survey on legal summarization: Challenges and future directions","venue":null,"work_id":"e3a35442-76db-4ebf-a38a-c0c97792a408","year":2025},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:e84a629d3c444ddc84ce6c51dbe9120fe552f90ad0d54a2972e7d86869d75cc8","observation_id":"5218224f-612e-4f50-8d49-c379d6cf3fe4","resolution":{"observed_at":"2026-05-27T02:18:41.271691Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Rouge: A package for automatic evaluation of summaries","venue":null,"work_id":"16202959-803f-4958-8e1b-b80fd09702aa","year":2004},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:9741859d7d3143cfdd72f25487413685ffecf2a3f6bcc6d6c946854e02b51c56","observation_id":"239e8610-854f-4e84-b17d-b4de0a7a82ff","resolution":{"observed_at":"2026-05-27T02:18:41.268099Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-07-05T05:10:42.921945Z","title":"Bleu: a method for automatic evaluation of machine translation","venue":null,"work_id":"6ef6c7e1-d7af-4ed2-a958-86a2285b5ebc","year":2002},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:285100e90246f9d330cc90fe554850af371edca1968bcffd50372623c26f3d66","observation_id":"9d0f86fb-6570-48d3-a36f-6ccb505a3897","resolution":{"observed_at":"2026-05-27T02:18:41.275790Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Moverscore: Text generation evaluating with contextualized embed- dings and earth mover distance","venue":null,"work_id":"c8e92aa8-9d8a-471b-99df-0c178bf6e38f","year":2019},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:16f66a16a9a60712ce6b16ed1d70b4b84fa65c0cfc9644a77542fe7491f52924","observation_id":"5714e02a-86a0-4cf6-ad24-26cf2a8f2dfa","resolution":{"observed_at":"2026-05-27T02:18:41.282606Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Summac: Re- visiting nli-based models for inconsistency detection in summarization","venue":null,"work_id":"6b717261-1b08-4e0a-9a61-dfedb9b6d493","year":2022},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:b6370d41e482d940dcc7f10300506c2f5b09607f55280c7f1953197da433b57e","observation_id":"03c01bae-c497-4fbd-88fe-144dd15b3096","resolution":{"observed_at":"2026-05-27T02:18:41.335865Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Questeval: Summarization asks for fact-based evalu- ation","venue":null,"work_id":"0e5c9098-280b-42b4-bb22-8ab48b2800d2","year":2021},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:8793fb652d1342799be3d9f4c8333d77026020af2bf2922806c4bd0655ef13f2","observation_id":"4d829cf8-640a-46ea-8a7e-e9df57bb1a43","resolution":{"observed_at":"2026-05-27T02:18:41.264591Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Bertscore is unfair: On social bias in language model-based metrics for text generation","venue":null,"work_id":"7e73d86b-3892-4387-826e-6ad68666c737","year":2022},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:83fdbfb08fa6936983d820386641d77f1843dbc830017b7b02be4b2ce5696b7a","observation_id":"3071e37d-b4bf-4d96-b2c4-f169e0435793","resolution":{"observed_at":"2026-05-27T02:18:41.238002Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Re- evaluating evaluation in text summarization","venue":null,"work_id":"c4df3e2e-5048-4b0b-a856-617dd15b25e6","year":2020},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:8062815ec0bff89684c943208df65c771b8234c5171acd5895d98aaaf26a9a8e","observation_id":"1bccc801-de93-4f65-ba1e-2b9affc8b7f5","resolution":{"observed_at":"2026-05-27T02:18:41.231119Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"How far are we from robust long abstractive summarization?","venue":null,"work_id":"23111ae2-af23-41f0-86f1-959e33d26877","year":2022},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:257e624d8b8f084e3ab06c777aa3d3266038f45c2938f81cadbd9361849c89db","observation_id":"89d7759a-7245-4626-a7b2-af854323034e","resolution":{"observed_at":"2026-05-27T02:18:41.227768Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Exploring prompting large language