{"as_of":"2026-08-07T06:54:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:88c337edd884dd3aad524f9b64965715d62c6fe9c5e91a844c5f4ea4ea744824","coverage":[{"denominator":26,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":26,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T16:12:42.069380Z","state":"measured"},{"denominator":26,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":26,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+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/2507.14374/citation-record","integrity":"/paper/2507.14374/integrity","json":"/paper/2507.14374/citation-record.json","paper":"/paper/2507.14374"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2204.13516","last_updated":"2022-04-28T14:07:25Z","snapshot_observed_at":"2026-07-06T13:04:41.675345Z","submitted_at":"2022-04-28T14:07:25Z","title":"What do You Mean by Relation Extraction? A Survey on Datasets and Study on Scientific Relation Classification","version":1},"cited_work":{"arxiv_id":"2204.13516","doi":null,"metadata_source":"pith","pith_arxiv_id":"2204.13516","snapshot_observed_at":"2026-08-06T16:12:42.504671Z","title":"What do You Mean by Relation Extraction? A Survey on Datasets and Study on Scientific Relation Classification","venue":"cs.CL","work_id":"ef44d48f-4d7a-42c7-973f-919366f574b0","year":2022},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:41.994374Z"},"links":{"cited_paper":"/paper/2204.13516","citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:f750cbe5e7fcb025ea911a4f4c6e54ab6e01b8abdef7b28ce69792ce43b7e568","observation_id":"5e9b9365-efa2-43e1-9107-e2e8f8c1cf33","resolution":{"observed_at":"2026-08-06T16:12:42.508164Z","resolver_source":"local_arxiv","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"}},{"citation":{"cited_paper":{"arxiv_id":"2305.16663","last_updated":"2023-06-15T02:43:12Z","snapshot_observed_at":"2026-08-04T20:08:06.963233Z","submitted_at":"2023-05-26T06:21:01Z","title":"GDA: Generative Data Augmentation Techniques for Relation Extraction Tasks","version":2},"cited_work":{"arxiv_id":"2305.16663","doi":null,"metadata_source":"pith","pith_arxiv_id":"2305.16663","snapshot_observed_at":"2026-08-06T16:12:42.490262Z","title":"GDA: Generative Data Augmentation Techniques for Relation Extraction Tasks","venue":"cs.CL","work_id":"a1186502-5aa5-4f2d-8e91-31fe7b2d2950","year":2023},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:42.002598Z"},"links":{"cited_paper":"/paper/2305.16663","citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:be880631fc0bca1edcce3422454c1dac0abedf960d24fc1b11166e7dc6966f1e","observation_id":"6829a607-28c7-4f0d-91b4-fb8413fee0db","resolution":{"observed_at":"2026-08-06T16:12:42.493788Z","resolver_source":"local_arxiv","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"}},{"citation":{"cited_paper":{"arxiv_id":"2503.23673","last_updated":"2025-03-31T02:36:30Z","snapshot_observed_at":"2026-08-07T00:42:11.983602Z","submitted_at":"2025-03-31T02:36:30Z","title":"WHERE and WHICH: Iterative Debate for Biomedical Synthetic Data Augmentation","version":1},"cited_work":{"arxiv_id":"2503.23673","doi":null,"metadata_source":"pith","pith_arxiv_id":"2503.23673","snapshot_observed_at":"2026-08-06T16:12:42.465884Z","title":"WHERE and WHICH: Iterative Debate for Biomedical Synthetic Data Augmentation","venue":"cs.CL","work_id":"3f6dac31-69df-4063-98ef-fe161024e4f5","year":2025},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:42.010149Z"},"links":{"cited_paper":"/paper/2503.23673","citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:70481237a61538f494f9350cdf8c526cbc9144aa9c83b598d76cc87d8395e52d","observation_id":"4eafe5ad-7a8e-4b4b-abcc-fd1a511c96c9","resolution":{"observed_at":"2026-08-06T16:12:42.469449Z","resolver_source":"local_arxiv","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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2504.08040","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:12:42.435951Z","title":"Can reasoning llms enhance clinical document classification? arXiv preprint