{"as_of":"2026-08-17T20:14:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:190177dfc6407c64ea15d3682580001bda131c00fc1eb0ccefac415c9ae1e676","coverage":[{"denominator":50,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":50,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T23:37:58.835144Z","state":"measured"},{"denominator":51,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":51,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-22T10:30:01.910920Z","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":"2026-05-22T10:31:25.435426Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"cited_work":{"arxiv_id":"2511.07457","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2511.07457","snapshot_observed_at":"2026-07-21T02:21:25.107561Z","title":"Grip: In-parameter graph reasoning through fine-tuning large language models","venue":null,"work_id":"a5300064-3c96-46bc-950f-a1f7064cb8ce","year":2025},"citing_paper":{"arxiv_id":"2603.02938","last_updated":"2026-05-21T07:56:15Z","snapshot_observed_at":"2026-08-15T15:24:59.576120Z","submitted_at":"2026-03-03T12:47:44Z","title":"Beyond One-Size-Fits-All: Adaptive Subgraph Denoising for Zero-Shot Graph Learning with Large Language Models","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-22T10:30:01.910920Z"},"links":{"cited_paper":"/paper/2511.07457","citing_paper":"/paper/2603.02938"},"observation_digest":"sha256:b5d094e7604e161d97ad7534eeef8e6b64427be0464743b168bdd488049d2c32","observation_id":"71736143-233a-4944-8fb7-2d52e6c61029","resolution":{"observed_at":"2026-07-21T02:21:25.107561Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2511.07457/citation-record","integrity":"/paper/2511.07457/integrity","json":"/paper/2511.07457/citation-record.json","paper":"/paper/2511.07457"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2309.14316","last_updated":"2024-07-16T10:22:51Z","snapshot_observed_at":"2026-08-16T14:57:46.371369Z","submitted_at":"2023-09-25T17:37:20Z","title":"Physics of Language Models: Part 3.1, Knowledge Storage and Extraction","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.14316","snapshot_observed_at":"2026-08-03T23:37:54.445297Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:54.445297Z"},"links":{"cited_paper":"/paper/2309.14316","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:4f5b4d67cf258e895574c1a509d06ae84f924a07a8c950ad99609449c011ded2","observation_id":"e2bd3065-4683-437a-a370-0ffdd5c8bb05","resolution":{"observed_at":"2026-08-03T23:37:54.445297Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T23:37:54.520829Z","title":null,"venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:54.520829Z"},"links":{"citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:7d5764bce3e9b19c234e3fae0583e4cdf15acbcbfc062d16e5a40852ea7b0f98","observation_id":"7d054dfe-4067-49f9-b9b2-e3491a7dc6bc","resolution":{"observed_at":"2026-08-03T23:37:54.520829Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T23:37:54.587511Z","title":null,"venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:54.587511Z"},"links":{"citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:2652a89348a8d6bc4d9aa785bdc3fd41ab4aa00cfc1ee125fa1a0dc037bbd0eb","observation_id":"b7bf8b84-eb64-4176-9878-707fb214ca00","resolution":{"observed_at":"2026-08-03T23:37:54.587511Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.06105","last_updated":"2025-06-09T14:19:59Z","snapshot_observed_at":"2026-08-12T19:22:14.414860Z","submitted_at":"2025-06-06T14:11:27Z","title":"Text-to-LoRA: Instant Transformer Adaption","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.06105","snapshot_observed_at":"2026-08-03T23:37:54.737812Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:54.737812Z"},"links":{"cited_paper":"/paper/2506.06105","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:cd70a8a5a10b11550b9acd85500b5e830c04c186391347d01606618c9ab50d67","observation_id":"fbe1561e-ffb8-4e58-8fd5-1c03d3a5109c","resolution":{"observed_at":"2026-08-03T23:37:54.737812Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T23:37:54.863930Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:54.863930Z"},"links":{"citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:a0305174dac995bdc5a7f1f05d6a2b2ce80309a923ad7fbb1e0417882429109e","observation_id":"4a49a4ef-a855-4000-85c1-d2976a3bd890","resolution":{"observed_at":"2026-08-03T23:37:54.863930Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.14168","last_updated":"2021-11-18T00:23:45Z","snapshot_observed_at":"2026-08-14T02:43:01.480086Z","submitted_at":"2021-10-27T04:49:45Z","title":"Training