models as explain- able metrics","venue":null,"work_id":"2525acac-822e-4e60-b8e0-aca6ebb2cea0","year":2023},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:22e312423f4acdeff87663090debe74702bf2157ac2709634b796536abdc97b0","observation_id":"94881ae8-5615-4668-bf11-a58f7640b2f0","resolution":{"observed_at":"2026-05-27T02:18:41.218489Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"A deep reinforced model for abstractive summarization","venue":null,"work_id":"e59e5f9d-e2bc-4864-8ea3-2cbc7b69f8d2","year":2018},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:b8d2fd587714ce0203b12a35032478e31328826f3a7367d2b5f97e0096bb709a","observation_id":"95ce0384-47b4-48d4-bdc4-96e817783b54","resolution":{"observed_at":"2026-05-27T02:18:41.221562Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"A reinforced topic-aware convolutional sequence-to-sequence model for abstractive text summarization","venue":null,"work_id":"ebf3b39d-662e-4a0b-add9-eae2ab083216","year":2018},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:d25994081aa1e94e9428fa22d9288b226f48238adf782ef1b11cb21a233531d8","observation_id":"76b00e13-c821-418e-a131-9dffb70c1b04","resolution":{"observed_at":"2026-05-27T02:18:41.257558Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.00069","last_updated":"2026-06-23T16:02:17Z","snapshot_observed_at":"2026-07-06T20:44:35.837721Z","submitted_at":"2025-02-27T13:26:07Z","title":"Societal Alignment Frameworks Can Improve LLM Alignment","version":2},"cited_work":{"arxiv_id":"2503.00069","doi":"10.48550/arxiv.2503.00069","metadata_source":"pith","pith_arxiv_id":"2503.00069","snapshot_observed_at":"2026-07-10T12:15:01.137692Z","title":"Societal Alignment Frameworks Can Improve","venue":"cs.CY","work_id":"f6f68ca9-14ec-4117-8f24-e5b170dd13cc","year":2025},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"cited_paper":"/paper/2503.00069","citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:19f1426506132dbdd17f0647270dd67a4a68f73f5026bc18d60a958312cb3a4f","observation_id":"a7874317-ce2a-4983-ae80-dc091dc6bebc","resolution":{"observed_at":"2026-06-24T02:14:45.762172Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Learning to summarize from llm-generated feedback","venue":null,"work_id":"458b9ac7-92d7-4f9b-ab6b-7e01468a97ac","year":2025},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:034465a5db2cbb33114d53d0031f64d2eb2ce4a54e383acde16d335a38da540c","observation_id":"bc59058b-7530-40d4-ad58-e696adab74a3","resolution":{"observed_at":"2026-05-27T02:18:41.234470Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Language mod- 14 els are few-shot learners","venue":null,"work_id":"578563cc-f83a-4c54-b721-39862354abb6","year":1901},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:7291e1ef18f57f78c51ca467280ea210160a8d597267c5729591d39657a46b12","observation_id":"24d39fb9-b39e-4d49-9b3f-694a41ed03bc","resolution":{"observed_at":"2026-05-27T02:18:41.306769Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-07-08T23:05:44.579640Z","title":"Training language models to follow instructions with human feedback","venue":null,"work_id":"6de2065a-afd9-45af-8961-27be26fbd586","year":2022},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:0274dfc8c51d24591da59585f37982a905953156d66e62d3e1a904d8ca75cfd7","observation_id":"d55097d4-59b0-4277-a8b3-506323179e99","resolution":{"observed_at":"2026-05-27T02:18:41.215144Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Large language models are state-of-the- art evaluators of translation quality","venue":null,"work_id":"5644980a-5f46-4d78-8f75-5d6fc0ceb68f","year":2023},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:72d5250dcd6ad54ee4ecacc73ea9cd31b6efb6ebe76926894f1b648d678a7f25","observation_id":"9e3788e3-fa56-4ef3-93e5-2bbf8b2dcda1","resolution":{"observed_at":"2026-05-27T02:18:41.211634Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"The pyramid method: Incorporating