{"as_of":"2026-08-09T15:44:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:efbe86b6b8a231b5df69d697597d1514adf10ca39fa8a94b3b04dd14261dabcf","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":"2026-08-09T06:31:02.800959+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":"2026-08-08T23:56:16.789485Z","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":"2026-05-24T05:13:56.830242Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2312.15883","last_updated":"2024-04-19T07:14:04Z","snapshot_observed_at":"2026-07-06T17:08:00.380938Z","submitted_at":"2023-12-26T04:49:56Z","title":"HyKGE: A Hypothesis Knowledge Graph Enhanced Framework for Accurate and Reliable Medical LLMs Responses","version":2},"cited_work":{"arxiv_id":"2312.15883","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.15883","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Think and retrieval: A hypothesis knowledge graph enhanced medical large language models","venue":null,"work_id":"63894c8c-f73c-490b-8e98-e86d9da1927d","year":2023},"citing_paper":{"arxiv_id":"2312.10997","last_updated":"2024-03-27T09:16:57Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-18T07:47:33Z","title":"Retrieval-Augmented Generation for Large Language Models: A Survey","version":5},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-05-24T05:10:25.171044Z"},"links":{"cited_paper":"/paper/2312.15883","citing_paper":"/paper/2312.10997"},"observation_digest":"sha256:c2701c783cb4880ba77f76b66dd8fcaa5e9e907c442252da82cb258dbc351465","observation_id":"642f1447-8d63-4cfb-9a2d-1c440fc68184","resolution":{"observed_at":"2026-05-24T05:13:56.834770Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.15883","last_updated":"2024-04-19T07:14:04Z","snapshot_observed_at":"2026-07-06T17:08:00.380938Z","submitted_at":"2023-12-26T04:49:56Z","title":"HyKGE: A Hypothesis Knowledge Graph Enhanced Framework for Accurate and Reliable Medical LLMs Responses","version":2},"cited_work":{"arxiv_id":"2312.15883","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.15883","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Think and retrieval: A hypothesis knowledge graph enhanced medical large language models","venue":null,"work_id":"63894c8c-f73c-490b-8e98-e86d9da1927d","year":2023},"citing_paper":{"arxiv_id":"2501.00309","last_updated":"2025-01-08T05:16:25Z","snapshot_observed_at":"2026-08-07T12:37:34.294206Z","submitted_at":"2024-12-31T06:59:35Z","title":"Retrieval-Augmented Generation with Graphs (GraphRAG)","version":2},"reference_index":185,"source":"pdf_text","source_observed_at":"2026-05-18T04:33:39.076517Z"},"links":{"cited_paper":"/paper/2312.15883","citing_paper":"/paper/2501.00309"},"observation_digest":"sha256:42704747303ff1be57d7029ff208c54688c81510af2611882cf1a755e83d04cd","observation_id":"b5fc0918-3d6f-4401-a949-1a51c2d0c36c","resolution":{"observed_at":"2026-05-18T04:33:39.322976Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.15883","last_updated":"2024-04-19T07:14:04Z","snapshot_observed_at":"2026-07-06T17:08:00.380938Z","submitted_at":"2023-12-26T04:49:56Z","title":"HyKGE: A Hypothesis Knowledge Graph Enhanced Framework for Accurate and Reliable Medical LLMs Responses","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.15883","snapshot_observed_at":"2026-08-08T23:56:16.789485Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.04413","last_updated":"2025-06-27T12:06:42Z","snapshot_observed_at":"2026-08-08T23:47:30.453622Z","submitted_at":"2025-02-06T12:27:35Z","title":"MedRAG: Enhancing Retrieval-augmented Generation with Knowledge Graph-Elicited Reasoning for Healthcare Copilot","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-08T23:56:16.789485Z"},"links":{"cited_paper":"/paper/2312.15883","citing_paper":"/paper/2502.04413"},"observation_digest":"sha256:c0ce841a1aa0a6e58398902e8f7c0605743698caf8c67353c1a6ef4bd0690ede","observation_id":"1c503fc7-2362-423c-9940-123ab23d7c98","resolution":{"observed_at":"2026-08-08T23:56:16.789485Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.15883","last_updated":"2024-04-19T07:14:04Z","snapshot_observed_at":"2026-07-06T17:08:00.380938Z","submitted_at":"2023-12-26T04:49:56Z","title":"HyKGE: A