{"as_of":"2026-08-20T19:01:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:cbe92c3413f5ced3271fe9ba27f6c99b7543c1937f292bbc87c1203aa80f7da3","coverage":[{"denominator":43,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":43,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T23:59:21.965294Z","state":"measured"},{"denominator":43,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":43,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2505.03373/citation-record","integrity":"/paper/2505.03373/integrity","json":"/paper/2505.03373/citation-record.json","paper":"/paper/2505.03373"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2305.13245","last_updated":"2023-12-23T17:55:11Z","snapshot_observed_at":"2026-08-15T06:28:09.529747Z","submitted_at":"2023-05-22T17:16:38Z","title":"GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.13245","snapshot_observed_at":"2026-08-15T23:59:21.827814Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.827814Z"},"links":{"cited_paper":"/paper/2305.13245","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:a651225230659852063df0b42f712c363bec29571d60eb16a92270d520f03e84","observation_id":"0014be80-f6cc-4f51-9f3d-5f436ed65982","resolution":{"observed_at":"2026-08-15T23:59:21.827814Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:59:22.337574Z","title":null,"venue":null,"work_id":"dde50b39-284d-4e20-9307-2cf61d980459","year":2024},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.832820Z"},"links":{"citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:2719add327e77617a2f2ae2b1af230488a36d7f26bcfaf7cac9fb4742d43f482","observation_id":"cfcbb4df-f044-4e9e-9e60-9891d7be8953","resolution":{"observed_at":"2026-08-15T23:59:22.340845Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:59:22.327717Z","title":"Apple intelligence: Ai for the rest of us","venue":null,"work_id":"27d56209-ed35-4346-9a8e-c61cb8375171","year":2024},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.836857Z"},"links":{"citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:46861f6ece4b4411382e64b0276e3be63d8bfb32cda61ea809dd9cbedc6df002","observation_id":"e3dffc4a-13c8-4f3c-809f-baf3aa8b9067","resolution":{"observed_at":"2026-08-15T23:59:22.331147Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.15024","last_updated":"2024-02-09T17:59:40Z","snapshot_observed_at":"2026-08-16T14:24:10.346445Z","submitted_at":"2024-01-26T17:35:45Z","title":"SliceGPT: Compress Large Language Models by Deleting Rows and Columns","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.15024","snapshot_observed_at":"2026-08-15T23:59:21.840221Z","title":"L., Nascimento, M","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.840221Z"},"links":{"cited_paper":"/paper/2401.15024","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:f8bb003c9f24748db38ebd549a437aec1670ae28ceb28e4ec406ff95a5c434f7","observation_id":"1ac7147b-2a27-4403-a302-ea6517f984a3","resolution":{"observed_at":"2026-08-15T23:59:21.840221Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:59:21.843725Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.843725Z"},"links":{"citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:d033ffe6e29334cb52f802963bac225d425edc8da50991ef3e3ca34cf2050cdf","observation_id":"7f465b6f-224c-4484-83f4-3b892f709d3e","resolution":{"observed_at":"2026-08-15T23:59:21.843725Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1803.05457","last_updated":"2018-03-14T18:04:21Z","snapshot_observed_at":"2026-08-14T19:36:07.505691Z","submitted_at":"2018-03-14T18:04:21Z","title":"Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1803.05457","snapshot_observed_at":"2026-08-15T23:59:21.846999Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.846999Z"},"links":{"cited_paper":"/paper/1803.05457","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:91bcb90cbb92b9f5a5e8f443426549b28c6b413958d119afb65702435f18bcb4","observation_id":"cad56c8c-5218-4d67-8f68-48696355c166","resolution":{"observed_at":"2026-08-15T23:59:21.846999Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:59:22.313095Z","title":"Deepseek-v3 technical