arXiv:2504.08040,","venue":null,"work_id":"08cf99f7-d25a-499c-959d-140596a77847","year":null},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:42.017112Z"},"links":{"citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:68dbc701aaf8870286150d857e17fbd7d03052a786d83618209ea9a1aa626977","observation_id":"e7ea1df3-830d-4860-bfca-7fd7124ead2d","resolution":{"observed_at":"2026-08-06T16:12:42.440917Z","resolver_source":"raw_fallback","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"}},{"citation":{"cited_paper":{"arxiv_id":"2407.00497","last_updated":"2024-06-29T17:16:04Z","snapshot_observed_at":"2026-07-06T18:38:59.090751Z","submitted_at":"2024-06-29T17:16:04Z","title":"LLMs-as-Instructors: Learning from Errors Toward Automating Model Improvement","version":1},"cited_work":{"arxiv_id":"2407.00497","doi":null,"metadata_source":"pith","pith_arxiv_id":"2407.00497","snapshot_observed_at":"2026-08-06T16:12:42.350784Z","title":"LLMs-as-Instructors: Learning from Errors Toward Automating Model Improvement","venue":"cs.CL","work_id":"8a6b2e03-614b-4999-9001-03b5aef5ebe3","year":2024},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:42.019984Z"},"links":{"cited_paper":"/paper/2407.00497","citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:9f63e89169186cc94cf6b6c3a6a62e264b5d6d43b4217f832bc551e43194c685","observation_id":"8dfeb7cd-34e3-4a6d-a1d3-df949f79aeda","resolution":{"observed_at":"2026-08-06T16:12:42.354779Z","resolver_source":"local_arxiv","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"}},{"citation":{"cited_paper":{"arxiv_id":"2505.00147","last_updated":"2025-09-10T22:32:09Z","snapshot_observed_at":"2026-07-06T21:17:19.119854Z","submitted_at":"2025-04-30T19:35:46Z","title":"AdaptMI: Adaptive Skill-based In-context Math Instruction for Small Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.00147","snapshot_observed_at":"2026-08-06T16:12:42.023069Z","title":"Adaptmi: Adaptive skill-based in-context math instruction for small language models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:42.023069Z"},"links":{"cited_paper":"/paper/2505.00147","citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:904509bf1421199d276a687770d8c0f8a4f88b354e174f85c1fb92c76be78a66","observation_id":"d5f2a02f-6377-42c9-a5aa-206afb036f1e","resolution":{"observed_at":"2026-08-06T16:12:42.023069Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.12052","last_updated":"2024-05-30T12:03:51Z","snapshot_observed_at":"2026-08-06T18:33:19.554464Z","submitted_at":"2024-02-19T11:11:08Z","title":"Small Models, Big Insights: Leveraging Slim Proxy Models To Decide When and What to Retrieve for LLMs","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.12052","snapshot_observed_at":"2026-08-06T16:12:42.026096Z","title":"Small models, big insights: Leveraging slim proxy models to decide when and what to retrieve for llms","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:42.026096Z"},"links":{"cited_paper":"/paper/2402.12052","citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:b576dd325982f1cc427bbbba1b9c58a02b5fd773500ef46275b6ddf061db9273","observation_id":"74193a09-a47e-469d-a293-1d92eec478bd","resolution":{"observed_at":"2026-08-06T16:12:42.026096Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.17140","last_updated":"2024-06-06T03:59:24Z","snapshot_observed_at":"2026-07-06T18:05:55.328415Z","submitted_at":"2024-04-26T03:41:28Z","title":"Small Language Models Need Strong Verifiers to Self-Correct Reasoning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.17140","snapshot_observed_at":"2026-08-06T16:12:42.029270Z","title":"Small language models need strong verifiers to self-correct reasoning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:42.029270Z"},"links":{"cited_paper":"/paper/2404.17140","citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:be2a86ea930e4a2449cef0a8e6b63aec36bbc87b3ba9d8f6e2dd4665d38701c8","observation_id":"7f8c6c4b-7dab-41a6-9e1e-9e893284199b","resolution":{"observed_at":"2026-08-06T16:12:42.029270Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.09906","last_updated":"2024-12-13T06:45:26Z","snapshot_observed_at":"2026-07-06T20:06:21.957662Z","submitted_at":"2024-12-13T06:45:26Z","title":"Enhancing the Reasoning Capabilities of Small Language Models via Solution Guidance Fine-Tuning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.09906","snapshot_observed_at":"2026-08-06T16:12:42.032360Z","title":"Enhancing the reasoning capabilities of small language models via solution guidance