Verifiers to Solve Math Word Problems","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.14168","snapshot_observed_at":"2026-08-03T23:37:55.024897Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:55.024897Z"},"links":{"cited_paper":"/paper/2110.14168","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:8f7a0c8f9afa96be0a3ebffc697f992aa3ade7678612aba6d4fc9e4496f238fd","observation_id":"bae9d81f-534f-492e-b26a-0873b9d8721d","resolution":{"observed_at":"2026-08-03T23:37:55.024897Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1707.01476","last_updated":"2018-07-04T09:53:46Z","snapshot_observed_at":"2026-08-14T20:49:30.127080Z","submitted_at":"2017-07-05T17:18:17Z","title":"Convolutional 2D Knowledge Graph Embeddings","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.01476","snapshot_observed_at":"2026-08-03T23:37:55.102169Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:55.102169Z"},"links":{"cited_paper":"/paper/1707.01476","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:aa042739342e7df74d290275097f8a3d5338633a45b1a76618134355ab1148e8","observation_id":"5ffe49ee-03e3-46b7-9b01-be25406d92d4","resolution":{"observed_at":"2026-08-03T23:37:55.102169Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.16130","last_updated":"2025-02-19T10:49:41Z","snapshot_observed_at":"2026-08-16T12:38:40.131901Z","submitted_at":"2024-04-24T18:38:11Z","title":"From Local to Global: A Graph RAG Approach to Query-Focused Summarization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.16130","snapshot_observed_at":"2026-08-03T23:37:55.234330Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:55.234330Z"},"links":{"cited_paper":"/paper/2404.16130","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:061fc69062770ee63814881a942be24495d170f1dfd735d2ebc603890b3debe7","observation_id":"f5e2f424-c418-4164-b404-e325eedfbafa","resolution":{"observed_at":"2026-08-03T23:37:55.234330Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14683","last_updated":"2024-10-19T18:47:33Z","snapshot_observed_at":"2026-08-16T13:40:57.477085Z","submitted_at":"2024-06-20T19:11:35Z","title":"TAGLAS: An atlas of text-attributed graph datasets in the era of large graph and language models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.14683","snapshot_observed_at":"2026-08-03T23:37:55.267414Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:55.267414Z"},"links":{"cited_paper":"/paper/2406.14683","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:4a111740276d98f1105ad3a00a8a7e769e04e52b129238abeff300b5512e7217","observation_id":"effb1f1b-ba34-4ba1-acec-4bce5c1895eb","resolution":{"observed_at":"2026-08-03T23:37:55.267414Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-08-13T17:20:44.002518Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-08-03T23:37:55.348598Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:55.348598Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:6828f631779d89e59d56e90604d748b21e048b5647ad87781334a78dedc46099","observation_id":"f47b5b3e-a033-4147-b7b4-6856ba3d3e81","resolution":{"observed_at":"2026-08-03T23:37:55.348598Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.14196","last_updated":"2024-01-26T09:23:11Z","snapshot_observed_at":"2026-08-06T22:40:28.707813Z","submitted_at":"2024-01-25T14:17:53Z","title":"DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.14196","snapshot_observed_at":"2026-08-03T23:37:55.409883Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:55.409883Z"},"links":{"cited_paper":"/paper/2401.14196","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:d4521f27578b2212066d499f4ded689de85bed7e182be3816780a987611214f0","observation_id":"6fcd525b-c867-4c8c-a1ae-f4d39d81da09","resolution":{"observed_at":"2026-08-03T23:37:55.409883Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T23:37:55.469035Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:55.469035Z"},"links":{"citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:6cba8478ca8e8b0b72fa6360ed2764cda9c8d580f4caf5a8bce836a876a296c5","observation