report","venue":null,"work_id":"991152e9-f73c-43e9-a664-4914812a6ad0","year":2025},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.850633Z"},"links":{"citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:2ffdce15a05ac3f9cd1f6a01b23f12c2e58d617c932b4a756bcfc8d30e8264ae","observation_id":"be36bd54-8c57-48b0-b03f-73d6d2f80a21","resolution":{"observed_at":"2026-08-15T23:59:22.316697Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.02924","last_updated":"2024-06-05T04:25:23Z","snapshot_observed_at":"2026-08-17T19:21:14.511913Z","submitted_at":"2024-06-05T04:25:23Z","title":"Pruner-Zero: Evolving Symbolic Pruning Metric from scratch for Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.02924","snapshot_observed_at":"2026-08-15T23:59:21.853686Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.853686Z"},"links":{"cited_paper":"/paper/2406.02924","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:fb2986e7596d8a2bac19fea54b7903240caf7878aeb9ab1d736c29cdcc5a2ea4","observation_id":"32bccd7b-cc3a-4321-be56-aa16c765c06d","resolution":{"observed_at":"2026-08-15T23:59:21.853686Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.17481","last_updated":"2024-12-07T12:01:28Z","snapshot_observed_at":"2026-08-17T09:04:00.137073Z","submitted_at":"2024-09-26T02:37:41Z","title":"MaskLLM: Learnable Semi-Structured Sparsity for Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.17481","snapshot_observed_at":"2026-08-15T23:59:21.857135Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.857135Z"},"links":{"cited_paper":"/paper/2409.17481","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:e5b8554e58cada6b706dbd563f8a8273c8b8be80380a9cee9ed0de4aca1dba8f","observation_id":"e22f9967-430b-4dfe-8406-39ad96c5d282","resolution":{"observed_at":"2026-08-15T23:59:21.857135Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:59:22.303050Z","title":"and Alistarh, D","venue":null,"work_id":"6d3f1bbd-ede7-408f-afc8-9bde8e49663d","year":2023},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.860663Z"},"links":{"citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:6c68879122a6daeaf06668117d668f87441f60f41b9cea9cbaeab2595179f641","observation_id":"83fccc48-24f3-4d04-b926-8a2bfcb52b16","resolution":{"observed_at":"2026-08-15T23:59:22.306345Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:59:21.863882Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.863882Z"},"links":{"citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:1a5b5ff1606a62c05fea450999907ad95b53ab398f9cb69b362740457a1eca8e","observation_id":"29e971b7-3997-4ad6-a263-2bea653ee8df","resolution":{"observed_at":"2026-08-15T23:59:21.863882Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:59:22.287923Z","title":null,"venue":null,"work_id":"4de9ac3d-8bcc-4bb7-ae4a-b9116b23f308","year":2024},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.866835Z"},"links":{"citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:5bea9c0e9ecf794054fe75988baabb50d6fc25aad30ea5ca6b49edbb33ee963f","observation_id":"85699077-fa2d-4f79-b23b-aa6c48e5e666","resolution":{"observed_at":"2026-08-15T23:59:22.291332Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.11805","last_updated":"2025-05-09T21:04:06Z","snapshot_observed_at":"2026-08-20T18:27:04.837880Z","submitted_at":"2023-12-19T02:39:27Z","title":"Gemini: A Family of Highly Capable Multimodal Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.11805","snapshot_observed_at":"2026-08-15T23:59:21.869662Z","title":"M., Hauth, A., et al","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.869662Z"},"links":{"cited_paper":"/paper/2312.11805","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:25e199de32a1e6fb611fa57d38c15004df5528937e35f4c9a7e48bf4215f2877","observation_id":"fb714285-3e60-4041-b434-7d454bc27d02","resolution":{"observed_at":"2026-08-15T23:59:21.869662Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-08-13T17:20:44.002518Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-08-15T23:59:21.873012Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.873012Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:291e6c6759aeca1f4da5ab8077261bc6972a59f110c463b38e46c0140eceed46","observation_id":"9d5d8998-0588-4316-a448-ac60a7a1d632","resolution":{"observed_at":"2026-08-15T23:59:21.873012Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:59:22.278233Z","title":null,"venue":null,"work_id":"6dc2b620-8f31-43e4-86d8-fa14064a16f3","year":2021},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.876157Z"},"links":{"citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:c27d941583494c3c18d38a6b4f3aaa261c92c40745b614d572ecb8e78ada88fe","observation_id":"bb9eb537-9fc1-42bd-96d5-0c89f323bbf9","resolution":{"observed_at":"2026-08-15T23:59:22.281652Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.09412","last_updated":"2025-01-16T09:38:39Z","snapshot_observed_at":"2026-08-14T17:40:53.436092Z","submitted_at":"2025-01-16T09:38:39Z","title":"FASP: