{"as_of":"2026-08-13T17:02:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:38858112c983003dd0f7b35d9b3acb5c861bff224d7cda311f5919b2cdfb070b","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":6,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":6,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":6,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":6,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T10:27:43.196823Z","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":"2026-05-16T08:07:34.306488Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2404.03626","last_updated":"2024-12-12T23:03:54Z","snapshot_observed_at":"2026-08-13T00:37:31.776122Z","submitted_at":"2024-04-04T17:48:28Z","title":"Training LLMs over Neurally Compressed Text","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03626","snapshot_observed_at":"2026-08-11T10:27:43.196823Z","title":"arXiv:2404.03626","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.16642","last_updated":"2024-12-24T04:20:18Z","snapshot_observed_at":"2026-08-11T15:37:23.283807Z","submitted_at":"2024-12-21T14:24:32Z","title":"L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T10:27:43.196823Z"},"links":{"cited_paper":"/paper/2404.03626","citing_paper":"/paper/2412.16642"},"observation_digest":"sha256:73d61efb5f2caf32f2597ad3178f1fccda5df94010be3e4865d49132aa7d6163","observation_id":"b23d894d-9ad1-4b35-a56e-6f0a8a8fb56d","resolution":{"observed_at":"2026-08-11T10:27:43.196823Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03626","last_updated":"2024-12-12T23:03:54Z","snapshot_observed_at":"2026-08-13T00:37:31.776122Z","submitted_at":"2024-04-04T17:48:28Z","title":"Training LLMs over Neurally Compressed Text","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03626","snapshot_observed_at":"2026-08-08T16:40:27.090758Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06139","last_updated":"2025-05-22T05:45:05Z","snapshot_observed_at":"2026-08-10T04:40:40.719875Z","submitted_at":"2025-02-10T04:02:18Z","title":"LCIRC: A Recurrent Compression Approach for Efficient Long-form Context and Query Dependent Modeling in LLMs","version":2},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-08T16:40:27.090758Z"},"links":{"cited_paper":"/paper/2404.03626","citing_paper":"/paper/2502.06139"},"observation_digest":"sha256:35a3ca029f0277d9fba7d0d3fc4ed95899e4ac1d3f956bd44983acb517e5093c","observation_id":"077fd05e-ef55-4c6c-9f93-bf5fd87e668d","resolution":{"observed_at":"2026-08-08T16:40:27.090758Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03626","last_updated":"2024-12-12T23:03:54Z","snapshot_observed_at":"2026-08-13T00:37:31.776122Z","submitted_at":"2024-04-04T17:48:28Z","title":"Training LLMs over Neurally Compressed Text","version":3},"cited_work":{"arxiv_id":"2404.03626","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2404.03626","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Lester, B., Lee, J., Alemi, A., Pennington, J., Roberts, A., Sohl-Dickstein, J., and Constant, N","venue":null,"work_id":"93265594-c964-45fd-ac73-18a3f46da9ae","year":2024},"citing_paper":{"arxiv_id":"2602.04289","last_updated":"2026-05-14T17:33:56Z","snapshot_observed_at":"2026-08-11T02:55:58.869095Z","submitted_at":"2026-02-04T07:36:46Z","title":"Proxy Compression for Language Modeling","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-16T08:03:01.274736Z"},"links":{"cited_paper":"/paper/2404.03626","citing_paper":"/paper/2602.04289"},"observation_digest":"sha256:cab5c5687acc0c2b566de0bbeffd46c0bab20f791650cf58c150f076a89e4f06","observation_id":"9fc8d7b9-3fdb-4b30-8fe5-7b60013d469b","resolution":{"observed_at":"2026-05-16T08:07:34.308507Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03626","last_updated":"2024-12-12T23:03:54Z","snapshot_observed_at":"2026-08-13T00:37:31.776122Z","submitted_at":"2024-04-04T17:48:28Z","title":"Training LLMs over Neurally Compressed Text","version":3},"cited_work":{"arxiv_id":"2404.03626","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2404.03626","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Lester, B., Lee, J., Alemi, A., Pennington, J., Roberts, A., Sohl-Dickstein, J., and Constant, N","venue":null,"work_id":"93265594-c964-45fd-ac73-18a3f46da9ae","year":2024},"citing_paper":{"arxiv_id":"2605.09630","last_updated":"2026-05-10T16:18:22Z","snapshot_observed_at":"2026-07-31T18:27:32.630942Z","submitted_at":"2026-05-10T16:18:22Z","title":"Scratchpad Patching: Decoupling Compute from Patch Size in Byte-Level Language Models","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-05-12T04:05:28.713898Z"},"links":{"cited_paper":"/paper/2404.03626","citing_paper":"/paper/2605.09630"},"observation_digest":"sha256:fe9f861eb1d78ca5d9ce0f4e18f3c576b5f82bb16f8eb0e757ba8c90c06e125e","observation_id":"2f26fe72-8ceb-49ad-9377-9faedc558799","resolution":{"observed_at":"2026-05-12T06:36:28.952129Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03626","last_updated":"2024-12-12T23:03:54Z","snapshot_observed_at":"2026-08-13T00:37:31.776122Z","submitted_at":"2024-04-04T17:48:28Z","title":"Training LLMs over Neurally Compressed Text","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03626","snapshot_observed_at":"2026-08-04T08:28:17.077324Z","title":"Lester, J","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.02376","last_updated":"2026-08-06T13:36:52Z","snapshot_observed_at":"2026-08-09T23:12:25.100583Z","submitted_at":"2026-08-03T15:20:36Z","title":"Token-Native Storage: Read and Write in your Agent's Language","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-04T08:28:17.077324Z"},"links":{"cited_paper":"/paper/2404.03626","citing_paper":"/paper/2608.02376"},"observation_digest":"sha256:753433df7f7e577037ff1f4f13971df5f6503bf6df3487f21497c9f59dd5a8b8","observation_id":"ac72afa8-2177-4b03-acdc-e8d28b0d67ad","resolution":{"observed_at":"2026-08-04T08:28:17.077324Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03626","last_updated":"2024-12-12T23:03:54Z","snapshot_observed_at":"2026-08-13T00:37:31.776122Z","submitted_at":"2024-04-04T17:48:28Z","title":"Training LLMs over Neurally Compressed Text","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03626","snapshot_observed_at":"2026-08-07T01:05:13.144091Z","title":"Lester, J","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.02376","last_updated":"2026-08-06T13:36:52Z","snapshot_observed_at":"2026-08-09T23:12:25.100583Z","submitted_at":"2026-08-03T15:20:36Z","title":"Token-Native Storage: Read and Write in your Agent's Language","version":2},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-07T01:05:13.144091Z"},"links":{"cited_paper":"/paper/2404.03626","citing_paper":"/paper/2608.02376"},"observation_digest":"sha256:91bb028aac3476b7941c25c4bb08d906ea22fafc66664879b7dde90b25460db9","observation_id":"7f8dd007-07a2-4fce-90a8-7f9df8ee990b","resolution":{"observed_at":"2026-08-07T01:05:13.144091Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2404.03626/citation-record","integrity":"/paper/2404.03626/integrity","json":"/paper/2404.03626/citation-record.json","paper":"/paper/2404.03626"},"outbound":[],"paper":{"arxiv_id":"2404.03626","last_updated":"2024-12-12T23:03:54Z","latest_version":3,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-13T00:37:31.776122Z","submitted_at":"2024-04-04T17:48:28Z","title":"Training LLMs over Neurally Compressed Text"},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2404.03626."}