_id":"2fa79d5a-41ca-4725-b8e4-8656224bfcdf","resolution":{"observed_at":"2026-08-03T23:37:55.469035Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T23:37:55.512466Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:55.512466Z"},"links":{"citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:68e5d06504896e4089a61b3d5c29b5e1ecff93b6bd8ec3266deedf0a81b08c4d","observation_id":"d5a6fbc3-a9e4-4f1f-b221-f8983b60575a","resolution":{"observed_at":"2026-08-03T23:37:55.512466Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.13630","last_updated":"2025-01-20T15:12:02Z","snapshot_observed_at":"2026-08-16T14:16:40.841450Z","submitted_at":"2024-02-21T09:06:31Z","title":"UniGraph: Learning a Unified Cross-Domain Foundation Model for Text-Attributed Graphs","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.13630","snapshot_observed_at":"2026-08-03T23:37:55.544673Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:55.544673Z"},"links":{"cited_paper":"/paper/2402.13630","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:0f8d3bf40ff49574a8841f3036033c32fe16d5bc0c41c3d1a093b52c5d505f80","observation_id":"da00aa21-262f-426c-9057-6b950f8e21c8","resolution":{"observed_at":"2026-08-03T23:37:55.544673Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T23:37:55.660056Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:55.660056Z"},"links":{"citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:a43321285dda9742c59ec0b06c37c1e78ca204af5eeb9369de2629529ddb6583","observation_id":"ac2b9c89-7a9a-4520-9c0c-f3aa95355148","resolution":{"observed_at":"2026-08-03T23:37:55.660056Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T23:37:55.739113Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:55.739113Z"},"links":{"citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:5751c83c74188f22878437f0182c685cb0407a50089ae7ae535a27ceeafc335e","observation_id":"8f4ef8c9-538e-45d5-bb2c-312edaa27af2","resolution":{"observed_at":"2026-08-03T23:37:55.739113Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T23:37:55.827173Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:55.827173Z"},"links":{"citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:0831ab9680109ecc753deefc87c62fe18909f0108a4b1bf41acac977481ae0d2","observation_id":"42066ade-384c-47b9-8751-ce8c20c55ca3","resolution":{"observed_at":"2026-08-03T23:37:55.827173Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T23:37:55.910557Z","title":"Gonzalez, Hao Zhang, and Ion Stoica","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:55.910557Z"},"links":{"citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:44b494f7200eb6892bc9c94d824415663fdfd79e29d708c024fcc8d77bea2b82","observation_id":"9887878f-c8d3-4d38-a31c-23a444c099d5","resolution":{"observed_at":"2026-08-03T23:37:55.910557Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.07559","last_updated":"2023-12-14T19:40:04Z","snapshot_observed_at":"2026-08-16T14:36:26.086381Z","submitted_at":"2023-12-08T18:50:20Z","title":"PaperQA: Retrieval-Augmented Generative Agent for Scientific Research","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.07559","snapshot_observed_at":"2026-08-03T23:37:55.971449Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:55.971449Z"},"links":{"cited_paper":"/paper/2312.07559","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:7b26cee7cf964b381b7ea6ca77620248ccb4d30b814ef5cd0b2683f7f822ee66","observation_id":"0ef4e293-29ca-496e-8ecd-99a0ac550be9","resolution":{"observed_at":"2026-08-03T23:37:55.971449Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T23:37:56.021239Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:56.021239Z"},"links":{"citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:8fbae6fae10512b594c024cda412a8536788f04c9558eaefc84e1c0e894929c1","observation_id":"70f752db-17f2-4e95-926c-278145a1b04a","resolution":{"observed_at":"2026-08-03T23:37:56.021239Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.05579","last_updated":"2024-12-10T05:49:12Z","snapshot_observed_at":"2026-08-17T10:18:05.650518Z","submitted_at":"2024-12-07T08:07:24Z","title":"LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.05579","snapshot_observed_at":"2026-08-03T23:37:56.075841Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:56.075841Z"},"links":{"cited_paper":"/paper/2412.05579","