{"as_of":"2026-08-10T00:54:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:892a0a4e44fb4d00aeca7907150140eef361e5d7f9b060a5a34a38759b60ca58","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":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T11:47:18.974003Z","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":"2026-05-16T20:18:23.712337Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.16500","last_updated":"2025-06-19T17:53:34Z","snapshot_observed_at":"2026-08-09T20:25:21.110158Z","submitted_at":"2025-06-19T17:53:34Z","title":"SparseLoRA: Accelerating LLM Fine-Tuning with Contextual Sparsity","version":1},"cited_work":{"arxiv_id":"2506.16500","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.16500","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Sparselora: Accelerat- ing llm fine-tuning with contextual sparsity","venue":null,"work_id":"cb948828-28dd-4aa2-996b-22f6311cf0aa","year":2025},"citing_paper":{"arxiv_id":"2512.19219","last_updated":"2026-05-11T05:06:06Z","snapshot_observed_at":"2026-07-06T22:39:48.048525Z","submitted_at":"2025-12-22T10:02:10Z","title":"Selective LoRA for Visual Tokens and Attention Heads","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-16T20:17:07.884892Z"},"links":{"cited_paper":"/paper/2506.16500","citing_paper":"/paper/2512.19219"},"observation_digest":"sha256:09cda95c767e72d194843b114e3bd6084486ce8f64e043476818147e7a02a4b0","observation_id":"3812250e-f85e-4288-bc9d-998dc44ea199","resolution":{"observed_at":"2026-05-16T20:18:23.714600Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.16500","last_updated":"2025-06-19T17:53:34Z","snapshot_observed_at":"2026-08-09T20:25:21.110158Z","submitted_at":"2025-06-19T17:53:34Z","title":"SparseLoRA: Accelerating LLM Fine-Tuning with Contextual Sparsity","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.16500","snapshot_observed_at":"2026-08-03T11:47:18.974003Z","title":"arXiv:2506.16500","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.16991","last_updated":"2026-07-20T07:18:25Z","snapshot_observed_at":"2026-08-09T19:36:24.077515Z","submitted_at":"2026-01-08T20:34:12Z","title":"Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-03T11:47:18.974003Z"},"links":{"cited_paper":"/paper/2506.16500","citing_paper":"/paper/2601.16991"},"observation_digest":"sha256:1483c21c6d6435b37ded00935d35fd38ebb74c60aa975859cc3e8388f84311e6","observation_id":"cb4a4133-1aa6-49b9-9167-76d301d32700","resolution":{"observed_at":"2026-08-03T11:47:18.974003Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2506.16500/citation-record","integrity":"/paper/2506.16500/integrity","json":"/paper/2506.16500/citation-record.json","paper":"/paper/2506.16500"},"outbound":[],"paper":{"arxiv_id":"2506.16500","last_updated":"2025-06-19T17:53:34Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-09T20:25:21.110158Z","submitted_at":"2025-06-19T17:53:34Z","title":"SparseLoRA: Accelerating LLM Fine-Tuning with Contextual Sparsity"},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2506.16500."}