Fast and Accurate Structured Pruning of Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.09412","snapshot_observed_at":"2026-08-15T23:59:21.879051Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.879051Z"},"links":{"cited_paper":"/paper/2501.09412","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:2dcdb4c3255ffb463d3e672bbc2976516549ec4a58067a5714e77fc13df2ca36","observation_id":"8a2b98f5-47a4-4ab2-bfcc-8c61d1a6ee32","resolution":{"observed_at":"2026-08-15T23:59:21.879051Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-08-17T19:26:44.032537Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-15T23:59:21.882013Z","title":null,"venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.882013Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:37009adbacadaa66478396830897117e04ac5790162a1f301b1b10e75787cee0","observation_id":"f8f2a5c6-1104-42bc-9e6d-73178991d407","resolution":{"observed_at":"2026-08-15T23:59:21.882013Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:59:22.268643Z","title":null,"venue":null,"work_id":"2a122179-664b-46fa-962e-59a0b1715530","year":2024},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.885061Z"},"links":{"citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:c68ca100814ad1586e74d9f9284fad41b7bf50f288b64e5dfa67327a0478c403","observation_id":"7e0735e5-b8a6-4491-a9a8-bac119b8cfae","resolution":{"observed_at":"2026-08-15T23:59:22.271853Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:59:22.258265Z","title":null,"venue":null,"work_id":"bbf2fd64-bd21-4984-a5bf-cbf40665177a","year":2024},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.888200Z"},"links":{"citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:3c9a256fcdcda719b57c70d5e6c7fdf863716fc40a743c8999c7801e36dc30ee","observation_id":"0b5de285-877d-40ac-b4a9-59e91ced00ae","resolution":{"observed_at":"2026-08-15T23:59:22.261557Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.11627","last_updated":"2023-09-28T03:59:27Z","snapshot_observed_at":"2026-08-16T15:31:43.348408Z","submitted_at":"2023-05-19T12:10:53Z","title":"LLM-Pruner: On the Structural Pruning of Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.11627","snapshot_observed_at":"2026-08-15T23:59:21.891302Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.891302Z"},"links":{"cited_paper":"/paper/2305.11627","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:0868a4bbf2d56cc2c42ef35d770bb6756f28c6c60a94f723cb3b5c830e804c04","observation_id":"7076de98-47f8-4453-995c-5c8cff13b7ab","resolution":{"observed_at":"2026-08-15T23:59:21.891302Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.03853","last_updated":"2024-10-11T09:43:32Z","snapshot_observed_at":"2026-08-16T14:12:14.696997Z","submitted_at":"2024-03-06T17:04:18Z","title":"ShortGPT: Layers in Large Language Models are More Redundant Than You Expect","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.03853","snapshot_observed_at":"2026-08-15T23:59:21.894461Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.894461Z"},"links":{"cited_paper":"/paper/2403.03853","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:ead97b36c492c8da374feafde24ef6158ffa9bdf8ee8506fcf64b2715f609aa9","observation_id":"0e2a46a9-0a87-4901-890a-89bc531f58c3","resolution":{"observed_at":"2026-08-15T23:59:21.894461Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.07831","last_updated":"2025-09-08T14:34:07Z","snapshot_observed_at":"2026-08-16T16:46:16.955197Z","submitted_at":"2024-06-12T02:57:41Z","title":"ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.07831","snapshot_observed_at":"2026-08-15T23:59:21.897702Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.897702Z"},"links":{"cited_paper":"/paper/2406.07831","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:5adb921c6c2f499349ed3da214b56ce7742116a0df49915b93214d03c9cac79f","observation_id":"a9f57036-7d34-4bdf-9bb4-4c52de7322eb","resolution":{"observed_at":"2026-08-15T23:59:21.897702Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1609.07843","last_updated":"2016-09-26T04:06:13Z","snapshot_observed_at":"2026-08-17T01:46:43.513643Z","submitted_at":"2016-09-26T04:06:13Z","title":"Pointer