{"as_of":"2026-08-11T01:07:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2918d260c9e4ef1e2f882e531b2544a3d2d47fd5344b1a17b77419ee2b4e3da9","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":7,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":7,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":7,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T00:53:24.535174Z","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":"2026-07-01T22:36:17.315641Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2005.07683","last_updated":"2020-10-23T16:14:58Z","snapshot_observed_at":"2026-08-11T00:50:04.275195Z","submitted_at":"2020-05-15T17:54:15Z","title":"Movement Pruning: Adaptive Sparsity by Fine-Tuning","version":2},"cited_work":{"arxiv_id":"2005.07683","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2005.07683","snapshot_observed_at":"2026-07-01T22:36:17.315641Z","title":"Movement pruning: Adaptive sparsity by ﬁne-tuning","venue":null,"work_id":"01cbb838-ddc2-48f2-9782-c3345e648f09","year":2005},"citing_paper":{"arxiv_id":"2205.14135","last_updated":"2022-06-23T17:53:32Z","snapshot_observed_at":"2026-07-06T13:14:48.753329Z","submitted_at":"2022-05-27T17:53:09Z","title":"FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness","version":2},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-05-12T16:22:08.801066Z"},"links":{"cited_paper":"/paper/2005.07683","citing_paper":"/paper/2205.14135"},"observation_digest":"sha256:63b145bc9d67056596ae1dc0a1eba3abda5d854606d75dabd04a86cc06269058","observation_id":"a4aa2277-24e4-4919-8932-a7ee14c9b863","resolution":{"observed_at":"2026-05-12T16:22:08.995801Z","resolver_source":"arxiv_id","status":"verified_exact"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2005.07683","last_updated":"2020-10-23T16:14:58Z","snapshot_observed_at":"2026-08-11T00:50:04.275195Z","submitted_at":"2020-05-15T17:54:15Z","title":"Movement Pruning: Adaptive Sparsity by Fine-Tuning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.07683","snapshot_observed_at":"2026-08-06T13:56:16.895359Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.20018","last_updated":"2025-07-29T05:18:46Z","snapshot_observed_at":"2026-08-10T00:19:13.677143Z","submitted_at":"2025-07-26T17:21:11Z","title":"The Carbon Cost of Conversation, Sustainability in the Age of Language Models","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-06T13:56:16.895359Z"},"links":{"cited_paper":"/paper/2005.07683","citing_paper":"/paper/2507.20018"},"observation_digest":"sha256:5643e33447ed69868674cef940740408ad3a1cae3b374869f9f2760cf520e318","observation_id":"ca6acc0d-72c8-4d27-b7b3-9a640d385e72","resolution":{"observed_at":"2026-08-06T13:56:16.895359Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2005.07683","last_updated":"2020-10-23T16:14:58Z","snapshot_observed_at":"2026-08-11T00:50:04.275195Z","submitted_at":"2020-05-15T17:54:15Z","title":"Movement Pruning: Adaptive Sparsity by Fine-Tuning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.07683","snapshot_observed_at":"2026-08-06T13:22:47.097104Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.20749","last_updated":"2025-07-28T11:57:52Z","snapshot_observed_at":"2026-08-08T16:13:24.324121Z","submitted_at":"2025-07-28T11:57:52Z","title":"Investigating Structural Pruning and Recovery Techniques for Compressing Multimodal Large Language Models: An Empirical Study","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T13:22:47.097104Z"},"links":{"cited_paper":"/paper/2005.07683","citing_paper":"/paper/2507.20749"},"observation_digest":"sha256:24c13e9dc6bcc3c5638a0c1bdc53b63e3b19d22fe3448e5d2d2a466cf62057bf","observation_id":"15bff839-5809-4602-a976-2975f142d3a1","resolution":{"observed_at":"2026-08-06T13:22:47.097104Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2005.07683","last_updated":"2020-10-23T16:14:58Z","snapshot_observed_at":"2026-08-11T00:50:04.275195Z","submitted_at":"2020-05-15T17:54:15Z","title":"Movement Pruning: Adaptive Sparsity by Fine-Tuning","version":2},"cited_work":{"arxiv_id":"2005.07683","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2005.07683","snapshot_observed_at":"2026-07-01T22:36:17.315641Z","title":"Movement pruning: Adaptive sparsity by ﬁne-tuning","venue":null,"work_id":"01cbb838-ddc2-48f2-9782-c3345e648f09","year":2005},"citing_paper":{"arxiv_id":"2604.24380","last_updated":"2026-04-27T12:10:44Z","snapshot_observed_at":"2026-07-06T23:10:24.992210Z","submitted_at":"2026-04-27T12:10:44Z","title":"Structural Pruning of Large Vision Language Models: A Comprehensive Study on Pruning Dynamics, Recovery, and