{"as_of":"2026-08-04T11:51:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:11f892c423a9250813d913de2c769ce3e63699e8a0df54c13600c2e83d36db27","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":"2026-08-04T06:34:03.388597+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":"2026-08-01T11:19:21.586164Z","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":"2026-07-03T17:08:43.678956Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2404.08080","last_updated":"2024-04-11T18:35:49Z","snapshot_observed_at":"2026-07-06T17:59:04.250437Z","submitted_at":"2024-04-11T18:35:49Z","title":"Variance-reduced Zeroth-Order Methods for Fine-Tuning Language Models","version":1},"cited_work":{"arxiv_id":"2404.08080","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2404.08080","snapshot_observed_at":"2026-07-03T17:08:43.678956Z","title":"arXiv preprint arXiv:2404.08080 , year=","venue":null,"work_id":"781b7a33-777b-4e7b-8974-383845c8da8a","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":17,"source":"pdf_text","source_observed_at":"2026-05-18T14:51:30.312509Z"},"links":{"cited_paper":"/paper/2404.08080","citing_paper":"/paper/2509.18993"},"observation_digest":"sha256:4a6906adc779cf3f1e719050128910c7007cb3be3a3acf332372aa713a25f68a","observation_id":"f0eebf04-6407-49fc-a7c4-6ac2cd92c98b","resolution":{"observed_at":"2026-05-18T14:52:41.152922Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.08080","last_updated":"2024-04-11T18:35:49Z","snapshot_observed_at":"2026-07-06T17:59:04.250437Z","submitted_at":"2024-04-11T18:35:49Z","title":"Variance-reduced Zeroth-Order Methods for Fine-Tuning Language Models","version":1},"cited_work":{"arxiv_id":"2404.08080","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2404.08080","snapshot_observed_at":"2026-07-03T17:08:43.678956Z","title":"arXiv preprint arXiv:2404.08080 , year=","venue":null,"work_id":"781b7a33-777b-4e7b-8974-383845c8da8a","year":2024},"citing_paper":{"arxiv_id":"2605.09034","last_updated":"2026-05-15T13:21:07Z","snapshot_observed_at":"2026-07-06T23:21:11.475005Z","submitted_at":"2026-05-09T16:16:45Z","title":"Accelerating Zeroth-Order Spectral Optimization with Partial Orthogonalization from Power Iteration","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-12T02:18:17.478817Z"},"links":{"cited_paper":"/paper/2404.08080","citing_paper":"/paper/2605.09034"},"observation_digest":"sha256:b9cfc0a3125c0bd6f90f4abd8265cbf132b8013354a9879d56e150e2b7cb0a94","observation_id":"33e937da-2f92-4758-95a1-85b43fec2d25","resolution":{"observed_at":"2026-05-12T07:41:42.876578Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.08080","last_updated":"2024-04-11T18:35:49Z","snapshot_observed_at":"2026-07-06T17:59:04.250437Z","submitted_at":"2024-04-11T18:35:49Z","title":"Variance-reduced Zeroth-Order Methods for Fine-Tuning Language Models","version":1},"cited_work":{"arxiv_id":"2404.08080","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2404.08080","snapshot_observed_at":"2026-07-03T17:08:43.678956Z","title":"arXiv preprint arXiv:2404.08080 , year=","venue":null,"work_id":"781b7a33-777b-4e7b-8974-383845c8da8a","year":2024},"citing_paper":{"arxiv_id":"2605.09034","last_updated":"2026-05-15T13:21:07Z","snapshot_observed_at":"2026-07-06T23:21:11.475005Z","submitted_at":"2026-05-09T16:16:45Z","title":"Accelerating Zeroth-Order Spectral Optimization with Partial Orthogonalization from Power Iteration","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-19T17:33:00.747846Z"},"links":{"cited_paper":"/paper/2404.08080","citing_paper":"/paper/2605.09034"},"observation_digest":"sha256:c7d34f581dc77c7b8336401d4241ca8115da7e3d9a5b597ead72d9876accf702","observation_id":"1314a47a-5f87-404e-9c82-969adf40c275","resolution":{"observed_at":"2026-05-19T17:33:09.420739Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.08080","last_updated":"2024-04-11T18:35:49Z","snapshot_observed_at":"2026-07-06T17:59:04.250437Z","submitted_at":"2024-04-11T18:35:49Z","title":"Variance-reduced