fine-tuning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:42.032360Z"},"links":{"cited_paper":"/paper/2412.09906","citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:f6c2def53815b00fcfae54b0f02cc9304f7a0b1e0e000af8341b749b47c79c61","observation_id":"85b10bc3-ed96-49e5-9542-daf85d2a01bb","resolution":{"observed_at":"2026-08-06T16:12:42.032360Z","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":"10.13026/wwfd-2t39","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:12:42.095245Z","title":"Released May 13, 2024; supports text, audio & vision input","venue":null,"work_id":"d2d302f6-9cb1-4a99-bc00-6cb763be5a65","year":2024},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:42.035523Z"},"links":{"citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:081f74867bce26f12e8d4cf950cb2f72d54dea4c59edb05d95205eba85d370fd","observation_id":"60961659-bfe2-4596-8f27-66a7a6e2464b","resolution":{"observed_at":"2026-08-06T16:12:42.100809Z","resolver_source":"doi","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"}},{"citation":{"cited_paper":{"arxiv_id":"2007.15779","last_updated":"2021-09-16T21:26:07Z","snapshot_observed_at":"2026-08-03T16:32:01.630626Z","submitted_at":"2020-07-31T00:04:15Z","title":"Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2007.15779","snapshot_observed_at":"2026-08-06T16:12:42.038846Z","title":"Domain-specific language model pretraining for biomedical natural language processing","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:42.038846Z"},"links":{"cited_paper":"/paper/2007.15779","citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:755a859f244d1d352353db5b5c00bf3167df4c1c40c170c1706e22d761267e3a","observation_id":"a4a4a07a-3d57-44b4-8036-d74c4364bb3a","resolution":{"observed_at":"2026-08-06T16:12:42.038846Z","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":"2026-08-06T16:12:42.555171Z","title":"Exploring large language models for knowledge graph completion","venue":null,"work_id":"2816766c-155e-46f5-b3bc-97fc33195a9a","year":2025},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:42.042231Z"},"links":{"citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:8e092794d437b84966831c7954175d994701fa00019e5029bbe13b4a9013c113","observation_id":"9e160753-8928-491b-a0a2-eb9892f64f4f","resolution":{"observed_at":"2026-08-06T16:12:42.558557Z","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":"2106.09685","last_updated":"2021-10-16T18:40:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2021-06-17T17:37:18Z","title":"LoRA: Low-Rank Adaptation of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.09685","snapshot_observed_at":"2026-08-06T16:12:42.045338Z","title":"Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Lu Wang, and Weizhu Chen","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:42.045338Z"},"links":{"cited_paper":"/paper/2106.09685","citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:cf4644647252cf4bba793bc25e1bd71aebae882287cb663e7ca9c4404d6b0559","observation_id":"ba5d9492-5ba4-458c-b550-bb5350f41c67","resolution":{"observed_at":"2026-08-06T16:12:42.045338Z","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":"2026-08-06T16:12:42.535424Z","title":"Me-llama: Foundation large language models for medical applications","venue":null,"work_id":"fe1df876-9006-48de-88fd-990beb3cfe57","year":2019},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:42.054970Z"},"links":{"citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:66683c00cf433d8a86c15dad85688fad92c79aae16d940112192194af55e0cb3","observation_id":"f67098be-2084-4d16-93ca-6ecd78884107","resolution":{"observed_at":"2026-08-06T16:12:42.538819Z","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":"2204.10360","last_updated":"2022-04-21T18:39:22Z","snapshot_observed_at":"2026-07-06T13:02:38.535183Z","submitted_at":"2022-04-21T18:39:22Z","title":"Decorate the Examples: A Simple Method of Prompt Design for Biomedical Relation Extraction","version":1},"cited_work":{"arxiv_id":"2204.10360","doi":null,"metadata_source":"pith","pith_arxiv_id":"2204.10360","snapshot_observed_at":"2026-08-06T16:12:42.249971Z","title":"Decorate the Examples: A Simple Method of Prompt Design for Biomedical Relation