Sentinel Mixture Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.07843","snapshot_observed_at":"2026-08-15T23:59:21.900844Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.900844Z"},"links":{"cited_paper":"/paper/1609.07843","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:7e0861561c124316eb944e548c71084f9b76e893fcd761b357357f547ae184c5","observation_id":"075fb19e-5d84-491d-845d-bcb61b4111dd","resolution":{"observed_at":"2026-08-15T23:59:21.900844Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:59:22.247866Z","title":"Llama-3: Meta ai's latest language model","venue":null,"work_id":"cac9bec1-0205-4789-a14b-af9b8daf9600","year":2023},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.904115Z"},"links":{"citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:385962d06df0963479c114902dcbc88dc1ea763f927e40512e1d63a754fe66b0","observation_id":"621566ed-81d3-4b90-905f-5b30ce6f0545","resolution":{"observed_at":"2026-08-15T23:59:22.252228Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1809.02789","last_updated":"2018-09-08T11:47:16Z","snapshot_observed_at":"2026-08-14T07:00:02.529732Z","submitted_at":"2018-09-08T11:47:16Z","title":"Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1809.02789","snapshot_observed_at":"2026-08-15T23:59:21.907040Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.907040Z"},"links":{"cited_paper":"/paper/1809.02789","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:8828ddf017d78e9cae186f8bd21c1885d0cc2c2b89abf8025f8a554927f92215","observation_id":"41b01414-4823-4bc1-9b2d-1f9ca2f9bf95","resolution":{"observed_at":"2026-08-15T23:59:21.907040Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.08378","last_updated":"2021-04-16T21:27:32Z","snapshot_observed_at":"2026-08-16T18:30:58.242028Z","submitted_at":"2021-04-16T21:27:32Z","title":"Accelerating Sparse Deep Neural Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.08378","snapshot_observed_at":"2026-08-15T23:59:21.910051Z","title":"A., Pool, J., Stosic, D., Stosic, D., Venkatesh, G., Yu, C., and Micikevicius, P","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.910051Z"},"links":{"cited_paper":"/paper/2104.08378","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:d027ab56435f811c7bf6feb72bef67349ec5fe91efc143157c52557367671457","observation_id":"9f10af0d-2536-4bfe-9ee7-8ad6543cde41","resolution":{"observed_at":"2026-08-15T23:59:21.910051Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:59:22.238347Z","title":"Gpt-4 technical report","venue":null,"work_id":"96501630-19d2-4ef8-9816-c9c7a618a2ad","year":2023},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.913467Z"},"links":{"citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:2456ac08bc8794c42d6e08c8a2055d589c065b2c3360cf646e7025e0e88f55f5","observation_id":"e7d7942f-ec87-4eda-b0b5-9ff2b07e2106","resolution":{"observed_at":"2026-08-15T23:59:22.241904Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:59:21.916678Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.916678Z"},"links":{"citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:be3811358eb3d632a072fe57d8d93deaf3d503930b4c62f18a47a04eefb1a5f8","observation_id":"31340767-9ee6-4ad2-b3b6-9c577efa1f83","resolution":{"observed_at":"2026-08-15T23:59:21.916678Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:59:22.222013Z","title":"Qwen2.5 technical report","venue":null,"work_id":"01e93d5c-ff12-4ca6-8eca-c39cb4d2bc40","year":2025},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.919764Z"},"links":{"citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:95dfa10ad9147cc436e1f737d74ffeacc6af8f2c31d90744c9105fa5dabc28af","observation_id":"8eed63e5-34a9-4de4-b0dc-b078e57e8e36","resolution":{"observed_at":"2026-08-15T23:59:22.225976Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:59:21.922871Z","title":"L., Bhagavatula, C., and Choi, Y","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.922871Z"},"links":{"citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:706c6db250af8a814546624dc5e84a8d417b6f15f492dcd1732d2aff74d4aecf","observation_id":"0cb477fa-8706-4a0c-96e7-f377aa299330","resolution":{"observed_at":"2026-08-15T23:59:21.922871Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:59:21.925899Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.925899Z"},"links":{"citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:f720aa88a0fe2f721fd1c85931404cfbc0fdfe8cae1470e3b7083e00902a418f","observation_id":"2e705268-4f48-4fd6-b3ef-491f61173a47","resolution":{"observed_at":"2026-08-15T23:59:21.925899Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.17372","last_updated":"2024-10-30T20:04:01Z","snapshot_observed_at":"2026-08-16T13:15:20.217440Z","submitted_at":"2024-09-25T21:32:12Z","title":"Search