{"as_of":"2026-08-08T04:43:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:bc08d4303f2896845243fbb4f07388544b8e666c24e6212a6b2063af1e6ec5d9","coverage":[{"denominator":14,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":14,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T19:49:32.579387Z","state":"measured"},{"denominator":16,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":16,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T10:36:23.222989Z","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":"2026-05-10T05:36:01.989610Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2507.04642","last_updated":"2025-08-06T17:29:40Z","snapshot_observed_at":"2026-08-06T19:40:47.446511Z","submitted_at":"2025-07-07T03:50:59Z","title":"R1-RE: Cross-Domain Relation Extraction with RLVR","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.04642","snapshot_observed_at":"2026-08-04T10:36:23.222989Z","title":"Zheng, R","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.09517","last_updated":"2026-07-02T09:56:45Z","snapshot_observed_at":"2026-08-08T00:15:14.362197Z","submitted_at":"2025-10-10T16:28:43Z","title":"StatEval: A Comprehensive Benchmark for Large Language Models in Statistics","version":2},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-04T10:36:23.222989Z"},"links":{"cited_paper":"/paper/2507.04642","citing_paper":"/paper/2510.09517"},"observation_digest":"sha256:46cbbec92a08d93ac50dc779f6c2c9611163ebf5449a12e71b685d7b90860672","observation_id":"754d3dcd-93db-4b4c-9628-e35e61c1e456","resolution":{"observed_at":"2026-08-04T10:36:23.222989Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.04642","last_updated":"2025-08-06T17:29:40Z","snapshot_observed_at":"2026-08-06T19:40:47.446511Z","submitted_at":"2025-07-07T03:50:59Z","title":"R1-RE: Cross-Domain Relation Extraction with RLVR","version":2},"cited_work":{"arxiv_id":"2507.04642","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2507.04642","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2507.04642 , year=","venue":null,"work_id":"984a2104-af51-4e4f-b424-3ea29041bcb9","year":null},"citing_paper":{"arxiv_id":"2604.18493","last_updated":"2026-04-20T16:43:28Z","snapshot_observed_at":"2026-08-07T12:08:03.856446Z","submitted_at":"2026-04-20T16:43:28Z","title":"Too Correct to Learn: Reinforcement Learning on Saturated Reasoning Data","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-05-10T05:32:23.972335Z"},"links":{"cited_paper":"/paper/2507.04642","citing_paper":"/paper/2604.18493"},"observation_digest":"sha256:f46342abb43d16f32c8ec47e0f2d99cd3d3606e36d2ef550729fcc8d21d4b4fc","observation_id":"d41f4700-3287-4645-9187-33226ff86958","resolution":{"observed_at":"2026-05-10T05:36:01.990762Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2507.04642/citation-record","integrity":"/paper/2507.04642/integrity","json":"/paper/2507.04642/citation-record.json","paper":"/paper/2507.04642"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:49:34.042975Z","title":"Use X to treat Y","venue":null,"work_id":"29ffec2d-e79a-4f90-9895-dfb362c7b789","year":null},"citing_paper":{"arxiv_id":"2507.04642","last_updated":"2025-08-06T17:29:40Z","snapshot_observed_at":"2026-08-06T19:40:47.446511Z","submitted_at":"2025-07-07T03:50:59Z","title":"R1-RE: Cross-Domain Relation Extraction with RLVR","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T19:49:31.912494Z"},"links":{"citing_paper":"/paper/2507.04642"},"observation_digest":"sha256:f0fe3b14c8f7936cc520a44c0b1313bb02d68db0997f4426bf062765109831a7","observation_id":"3fb5e59e-8286-4782-b897-6f8b96f4ca6b","resolution":{"observed_at":"2026-08-06T19:49:34.154641Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:49:33.803352Z","title":"X is hyponym-of Y","venue":null,"work_id":"5d3a93d9-44c5-4aa7-9c03-1b6ff664af73","year":null},"citing_paper":{"arxiv_id":"2507.04642","last_updated":"2025-08-06T17:29:40Z","snapshot_observed_at":"2026-08-06T19:40:47.446511Z","submitted_at":"2025-07-07T03:50:59Z","title":"R1-RE: Cross-Domain Relation Extraction with