Extraction","venue":"cs.CL","work_id":"7b0d8e3e-7014-4350-9131-45192d283b06","year":2022},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:42.060856Z"},"links":{"cited_paper":"/paper/2204.10360","citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:c5924e54b7a0fc78164445f03c45b4599cd095cc51d5df6a0bd3ab0a9dec588b","observation_id":"071ec9ce-f705-4efb-b24a-f0e62cb050fb","resolution":{"observed_at":"2026-08-06T16:12:42.253472Z","resolver_source":"local_arxiv","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"}},{"citation":{"cited_paper":{"arxiv_id":"2106.03598","last_updated":"2021-05-28T06:09:23Z","snapshot_observed_at":"2026-08-04T08:32:19.594748Z","submitted_at":"2021-05-28T06:09:23Z","title":"SciFive: a text-to-text transformer model for biomedical literature","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.03598","snapshot_observed_at":"2026-08-06T16:12:42.063803Z","title":"Scifive: a text-to-text transformer model for biomedical literature","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:42.063803Z"},"links":{"cited_paper":"/paper/2106.03598","citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:872bdcf2cb18f7d994f884e9631c3e891233c34a10a54a90a94f25c18f95fd96","observation_id":"38576c62-c9f6-4f17-8996-8d17cc6c4c6d","resolution":{"observed_at":"2026-08-06T16:12:42.063803Z","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":"2505.00814","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:12:42.220616Z","title":"Knowledge-augmented pre-trained language models for biomedical relation extraction","venue":null,"work_id":"a3f28820-1b81-4a59-b919-417fb601b252","year":null},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:42.066718Z"},"links":{"citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:532dfd933b0e983e11b3b5ce77eea64e13d204875098c91f4d22283e8fe6fa3d","observation_id":"8cf53dba-12bf-4272-a3ea-597baa26ea88","resolution":{"observed_at":"2026-08-06T16:12:42.226328Z","resolver_source":"raw_fallback","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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:12:42.525815Z","title":"Relational extraction from biomedical texts with capsule network and hybrid knowledge graph embeddings","venue":null,"work_id":"c763c4bf-a79d-46d2-9e05-c433093edb1c","year":2020},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:42.069380Z"},"links":{"citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:e6bdd0325519fab7475560ccca5d5c707043138aaa6cc199fece6e8184daa554","observation_id":"89ece5b0-0165-4552-82a4-553ad8ca2921","resolution":{"observed_at":"2026-08-06T16:12:42.529218Z","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":"2026-08-06T16:12:42.545352Z","title":"Extracting drug-drug and protein-protein interactions from text using a continuous update of tree-transformers","venue":null,"work_id":"4e8744eb-ce45-42cd-a423-5a3e44036012","year":2022},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":2009,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:42.048492Z"},"links":{"citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:c818f46fbd56aa9b0afa53fc56d67a7b7231385560bbed7667a02c146e7be6b7","observation_id":"47f32010-9368-4b4c-a2d6-b195a2cecfa8","resolution":{"observed_at":"2026-08-06T16:12:42.548723Z","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":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-06T16:12:41.985696Z","title":"Gpt-4 technical report","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:41.985696Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:05161bc638a9e13bc1c80c547f7edbcace5be50cedbc09edf45df4de862fc443","observation_id":"54d4268c-0e61-4bb0-9c92-342699a37c4d","resolution":{"observed_at":"2026-08-06T16:12:41.985696Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.15827","last_updated":"2022-03-29T18:01:24Z","snapshot_observed_at":"2026-08-06T19:04:02.601531Z","submitted_at":"2022-03-29T18:01:24Z","title":"LinkBERT: Pretraining Language Models with Document Links","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.15827","snapshot_observed_at":"2026-08-06T16:12:42.057818Z","title":"Linkbert: Pretraining language models with document links","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:42.057818Z"},"links":{"cited_paper":"/paper/2203.15827","citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:7d0cebf9fedc9b1dbe630c9b19547804bc484cb5a17609d2661d1f9f1290e99d","observation_id":"4568f32f-3315-413b-b280-7e77354c1b13","resolution":{"observed_at":"2026-08-06T16:12:42.057818Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.09288","last_updated":"2023-07-19T17:08:59Z","snapshot_observed_at":"2026-08-02T11:57:18.735747Z","submitted_at":"2023-07-18T14:31:57Z","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.09288","snapshot_observed_at":"2026-08-06T16:12:42.051859Z","title":"Llama 