for Efficient Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.17372","snapshot_observed_at":"2026-08-15T23:59:21.929165Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.929165Z"},"links":{"cited_paper":"/paper/2409.17372","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:bc9cd43e8a33a328127c83597320a374374b8d16a0b84b5a4f35f36b3dbdf8d2","observation_id":"2a88c8d7-6d27-48a3-8d96-afe62660db23","resolution":{"observed_at":"2026-08-15T23:59:21.929165Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.11695","last_updated":"2024-05-06T17:47:01Z","snapshot_observed_at":"2026-08-20T04:15:03.506960Z","submitted_at":"2023-06-20T17:18:20Z","title":"A Simple and Effective Pruning Approach for Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.11695","snapshot_observed_at":"2026-08-15T23:59:21.932318Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.932318Z"},"links":{"cited_paper":"/paper/2306.11695","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:fe41939944518a6f5092910ff0a70ad86767073e1ff19757f725ce62b5c62586","observation_id":"a796112b-bece-4df7-94c5-41206e66cfc0","resolution":{"observed_at":"2026-08-15T23:59:21.932318Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.13971","last_updated":"2023-02-27T17:11:15Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-02-27T17:11:15Z","title":"LLaMA: Open and Efficient Foundation Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.13971","snapshot_observed_at":"2026-08-15T23:59:21.935578Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.935578Z"},"links":{"cited_paper":"/paper/2302.13971","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:bbcfdcb48dd2acceb248ce7d515149bd7048ffae9ceeb90708caaaa9514abecf","observation_id":"8a8b9b27-fd04-4fa7-b1b5-3428d8ff95e6","resolution":{"observed_at":"2026-08-15T23:59:21.935578Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.09288","last_updated":"2023-07-19T17:08:59Z","snapshot_observed_at":"2026-08-07T12:56:43.323460Z","submitted_at":"2023-07-18T14:31:57Z","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.09288","snapshot_observed_at":"2026-08-15T23:59:21.938854Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.938854Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:d4ca3839397c537c3d5446302eb03dbfcb89b11f7e124572bdfd480b34e50b08","observation_id":"4610e7c1-db3b-458d-9640-06e034dcd8a2","resolution":{"observed_at":"2026-08-15T23:59:21.938854Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1804.07461","last_updated":"2019-02-22T23:53:34Z","snapshot_observed_at":"2026-08-16T09:50:11.319379Z","submitted_at":"2018-04-20T06:35:04Z","title":"GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1804.07461","snapshot_observed_at":"2026-08-15T23:59:21.941873Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.941873Z"},"links":{"cited_paper":"/paper/1804.07461","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:fe88364d61ec9f8406a51ea7561799c3f186c509048f48860c35847d595e9639","observation_id":"5599036f-1bed-4630-94ba-9a4b532d3f4c","resolution":{"observed_at":"2026-08-15T23:59:21.941873Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.13199","last_updated":"2024-12-10T02:55:21Z","snapshot_observed_at":"2026-08-18T03:17:48.064956Z","submitted_at":"2024-09-20T04:03:27Z","title":"CFSP: An Efficient Structured Pruning Framework for LLMs with Coarse-to-Fine Activation Information","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.13199","snapshot_observed_at":"2026-08-15T23:59:21.945152Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.945152Z"},"links":{"cited_paper":"/paper/2409.13199","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:1a4d2d72154d113530a4868fa0af7a78882d326ae0fcdfac3eee20785943b181","observation_id":"cc56bfc5-33f8-41f4-908f-5b9832044e55","resolution":{"observed_at":"2026-08-15T23:59:21.945152Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.03771","last_updated":"2020-07-14T03:42:34Z","snapshot_observed_at":"2026-07-06T08:27:58.343233Z","submitted_at":"2019-10-09T03:23:22Z","title":"HuggingFace's Transformers: State-of-the-art Natural Language Processing","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.03771","snapshot_observed_at":"2026-08-15T23:59:21.948475Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.948475Z"},"links":{"cited_paper":"/paper/1910.03771","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:0c54cbcec57b404038758706b6962a5a0e9fc05e76bac510891fb36c6998294b","observation_id":"7b321e2e-509c-4eee-8a56-795fdb8df737","resolution":{"observed_at":"2026-08-15T23:59:21.948475Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11187","last_updated":"2024-10-15T01:58:58Z","snapshot_observed_at":"2026-08-16T14:17:47.965208Z","submitted_at":"2024-02-17T04:16:30Z","title":"LaCo: Large Language Model Pruning via Layer Collapse","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.11187","snapshot_observed_at":"2026-08-15T23:59:21.951720Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.951720Z"},"links":{"cited_paper":"/paper/2402.11187","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:414594045f5fcb636f604325c8b3396facbf78dfdcccff0454ee8ae4bc3ba8c1","observation_id":"2f53fb20-b5da-4deb-9445-b0060ebfd290","resolution":{"observed_at":"2026-08-15T23:59:21.951720Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2205.01068","last_updated":"2022-06-21T17:04:40Z","snapshot_observed_at":"2026-08-06T03:13:37.403059Z","submitted_at":"2022-05-02T17:49:50Z","title":"OPT: Open Pre-trained Transformer Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.01068","snapshot_observed_at":"2026-08-15T23:59:21.955351Z","title":"V., et al","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.955351Z"},"links":{"cited_paper":"/paper/2205.01068","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:3e4a2f9eb01ebdb3bbfe83785a0f2bd27ca4283261f4b38f9cc21e04c9b99bc6","observation_id":"f046d744-6047-4049-bb16-dc644a7faccf","resolution":{"observed_at":"2026-08-15T23:59:21.955351Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18218","last_updated":"2024-10-20T09:10:25Z","snapshot_observed_at":"2026-08-19T00:58:28.006193Z","submitted_at":"2024-05-28T14:21:15Z","title":"FinerCut: Finer-grained Interpretable Layer Pruning for Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18218","snapshot_observed_at":"2026-08-15T23:59:21.958580Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.958580Z"},"links":{"cited_paper":"/paper/2405.18218","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:38cd0f76e092b733df1da42d7e3b5f4518d08c04666ee2017b1af6450b7d6310","observation_id":"3c08c326-0638-4f05-b610-538d129b6267","resolution":{"observed_at":"2026-08-15T23:59:21.958580Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.03728","last_updated":"2024-08-07T12:33:46Z","snapshot_observed_at":"2026-08-16T13:27:58.836625Z","submitted_at":"2024-08-07T12:33:46Z","title":"A Convex-optimization-based Layer-wise Post-training Pruner for Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.03728","snapshot_observed_at":"2026-08-15T23:59:21.961549Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.961549Z"},"links":{"cited_paper":"/paper/2408.03728","citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:c08fb3a4419b2a32ef710d4448224bbfcb452b2a9bad6a715dd14482c97712a2","observation_id":"1c2d9fba-a45f-47dd-8389-04a8b1fd9a63","resolution":{"observed_at":"2026-08-15T23:59:21.961549Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T23:59:22.200479Z","title":null,"venue":null,"work_id":"4bd74143-ac8a-40a0-b768-c1c75470e7b1","year":2024},"citing_paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-15T23:59:21.965294Z"},"links":{"citing_paper":"/paper/2505.03373"},"observation_digest":"sha256:e39cb26f8da7f6df22d34afd9edf43290c0c5c3ac9a18bcbbc2c7841325e2b51","observation_id":"72aa3154-9705-49dd-a307-a7f5a58483cf","resolution":{"observed_at":"2026-08-15T23:59:22.205019Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.03373","last_updated":"2025-05-06T09:47:53Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-18T23:35:38.597843Z","submitted_at":"2025-05-06T09:47:53Z","title":"SPAP: Structured Pruning via Alternating Optimization and Penalty Methods"},"reference_resolution":{"displayed":43,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":37,"verified_exact":0,"verified_fuzzy":6},"total_outbound_references":43},"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":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2505.03373."}