RLVR","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T19:49:32.066283Z"},"links":{"citing_paper":"/paper/2507.04642"},"observation_digest":"sha256:e5ec876daac66f6f316c371414609beb27037053011d23c271810cedebd102d2","observation_id":"661acfe0-3322-4041-9551-9d5c72af1e5e","resolution":{"observed_at":"2026-08-06T19:49:33.903165Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:49:33.033852Z","title":"The sentence mentions that these antipsychotics are used specifically in the context of women with schizophrenia, implying a therapeutic use","venue":null,"work_id":"7707f034-9f5f-4c3d-b762-19462229f0a1","year":null},"citing_paper":{"arxiv_id":"2507.04642","last_updated":"2025-08-06T17:29:40Z","snapshot_observed_at":"2026-08-06T19:40:47.446511Z","submitted_at":"2025-07-07T03:50:59Z","title":"R1-RE: Cross-Domain Relation Extraction with RLVR","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T19:49:32.475901Z"},"links":{"citing_paper":"/paper/2507.04642"},"observation_digest":"sha256:005e14a58335ef6106df4e2729bb841f8ac03e4b44516e03e663e2e6759bd215","observation_id":"6f4d76df-47a3-4be5-bcec-b59cdfc0ae8a","resolution":{"observed_at":"2026-08-06T19:49:33.126365Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:49:32.799306Z","title":"being treated with,","venue":null,"work_id":"d25f2d02-60a9-4fbd-ad5e-4d88992f0ab2","year":null},"citing_paper":{"arxiv_id":"2507.04642","last_updated":"2025-08-06T17:29:40Z","snapshot_observed_at":"2026-08-06T19:40:47.446511Z","submitted_at":"2025-07-07T03:50:59Z","title":"R1-RE: Cross-Domain Relation Extraction with RLVR","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T19:49:32.579387Z"},"links":{"citing_paper":"/paper/2507.04642"},"observation_digest":"sha256:a8c89660fb8056ae5f8aa36d3946b9f6421425e2a89dca96d88dee0cd6745426","observation_id":"70a2099a-d2df-4908-835b-3d3503bdf940","resolution":{"observed_at":"2026-08-06T19:49:32.884418Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:49:34.309182Z","title":"InProceedings of the conference","venue":null,"work_id":"bf402d47-a635-4eb6-b9b2-c48017f863dc","year":2023},"citing_paper":{"arxiv_id":"2507.04642","last_updated":"2025-08-06T17:29:40Z","snapshot_observed_at":"2026-08-06T19:40:47.446511Z","submitted_at":"2025-07-07T03:50:59Z","title":"R1-RE: Cross-Domain Relation Extraction with RLVR","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T19:49:31.412545Z"},"links":{"citing_paper":"/paper/2507.04642"},"observation_digest":"sha256:b386e6fcc39dccf5821299dffe493dda084e5f3ea8adba8cc865497efe5c7183","observation_id":"9846a3ec-a82b-4d4c-87fc-79ea6cbcd69b","resolution":{"observed_at":"2026-08-06T19:49:34.481507Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.02105","last_updated":"2023-12-09T02:05:05Z","snapshot_observed_at":"2026-08-03T17:11:00.296256Z","submitted_at":"2023-05-03T13:28:08Z","title":"GPT-RE: In-context Learning for Relation Extraction using Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.02105","snapshot_observed_at":"2026-08-06T19:49:31.531164Z","title":"Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, and 1 others","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.04642","last_updated":"2025-08-06T17:29:40Z","snapshot_observed_at":"2026-08-06T19:40:47.446511Z","submitted_at":"2025-07-07T03:50:59Z","title":"R1-RE: Cross-Domain Relation Extraction with RLVR","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T19:49:31.531164Z"},"links":{"cited_paper":"/paper/2305.02105","citing_paper":"/paper/2507.04642"},"observation_digest":"sha256:7c786a8f1be6918c5d602acb95603a82dec7b29621c878ec84976efa46522681","observation_id":"6ba54397-fe78-4232-b59a-9646f8f79f0a","resolution":{"observed_at":"2026-08-06T19:49:31.531164Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.01555","last_updated":"2023-06-09T15:59:18Z","snapshot_observed_at":"2026-07-06T15:22:25.008777Z","submitted_at":"2023-05-02T15:55:41Z","title":"How to Unleash the Power of Large Language Models for Few-shot Relation Extraction?","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.01555","snapshot_observed_at":"2026-08-06T19:49:31.671789Z","title":"Yue Yang, Kaixian Yu, Shan