{"as_of":"2026-08-09T09:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a0e8958acc10792cc2c57d6c96072e00460faa559401ce87d1688c9017678653","coverage":[{"denominator":66,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":66,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:11:02.432690Z","state":"measured"},{"denominator":68,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":68,"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":"2026-08-05T21:05:00.103629Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-05T21:05:04.132846Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"cited_work":{"arxiv_id":"2505.16284","doi":null,"metadata_source":"pith","pith_arxiv_id":"2505.16284","snapshot_observed_at":"2026-08-05T21:05:04.132846Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","venue":"cs.LG","work_id":"9498e2d1-61c1-4cc2-af39-7b32de8875f1","year":2025},"citing_paper":{"arxiv_id":"2508.09628","last_updated":"2025-08-13T08:59:13Z","snapshot_observed_at":"2026-08-08T15:12:43.884415Z","submitted_at":"2025-08-13T08:59:13Z","title":"Attention's forward pass and Frank-Wolfe","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-05T21:05:00.103629Z"},"links":{"cited_paper":"/paper/2505.16284","citing_paper":"/paper/2508.09628"},"observation_digest":"sha256:3bc34a70f205b64014bd103c4e21dbe69a58e7a7565416ce7442d9623d760259","observation_id":"d2d0fa49-e60d-42c1-aa89-fb76debf5d82","resolution":{"observed_at":"2026-08-05T21:05:04.193376Z","resolver_source":"local_arxiv","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":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.16284","snapshot_observed_at":"2026-08-02T03:08:33.307962Z","title":"Only large weights (and not skip connections) can prevent the perils of rank collapse","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.14018","last_updated":"2026-07-15T16:50:43Z","snapshot_observed_at":"2026-08-05T03:03:44.055926Z","submitted_at":"2026-07-15T16:50:43Z","title":"Transforming Rank: How Architecture Navigates the Spectral Pathologies of Depth","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-02T03:08:33.307962Z"},"links":{"cited_paper":"/paper/2505.16284","citing_paper":"/paper/2607.14018"},"observation_digest":"sha256:a65918f9530f6c1bf79f98980e28758d4d22460d11128f1043de86be1bcaa4fe","observation_id":"e48fb2be-2297-48ac-8c9a-88159c794113","resolution":{"observed_at":"2026-08-02T03:08:33.307962Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2505.16284/citation-record","integrity":"/paper/2505.16284/integrity","json":"/paper/2505.16284/citation-record.json","paper":"/paper/2505.16284"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2311.15127","last_updated":"2023-11-25T22:28:38Z","snapshot_observed_at":"2026-08-07T21:47:08.589400Z","submitted_at":"2023-11-25T22:28:38Z","title":"Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.15127","snapshot_observed_at":"2026-08-07T15:10:57.287233Z","title":"Stable video diffusion: Scaling latent video diffusion models t o large datasets","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:57.287233Z"},"links":{"cited_paper":"/paper/2311.15127","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:27c04df5c214dc1d03e8cd7d9234d87e8c26ae6dac15596bcb3c42416582afb3","observation_id":"ae5ca992-6ec5-4dca-b6ea-df7be148469d","resolution":{"observed_at":"2026-08-07T15:10:57.287233Z","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":"2026-08-07T15:11:08.593803Z","title":"On the dangers of stochastic parrots: Can langu age models be too big? In Proceedings of the 2021 ACM conference on fairness, accounta bility, and trans- parency, pages 610–623,","venue":null,"work_id":"cde1e91c-6f74-4d94-ad74-ceb36c367165","year":2021},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:57.419881Z"},"links":{"citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:676f5d5aa593d85a5cc942283600734afce72f144d84bb63b652e7fe5e81a617","observation_id":"4e35be60-8cad-42e9-a3d0-40c12a25d9bf","resolution":{"observed_at":"2026-08-07T15:11:08.686165Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2004.05150","last_updated":"2020-12-02T17:52:35Z","snapshot_observed_at":"2026-07-31T17:17:17.205582Z","submitted_at":"2020-04-10T17:54:09Z","title":"Longformer: The Long-Document