{"as_of":"2026-08-08T19:35:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5696ece2ca8af04f4a4c92d6daf8cf7e0aeb5c023b3bfd7c4bba86fcb95aa86a","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":"2026-08-08T06:32:00.761636+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":"2026-08-07T00:25:29.196199Z","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":"2026-07-03T14:08:21.874920Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2409.14396","last_updated":"2025-05-24T12:19:58Z","snapshot_observed_at":"2026-07-06T19:19:24.759288Z","submitted_at":"2024-09-22T11:24:10Z","title":"Flat-LoRA: Low-Rank Adaptation over a Flat Loss Landscape","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.14396","snapshot_observed_at":"2026-08-07T00:25:29.196199Z","title":"Flat-LoRA: Low-rank adaption over a flat loss landscape.arXiv:2409.14396, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.14280","last_updated":"2025-06-17T07:49:43Z","snapshot_observed_at":"2026-08-07T00:15:47.470312Z","submitted_at":"2025-06-17T07:49:43Z","title":"Improving LoRA with Variational Learning","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T00:25:29.196199Z"},"links":{"cited_paper":"/paper/2409.14396","citing_paper":"/paper/2506.14280"},"observation_digest":"sha256:625ee0478f5b45f015011ac41aae5a49b2b8885bc336721448ab9d6578adc35b","observation_id":"4b8c8797-c967-4302-985e-39f25c8c08e0","resolution":{"observed_at":"2026-08-07T00:25:29.196199Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.14396","last_updated":"2025-05-24T12:19:58Z","snapshot_observed_at":"2026-07-06T19:19:24.759288Z","submitted_at":"2024-09-22T11:24:10Z","title":"Flat-LoRA: Low-Rank Adaptation over a Flat Loss Landscape","version":2},"cited_work":{"arxiv_id":"2409.14396","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.14396","snapshot_observed_at":"2026-07-03T14:08:21.874920Z","title":"Flat-lora: Low-rank adaptation over a flat loss landscape","venue":null,"work_id":"c35b5acd-e54f-49fa-8569-47373776ed0a","year":2024},"citing_paper":{"arxiv_id":"2604.04516","last_updated":"2026-04-21T01:46:58Z","snapshot_observed_at":"2026-08-01T19:37:28.987248Z","submitted_at":"2026-04-06T08:27:55Z","title":"GAIN: Multiplicative Modulation for Domain Adaptation","version":2},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-05-10T20:29:15.163234Z"},"links":{"cited_paper":"/paper/2409.14396","citing_paper":"/paper/2604.04516"},"observation_digest":"sha256:84ee2e73b5bbd168e3765c8b5924834a641f6d138bae9a8ea7251ffa568c8618","observation_id":"fbbeeddc-b77e-4c61-8fbe-e82934ba23e3","resolution":{"observed_at":"2026-05-10T21:55:50.677943Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.14396","last_updated":"2025-05-24T12:19:58Z","snapshot_observed_at":"2026-07-06T19:19:24.759288Z","submitted_at":"2024-09-22T11:24:10Z","title":"Flat-LoRA: Low-Rank Adaptation over a Flat Loss Landscape","version":2},"cited_work":{"arxiv_id":"2409.14396","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.14396","snapshot_observed_at":"2026-07-03T14:08:21.874920Z","title":"Flat-lora: Low-rank adaptation over a flat loss landscape","venue":null,"work_id":"c35b5acd-e54f-49fa-8569-47373776ed0a","year":2024},"citing_paper":{"arxiv_id":"2605.13652","last_updated":"2026-05-19T00:27:00Z","snapshot_observed_at":"2026-07-06T23:25:11.623026Z","submitted_at":"2026-05-13T15:11:37Z","title":"Beyond Perplexity: A Geometric and Spectral Study of Low-Rank Pre-Training","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-14T19:19:18.275446Z"},"links":{"cited_paper":"/paper/2409.14396","citing_paper":"/paper/2605.13652"},"observation_digest":"sha256:e7a95e292308d1a4c43d4cd5e51b60d145646f594f3fe2fd055554092b5645f6","observation_id":"31e2af1f-eed8-40a5-9caf-e401744ecd1c","resolution":{"observed_at":"2026-05-14T19:19:23.594846Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.14396","last_updated":"2025-05-24T12:19:58Z","snapshot_observed_at":"2026-07-06T19:19:24.759288Z","submitted_at":"2024-09-22T11:24:10Z","title":"Flat-LoRA: Low-Rank Adaptation over a Flat Loss Landscape","version":2},"cited_work":{"arxiv_id":"2409.14396","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.14396","snapshot_observed_at":"2026-07-03T14:08:21.874920Z","title":"Flat-lora: Low-rank adaptation over a flat loss landscape","venue":null,"work_id":"c35b5acd-e54f-49fa-8569-47373776ed0a","year":2024},"citing_paper":{"arxiv_id":"2605.13652","last_updated":"2026-05-19T00:27:00Z","snapshot_observed_at":"2026-07-06T23:25:11.623026Z","submitted_at":"2026-05-13T15:11:37Z","title":"Beyond Perplexity: A Geometric and Spectral Study of Low-Rank Pre-Training","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-20T20:24:26.681383Z"},"links":{"cited_paper":"/paper/2409.14396","citing_paper":"/paper/2605.13652"},"observation_digest":"sha256:cff287eff4bd6ace92ff2aacc3154a1781981ac0e590aefd34db282ed24e2de7","observation_id":"dd19965f-c5c3-4d2c-a440-07a91b5ed391","resolution":{"observed_at":"2026-05-20T20:28:59.919870Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.14396","last_updated":"2025-05-24T12:19:58Z","snapshot_observed_at":"2026-07-06T19:19:24.759288Z","submitted_at":"2024-09-22T11:24:10Z","title":"Flat-LoRA: Low-Rank Adaptation over a Flat Loss Landscape","version":2},"cited_work":{"arxiv_id":"2409.14396","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.14396","snapshot_observed_at":"2026-07-03T14:08:21.874920Z","title":"Flat-lora: Low-rank adaptation over a flat loss landscape","venue":null,"work_id":"c35b5acd-e54f-49fa-8569-47373776ed0a","year":2024},"citing_paper":{"arxiv_id":"2606.10488","last_updated":"2026-06-09T07:03:43Z","snapshot_observed_at":"2026-08-06T17:20:13.744778Z","submitted_at":"2026-06-09T07:03:43Z","title":"5% > 100%: Flatness Preference is All You Need for Multimodal Parameter-Efficient Fine-Tuning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-06-27T14:03:24.516255Z"},"links":{"cited_paper":"/paper/2409.14396","citing_paper":"/paper/2606.10488"},"observation_digest":"sha256:2349bf387a538ebc078e2a4571970ecde8ce61d1427723b6b2b333cf4988c4d5","observation_id":"29bb3a27-d8f5-45e8-a5d9-eee2f46d3cce","resolution":{"observed_at":"2026-07-03T04:17:37.219830Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.14396","last_updated":"2025-05-24T12:19:58Z","snapshot_observed_at":"2026-07-06T19:19:24.759288Z","submitted_at":"2024-09-22T11:24:10Z","title":"Flat-LoRA: Low-Rank Adaptation over a Flat Loss Landscape","version":2},"cited_work":{"arxiv_id":"2409.14396","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.14396","snapshot_observed_at":"2026-07-03T14:08:21.874920Z","title":"Flat-lora: Low-rank adaptation over a flat loss landscape","venue":null,"work_id":"c35b5acd-e54f-49fa-8569-47373776ed0a","year":2024},"citing_paper":{"arxiv_id":"2606.12883","last_updated":"2026-06-11T04:19:32Z","snapshot_observed_at":"2026-08-02T22:02:12.932569Z","submitted_at":"2026-06-11T04:19:32Z","title":"The Hidden Power of Scaling Factor in LoRA Optimization","version":1},"reference_index":96,"source":"arxiv_source","source_observed_at":"2026-06-27T07:14:08.479610Z"},"links":{"cited_paper":"/paper/2409.14396","citing_paper":"/paper/2606.12883"},"observation_digest":"sha256:2fbf13ba36ab399925529a698590e88a57e9d31ebf91b6c01679c8fdf7aaff18","observation_id":"e6c446e6-7090-4ad1-b3a6-572745da2e6b","resolution":{"observed_at":"2026-07-03T14:08:21.876401Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2409.14396/citation-record","integrity":"/paper/2409.14396/integrity","json":"/paper/2409.14396/citation-record.json","paper":"/paper/2409.14396"},"outbound":[],"paper":{"arxiv_id":"2409.14396","last_updated":"2025-05-24T12:19:58Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T19:19:24.759288Z","submitted_at":"2024-09-22T11:24:10Z","title":"Flat-LoRA: Low-Rank Adaptation over a Flat Loss Landscape"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2409.14396."}