human content selection variation in summarization evalu- ation","venue":null,"work_id":"2d92ab2f-ed7a-4a8b-9705-9c97ba4f948d","year":2007},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:96366a8ffc809a5857fd53edcbf581f0dcf16d765539656b3b5cee91cdaacdd1","observation_id":"0349be2d-8d84-4dc3-9b10-505f25f065d2","resolution":{"observed_at":"2026-05-27T02:18:41.254615Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Large language models are not fair evaluators","venue":null,"work_id":"f58afd9f-575c-45d0-8768-d60300c9bcfb","year":2024},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:885c621201a31494e137b7612c211ab3302ca8ed2cdc7faea54251aafcfabee1","observation_id":"bc51b7cb-2544-46cf-8abf-7f665ac80704","resolution":{"observed_at":"2026-05-27T02:18:41.241092Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Improving factuality and reasoning in language models through multiagent debate","venue":null,"work_id":"4c6adf06-7acb-4f77-847e-2fd6f7d2394d","year":2023},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:1d89ea46ae3b9757f309008d5d3ba0d5b7f54eda44b9ffc7a6d51354f85af10f","observation_id":"11beb7a9-3253-4335-8cac-690341f433ab","resolution":{"observed_at":"2026-05-27T02:18:41.267869Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Generating sequences by learning to self-correct","venue":null,"work_id":"57a20e01-84cc-4ed7-85c1-3845f8141e0f","year":2023},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:48b0d6a4ebea298430c874434718bebd56911e043b01f12ce878a7a1a3e0bb11","observation_id":"9eaa0987-2ee1-41b8-92f6-80f33a2a8f3f","resolution":{"observed_at":"2026-05-27T02:18:41.243859Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2212.08073","last_updated":"2022-12-15T06:19:23Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-12-15T06:19:23Z","title":"Constitutional AI: Harmlessness from AI Feedback","version":1},"cited_work":{"arxiv_id":"2212.08073","doi":"10.48550/arxiv.2212.08073","metadata_source":"pith","pith_arxiv_id":"2212.08073","snapshot_observed_at":"2026-07-11T02:47:49.311954Z","title":"Constitutional AI: Harmlessness from AI Feedback","venue":"cs.CL","work_id":"faaaa4e0-2676-4fac-a0b4-99aef10d2095","year":2022},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"cited_paper":"/paper/2212.08073","citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:d052c08ebfd5c3f28674d3227a1570ad6db9c8aecb3d2c6a0162f2fb4fcb55f2","observation_id":"61598f63-b220-4e6f-b843-62912c8715c5","resolution":{"observed_at":"2026-05-11T23:46:38.888781Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-05-22T21:23:21.899952+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-22T21:23:21.899952+00:00","source":"openalex_status_cache"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-07-09T19:56:29.604813Z","title":"Self-refine: Iter- ative refinement with self-feedback","venue":null,"work_id":"2d85cb7a-91d5-43ab-a88f-dace9892814b","year":2023},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:93fef68f568fd2cb432390668029b0cc55ed213c57801570fc20c719a527c705","observation_id":"1216539e-bdc4-4d05-b173-920b66ce80d1","resolution":{"observed_at":"2026-05-27T02:18:41.201654Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"On faithfulness and factuality in abstractive summarization","venue":null,"work_id":"25ce139a-4811-4efa-a9b1-33fd65869fcb","year":2020},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:014f27a506df1117d8d214337174e17a0f4187cb4814415b02bdeb4d353e2297","observation_id":"d54fde71-cb42-4826-ab07-af0a8d33d956","resolution":{"observed_at":"2026-05-27T02:18:41.260859Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Learning to summarize with human feedback","venue":null,"work_id":"33527e0f-22ae-4aa7-8c90-c0bf53f80a93","year":2020},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:20877cf098e858b8a1738c1400e4f6152df6e5dfb80f01882f040c044a991618","observation_id":"41a1a76c-ddc4-4e76-a9d1-4a4fc852f22e","resolution":{"observed_at":"2026-05-27T02:18:41.247077Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Asking