{"as_of":"2026-08-12T10:01:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b05d0f7a80383d0b6d5ccd2db37c1076c3572a95d2313a6574688b2382bb82a3","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":10,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":10,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+00:00","state":"measured"},{"denominator":10,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":10,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T20:37:54.096111Z","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":"2026-05-09T06:45:44.147833Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2401.02981","last_updated":"2024-01-24T18:16:34Z","snapshot_observed_at":"2026-07-06T17:12:06.715778Z","submitted_at":"2024-01-01T06:22:04Z","title":"Fine-tuning and Utilization Methods of Domain-specific LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.02981","snapshot_observed_at":"2026-08-11T20:37:54.096111Z","title":"ACM Transactions on Information Systems","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.05587","last_updated":"2024-12-11T13:56:40Z","snapshot_observed_at":"2026-08-11T20:31:35.126413Z","submitted_at":"2024-12-07T08:50:24Z","title":"GEE-OPs: An Operator Knowledge Base for Geospatial Code Generation on the Google Earth Engine Platform Powered by Large Language Models","version":2},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-11T20:37:54.096111Z"},"links":{"cited_paper":"/paper/2401.02981","citing_paper":"/paper/2412.05587"},"observation_digest":"sha256:0791d0cfe7458b45e37778c28e11e84bfd858964e528dc0aa1a5fb99d5e38853","observation_id":"3f49c9ca-e82e-4dad-ad40-fbca0571d6ec","resolution":{"observed_at":"2026-08-11T20:37:54.096111Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.02981","last_updated":"2024-01-24T18:16:34Z","snapshot_observed_at":"2026-07-06T17:12:06.715778Z","submitted_at":"2024-01-01T06:22:04Z","title":"Fine-tuning and Utilization Methods of Domain-specific LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.02981","snapshot_observed_at":"2026-08-11T17:25:31.568737Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.08972","last_updated":"2025-05-30T17:43:10Z","snapshot_observed_at":"2026-08-12T04:44:29.839912Z","submitted_at":"2024-12-12T06:08:46Z","title":"RuleArena: A Benchmark for Rule-Guided Reasoning with LLMs in Real-World Scenarios","version":2},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-11T17:25:31.568737Z"},"links":{"cited_paper":"/paper/2401.02981","citing_paper":"/paper/2412.08972"},"observation_digest":"sha256:1167dbea407b478d2d33c264692268bc505f05661e5fe8babdfd0c306d478629","observation_id":"1bcfb457-4e42-403d-b33e-24e07603a894","resolution":{"observed_at":"2026-08-11T17:25:31.568737Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.02981","last_updated":"2024-01-24T18:16:34Z","snapshot_observed_at":"2026-07-06T17:12:06.715778Z","submitted_at":"2024-01-01T06:22:04Z","title":"Fine-tuning and Utilization Methods of Domain-specific LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.02981","snapshot_observed_at":"2026-08-11T12:47:17.404578Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.13845","last_updated":"2025-02-24T03:37:59Z","snapshot_observed_at":"2026-08-11T14:35:32.643550Z","submitted_at":"2024-12-18T13:38:06Z","title":"Do Language Models Understand Time?","version":3},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-11T12:47:17.404578Z"},"links":{"cited_paper":"/paper/2401.02981","citing_paper":"/paper/2412.13845"},"observation_digest":"sha256:46ae820d2d0f2656afe33cf2af55ac5d099708870c9676edd8d01145b6319b61","observation_id":"a5779f29-c2d7-4ac4-bfd2-bbe1dfdd6415","resolution":{"observed_at":"2026-08-11T12:47:17.404578Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.02981","last_updated":"2024-01-24T18:16:34Z","snapshot_observed_at":"2026-07-06T17:12:06.715778Z","submitted_at":"2024-01-01T06:22:04Z","title":"Fine-tuning and Utilization Methods of Domain-specific LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.02981","snapshot_observed_at":"2026-08-11T12:17:56.690667Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.14426","last_updated":"2024-12-20T15:57:10Z","snapshot_observed_at":"2026-08-12T07:19:13.350732Z","submitted_at":"2024-12-19T00:41:40Z","title":"All-in-One Tuning and Structural Pruning for Domain-Specific LLMs","version":2},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-11T12:17:56.690667Z"},"links":{"cited_paper":"/paper/2401.02981","citing_paper":"/paper/2412.14426"},"observation_digest":"sha256:080d488789402e9eb1938fe690225fd5dd0c30a68fac141276bfd0ea9feae5f0","observation_id":"c118b74d-40f4-45a1-bf3f-18eafd6e1160","resolution":{"observed_at":"2026-08-11T12:17:56.690667Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.02981","last_updated":"2024-01-24T18:16:34Z","snapshot_observed_at":"2026-07-06T17:12:06.715778Z","submitted_at":"2024-01-01T06:22:04Z","title":"Fine-tuning and Utilization Methods of Domain-specific LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.02981","snapshot_observed_at":"2026-08-11T11:58:36.372258Z","title":"Fine-tuning and utilization methods of domain-specific llms","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.14771","last_updated":"2024-12-19T11:55:51Z","snapshot_observed_at":"2026-08-11T19:31:04.477777Z","submitted_at":"2024-12-19T11:55:51Z","title":"ALKAFI-LLAMA3: Fine-Tuning LLMs for Precise Legal Understanding in Palestine","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T11:58:36.372258Z"},"links":{"cited_paper":"/paper/2401.02981","citing_paper":"/paper/2412.14771"},"observation_digest":"sha256:c6fa2c6153608154cdc84c495f910619e885591d7471e7d8eaa030adcc523f5f","observation_id":"90babf4d-787c-4953-bef6-d13179e3a0af","resolution":{"observed_at":"2026-08-11T11:58:36.372258Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.02981","last_updated":"2024-01-24T18:16:34Z","snapshot_observed_at":"2026-07-06T17:12:06.715778Z","submitted_at":"2024-01-01T06:22:04Z","title":"Fine-tuning and Utilization Methods of Domain-specific LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.02981","snapshot_observed_at":"2026-08-07T12:40:22.930321Z","title":"Fine-tuning and utilization methods of domain-specific llms.arXiv preprint arXiv:2401.02981 , 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.15702","last_updated":"2025-05-30T01:54:12Z","snapshot_observed_at":"2026-08-11T18:09:50.294615Z","submitted_at":"2025-05-30T01:54:12Z","title":"Minifinetuning: Low-Data Generation Domain Adaptation through Corrective Self-Distillation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T12:40:22.930321Z"},"links":{"cited_paper":"/paper/2401.02981","citing_paper":"/paper/2506.15702"},"observation_digest":"sha256:92cdd15e2ccde57b924e3e0ae06c56ac093a33e5470dc5c116bd9b353beef5ab","observation_id":"56542d17-5577-4ebc-bd31-b1ba87260097","resolution":{"observed_at":"2026-08-07T12:40:22.930321Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.02981","last_updated":"2024-01-24T18:16:34Z","snapshot_observed_at":"2026-07-06T17:12:06.715778Z","submitted_at":"2024-01-01T06:22:04Z","title":"Fine-tuning and Utilization Methods of Domain-specific LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.02981","snapshot_observed_at":"2026-08-05T11:39:16.601283Z","title":"Fine-tuning and utilization methods of domain-specific llms,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02411","last_updated":"2025-09-02T15:19:57Z","snapshot_observed_at":"2026-08-06T21:38:56.067118Z","submitted_at":"2025-09-02T15:19:57Z","title":"A Survey: Towards Privacy and Security in Mobile Large Language Models","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-05T11:39:16.601283Z"},"links":{"cited_paper":"/paper/2401.02981","citing_paper":"/paper/2509.02411"},"observation_digest":"sha256:d0e1104c227149c6d345b039db0e77c06c823f108c612aca46810d2c3f4f0592","observation_id":"aef514c6-a7c5-4339-9c70-628bbe89d3c4","resolution":{"observed_at":"2026-08-05T11:39:16.601283Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.02981","last_updated":"2024-01-24T18:16:34Z","snapshot_observed_at":"2026-07-06T17:12:06.715778Z","submitted_at":"2024-01-01T06:22:04Z","title":"Fine-tuning