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:283fe945c4f2fc5ca0a8ad348dad683bf4d86a1b3072256b2a69c331873605be","observation_id":"bcdb275d-cf57-4990-8ee7-1c2f8fae8ed3","resolution":{"observed_at":"2026-08-03T23:37:56.075841Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T23:37:56.155500Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:56.155500Z"},"links":{"citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:93b575993527c8dcfb959b43a48fb71f2a61d853fedc4493645d70351bcd522b","observation_id":"be6d3829-1fdd-4ec3-b4dd-ef257e49c71f","resolution":{"observed_at":"2026-08-03T23:37:56.155500Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.13562","last_updated":"2025-02-19T09:14:19Z","snapshot_observed_at":"2026-08-17T19:46:03.770948Z","submitted_at":"2025-02-19T09:14:19Z","title":"Are Large Language Models In-Context Graph Learners?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.13562","snapshot_observed_at":"2026-08-03T23:37:56.167724Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:56.167724Z"},"links":{"cited_paper":"/paper/2502.13562","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:7b2784974c0a7ccef430efca093147160f284893dd3bf4c1b388dcace14dda08","observation_id":"59df3133-c469-445f-b1f7-a388d64ab850","resolution":{"observed_at":"2026-08-03T23:37:56.167724Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.14961","last_updated":"2024-10-19T03:27:19Z","snapshot_observed_at":"2026-08-16T13:07:51.768492Z","submitted_at":"2024-10-19T03:27:19Z","title":"LangGFM: A Large Language Model Alone Can be a Powerful Graph Foundation Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.14961","snapshot_observed_at":"2026-08-03T23:37:56.282671Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:56.282671Z"},"links":{"cited_paper":"/paper/2410.14961","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:b5f9888739762308b63ec150262fe9324d4ff0653ffc16da06eaa201370782e9","observation_id":"63b34b31-3263-46ca-b621-ea1a5bae1a01","resolution":{"observed_at":"2026-08-03T23:37:56.282671Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.19437","last_updated":"2025-02-18T17:26:38Z","snapshot_observed_at":"2026-08-15T17:27:11.980940Z","submitted_at":"2024-12-27T04:03:16Z","title":"DeepSeek-V3 Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.19437","snapshot_observed_at":"2026-08-03T23:37:56.415882Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:56.415882Z"},"links":{"cited_paper":"/paper/2412.19437","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:0f5bbfd51f40a3472f2e46fe0fd0ccddc3bcf2a89b4744f8bb7e64873366e051","observation_id":"7982fea4-6ef3-4c71-b4b3-9f8e407b86d5","resolution":{"observed_at":"2026-08-03T23:37:56.415882Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T23:37:56.504668Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:56.504668Z"},"links":{"citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:be83e2a8bebed320a2da6cd99e33dae2f934c9faf477e9d4910980a83d2e6371","observation_id":"dc1bf3ed-cc6c-439b-b17f-ff82c3c8f39b","resolution":{"observed_at":"2026-08-03T23:37:56.504668Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.01899","last_updated":"2020-10-05T10:28:03Z","snapshot_observed_at":"2026-08-16T19:15:52.465750Z","submitted_at":"2020-10-05T10:28:03Z","title":"Dynamic Anticipation and Completion for Multi-Hop Reasoning over Sparse Knowledge Graph","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.01899","snapshot_observed_at":"2026-08-03T23:37:56.580729Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:56.580729Z"},"links":{"cited_paper":"/paper/2010.01899","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:d0f4d637e6af7b81a66b875d4d288e4d1a6620a1bda80742664cf784d345422b","observation_id":"d3c654e0-79f7-482b-80e9-e5832f4dd48e","resolution":{"observed_at":"2026-08-03T23:37:56.580729Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.13626","last_updated":"2024-12-18T09:04:55Z","snapshot_observed_at":"2026-08-16T21:08:24.857431Z","submitted_at":"2024-12-18T09:04:55Z","title":"LIFT: Improving Long Context Understanding Through Long Input