and answering questions to evaluate the factual consistency of summaries","venue":null,"work_id":"ff97c41b-8c20-4a60-9265-55b87bf94a25","year":2020},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:a66d80511470932db7f6e3695af1aebf3dab7efe0eb86acb71f43a3b7ed9023c","observation_id":"960b3289-d4ea-49da-808d-0ca9ddc9f387","resolution":{"observed_at":"2026-05-27T02:18:41.264329Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Long document summarization with top-down and bottom-up infer- ence","venue":null,"work_id":"f8af59a2-3bda-463f-b3ed-f51205ebb58e","year":2023},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:4da905ee4da3da0d9f96b8b8f940c709901e3e27ef6e005a9171c9d8925367aa","observation_id":"4cf0bccc-9a9f-4a80-acb2-c948a35bd23a","resolution":{"observed_at":"2026-05-27T02:18:41.257937Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Dyle: Dynamic latent extraction for ab- stractive long-input summarization","venue":null,"work_id":"53c45934-801c-4bfb-9435-99f8c5c58efb","year":2022},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:443d6544f40bee62ca4451cc6588139b140641f9767473dd2c3c3b263f316535","observation_id":"b9e1064c-0c57-4e83-b935-c6277d7c7d8a","resolution":{"observed_at":"2026-05-27T02:18:41.322883Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Bigpatent: A large-scale dataset for abstractive and coherent summarization","venue":null,"work_id":"4fc11e62-b66d-486e-aa14-9c468ed254e9","year":2019},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:cf989ecb3b1b4ca7fb94e260a5dd97a78b84b447670dd22ecfe515cb878c8a76","observation_id":"1371ae96-4f0d-400f-8c3f-760ba8dac6eb","resolution":{"observed_at":"2026-05-27T02:18:41.348589Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-07-05T05:10:42.938550Z","title":"Meteor: An automatic metric for mt evalua- tion with improved correlation with human judgments","venue":null,"work_id":"693b2dbd-04e9-49d5-a476-8379dddbbad9","year":2005},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:eaebe148f9871da80f8a255947651beb77f5df02d7419b4938009be9ce77a15c","observation_id":"b1dab50d-fc90-4f7b-baf2-a8a9657a0d77","resolution":{"observed_at":"2026-05-27T02:18:41.261374Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"chrf: character n-gram f-score for automatic mt evalu- ation","venue":null,"work_id":"c117329d-e056-4677-8fd2-21642d2bc9d0","year":2015},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:c388e7742b5dfb957cb229873cca66e44aecba9d75b66caa117ca0c695a03161","observation_id":"0ef08044-06c7-4937-abe8-bed84608b863","resolution":{"observed_at":"2026-05-27T02:18:41.326304Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Bartscore: Evaluating generated text as text generation","venue":null,"work_id":"da6016a4-86c7-4049-bf12-12d4cab99ada","year":2021},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:b06cb1c37b0a8f728a86569428e13e4c7dd46d01245799cad2f97a2bd32939a0","observation_id":"198a4358-256f-4586-b950-dc16eed3ad0e","resolution":{"observed_at":"2026-05-27T02:18:41.329386Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Answers unite! unsupervised metrics for reinforced summarization models","venue":null,"work_id":"0f8786b5-0f09-4cd4-945a-91848eec671d","year":2019},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:00963063be4230ca59e8faf2bd284092844c086b63e2e74287de3abdf022dc9e","observation_id":"41855178-594f-4173-98c7-3d9c2c9e991b","resolution":{"observed_at":"2026-05-27T02:18:41.342674Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Towards question- answering as an automatic metric for evaluating the content quality of a summary","venue":null,"work_id":"9e0e825c-e561-4ded-8d21-5414e3c4894b","year":2021},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:41a757fecd83166b567d27df2128627f42c1ab142135f629f6697a686d1ffbc9","observation_id":"9549ca5b-2d1e-4c60-a9b5-1ca2aab59c73","resolution":{"observed_at":"2026-05-27T02:18:41.333175Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Fill