Transformer","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.05150","snapshot_observed_at":"2026-08-07T15:10:57.574963Z","title":"Longf ormer: The long-document transformer","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:57.574963Z"},"links":{"cited_paper":"/paper/2004.05150","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:f3beecd0f6febd4b7b2af586992cdaf789d25643e84ec86da6b4475370312a6e","observation_id":"d13856f3-6a2a-4447-981a-e3ff59db4d3c","resolution":{"observed_at":"2026-08-07T15:10:57.574963Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.00688","last_updated":"2025-02-02T06:19:59Z","snapshot_observed_at":"2026-07-06T20:29:45.369233Z","submitted_at":"2025-02-02T06:19:59Z","title":"High-Order Matching for One-Step Shortcut Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.00688","snapshot_observed_at":"2026-08-07T15:10:57.772656Z","title":"High-order matching for one-step shor tcut diffusion models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:57.772656Z"},"links":{"cited_paper":"/paper/2502.00688","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:182558da5e4aceb25e03936b5a52b91e00527d2c1486c0a90a95120089643101","observation_id":"397d7ef6-e300-4ac1-bb06-9320443501db","resolution":{"observed_at":"2026-08-07T15:10:57.772656Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1904.10509","last_updated":"2019-04-23T19:29:47Z","snapshot_observed_at":"2026-08-09T05:01:32.757930Z","submitted_at":"2019-04-23T19:29:47Z","title":"Generating Long Sequences with Sparse Transformers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1904.10509","snapshot_observed_at":"2026-08-07T15:10:57.846217Z","title":"Generating long se- quences with sparse transformers","venue":null,"work_id":null,"year":1904},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:57.846217Z"},"links":{"cited_paper":"/paper/1904.10509","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:6605d7a200d492ddfdbc95a74c7808cd231c403d69dbb4132feb2bea1fcbb561","observation_id":"7081f584-5fae-4e2d-94c3-7dd542adfeb8","resolution":{"observed_at":"2026-08-07T15:10:57.846217Z","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":"2026-08-07T15:10:58.064002Z","title":"Fast gradient computation for rope attention in almost line ar time","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:58.064002Z"},"links":{"citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:99e6b584b92dfd2c91471fa730c61658d6b0bd1387e7b84ea1dcd87812571ec7","observation_id":"37ed28c8-f28f-44b9-ad8d-4ffbce2ddeda","resolution":{"observed_at":"2026-08-07T15:10:58.064002Z","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":"2026-08-07T15:11:08.303997Z","title":"Kernel den- sity estimation through density constrained near neighbor search","venue":null,"work_id":"ba94c7f4-33b0-4562-ae9f-5a733e22acbc","year":2020},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:58.172393Z"},"links":{"citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:f367f0640f75a3f8bbe9da2891c4a58a9d9479c03ee29b4a2c3148dc9990247e","observation_id":"9def2f06-a17f-4cba-ad90-fbee17a36fff","resolution":{"observed_at":"2026-08-07T15:11:08.379084Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2410.10165","last_updated":"2025-02-24T08:42:25Z","snapshot_observed_at":"2026-07-06T19:32:51.287674Z","submitted_at":"2024-10-14T05:18:02Z","title":"HSR-Enhanced Sparse Attention Acceleration","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.10165","snapshot_observed_at":"2026-08-07T15:10:58.408350Z","title":"Hsr-enhanced sparse attention acceleration","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:58.408350Z"},"links":{"cited_paper":"/paper/2410.10165","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:6e82cac11468b17bfcc567b7abaf56f00f34de2dd630aee10371b5f4dca012b2","observation_id":"e1c7ada7-7a00-4393-86cc-f21411dd0f20","resolution":{"observed_at":"2026-08-07T15:10:58.408350Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1810.04805","last_updated":"2019-05-24T20:37:26Z","snapshot_observed_at":"2026-07-30T09:12:38.100527Z","submitted_at":"2018-10-11T00:50:01Z","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.04805","snapshot_observed_at":"2026-08-07T15:10:58.490210Z","title":"Bert: Pre- training of deep bidirectional transformers for