Fine-Tuning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.13626","snapshot_observed_at":"2026-08-03T23:37:56.701093Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:56.701093Z"},"links":{"cited_paper":"/paper/2412.13626","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:a502131d05e19772a1e8d9174ef201682208673fff3b8810e1ec84b3264f7d72","observation_id":"d24f55a2-ba63-4e50-bdd5-620d050f8b72","resolution":{"observed_at":"2026-08-03T23:37:56.701093Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-17T09:58:46.058102Z","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":"2026-08-03T23:37:56.795855Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:56.795855Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:8201ad8cc4d9e70129a9683d687caa71e8099608773ec4668fcbcaf75b1ec15b","observation_id":"562ff556-7284-4536-8472-384b99f859d7","resolution":{"observed_at":"2026-08-03T23:37:56.795855Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T23:37:56.904733Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:56.904733Z"},"links":{"citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:1a8ef0a0151c6fd0e3be8bd06b4b5f63dd32995d93107dab197d17cfcf90e1b6","observation_id":"765c1873-ffac-4dc5-af28-c753c87bcc87","resolution":{"observed_at":"2026-08-03T23:37:56.904733Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.20583","last_updated":"2025-08-28T09:20:47Z","snapshot_observed_at":"2026-08-16T07:19:00.440841Z","submitted_at":"2025-08-28T09:20:47Z","title":"A Graph Talks, But Who's Listening? Rethinking Evaluations for Graph-Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.20583","snapshot_observed_at":"2026-08-03T23:37:56.987730Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:56.987730Z"},"links":{"cited_paper":"/paper/2508.20583","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:88928e504462343e738b8ddc8ac8e33932138f1a238a01e80514e6a3020b8219","observation_id":"a119f3bf-caf9-4d5a-b73d-0f01af0b564c","resolution":{"observed_at":"2026-08-03T23:37:56.987730Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07810","last_updated":"2020-10-06T09:10:10Z","snapshot_observed_at":"2026-08-13T19:24:44.750282Z","submitted_at":"2020-09-16T17:08:23Z","title":"CoDEx: A Comprehensive Knowledge Graph Completion Benchmark","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07810","snapshot_observed_at":"2026-08-03T23:37:57.145621Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:57.145621Z"},"links":{"cited_paper":"/paper/2009.07810","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:dc2c508b1611cef594a536bea9807336dd474d4ed1dcb56526d09c63bac4e3dc","observation_id":"6dfc4dff-ef1d-4c24-a6e4-8c00c57c220e","resolution":{"observed_at":"2026-08-03T23:37:57.145621Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T23:37:57.368494Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:57.368494Z"},"links":{"citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:3753a6d1630720fc360dd20cacf29408e1b7738e067e2e8e2a49e6fc37910e77","observation_id":"2418ae4a-8ac0-41e1-8505-2b83fd498168","resolution":{"observed_at":"2026-08-03T23:37:57.368494Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.19735","last_updated":"2024-10-25T17:59:55Z","snapshot_observed_at":"2026-08-16T13:05:52.730029Z","submitted_at":"2024-10-25T17:59:55Z","title":"Model merging with SVD to tie the Knots","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.19735","snapshot_observed_at":"2026-08-03T23:37:57.489217Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:57.489217Z"},"links":{"cited_paper":"/paper/2410.19735","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:10821fa8e8efbd52cd2cf61ee4249e73c6e1ab4c4114c33198c6abf7b62a5706","observation_id":"ae7d71c4-e515-4e96-86a7-446eba686b9e","resolution":{"observed_at":"2026-08-03T23:37:57.489217Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.15915","last_updated":"2025-01-27T10:04:49Z","snapshot_observed_at":"2026-08-17T02:53:35.043466Z","submitted_at":"2025-01-27T10:04:49Z","title":"Parametric Retrieval Augmented Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.15915","snapshot_observed_at":"2026-08-03T23:37:57.601173Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:57.601173Z"},"links":{"cited_paper":"/paper/2501.15915","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:f1468f6e3593553194df7313fddf8329987b679621819eeb05a1adbf2c73665b","observation_id":"9c6ead3c-d3d2-4bdc-a18e-ae9c164a4560","resolution":{"observed_at":"2026-08-03T23:37:57.601173Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.23895","last_updated":"2025-05-06T03:04:20Z","snapshot_observed_at":"2026-08-16T12:45:25.409350Z","submitted_at":"2025-03-31T09:46:35Z","title":"Dynamic