in the blanc: Human-free quality estimation of document summaries","venue":null,"work_id":"f47199e8-7474-4344-aaaf-500eb7876bcf","year":2020},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:65e0832d260ee50a5ffb5182e4ae51124dcfdcad40a5870b382f154011111358","observation_id":"5b5e1d38-52ae-41f2-92c9-ca49869106bf","resolution":{"observed_at":"2026-05-27T02:18:41.319857Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"The llama 3 herd of models","venue":null,"work_id":"0e6984ac-7e9d-4078-b0b5-00d2daee381a","year":2024},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:dbf645170e18be8e0f1cffeafa6bc59867af1a3e4fcde510ff776f0d6e0db2b1","observation_id":"8b71fce2-93de-4f00-a2ea-a99e10efe53b","resolution":{"observed_at":"2026-05-27T02:18:41.338650Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.10671","last_updated":"2024-09-10T13:25:53Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-07-15T12:35:42Z","title":"Qwen2 Technical Report","version":4},"cited_work":{"arxiv_id":"2407.10671","doi":"10.18653/v1/2024.naacl-long.246","metadata_source":"pith","pith_arxiv_id":"2407.10671","snapshot_observed_at":"2026-07-11T11:50:26.030339Z","title":"Qwen2 Technical Report","venue":"cs.CL","work_id":"a1857881-ab9b-4b80-9b5f-9ae4b5c2566d","year":2024},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"cited_paper":"/paper/2407.10671","citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:2c4b5e7e2a19af8b931f2cb3242fa5856ee1399dda3820a006df320fa843da63","observation_id":"0087a38a-3e74-4f86-866d-a4bf0cc0fbc0","resolution":{"observed_at":"2026-05-11T23:46:38.585625Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.08905","last_updated":"2024-12-12T03:37:41Z","snapshot_observed_at":"2026-07-06T20:05:41.350080Z","submitted_at":"2024-12-12T03:37:41Z","title":"Phi-4 Technical Report","version":1},"cited_work":{"arxiv_id":"2412.08905","doi":"10.48550/arxiv.2412.08905","metadata_source":"pith","pith_arxiv_id":"2412.08905","snapshot_observed_at":"2026-07-11T00:47:43.055842Z","title":"Phi-4 Technical Report","venue":"cs.CL","work_id":"b6274271-7af9-4ee8-993b-ba1ba4205ba8","year":2024},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"cited_paper":"/paper/2412.08905","citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:2e6850242c397ad93572601595309f2413c021c8d623d9cfff963e2320b21208","observation_id":"758ed51d-439c-4b40-a2d2-2a5598d1c275","resolution":{"observed_at":"2026-05-11T23:46:38.302183Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Overview of duc 2005","venue":null,"work_id":"694f228c-ab54-4524-868c-aff55f4ced4b","year":2005},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:14db32318b2df2408187cf7f07a7f4e7a778ee33ee9a642f7b2bd67ab7e6e525","observation_id":"9beaafde-565e-4413-b9e5-fb7ab147acf8","resolution":{"observed_at":"2026-05-27T02:18:41.345621Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"To point or not to point: Understanding how abstractive summarizers paraphrase text","venue":null,"work_id":"93c8c6ea-a597-4f29-b3a7-5ac0713ba4b3","year":2021},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:81abf619a388fc960582cd260127bdb833022e1f98e080372d3f1d1fe181ad73","observation_id":"7281b40e-9bcb-42e4-9ddc-815d29d0e642","resolution":{"observed_at":"2026-05-27T02:18:41.299736Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Billsum: A corpus for automatic summarization of us legislation","venue":null,"work_id":"b92078e6-d089-4203-a97d-e324a8acb546","year":2019},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:4cb777e71c3454e6d1d976c22f883c931c4f1133271d680cae32dbb3dbc52191","observation_id":"cb5ae157-6f1d-4790-be62-6e0bb52e0c7b","resolution":{"observed_at":"2026-05-27T02:18:41.303392Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Chateval: Towards better LLM-based