and Utilization Methods of Domain-specific LLMs","version":2},"cited_work":{"arxiv_id":"2401.02981","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2401.02981","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Fine-tuning and utilization methods of domain- specific llms.arXiv preprint arXiv:2401.02981","venue":null,"work_id":"dc3620a8-9b8b-4ddb-9f2e-108d0cb80cb6","year":null},"citing_paper":{"arxiv_id":"2605.04572","last_updated":"2026-05-06T07:17:33Z","snapshot_observed_at":"2026-08-01T20:51:20.997015Z","submitted_at":"2026-05-06T07:17:33Z","title":"From Parameter Dynamics to Risk Scoring : Quantifying Sample-Level Safety Degradation in LLM Fine-tuning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-08T18:08:11.122577Z"},"links":{"cited_paper":"/paper/2401.02981","citing_paper":"/paper/2605.04572"},"observation_digest":"sha256:e20ffa33c89fc67ef15d450733df0249a325c9f43a7cec4bddf7b7f071273b5f","observation_id":"579eb49c-b699-4724-928f-819cc85ff41c","resolution":{"observed_at":"2026-05-09T06:45:44.157141Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.02981","last_updated":"2024-01-24T18:16:34Z","snapshot_observed_at":"2026-07-06T17:12:06.715778Z","submitted_at":"2024-01-01T06:22:04Z","title":"Fine-tuning and Utilization Methods of Domain-specific LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.02981","snapshot_observed_at":"2026-08-06T14:54:47.266786Z","title":"Fine-tuning and utilization methods of domain-specific llms,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.04854","last_updated":"2026-08-05T13:47:59Z","snapshot_observed_at":"2026-08-11T01:54:15.111239Z","submitted_at":"2026-08-05T13:47:59Z","title":"Transforming Remanufacturing Automation with Large Language Models: A Forward-Looking Analysis with Case Studies","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T14:54:47.266786Z"},"links":{"cited_paper":"/paper/2401.02981","citing_paper":"/paper/2608.04854"},"observation_digest":"sha256:c9b870a10bb86f1690c0c5b83c25289cdd146e2892f73c4216d1ce79f76005c2","observation_id":"fc4598c9-bf75-496b-879b-eeecfad14b60","resolution":{"observed_at":"2026-08-06T14:54:47.266786Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.02981","last_updated":"2024-01-24T18:16:34Z","snapshot_observed_at":"2026-07-06T17:12:06.715778Z","submitted_at":"2024-01-01T06:22:04Z","title":"Fine-tuning and Utilization Methods of Domain-specific LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.02981","snapshot_observed_at":"2026-08-07T15:39:21.007950Z","title":"Joel,S.;Wu,J.;andFard,F.2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.06069","last_updated":"2026-08-06T14:13:02Z","snapshot_observed_at":"2026-08-12T03:17:27.848518Z","submitted_at":"2026-08-06T14:13:02Z","title":"Training-Free Token-Level Steering for LLM Personalized Co-Writing","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T15:39:21.007950Z"},"links":{"cited_paper":"/paper/2401.02981","citing_paper":"/paper/2608.06069"},"observation_digest":"sha256:af68697f230c242b5c1322f3cd70296121d3f230706855f22c0061ea76fa1122","observation_id":"d9e56cd2-1b5c-48d7-aa6f-f9e9e1ae5fc6","resolution":{"observed_at":"2026-08-07T15:39:21.007950Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2401.02981/citation-record","integrity":"/paper/2401.02981/integrity","json":"/paper/2401.02981/citation-record.json","paper":"/paper/2401.02981"},"outbound":[],"paper":{"arxiv_id":"2401.02981","last_updated":"2024-01-24T18:16:34Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T17:12:06.715778Z","submitted_at":"2024-01-01T06:22:04Z","title":"Fine-tuning and Utilization Methods of Domain-specific LLMs"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2401.02981."}