{"as_of":"2026-08-07T23:30:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:77fe73bcfb472afdb3e03df1bf23febbe0c78b6c532cc4ffaa7f399f9564fd84","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T11:20:43.149426Z","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":1,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2405.18886","last_updated":"2024-11-03T20:25:29Z","snapshot_observed_at":"2026-08-04T06:04:53.921680Z","submitted_at":"2024-05-29T08:42:30Z","title":"Compressing Large Language Models using Low Rank and Low Precision Decomposition","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18886","snapshot_observed_at":"2026-08-07T11:20:43.149426Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.02818","last_updated":"2025-06-03T12:47:23Z","snapshot_observed_at":"2026-08-07T11:12:49.745940Z","submitted_at":"2025-06-03T12:47:23Z","title":"ProcrustesGPT: Compressing LLMs with Structured Matrices and Orthogonal Transformations","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-07T11:20:43.149426Z"},"links":{"cited_paper":"/paper/2405.18886","citing_paper":"/paper/2506.02818"},"observation_digest":"sha256:64a63101ae76e74b73e6de6b59858931727621d1843151907d5f72aa0d15376f","observation_id":"7da6e152-8ad4-4cea-ac32-69c7dc5cf007","resolution":{"observed_at":"2026-08-07T11:20:43.149426Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18886","last_updated":"2024-11-03T20:25:29Z","snapshot_observed_at":"2026-08-04T06:04:53.921680Z","submitted_at":"2024-05-29T08:42:30Z","title":"Compressing Large Language Models using Low Rank and Low Precision Decomposition","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18886","snapshot_observed_at":"2026-08-06T18:07:17.680950Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.09428","last_updated":"2025-07-12T23:39:14Z","snapshot_observed_at":"2026-08-07T02:29:11.658442Z","submitted_at":"2025-07-12T23:39:14Z","title":"On Information Geometry and Iterative Optimization in Model Compression: Operator Factorization","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-06T18:07:17.680950Z"},"links":{"cited_paper":"/paper/2405.18886","citing_paper":"/paper/2507.09428"},"observation_digest":"sha256:9c5c3d6e986fc64b9c69c6c02ae6e1a3e531906d62f3d44696ab71a148901a69","observation_id":"f7cc1034-a6d6-4036-bc85-fa35fd6a9907","resolution":{"observed_at":"2026-08-06T18:07:17.680950Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18886","last_updated":"2024-11-03T20:25:29Z","snapshot_observed_at":"2026-08-04T06:04:53.921680Z","submitted_at":"2024-05-29T08:42:30Z","title":"Compressing Large Language Models using Low Rank and Low Precision Decomposition","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18886","snapshot_observed_at":"2026-08-06T15:24:45.783003Z","title":"Goldsmith, and Mert Pilanci","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.15977","last_updated":"2025-07-21T18:17:18Z","snapshot_observed_at":"2026-08-06T23:33:13.768980Z","submitted_at":"2025-07-21T18:17:18Z","title":"On the transferability of Sparse Autoencoders for interpreting compressed models","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-06T15:24:45.783003Z"},"links":{"cited_paper":"/paper/2405.18886","citing_paper":"/paper/2507.15977"},"observation_digest":"sha256:2e59728b50894cadabda7ff2bd898c0626c0e74ac1f535ad2d9644e540726b7a","observation_id":"b24e3611-12d8-4704-a2db-70d60ead3a6b","resolution":{"observed_at":"2026-08-06T15:24:45.783003Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18886","last_updated":"2024-11-03T20:25:29Z","snapshot_observed_at":"2026-08-04T06:04:53.921680Z","submitted_at":"2024-05-29T08:42:30Z","title":"Compressing Large Language Models using Low Rank and Low Precision Decomposition","version":2},"cited_work":{"arxiv_id":"2405.18886","doi":"10.48550/arxiv.2405.18886","metadata_source":"arxiv_reference","pith_arxiv_id":"2405.18886","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"and Pilanci, Mert , month = nov, year =","venue":"arXiv (Cornell University)","work_id":"d5934b59-b2f3-40be-a2ec-9bcadd25f022","year":null},"citing_paper":{"arxiv_id":"2606.07098","last_updated":"2026-06-05T09:48:58Z","snapshot_observed_at":"2026-08-04T03:17:05.076864Z","submitted_at":"2026-06-05T09:48:58Z","title":"SigmaScale: LLM Compression with SVD-based Low-Rank Decomposition and Learned Scaling Matrices","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-06-27T22:04:32.524875Z"},"links":{"cited_paper":"/paper/2405.18886","citing_paper":"/paper/2606.07098"},"observation_digest":"sha256:e40cf213cd6cbbcae8790b9ad7e6d01660db115f4bbb36de0c19a1b30720a943","observation_id":"3c9189af-1abb-46b4-a642-9bd527f4b9f1","resolution":{"observed_at":"2026-06-27T22:11:20.850073Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2405.18886/citation-record","integrity":"/paper/2405.18886/integrity","json":"/paper/2405.18886/citation-record.json","paper":"/paper/2405.18886"},"outbound":[],"paper":{"arxiv_id":"2405.18886","last_updated":"2024-11-03T20:25:29Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-04T06:04:53.921680Z","submitted_at":"2024-05-29T08:42:30Z","title":"Compressing Large Language Models using Low Rank and Low Precision Decomposition"},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2405.18886."}