Parametric Retrieval Augmented Generation for Test-time Knowledge Enhancement","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.23895","snapshot_observed_at":"2026-08-03T23:37:57.741918Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:57.741918Z"},"links":{"cited_paper":"/paper/2503.23895","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:495491454351d28e018debbbb6ecae80f624580fecdc47f7fe587cca63bc6785","observation_id":"1a001a04-8f2b-4e93-82ac-6eea4dc30e8a","resolution":{"observed_at":"2026-08-03T23:37:57.741918Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T23:37:57.848285Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:57.848285Z"},"links":{"citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:87b70d0a86c99129b2adf62c33f6f0901143e2123d2879e0639a191a045d9085","observation_id":"0f2dc2c8-19aa-4a53-bc02-e08bb21d8eb7","resolution":{"observed_at":"2026-08-03T23:37:57.848285Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T23:37:57.920508Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:57.920508Z"},"links":{"citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:56c1a2e19a9a710c3dd5a59214953287e46fd71155b367d0bfbb9994558127dc","observation_id":"6136ddce-a010-42f6-836a-60d22e2c44ee","resolution":{"observed_at":"2026-08-03T23:37:57.920508Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.11836","last_updated":"2025-06-09T00:14:59Z","snapshot_observed_at":"2026-08-16T12:57:42.760127Z","submitted_at":"2025-02-17T14:31:00Z","title":"Model Generalization on Text Attribute Graphs: Principles with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.11836","snapshot_observed_at":"2026-08-03T23:37:58.012767Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:58.012767Z"},"links":{"cited_paper":"/paper/2502.11836","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:9139367a57cdd861cdde57340ff270d3d040754112b78fedec14b910f32a0efe","observation_id":"d8885888-f749-4fc0-8596-27c06e96d018","resolution":{"observed_at":"2026-08-03T23:37:58.012767Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.11504","last_updated":"2024-09-11T02:22:58Z","snapshot_observed_at":"2026-08-16T14:25:48.078062Z","submitted_at":"2024-01-21T14:28:41Z","title":"With Greater Text Comes Greater Necessity: Inference-Time Training Helps Long Text Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.11504","snapshot_observed_at":"2026-08-03T23:37:58.111327Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:58.111327Z"},"links":{"cited_paper":"/paper/2401.11504","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:0991271f9a3cd7217e900c2a0cd40c3c5112f4d8bd4740baac98a7019ea10792","observation_id":"2b37f74b-8458-4ea6-bf7d-be9e2d2cc8bb","resolution":{"observed_at":"2026-08-03T23:37:58.111327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.03771","last_updated":"2020-07-14T03:42:34Z","snapshot_observed_at":"2026-07-06T08:27:58.343233Z","submitted_at":"2019-10-09T03:23:22Z","title":"HuggingFace's Transformers: State-of-the-art Natural Language Processing","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.03771","snapshot_observed_at":"2026-08-03T23:37:58.199808Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:58.199808Z"},"links":{"cited_paper":"/paper/1910.03771","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:5de2668718f299f57368a6101703adc779642e2d97b15ba2dff1bd070713f569","observation_id":"8c0dca63-800b-4d98-8fff-ef4dc3354e99","resolution":{"observed_at":"2026-08-03T23:37:58.199808Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T23:37:58.290184Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:58.290184Z"},"links":{"citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:2105bb1bb685aa78a8df09d56f42a78d623b730cfcb197e14b8e3e142d641a37","observation_id":"5e1900ed-b78f-481b-8639-378ae05494bf","resolution":{"observed_at":"2026-08-03T23:37:58.290184Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.10671","last_updated":"2024-09-10T13:25:53Z","snapshot_observed_at":"2026-08-17T11:08:48.802438Z","submitted_at":"2024-07-15T12:35:42Z","title":"Qwen2 Technical