{"as_of":"2026-08-18T19:09:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:43846859f369542ce9740cc7f1640d564a6faf5e65526156cd6a7cf1f717c425","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":8,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":8,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":8,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T18:32:03.898904Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2402.13449","last_updated":"2024-02-21T01:00:17Z","snapshot_observed_at":"2026-08-16T14:16:46.564105Z","submitted_at":"2024-02-21T01:00:17Z","title":"CAMELoT: Towards Large Language Models with Training-Free Consolidated Associative Memory","version":1},"cited_work":{"arxiv_id":"2402.13449","doi":"10.48550/arxiv.2402.13449","metadata_source":"arxiv_reference","pith_arxiv_id":"2402.13449","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Camelot: Towards large language models with training-free consolidated associative memory","venue":"arXiv (Cornell University)","work_id":"68a8ca8c-adaf-41e9-a185-0a04d118564d","year":2024},"citing_paper":{"arxiv_id":"2501.00663","last_updated":"2024-12-31T22:32:03Z","snapshot_observed_at":"2026-08-16T10:45:05.594811Z","submitted_at":"2024-12-31T22:32:03Z","title":"Titans: Learning to Memorize at Test Time","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-14T22:08:14.982302Z"},"links":{"cited_paper":"/paper/2402.13449","citing_paper":"/paper/2501.00663"},"observation_digest":"sha256:d8b557a0916a6f620f3dc5324ef6e91e36015e33308531db4b5178230d2f9e34","observation_id":"ef098124-ac88-48d1-8176-ccd975d81efe","resolution":{"observed_at":"2026-05-14T22:08:15.250278Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.13449","last_updated":"2024-02-21T01:00:17Z","snapshot_observed_at":"2026-08-16T14:16:46.564105Z","submitted_at":"2024-02-21T01:00:17Z","title":"CAMELoT: Towards Large Language Models with Training-Free Consolidated Associative Memory","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.13449","snapshot_observed_at":"2026-08-09T18:32:03.898904Z","title":"Camelot: Towards large language models 10 M+: Extending MemoryLLM with Scalable Long-Term Memory with training-free consolidated associative memory.arXiv preprint arXiv:2402.13449,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.00592","last_updated":"2025-05-30T14:40:56Z","snapshot_observed_at":"2026-08-15T21:25:52.230059Z","submitted_at":"2025-02-01T23:13:10Z","title":"M+: Extending MemoryLLM with Scalable Long-Term Memory","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-09T18:32:03.898904Z"},"links":{"cited_paper":"/paper/2402.13449","citing_paper":"/paper/2502.00592"},"observation_digest":"sha256:52b48c54002781efdbb4a8e0d4674eeabae4dde897cbefce9b7ee4ec90ca3754","observation_id":"c0364a55-dcc9-4a2c-96fb-1f7365dce364","resolution":{"observed_at":"2026-08-09T18:32:03.898904Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.13449","last_updated":"2024-02-21T01:00:17Z","snapshot_observed_at":"2026-08-16T14:16:46.564105Z","submitted_at":"2024-02-21T01:00:17Z","title":"CAMELoT: Towards Large Language Models with Training-Free Consolidated Associative Memory","version":1},"cited_work":{"arxiv_id":"2402.13449","doi":"10.48550/arxiv.2402.13449","metadata_source":"arxiv_reference","pith_arxiv_id":"2402.13449","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Camelot: Towards large language models with training-free consolidated associative memory","venue":"arXiv (Cornell University)","work_id":"68a8ca8c-adaf-41e9-a185-0a04d118564d","year":2024},"citing_paper":{"arxiv_id":"2502.05171","last_updated":"2025-02-17T17:14:04Z","snapshot_observed_at":"2026-08-15T00:53:48.099058Z","submitted_at":"2025-02-07T18:55:02Z","title":"Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach","version":2},"reference_index":70,"source":"arxiv_source","source_observed_at":"2026-05-12T15:39:40.845703Z"},"links":{"cited_paper":"/paper/2402.13449","citing_paper":"/paper/2502.05171"},"observation_digest":"sha256:04acf7141973051f444f2d8b32be4af801fc3c4389b91758dbb8a89b02c51d57","observation_id":"2337a906-3d91-452b-87cc-999181a596bc","resolution":{"observed_at":"2026-05-12T15:39:41.305467Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.13449","last_updated":"2024-02-21T01:00:17Z","snapshot_observed_at":"2026-08-16T14:16:46.564105Z","submitted_at":"2024-02-21T01:00:17Z","title":"CAMELoT: Towards Large Language Models with Training-Free Consolidated Associative Memory","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.13449","snapshot_observed_at":"2026-08-07T12:44:17.822369Z","title":"CAMELoT: Towards Large Language Models with Training-Free Consolidated Associative Memory","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23735","last_updated":"2025-05-29T17:57:16Z","snapshot_observed_at":"2026-08-14T11:18:31.036773Z","submitted_at":"2025-05-29T17:57:16Z","title":"ATLAS: Learning to Optimally Memorize the Context at Test Time","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T12:44:17.822369Z"},"links":{"cited_paper":"/paper/2402.13449","citing_paper":"/paper/2505.23735"},"observation_digest":"sha256:e04ed70efd0d6090918484e17702c1f5e172688959ef819b0473d9d3b2f83c45","observation_id":"7081f72f-6da4-4bdb-824c-7d48c125f266","resolution":{"observed_at":"2026-08-07T12:44:17.822369Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.13449","last_updated":"2024-02-21T01:00:17Z","snapshot_observed_at":"2026-08-16T14:16:46.564105Z","submitted_at":"2024-02-21T01:00:17Z","title":"CAMELoT: Towards Large Language Models with Training-Free Consolidated Associative Memory","version":1},"cited_work":{"arxiv_id":"2402.13449","doi":"10.48550/arxiv.2402.13449","metadata_source":"arxiv_reference","pith_arxiv_id":"2402.13449","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Camelot: Towards large language models with training-free consolidated associative memory","venue":"arXiv (Cornell University)","work_id":"68a8ca8c-adaf-41e9-a185-0a04d118564d","year":2024},"citing_paper":{"arxiv_id":"2507.07957","last_updated":"2025-07-10T17:40:11Z","snapshot_observed_at":"2026-08-16T07:12:52.228757Z","submitted_at":"2025-07-10T17:40:11Z","title":"MIRIX: Multi-Agent Memory System for LLM-Based Agents","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-15T05:57:52.610922Z"},"links":{"cited_paper":"/paper/2402.13449","citing_paper":"/paper/2507.07957"},"observation_digest":"sha256:fefb9406a089d33e1a5b9a7a213bb3e6284fe6ac2172e4a9590e159f228c5182","observation_id":"c010a8bc-8de4-410b-b0b5-10253169ea13","resolution":{"observed_at":"2026-05-15T05:57:52.763775Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.13449","last_updated":"2024-02-21T01:00:17Z","snapshot_observed_at":"2026-08-16T14:16:46.564105Z","submitted_at":"2024-02-21T01:00:17Z","title":"CAMELoT: Towards Large Language Models with Training-Free Consolidated Associative Memory","version":1},"cited_work":{"arxiv_id":"2402.13449","doi":"10.48550/arxiv.2402.13449","metadata_source":"arxiv_reference","pith_arxiv_id":"2402.13449","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Camelot: Towards large language models with training-free consolidated associative memory","venue":"arXiv (Cornell University)","work_id":"68a8ca8c-adaf-41e9-a185-0a04d118564d","year":2024},"citing_paper":{"arxiv_id":"2510.07048","last_updated":"2026-04-09T10:25:15Z","snapshot_observed_at":"2026-08-15T04:55:52.162621Z","submitted_at":"2025-10-08T14:16:20Z","title":"Search-R3: Unifying Reasoning and Embedding in Large Language Models","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-18T09:25:06.990685Z"},"links":{"cited_paper":"/paper/2402.13449","citing_paper":"/paper/2510.07048"},"observation_digest":"sha256:2a114e770890dfb23fb6c2103b2c8f0a7786f4794a39bcbdca3db581404107cd","observation_id":"2c716df9-a973-40d4-893f-e272db52bb00","resolution":{"observed_at":"2026-05-18T09:26:10.549528Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.13449","last_updated":"2024-02-21T01:00:17Z","snapshot_observed_at":"2026-08-16T14:16:46.564105Z","submitted_at":"2024-02-21T01:00:17Z","title":"CAMELoT: Towards Large Language Models with Training-Free Consolidated Associative Memory","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.13449","snapshot_observed_at":"2026-08-02T19:33:03.543426Z","title":"Camelot: Towards large language mod- els with training-free consolidated associative memory","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2603.01761","last_updated":"2026-06-16T11:36:48Z","snapshot_observed_at":"2026-08-12T22:34:50.284520Z","submitted_at":"2026-03-02T11:40:05Z","title":"Position: Modular Memory is the Key to Continual Learning Agents","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-02T19:33:03.543426Z"},"links":{"cited_paper":"/paper/2402.13449","citing_paper":"/paper/2603.01761"},"observation_digest":"sha256:360efe6a8c2e024dffb921a0ae187f68dc07f45fcc5f5a3b0f995e7722300b25","observation_id":"baec0d59-4fb6-48f0-9d23-ff9b6ee200c9","resolution":{"observed_at":"2026-08-02T19:33:03.543426Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.13449","last_updated":"2024-02-21T01:00:17Z","snapshot_observed_at":"2026-08-16T14:16:46.564105Z","submitted_at":"2024-02-21T01:00:17Z","title":"CAMELoT: Towards Large Language Models with Training-Free Consolidated Associative Memory","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.13449","snapshot_observed_at":"2026-07-14T04:23:21.000846Z","title":"arXiv preprint arXiv:2402.13449 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.11614","last_updated":"2026-07-13T14:37:24Z","snapshot_observed_at":"2026-08-15T06:02:40.856312Z","submitted_at":"2026-07-13T14:37:24Z","title":"Extending LLM Context via Associative Recurrent Memory","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-07-14T04:23:21.000846Z"},"links":{"cited_paper":"/paper/2402.13449","citing_paper":"/paper/2607.11614"},"observation_digest":"sha256:dd46c912793c579663f678733bab9c68e8d73d5deb4b6c37ea7888e39a43b666","observation_id":"c56e311a-e789-41c8-b385-760f7da2936f","resolution":{"observed_at":"2026-07-14T04:23:21.000846Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2402.13449/citation-record","integrity":"/paper/2402.13449/integrity","json":"/paper/2402.13449/citation-record.json","paper":"/paper/2402.13449"},"outbound":[],"paper":{"arxiv_id":"2402.13449","last_updated":"2024-02-21T01:00:17Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-16T14:16:46.564105Z","submitted_at":"2024-02-21T01:00:17Z","title":"CAMELoT: Towards Large Language Models with Training-Free Consolidated Associative Memory"},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2402.13449."}