{"as_of":"2026-08-11T01:36:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:08870078bf7a3055b88f6e0c45af5b7aba36fb5e906ec48cb5f0776820f87299","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":"2026-08-10T06:31:04.303077+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":"2026-08-10T14:26:48.265673Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-07T11:42:35.557822Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2411.15385","last_updated":"2024-11-23T00:00:28Z","snapshot_observed_at":"2026-07-06T19:55:51.415524Z","submitted_at":"2024-11-23T00:00:28Z","title":"Gradient dynamics for low-rank fine-tuning beyond kernels","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.15385","snapshot_observed_at":"2026-08-10T14:26:48.265673Z","title":"Gradient dynamics for low-rank fine-tuning beyond kernels,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.15361","last_updated":"2025-08-21T21:26:39Z","snapshot_observed_at":"2026-08-10T19:15:36.118847Z","submitted_at":"2025-01-26T01:56:25Z","title":"Decentralized Low-Rank Fine-Tuning of Large Language Models","version":5},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-10T14:26:48.265673Z"},"links":{"cited_paper":"/paper/2411.15385","citing_paper":"/paper/2501.15361"},"observation_digest":"sha256:e519cb75a62e5f4c5a48d8bd08a08248c4f25a8ffcbfccd2a21cee0ed608a8e4","observation_id":"3eb0d64b-4891-4e21-aa78-e493ce0d0a48","resolution":{"observed_at":"2026-08-10T14:26:48.265673Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.15385","last_updated":"2024-11-23T00:00:28Z","snapshot_observed_at":"2026-07-06T19:55:51.415524Z","submitted_at":"2024-11-23T00:00:28Z","title":"Gradient dynamics for low-rank fine-tuning beyond kernels","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.15385","snapshot_observed_at":"2026-08-09T16:14:02.937714Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.01235","last_updated":"2025-06-23T09:29:57Z","snapshot_observed_at":"2026-08-09T15:55:13.459556Z","submitted_at":"2025-02-03T10:50:03Z","title":"LoRA-One: One-Step Full Gradient Could Suffice for Fine-Tuning Large Language Models, Provably and Efficiently","version":3},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-09T16:14:02.937714Z"},"links":{"cited_paper":"/paper/2411.15385","citing_paper":"/paper/2502.01235"},"observation_digest":"sha256:0d1447188ec5126f50d029c13f645b94c39e63d64abaacc04eb554cb0d97ef5c","observation_id":"bf0b7bf0-f1c0-48d5-acaf-4b6dc09c3b45","resolution":{"observed_at":"2026-08-09T16:14:02.937714Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.15385","last_updated":"2024-11-23T00:00:28Z","snapshot_observed_at":"2026-07-06T19:55:51.415524Z","submitted_at":"2024-11-23T00:00:28Z","title":"Gradient dynamics for low-rank fine-tuning beyond kernels","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.15385","snapshot_observed_at":"2026-08-07T21:56:27.937594Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.09376","last_updated":"2025-06-03T01:42:41Z","snapshot_observed_at":"2026-08-10T07:38:47.401063Z","submitted_at":"2025-02-13T14:45:11Z","title":"LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail)","version":3},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-07T21:56:27.937594Z"},"links":{"cited_paper":"/paper/2411.15385","citing_paper":"/paper/2502.09376"},"observation_digest":"sha256:43fcc029aa48845af021d556bc633cc9af5d6d0cb242fc69362fa3b6e6ac9e8b","observation_id":"98c220fe-5550-4078-a9af-aa78bbf0f120","resolution":{"observed_at":"2026-08-07T21:56:27.937594Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.15385","last_updated":"2024-11-23T00:00:28Z","snapshot_observed_at":"2026-07-06T19:55:51.415524Z","submitted_at":"2024-11-23T00:00:28Z","title":"Gradient dynamics for low-rank fine-tuning beyond kernels","version":1},"cited_work":{"arxiv_id":"2411.15385","doi":null,"metadata_source":"pith","pith_arxiv_id":"2411.15385","snapshot_observed_at":"2026-08-07T11:42:35.557822Z","title":"Gradient dynamics for low-rank fine-tuning beyond kernels","venue":"cs.LG","work_id":"49e855d2-69aa-4e4d-a702-a4bf2ec1a076","year":2024},"citing_paper":{"arxiv_id":"2506.01656","last_updated":"2025-08-15T20:45:26Z","snapshot_observed_at":"2026-08-07T11:34:07.584118Z","submitted_at":"2025-06-02T13:26:44Z","title":"Mixture of Experts Provably Detect and Learn the Latent Cluster Structure in Gradient-Based Learning","version":2},"reference_index":1262,"source":"pdf_text","source_observed_at":"2026-08-07T11:42:35.441065Z"},"links":{"cited_paper":"/paper/2411.15385","citing_paper":"/paper/2506.01656"},"observation_digest":"sha256:792f238a548df44c707b109415ef12b6b57f78673db813b045fb5e4c9ceed35a","observation_id":"041102b9-2251-4a42-8ab1-c4229f97642f","resolution":{"observed_at":"2026-08-07T11:42:35.567643Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2411.15385/citation-record","integrity":"/paper/2411.15385/integrity","json":"/paper/2411.15385/citation-record.json","paper":"/paper/2411.15385"},"outbound":[],"paper":{"arxiv_id":"2411.15385","last_updated":"2024-11-23T00:00:28Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T19:55:51.415524Z","submitted_at":"2024-11-23T00:00:28Z","title":"Gradient dynamics for low-rank fine-tuning beyond kernels"},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2411.15385."}