evaluators through multi- agent debate","venue":null,"work_id":"1a0aa4c4-0ca8-499a-aa5e-bb6b7c8f5a43","year":2024},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:2f090bb25e65d9f40c9a8059631ad7499f1e8bab7ba83741e4b6514eeaf6d254","observation_id":"6bd6105b-6233-4113-9df5-b7b4aa46df68","resolution":{"observed_at":"2026-05-27T02:18:41.310153Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"On the emergence of position bias in transformers","venue":null,"work_id":"d46b1746-26b1-478e-a384-d11cdc06101a","year":2025},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:7603c6059cd0d05e3b49a89ca1b9e9415a50bbb831f3711c87d24ca8d6e9e861","observation_id":"c3c63e61-dd18-4774-b9cb-513130350f1f","resolution":{"observed_at":"2026-05-27T02:18:41.313392Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-07-05T10:31:00.823910Z","title":"Towards mitigating llm hallucination via self reflection","venue":null,"work_id":"78327f27-4b91-4279-8305-c87e0af36c2c","year":2023},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:140e0b810c6e37a3c6008f26baee584d9dc6abd4cd13dac1a3bfa0576902bc58","observation_id":"84e97205-6187-4ed7-aefd-598245b8e525","resolution":{"observed_at":"2026-05-27T02:18:41.292467Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Holistic evaluation of language models","venue":null,"work_id":"32d0fdd0-a81b-4748-847c-af5abd4a3aa3","year":2023},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:d65f1b2a7432aa1f0f53e9fc4336a2af55b414a48333166f9c1decaa8509d10b","observation_id":"e657cb2f-1a63-4ba5-8b08-a9f27fc9b69b","resolution":{"observed_at":"2026-05-27T02:18:41.288965Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"The financial narrative summarisation shared task (fns 2020)","venue":null,"work_id":"9bb64afc-a078-4c78-bb07-e6d2ec53ac25","year":2020},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:d7f2951290f2b0d57db464f68e6a9443e7276cd725e4ae7c8a5286c8f60f9d81","observation_id":"4c4196f7-26aa-4c68-8698-379a503abcb0","resolution":{"observed_at":"2026-05-27T02:18:41.295990Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Automatic summarization of scientific articles: A survey","venue":null,"work_id":"eafc7a72-ac83-4f39-a16e-449870290500","year":2022},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:4cabebde90cbce34d89b7f208a818a0f6cb60e96f0d0d37228639cdc6d1956cf","observation_id":"6345f147-0721-44f0-ab4f-51feedcdc332","resolution":{"observed_at":"2026-05-27T02:18:41.316711Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+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":"2026-06-05T21:23:00.469572Z","title":"Prometheus: Inducing fine-grained evaluation capability in language models","venue":null,"work_id":"ddc36733-51c6-4d87-b925-7b6a367223ae","year":2024},"citing_paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-05-07T16:20:50.111108Z"},"links":{"citing_paper":"/paper/2604.25665"},"observation_digest":"sha256:49d2821cf3ca131a2a70a0b7ffdf7739401058e0eecb348b1e3232c4bd651f4c","observation_id":"9ea8e733-597e-4868-ac2d-885cd7f209f6","resolution":{"observed_at":"2026-05-27T02:18:41.351998Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2604.25665","last_updated":"2026-04-28T14:00:09Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T23:11:30.068819Z","submitted_at":"2026-04-28T14:00:09Z","title":"LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation"},"reference_resolution":{"displayed":64,"state_counts":{"malformed_identifier":0,"metadata_mismatch":2,"parse_uncertain":0,"unresolved":0,"verified_exact":6,"verified_fuzzy":56},"total_outbound_references":64},"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":"2026-07-31T06:34:12.847434+00:00","source":"crossref"},{"observed_at":"2026-07-31T06:34:08.642788+00:00","source":"retraction_watch"}],"thesis":"As of 31 July 2026, this Paper Citation Record lists 64 of 64 outbound references and 0 inbound Pith citation observations for arXiv:2604.25665."}