{"as_of":"2026-08-07T12:54:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1f1164c005c57ad8f2e32cb46ff8f9e00b314f67411b0305fc4e4a4a5443eca2","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":"2026-07-13T04:08:39.594367Z","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":"2026-05-20T20:28:59.926660Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2406.02214","last_updated":"2024-11-02T06:00:03Z","snapshot_observed_at":"2026-08-04T13:15:41.775650Z","submitted_at":"2024-06-04T11:14:21Z","title":"SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretraining","version":2},"cited_work":{"arxiv_id":"2406.02214","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.02214","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretraining","venue":null,"work_id":"fea80c45-4376-4f75-b959-b57b59fe4c1f","year":2024},"citing_paper":{"arxiv_id":"2509.18993","last_updated":"2026-05-13T13:30:21Z","snapshot_observed_at":"2026-08-02T18:52:22.902766Z","submitted_at":"2025-09-23T13:43:02Z","title":"CR-Net: Scaling Parameter-Efficient Training with Cross-Layer Low-Rank Structure","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-18T14:51:30.312509Z"},"links":{"cited_paper":"/paper/2406.02214","citing_paper":"/paper/2509.18993"},"observation_digest":"sha256:142d7a5128605430261974c6bcc2a94ddcc3e509b66264cac6629aa914dfe977","observation_id":"ec760663-73c7-4333-9b9c-47350b3b7ba0","resolution":{"observed_at":"2026-05-18T14:52:41.259945Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2406.02214","last_updated":"2024-11-02T06:00:03Z","snapshot_observed_at":"2026-08-04T13:15:41.775650Z","submitted_at":"2024-06-04T11:14:21Z","title":"SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretraining","version":2},"cited_work":{"arxiv_id":"2406.02214","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.02214","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretraining","venue":null,"work_id":"fea80c45-4376-4f75-b959-b57b59fe4c1f","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":6,"source":"pdf_text","source_observed_at":"2026-05-14T19:19:18.275446Z"},"links":{"cited_paper":"/paper/2406.02214","citing_paper":"/paper/2605.13652"},"observation_digest":"sha256:85083458e5ace060d33ce0e8ee1fb83e2919044f2ea4d6dfa41e49f4b8d5dc01","observation_id":"1040b1bd-ec08-4815-8228-0ae005492bfe","resolution":{"observed_at":"2026-05-14T19:19:23.542591Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2406.02214","last_updated":"2024-11-02T06:00:03Z","snapshot_observed_at":"2026-08-04T13:15:41.775650Z","submitted_at":"2024-06-04T11:14:21Z","title":"SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretraining","version":2},"cited_work":{"arxiv_id":"2406.02214","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.02214","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretraining","venue":null,"work_id":"fea80c45-4376-4f75-b959-b57b59fe4c1f","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":6,"source":"pdf_text","source_observed_at":"2026-05-20T20:24:26.681383Z"},"links":{"cited_paper":"/paper/2406.02214","citing_paper":"/paper/2605.13652"},"observation_digest":"sha256:3ba3e42d58130ed9cd26ab43bf5454a586e2a388ba3ef8652f7884445268f2c5","observation_id":"653513c9-48da-42fb-ab60-ef80b9940116","resolution":{"observed_at":"2026-05-20T20:28:59.928172Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2406.02214","last_updated":"2024-11-02T06:00:03Z","snapshot_observed_at":"2026-08-04T13:15:41.775650Z","submitted_at":"2024-06-04T11:14:21Z","title":"SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretraining","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.02214","snapshot_observed_at":"2026-07-13T04:08:39.594367Z","title":"Sltrain: a sparse plus low-rank approach for parameter and memory efficient pretraining","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.09287","last_updated":"2026-07-10T10:55:28Z","snapshot_observed_at":"2026-08-06T10:40:57.712485Z","submitted_at":"2026-07-10T10:55:28Z","title":"Super-Tuning: From Activation-Aware Pruning to Sparse Fine-Tuning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-13T04:08:39.594367Z"},"links":{"cited_paper":"/paper/2406.02214","citing_paper":"/paper/2607.09287"},"observation_digest":"sha256:c9cdde1126356b631951db7e1a46d38f347388035183e6025a14d3a48ab4bc0c","observation_id":"2d914d76-aefd-4b87-b037-c398446fd5b0","resolution":{"observed_at":"2026-07-13T04:08:39.594367Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2406.02214/citation-record","integrity":"/paper/2406.02214/integrity","json":"/paper/2406.02214/citation-record.json","paper":"/paper/2406.02214"},"outbound":[],"paper":{"arxiv_id":"2406.02214","last_updated":"2024-11-02T06:00:03Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-04T13:15:41.775650Z","submitted_at":"2024-06-04T11:14:21Z","title":"SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretraining"},"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:2406.02214."}