2: Open foundation and fine-tuned chat models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:42.051859Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:14e9cbd54d54986ca5b644889488680df0fc697c03b249bd3b031a59c54dd97a","observation_id":"4d11a1bc-93ea-489f-a0b0-755df028861e","resolution":{"observed_at":"2026-08-06T16:12:42.051859Z","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":"2026-08-06T16:12:42.565143Z","title":"Relation classification via bidirectional prompt learning with data augmentation by large language model","venue":null,"work_id":"9d7a9d8a-4cc5-4c67-b944-b748e655c0ec","year":2024},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:41.998174Z"},"links":{"citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:da9528f6188281e9bd4b88b3a358ea8930be1c796c53dd2641efbef8ac8ebeed","observation_id":"a8f5b012-d020-40a3-93cd-27fa7977cf81","resolution":{"observed_at":"2026-08-06T16:12:42.568598Z","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":"1601.03651","last_updated":"2016-10-13T07:11:46Z","snapshot_observed_at":"2026-07-06T04:42:54.633725Z","submitted_at":"2016-01-14T16:30:41Z","title":"Improved Relation Classification by Deep Recurrent Neural Networks with Data Augmentation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1601.03651","snapshot_observed_at":"2026-08-06T16:12:42.006227Z","title":"Improved relation classification by deep recurrent neural networks with data augmentation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:42.006227Z"},"links":{"cited_paper":"/paper/1601.03651","citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:cf5618ac989c77ece224301794cd295877a32f3e4b9dd8bff5b4656c91eb4ea8","observation_id":"cfd8494a-9413-455c-8c8d-d25e2a6e4303","resolution":{"observed_at":"2026-08-06T16:12:42.006227Z","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":"2026-08-06T16:12:42.576128Z","title":"What’s wrong with your model? a quantitative analysis of relation classification","venue":null,"work_id":"9551ffd5-5545-4644-b862-ef192a126b30","year":2024},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:41.991097Z"},"links":{"citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:703771d0df8315058d861150bae795acd689d41bf22ea0bd2c219e68c0177ebe","observation_id":"1dff7393-44be-4f91-b247-0b72aa1885ba","resolution":{"observed_at":"2026-08-06T16:12:42.579791Z","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":"2311.05922","last_updated":"2024-03-08T06:51:43Z","snapshot_observed_at":"2026-08-06T08:21:22.007534Z","submitted_at":"2023-11-10T08:12:00Z","title":"Chain of Thought with Explicit Evidence Reasoning for Few-shot Relation Extraction","version":3},"cited_work":{"arxiv_id":"2311.05922","doi":null,"metadata_source":"pith","pith_arxiv_id":"2311.05922","snapshot_observed_at":"2026-08-06T16:12:42.451271Z","title":"Chain of Thought with Explicit Evidence Reasoning for Few-shot Relation Extraction","venue":"cs.CL","work_id":"21f991e8-3f45-4215-9f16-73337a4b1cac","year":2023},"citing_paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:42.013543Z"},"links":{"cited_paper":"/paper/2311.05922","citing_paper":"/paper/2507.14374"},"observation_digest":"sha256:d84c0f746956483b56f981f716d8dced9cb0fe44a172acd6127ff2dcad0870aa","observation_id":"c1d11a58-118a-4006-b0ac-66e3ce297332","resolution":{"observed_at":"2026-08-06T16:12:42.455599Z","resolver_source":"local_arxiv","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"}}],"paper":{"arxiv_id":"2507.14374","last_updated":"2025-07-18T21:41:20Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-06T15:55:28.363069Z","submitted_at":"2025-07-18T21:41:20Z","title":"Error-Aware Curriculum Learning for Biomedical Relation Classification"},"reference_resolution":{"displayed":26,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":11,"verified_exact":9,"verified_fuzzy":6},"total_outbound_references":26},"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 7 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2507.14374."}