Gao, Sheng Yu, Di Xiong, Chuanyang Qin, Huiyuan Chen, Jiarui Tang, Nian- sheng Tang, and Hongtu Zhu","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.04642","last_updated":"2025-08-06T17:29:40Z","snapshot_observed_at":"2026-08-06T19:40:47.446511Z","submitted_at":"2025-07-07T03:50:59Z","title":"R1-RE: Cross-Domain Relation Extraction with RLVR","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T19:49:31.671789Z"},"links":{"cited_paper":"/paper/2305.01555","citing_paper":"/paper/2507.04642"},"observation_digest":"sha256:906cf846cb49ee1efa42b9e5eeb1cb0a6dbd2148c5f947c8c753a98f68f1324b","observation_id":"0d99eb02-d1ea-4f4a-8389-9b1f984ff5be","resolution":{"observed_at":"2026-08-06T19:49:31.671789Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.14476","last_updated":"2025-05-20T01:37:34Z","snapshot_observed_at":"2026-08-02T01:40:54.187278Z","submitted_at":"2025-03-18T17:49:06Z","title":"DAPO: An Open-Source LLM Reinforcement Learning System at Scale","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.14476","snapshot_observed_at":"2026-08-06T19:49:31.778885Z","title":"X is risk-factor-of Y","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.04642","last_updated":"2025-08-06T17:29:40Z","snapshot_observed_at":"2026-08-06T19:40:47.446511Z","submitted_at":"2025-07-07T03:50:59Z","title":"R1-RE: Cross-Domain Relation Extraction with RLVR","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T19:49:31.778885Z"},"links":{"cited_paper":"/paper/2503.14476","citing_paper":"/paper/2507.04642"},"observation_digest":"sha256:b0558591ff09ae5ee1e9922d82d0cb15498c06aa14e52c4e326af2b092b075df","observation_id":"48da0996-67c6-4b7c-b833-e7241dc2901c","resolution":{"observed_at":"2026-08-06T19:49:31.778885Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:49:33.551197Z","title":"- <e2>prolactin-increasing antipsychotics</e2> is a type of medication or treatment","venue":null,"work_id":"5fddeb01-4cee-4e32-a3aa-0c53435c8ba2","year":null},"citing_paper":{"arxiv_id":"2507.04642","last_updated":"2025-08-06T17:29:40Z","snapshot_observed_at":"2026-08-06T19:40:47.446511Z","submitted_at":"2025-07-07T03:50:59Z","title":"R1-RE: Cross-Domain Relation Extraction with RLVR","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T19:49:32.198329Z"},"links":{"citing_paper":"/paper/2507.04642"},"observation_digest":"sha256:22a96a4acd584e097013979bae457509fb6b4e07fe8e7acef0fd347ae852f753","observation_id":"08449154-a98a-4b5b-8ee3-e4dbcf9e8b6e","resolution":{"observed_at":"2026-08-06T19:49:33.695688Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:49:33.258804Z","title":"- We need to determine if this relation is that schizophrenia leads to or is treated by these antipsychotics, or if it’s some other relation","venue":null,"work_id":"355cac4d-bd33-4ff7-b9a2-05fecee98052","year":null},"citing_paper":{"arxiv_id":"2507.04642","last_updated":"2025-08-06T17:29:40Z","snapshot_observed_at":"2026-08-06T19:40:47.446511Z","submitted_at":"2025-07-07T03:50:59Z","title":"R1-RE: Cross-Domain Relation Extraction with RLVR","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T19:49:32.333377Z"},"links":{"citing_paper":"/paper/2507.04642"},"observation_digest":"sha256:6d10b9fce5ed1691b7e344a98d611c0cf6e5d7e1d98efb2d493f9503a76b5076","observation_id":"67e21e60-ac4e-45af-b105-8b7928559504","resolution":{"observed_at":"2026-08-06T19:49:33.428684Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.03300","last_updated":"2024-04-27T15:25:53Z","snapshot_observed_at":"2026-08-06T14:58:42.911363Z","submitted_at":"2024-02-05T18:55:32Z","title":"DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.03300","snapshot_observed_at":"2026-08-06T19:49:31.256080Z","title":"In Proceedings of the Sixteenth International Confer- ence on Machine Learning, pages 278–287","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.04642","last_updated":"2025-08-06T17:29:40Z","snapshot_observed_at":"2026-08-06T19:40:47.446511Z","submitted_at":"2025-07-07T03:50:59Z","title":"R1-RE: Cross-Domain Relation Extraction with