Zeroth-Order Methods for Fine-Tuning Language Models","version":1},"cited_work":{"arxiv_id":"2404.08080","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2404.08080","snapshot_observed_at":"2026-07-03T17:08:43.678956Z","title":"arXiv preprint arXiv:2404.08080 , year=","venue":null,"work_id":"781b7a33-777b-4e7b-8974-383845c8da8a","year":2024},"citing_paper":{"arxiv_id":"2605.15622","last_updated":"2026-05-18T07:21:10Z","snapshot_observed_at":"2026-07-06T23:26:51.110846Z","submitted_at":"2026-05-15T05:11:43Z","title":"Position: Zeroth-Order Optimization in Deep Learning Is Underexplored, Not Underpowered","version":2},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-05-20T21:19:55.074853Z"},"links":{"cited_paper":"/paper/2404.08080","citing_paper":"/paper/2605.15622"},"observation_digest":"sha256:c8451777097b900d925edb22be3bc5cdb9c908cf5749e27ff6da00891f1f93bd","observation_id":"33c6d116-37e8-4f3b-b9ac-1fa2fa7f43df","resolution":{"observed_at":"2026-05-20T21:23:44.510194Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.08080","last_updated":"2024-04-11T18:35:49Z","snapshot_observed_at":"2026-07-06T17:59:04.250437Z","submitted_at":"2024-04-11T18:35:49Z","title":"Variance-reduced Zeroth-Order Methods for Fine-Tuning Language Models","version":1},"cited_work":{"arxiv_id":"2404.08080","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2404.08080","snapshot_observed_at":"2026-07-03T17:08:43.678956Z","title":"arXiv preprint arXiv:2404.08080 , year=","venue":null,"work_id":"781b7a33-777b-4e7b-8974-383845c8da8a","year":2024},"citing_paper":{"arxiv_id":"2606.14970","last_updated":"2026-06-22T08:40:27Z","snapshot_observed_at":"2026-07-06T23:52:28.557859Z","submitted_at":"2026-06-12T21:46:54Z","title":"Zero-order Parameter-free Optimization for LMO-based Methods: Novel Approach for Efficient Fine-tuning","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-06-27T04:33:10.554853Z"},"links":{"cited_paper":"/paper/2404.08080","citing_paper":"/paper/2606.14970"},"observation_digest":"sha256:91f613c9173e5bde363ea0869e5566d86c5dd39422dbbf716cea7f2ae70dba0d","observation_id":"8f7cafd0-0d0b-46f6-85a9-6dbb173bfc19","resolution":{"observed_at":"2026-07-03T17:08:43.680445Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.08080","last_updated":"2024-04-11T18:35:49Z","snapshot_observed_at":"2026-07-06T17:59:04.250437Z","submitted_at":"2024-04-11T18:35:49Z","title":"Variance-reduced Zeroth-Order Methods for Fine-Tuning Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.08080","snapshot_observed_at":"2026-08-01T11:19:21.586164Z","title":"Gautam, Y","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19965","last_updated":"2026-07-22T09:48:50Z","snapshot_observed_at":"2026-08-01T11:19:17.407603Z","submitted_at":"2026-07-22T09:48:50Z","title":"Accelerated Stochastic Zeroth-Order Quasar-Convex Optimization","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-01T11:19:21.586164Z"},"links":{"cited_paper":"/paper/2404.08080","citing_paper":"/paper/2607.19965"},"observation_digest":"sha256:6fcfc66184c626f1eeed18f2f23726eeb742458eedb5fe5af244b217ae00eb28","observation_id":"31ffbb29-d815-4946-af5d-c57eb0a8cfe3","resolution":{"observed_at":"2026-08-01T11:19:21.586164Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2404.08080/citation-record","integrity":"/paper/2404.08080/integrity","json":"/paper/2404.08080/citation-record.json","paper":"/paper/2404.08080"},"outbound":[],"paper":{"arxiv_id":"2404.08080","last_updated":"2024-04-11T18:35:49Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T17:59:04.250437Z","submitted_at":"2024-04-11T18:35:49Z","title":"Variance-reduced Zeroth-Order Methods for Fine-Tuning Language Models"},"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":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"thesis":"As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2404.08080."}