language understanding","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:58.490210Z"},"links":{"cited_paper":"/paper/1810.04805","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:defdd80d3c6351e8e2c53a688be53590218e8ab91a8731f72bc42aa5fbb60b2c","observation_id":"d4b62067-6cb4-4d04-85ba-d72e773e1f4e","resolution":{"observed_at":"2026-08-07T15:10:58.490210Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.00406","last_updated":"2023-06-01T07:12:00Z","snapshot_observed_at":"2026-08-05T08:31:53.334547Z","submitted_at":"2023-06-01T07:12:00Z","title":"Faster Robust Tensor Power Method for Arbitrary Order","version":1},"cited_work":{"arxiv_id":"2306.00406","doi":null,"metadata_source":"pith","pith_arxiv_id":"2306.00406","snapshot_observed_at":"2026-08-07T15:11:06.296716Z","title":"Faster Robust Tensor Power Method for Arbitrary Order","venue":"cs.LG","work_id":"3145ce8b-84aa-4800-82ed-bc394a02ba8d","year":2023},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:58.679033Z"},"links":{"cited_paper":"/paper/2306.00406","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:92ad06bae7fbe726ad23b0afdb48f30196bcac624ae8b71076af5bcce0090d3d","observation_id":"eadad6f9-9605-421c-a73a-39a129b31740","resolution":{"observed_at":"2026-08-07T15:11:06.390357Z","resolver_source":"local_arxiv","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:10:58.816750Z","title":"Superiori ty of softmax: Unveiling the performance edge over linear attention","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:58.816750Z"},"links":{"citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:39425e86fe1380eae2c93ab6b0d980e95dc819d84cfb9908cd80034bdc45024d","observation_id":"26be70bb-8984-44cb-b130-d37eff4387f7","resolution":{"observed_at":"2026-08-07T15:10:58.816750Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12557","last_updated":"2025-06-23T14:26:35Z","snapshot_observed_at":"2026-07-06T19:34:32.629776Z","submitted_at":"2024-10-16T13:34:40Z","title":"One Step Diffusion via Shortcut Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12557","snapshot_observed_at":"2026-08-07T15:10:58.928180Z","title":"One step diffusion via shortcut models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:58.928180Z"},"links":{"cited_paper":"/paper/2410.12557","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:6dd25f0b96a68d2742bd6d186e736c9b77c71daf67afb8e551223e7786054c56","observation_id":"c478d835-b6c2-4113-bfc8-5d7b9b0c8a5c","resolution":{"observed_at":"2026-08-07T15:10:58.928180Z","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":"2026-08-07T15:11:08.168022Z","title":"Sagn: semantic adaptive gr aph network for skeleton-based human action recognition","venue":null,"work_id":"1eac2d99-9a02-4f41-a80d-ddbd2a4c7c6a","year":2021},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:59.035907Z"},"links":{"citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:b832d73f6a4d93fc166d4e9cf38d44e567a258e0ec8257c9e77d7ee9939fab85","observation_id":"69fed7b7-7f73-48cf-8523-af0a8a9116f5","resolution":{"observed_at":"2026-08-07T15:11:08.236300Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2504.04051","last_updated":"2025-04-05T04:13:06Z","snapshot_observed_at":"2026-08-07T16:08:27.784868Z","submitted_at":"2025-04-05T04:13:06Z","title":"Can You Count to Nine? A Human Evaluation Benchmark for Counting Limits in Modern Text-to-Video Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.04051","snapshot_observed_at":"2026-08-07T15:10:59.137393Z","title":"Can you count to nine? a human evaluation bench mark for counting limits in modern text-to-video models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:59.137393Z"},"links":{"cited_paper":"/paper/2504.04051","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:0740ad13abf77e20f89cbaa604bd104b1f8de75cfff5de0f32cda19d30a52041","observation_id":"4effcbb0-a951-42ff-9e5a-da04e9db2bb3","resolution":{"observed_at":"2026-08-07T15:10:59.137393Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.00337","last_updated":"2025-05-01T06:34:55Z","snapshot_observed_at":"2026-08-07T22:04:00.593389Z","submitted_at":"2025-05-01T06:34:55Z","title":"T2VPhysBench: A First-Principles Benchmark for Physical Consistency in