RLVR","version":2},"reference_index":1999,"source":"pdf_text","source_observed_at":"2026-08-06T19:49:31.256080Z"},"links":{"cited_paper":"/paper/2402.03300","citing_paper":"/paper/2507.04642"},"observation_digest":"sha256:4c0432c48cef17eab48d927aa56d67415273e6b648acfc0915b23e607a042a0a","observation_id":"01f709b3-d1cf-47c8-898b-b4623a334699","resolution":{"observed_at":"2026-08-06T19:49:31.256080Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.12024","last_updated":"2023-10-18T14:58:13Z","snapshot_observed_at":"2026-07-06T16:35:07.121479Z","submitted_at":"2023-10-18T14:58:13Z","title":"CORE: A Few-Shot Company Relation Classification Dataset for Robust Domain Adaptation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.12024","snapshot_observed_at":"2026-08-06T19:49:30.917128Z","title":"Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, and 1 others","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.04642","last_updated":"2025-08-06T17:29:40Z","snapshot_observed_at":"2026-08-06T19:40:47.446511Z","submitted_at":"2025-07-07T03:50:59Z","title":"R1-RE: Cross-Domain Relation Extraction with RLVR","version":2},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-06T19:49:30.917128Z"},"links":{"cited_paper":"/paper/2310.12024","citing_paper":"/paper/2507.04642"},"observation_digest":"sha256:8f758b23938881e95e2cbd1ba20b7905778d20d2af6de665695b21271def526a","observation_id":"6d87fd08-508f-4534-86a1-2d0aad383deb","resolution":{"observed_at":"2026-08-06T19:49:30.917128Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.15594","last_updated":"2025-10-19T10:32:43Z","snapshot_observed_at":"2026-08-02T10:23:50.881300Z","submitted_at":"2024-11-23T16:03:35Z","title":"A Survey on LLM-as-a-Judge","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.15594","snapshot_observed_at":"2026-08-06T19:49:31.137537Z","title":"Daya Guo, Dejian Yang, Haowei Zhang, Junxiao Song, Ruoyu Zhang, Runxin Xu, Qihao Zhu, Shi- rong Ma, Peiyi Wang, Xiao Bi, and 1 others","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.04642","last_updated":"2025-08-06T17:29:40Z","snapshot_observed_at":"2026-08-06T19:40:47.446511Z","submitted_at":"2025-07-07T03:50:59Z","title":"R1-RE: Cross-Domain Relation Extraction with RLVR","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-06T19:49:31.137537Z"},"links":{"cited_paper":"/paper/2411.15594","citing_paper":"/paper/2507.04642"},"observation_digest":"sha256:43ad7f877c9ff6d68ca23974a9b1d2bfc0dc80ea9778a9e48814e9135bd18da1","observation_id":"3734e733-76b9-4cf0-a6ca-b28babee851d","resolution":{"observed_at":"2026-08-06T19:49:31.137537Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.03714","last_updated":"2025-07-07T04:11:47Z","snapshot_observed_at":"2026-08-07T16:29:49.116124Z","submitted_at":"2025-03-28T16:23:59Z","title":"Breach in the Shield: Unveiling the Vulnerabilities of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.03714","snapshot_observed_at":"2026-08-06T19:49:31.053849Z","title":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.04642","last_updated":"2025-08-06T17:29:40Z","snapshot_observed_at":"2026-08-06T19:40:47.446511Z","submitted_at":"2025-07-07T03:50:59Z","title":"R1-RE: Cross-Domain Relation Extraction with RLVR","version":2},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-06T19:49:31.053849Z"},"links":{"cited_paper":"/paper/2504.03714","citing_paper":"/paper/2507.04642"},"observation_digest":"sha256:f276b26f7826d65ebb499a9e4619a925c42fe1309fd738f432829394d8f3f523","observation_id":"13eb2014-cd60-4b59-91e4-222656889e8e","resolution":{"observed_at":"2026-08-06T19:49:31.053849Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2507.04642","last_updated":"2025-08-06T17:29:40Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-06T19:40:47.446511Z","submitted_at":"2025-07-07T03:50:59Z","title":"R1-RE: Cross-Domain Relation Extraction with RLVR"},"reference_resolution":{"displayed":14,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":7,"verified_exact":0,"verified_fuzzy":7},"total_outbound_references":14},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 2 inbound Pith citation observations for arXiv:2507.04642."}