Data Efficiency","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-08T03:47:38.100037Z"},"links":{"cited_paper":"/paper/2005.07683","citing_paper":"/paper/2604.24380"},"observation_digest":"sha256:0883714199f4ef72377e492a404fc2e17298186418ada97bcb08f1e1cf421405","observation_id":"92fcb2b2-ed16-4e93-a05c-feab83f9e0a1","resolution":{"observed_at":"2026-05-11T21:56:14.886080Z","resolver_source":"arxiv_id","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"}},{"citation":{"cited_paper":{"arxiv_id":"2005.07683","last_updated":"2020-10-23T16:14:58Z","snapshot_observed_at":"2026-08-11T00:50:04.275195Z","submitted_at":"2020-05-15T17:54:15Z","title":"Movement Pruning: Adaptive Sparsity by Fine-Tuning","version":2},"cited_work":{"arxiv_id":"2005.07683","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2005.07683","snapshot_observed_at":"2026-07-01T22:36:17.315641Z","title":"Movement pruning: Adaptive sparsity by ﬁne-tuning","venue":null,"work_id":"01cbb838-ddc2-48f2-9782-c3345e648f09","year":2005},"citing_paper":{"arxiv_id":"2604.26587","last_updated":"2026-04-29T12:10:35Z","snapshot_observed_at":"2026-07-06T23:12:15.279847Z","submitted_at":"2026-04-29T12:10:35Z","title":"Sparse-on-Dense: Area and Energy-Efficient Computing of Sparse Neural Networks on Dense Matrix Multiplication Accelerators","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-07T12:35:35.665508Z"},"links":{"cited_paper":"/paper/2005.07683","citing_paper":"/paper/2604.26587"},"observation_digest":"sha256:8127ed124fb73cf10f3103c81666c217beecc058cc9f2260c712f23785008f90","observation_id":"137020c2-d170-4874-bff3-73701d0d83db","resolution":{"observed_at":"2026-05-12T09:11:27.009057Z","resolver_source":"arxiv_id","status":"verified_exact"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2005.07683","last_updated":"2020-10-23T16:14:58Z","snapshot_observed_at":"2026-08-11T00:50:04.275195Z","submitted_at":"2020-05-15T17:54:15Z","title":"Movement Pruning: Adaptive Sparsity by Fine-Tuning","version":2},"cited_work":{"arxiv_id":"2005.07683","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2005.07683","snapshot_observed_at":"2026-07-01T22:36:17.315641Z","title":"Movement pruning: Adaptive sparsity by ﬁne-tuning","venue":null,"work_id":"01cbb838-ddc2-48f2-9782-c3345e648f09","year":2005},"citing_paper":{"arxiv_id":"2606.04032","last_updated":"2026-06-04T17:08:43Z","snapshot_observed_at":"2026-07-06T23:44:14.261541Z","submitted_at":"2026-06-01T20:59:05Z","title":"Do Transformers Need Three Projections? Systematic Study of QKV Variants","version":2},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-06-28T15:14:49.475561Z"},"links":{"cited_paper":"/paper/2005.07683","citing_paper":"/paper/2606.04032"},"observation_digest":"sha256:39a4a99f2b65b97e85392bb78b899b9c5ce720d89cc87be12e4affbc62589316","observation_id":"2ca13b8d-257c-4d8a-a80d-5983e3ff57ae","resolution":{"observed_at":"2026-07-01T22:36:17.316951Z","resolver_source":"arxiv_id","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"}},{"citation":{"cited_paper":{"arxiv_id":"2005.07683","last_updated":"2020-10-23T16:14:58Z","snapshot_observed_at":"2026-08-11T00:50:04.275195Z","submitted_at":"2020-05-15T17:54:15Z","title":"Movement Pruning: Adaptive Sparsity by Fine-Tuning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.07683","snapshot_observed_at":"2026-08-08T00:53:24.535174Z","title":", title =","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2608.04057","last_updated":"2026-08-04T12:17:00Z","snapshot_observed_at":"2026-08-11T00:21:41.715620Z","submitted_at":"2026-08-04T12:17:00Z","title":"LaPrune: Controllable Differentiable Sparsity at Million Scale","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-08T00:53:24.535174Z"},"links":{"cited_paper":"/paper/2005.07683","citing_paper":"/paper/2608.04057"},"observation_digest":"sha256:bf531fda84230d9b9d805457413770fffcacd041d636acd62bc4893ff978ce9e","observation_id":"5928049c-2f59-4a2f-9079-75ee789d1919","resolution":{"observed_at":"2026-08-08T00:53:24.535174Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2005.07683/citation-record","integrity":"/paper/2005.07683/integrity","json":"/paper/2005.07683/citation-record.json","paper":"/paper/2005.07683"},"outbound":[],"paper":{"arxiv_id":"2005.07683","last_updated":"2020-10-23T16:14:58Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-11T00:50:04.275195Z","submitted_at":"2020-05-15T17:54:15Z","title":"Movement Pruning: Adaptive Sparsity by Fine-Tuning"},"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 7 inbound Pith citation observations for arXiv:2005.07683."}