Hypothesis Knowledge Graph Enhanced Framework for Accurate and Reliable Medical LLMs Responses","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.15883","snapshot_observed_at":"2026-08-08T17:31:59.820951Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.05911","last_updated":"2025-02-09T14:11:30Z","snapshot_observed_at":"2026-08-09T10:26:49.594398Z","submitted_at":"2025-02-09T14:11:30Z","title":"GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-08T17:31:59.820951Z"},"links":{"cited_paper":"/paper/2312.15883","citing_paper":"/paper/2502.05911"},"observation_digest":"sha256:fd6c216ea69957b49c68a730c78631786a04b64bfc1df3d9f7a3227b3883114c","observation_id":"fd7b17a7-b4e3-43e7-9c07-18ca3bd834b9","resolution":{"observed_at":"2026-08-08T17:31:59.820951Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.15883","last_updated":"2024-04-19T07:14:04Z","snapshot_observed_at":"2026-07-06T17:08:00.380938Z","submitted_at":"2023-12-26T04:49:56Z","title":"HyKGE: A Hypothesis Knowledge Graph Enhanced Framework for Accurate and Reliable Medical LLMs Responses","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.15883","snapshot_observed_at":"2026-08-07T11:49:50.415297Z","title":"Think and retrieval: A hypothesis knowledge graph enhanced medical large language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.01364","last_updated":"2025-06-02T06:46:42Z","snapshot_observed_at":"2026-08-08T09:15:38.444850Z","submitted_at":"2025-06-02T06:46:42Z","title":"Unraveling Spatio-Temporal Foundation Models via the Pipeline Lens: A Comprehensive Review","version":1},"reference_index":224,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:50.415297Z"},"links":{"cited_paper":"/paper/2312.15883","citing_paper":"/paper/2506.01364"},"observation_digest":"sha256:f78fa93fdd844591df5f74a7bd2e9450f40dcf3c99588bb1ee8cefcb3228024f","observation_id":"bed7aef2-1eaa-4ceb-b6bb-992919c033af","resolution":{"observed_at":"2026-08-07T11:49:50.415297Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.15883","last_updated":"2024-04-19T07:14:04Z","snapshot_observed_at":"2026-07-06T17:08:00.380938Z","submitted_at":"2023-12-26T04:49:56Z","title":"HyKGE: A Hypothesis Knowledge Graph Enhanced Framework for Accurate and Reliable Medical LLMs Responses","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.15883","snapshot_observed_at":"2026-08-07T05:08:24.428211Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.08771","last_updated":"2025-06-10T13:13:55Z","snapshot_observed_at":"2026-08-08T05:07:43.905324Z","submitted_at":"2025-06-10T13:13:55Z","title":"Paths to Causality: Finding Informative Subgraphs Within Knowledge Graphs for Knowledge-Based Causal Discovery","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T05:08:24.428211Z"},"links":{"cited_paper":"/paper/2312.15883","citing_paper":"/paper/2506.08771"},"observation_digest":"sha256:d280a0673e251b72ac5a74b9476c19b34966df00c12838e797b0167208d615e4","observation_id":"8129153e-5ee5-4bee-a907-a9dc1584e4b0","resolution":{"observed_at":"2026-08-07T05:08:24.428211Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.15883","last_updated":"2024-04-19T07:14:04Z","snapshot_observed_at":"2026-07-06T17:08:00.380938Z","submitted_at":"2023-12-26T04:49:56Z","title":"HyKGE: A Hypothesis Knowledge Graph Enhanced Framework for Accurate and Reliable Medical LLMs Responses","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.15883","snapshot_observed_at":"2026-08-06T16:42:29.763560Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.12774","last_updated":"2025-07-17T04:31:55Z","snapshot_observed_at":"2026-08-08T03:04:37.730389Z","submitted_at":"2025-07-17T04:31:55Z","title":"A Comprehensive Survey of Electronic Health Record Modeling: From Deep Learning Approaches to Large Language Models","version":1},"reference_index":117,"source":"pdf_text","source_observed_at":"2026-08-06T16:42:29.763560Z"},"links":{"cited_paper":"/paper/2312.15883","citing_paper":"/paper/2507.12774"},"observation_digest":"sha256:f0799c15be3d4b32a9fd3f0f178adf87955ef5da786fd52aa12b154b061be54d","observation_id":"725169a8-a113-49a8-ac35-31ddec12412c","resolution":{"observed_at":"2026-08-06T16:42:29.763560Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.15883","last_updated":"2024-04-19T07:14:04Z","snapshot_observed_at":"2026-07-06T17:08:00.380938Z","submitted_at":"2023-12-26T04:49:56Z","title":"HyKGE: A Hypothesis Knowledge Graph Enhanced Framework for Accurate and Reliable Medical LLMs Responses","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.15883","snapshot_observed_at":"2026-08-05T19:02:49.904460Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.13606","last_updated":"2025-08-19T08:12:45Z","snapshot_observed_at":"2026-08-05T19:02:49.194056Z","submitted_at":"2025-08-19T08:12:45Z","title":"AdaDocVQA: Adaptive Framework for Long Document Visual Question Answering in Low-Resource Settings","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T19:02:49.904460Z"},"links":{"cited_paper":"/paper/2312.15883","citing_paper":"/paper/2508.13606"},"observation_digest":"sha256:572bc9c457b5f270108c5df505d6524e78635dafc364d7c6b84f3f0d169358e0","observation_id":"b57c4ce9-ea3a-43d1-901c-ce70c3a3a3fb","resolution":{"observed_at":"2026-08-05T19:02:49.904460Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.15883","last_updated":"2024-04-19T07:14:04Z","snapshot_observed_at":"2026-07-06T17:08:00.380938Z","submitted_at":"2023-12-26T04:49:56Z","title":"HyKGE: A Hypothesis Knowledge Graph Enhanced Framework for Accurate and Reliable Medical LLMs Responses","version":2},"cited_work":{"arxiv_id":"2312.15883","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.15883","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Think and retrieval: A hypothesis knowledge graph enhanced medical large language models","venue":null,"work_id":"63894c8c-f73c-490b-8e98-e86d9da1927d","year":2023},"citing_paper":{"arxiv_id":"2604.17458","last_updated":"2026-04-21T06:43:15Z","snapshot_observed_at":"2026-07-06T23:04:32.734175Z","submitted_at":"2026-04-19T14:18:49Z","title":"EHRAG: Bridging Semantic Gaps in Lightweight GraphRAG via Hybrid Hypergraph Construction and Retrieval","version":2},"reference_index":76,"source":"arxiv_source","source_observed_at":"2026-05-10T05:43:04.813867Z"},"links":{"cited_paper":"/paper/2312.15883","citing_paper":"/paper/2604.17458"},"observation_digest":"sha256:cbfafa07bb159a3d2e909ac74aba17499784e5a5aeea0b2b5bbdadd271db9d87","observation_id":"6153e4db-502e-4af8-aede-cdd27ec8039b","resolution":{"observed_at":"2026-05-10T05:51:10.624995Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.15883","last_updated":"2024-04-19T07:14:04Z","snapshot_observed_at":"2026-07-06T17:08:00.380938Z","submitted_at":"2023-12-26T04:49:56Z","title":"HyKGE: A Hypothesis Knowledge Graph Enhanced Framework for Accurate and Reliable Medical LLMs Responses","version":2},"cited_work":{"arxiv_id":"2312.15883","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.15883","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Think and retrieval: A hypothesis knowledge graph enhanced medical large language models","venue":null,"work_id":"63894c8c-f73c-490b-8e98-e86d9da1927d","year":2023},"citing_paper":{"arxiv_id":"2605.09492","last_updated":"2026-05-20T15:55:09Z","snapshot_observed_at":"2026-07-06T23:21:35.327066Z","submitted_at":"2026-05-10T11:57:39Z","title":"APCD: Adaptive Path-Contrastive Decoding for Reliable Large Language Model Generation","version":1},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-05-12T05:22:25.475956Z"},"links":{"cited_paper":"/paper/2312.15883","citing_paper":"/paper/2605.09492"},"observation_digest":"sha256:75992297f396a5b5ef8fdf40549831d436a61a590977e82a78af2e6f6c8283b2","observation_id":"a4296370-bfb3-4281-ba89-cbc367452a8e","resolution":{"observed_at":"2026-05-12T05:26:25.181448Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2312.15883/citation-record","integrity":"/paper/2312.15883/integrity","json":"/paper/2312.15883/citation-record.json","paper":"/paper/2312.15883"},"outbound":[],"paper":{"arxiv_id":"2312.15883","last_updated":"2024-04-19T07:14:04Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T17:08:00.380938Z","submitted_at":"2023-12-26T04:49:56Z","title":"HyKGE: A Hypothesis Knowledge Graph Enhanced Framework for Accurate and Reliable Medical LLMs Responses"},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2312.15883."}