Report","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.10671","snapshot_observed_at":"2026-08-03T23:37:58.381913Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:58.381913Z"},"links":{"cited_paper":"/paper/2407.10671","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:86a493c29ca39ef825cfa8117a29c20436ab5a3295cd2d38acc9a49677dc7601","observation_id":"16562c46-087b-4972-8263-5ad3112da8fb","resolution":{"observed_at":"2026-08-03T23:37:58.381913Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T23:37:58.460813Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:58.460813Z"},"links":{"citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:f12627b9484d4185f7d8cbb21a4cf7a7d3af25b2d1d9480a6dfdeed2cb4d4615","observation_id":"b92b102d-b40b-4045-95c6-dae83cf13a73","resolution":{"observed_at":"2026-08-03T23:37:58.460813Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.07197","last_updated":"2024-02-28T02:42:35Z","snapshot_observed_at":"2026-08-16T14:19:33.419601Z","submitted_at":"2024-02-11T13:24:13Z","title":"GraphTranslator: Aligning Graph Model to Large Language Model for Open-ended Tasks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.07197","snapshot_observed_at":"2026-08-03T23:37:58.571567Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:58.571567Z"},"links":{"cited_paper":"/paper/2402.07197","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:8fee4ec021bf90ec444ef54069a1736a4118a56098e2d344cf88f8657f4d5b77","observation_id":"826e047c-889e-430a-aeb6-0955aac5a369","resolution":{"observed_at":"2026-08-03T23:37:58.571567Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T23:37:58.667542Z","title":"A green apple is on the table at position (5, 10)","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:58.667542Z"},"links":{"citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:434bbcc54b313843d90a4241782209b0e7ad6f0f60b34c2a0ff712da51ee4518","observation_id":"ba6e0f14-50ff-4113-a7ac-9cb7c6339de9","resolution":{"observed_at":"2026-08-03T23:37:58.667542Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T23:37:58.741727Z","title":"Two sample questions must differ in at least one di- mension: Interrogative, Format, Focus","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:58.741727Z"},"links":{"citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:16e429f38decf2d6c014b4d687ddeabf69d1aa004f3b1f020f66c8405e7fa34e","observation_id":"b9bc91c8-3c1b-45c0-8dcd-66b145327075","resolution":{"observed_at":"2026-08-03T23:37:58.741727Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T23:37:58.835144Z","title":"how many","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:58.835144Z"},"links":{"citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:cfc1bf1e6998b6954291aa4726eea4de71f294036658585e2ba4a415eb9ba594","observation_id":"dfda891c-309e-4b63-8c47-7186f8e43959","resolution":{"observed_at":"2026-08-03T23:37:58.835144Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.13269","last_updated":"2024-08-19T03:31:19Z","snapshot_observed_at":"2026-08-16T15:13:34.132588Z","submitted_at":"2023-07-25T05:39:21Z","title":"LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.13269","snapshot_observed_at":"2026-08-03T23:37:55.781717Z","title":"arXiv preprint arXiv:2307.13269(2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:55.781717Z"},"links":{"cited_paper":"/paper/2307.13269","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:95fc403293e633cfc1afd847d4a0db7118202812b75ef11c8d33f6d61de1801a","observation_id":"1c3460a2-315e-4135-b7db-f1f8ca6f0e8e","resolution":{"observed_at":"2026-08-03T23:37:55.781717Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T23:37:54.908843Z","title":"InInternational Conference on Machine Learning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:54.908843Z"},"links":{"citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:f6a4ddb4783cedf2e48a78eae325fc463342d92d8211c3eb5a410928c4e138a1","observation_id":"cf38ab22-7413-4ba5-bff7-2ffd3a8be792","resolution":{"observed_at":"2026-08-03T23:37:54.908843Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-16T01:36:11.177266Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models"},"reference_resolution":{"displayed":50,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":50,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":50},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 1 inbound Pith citation observation for arXiv:2511.07457."}