Text-to-Video Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.00337","snapshot_observed_at":"2026-08-07T15:10:59.227370Z","title":"T2vphysbench: A first-principles benchmark for physical co nsistency in text-to-video generation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:59.227370Z"},"links":{"cited_paper":"/paper/2505.00337","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:1910143b00cc363102755597826b0c48cbdb8c09d02f6fc131372502e51df45d","observation_id":"8cb376a6-b392-45e1-bb4c-431867813afe","resolution":{"observed_at":"2026-08-07T15:10:59.227370Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.04946","last_updated":"2025-05-08T04:49:52Z","snapshot_observed_at":"2026-08-07T15:48:55.791149Z","submitted_at":"2025-05-08T04:49:52Z","title":"T2VTextBench: A Human Evaluation Benchmark for Textual Control in Video Generation Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.04946","snapshot_observed_at":"2026-08-07T15:10:59.330611Z","title":"T2vtextbench: A human evaluation benchmark for textual control in video generation models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:59.330611Z"},"links":{"cited_paper":"/paper/2505.04946","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:edda9dce7960643eca15b448aeaff27f80f45ab2216bf9727fd106140bef97e1","observation_id":"7b4ff729-256f-4dc6-98e9-7ba0a5ad3299","resolution":{"observed_at":"2026-08-07T15:10:59.330611Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.14840","last_updated":"2025-05-20T19:12:43Z","snapshot_observed_at":"2026-08-08T17:27:21.465455Z","submitted_at":"2025-05-20T19:12:43Z","title":"Subquadratic Algorithms and Hardness for Attention with Any Temperature","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.14840","snapshot_observed_at":"2026-08-07T15:10:59.474337Z","title":"Sub- quadratic algorithms and hardness for attention with any te mperature","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:59.474337Z"},"links":{"cited_paper":"/paper/2505.14840","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:c6c711b903586daa30b681c2070d7b82fed14f0d8a849eeaef034f2b999fa35a","observation_id":"e89f4b95-e4dd-4266-b404-8d946c58019e","resolution":{"observed_at":"2026-08-07T15:10:59.474337Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.15010","last_updated":"2023-04-28T17:59:25Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-04-28T17:59:25Z","title":"LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.15010","snapshot_observed_at":"2026-08-07T15:10:59.558588Z","title":"Llama-adapter v2: Parameter- efficient visual instruction model","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:59.558588Z"},"links":{"cited_paper":"/paper/2304.15010","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:3ff9e73da0a0dc13cdc0b92a798366346312362e240b782c091b297aae409f3e","observation_id":"1be84ea0-f6bc-42ad-8bd9-dbb8b6ce5056","resolution":{"observed_at":"2026-08-07T15:10:59.558588Z","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":"2026-08-07T15:10:59.690542Z","title":"On computational limits of flowar models: Express ivity and efficiency","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:59.690542Z"},"links":{"citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:37140d9923155e4374ab531b0e93f31d7c888deace7d3830655436f0e7bcb2d0","observation_id":"1a39ee53-ea4e-4dbe-b892-8a20a1b03f89","resolution":{"observed_at":"2026-08-07T15:10:59.690542Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.16504","last_updated":"2023-03-29T07:29:07Z","snapshot_observed_at":"2026-08-06T05:59:13.906664Z","submitted_at":"2023-03-29T07:29:07Z","title":"An Over-parameterized Exponential Regression","version":1},"cited_work":{"arxiv_id":"2303.16504","doi":null,"metadata_source":"pith","pith_arxiv_id":"2303.16504","snapshot_observed_at":"2026-08-07T15:11:05.734621Z","title":"An Over-parameterized Exponential Regression","venue":"cs.LG","work_id":"5709f6e5-a23c-4a31-9416-2894a5847a6c","year":2023},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:59.813587Z"},"links":{"cited_paper":"/paper/2303.16504","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:dca7aaf1502668cd56934e23801dfe30791223a4184a0d613434e1e12b82f67f","observation_id":"7c72273d-d255-4923-9ff0-cf02b744c4b2","resolution":{"observed_at":"2026-08-07T15:11:05.853106Z","resolver_source":"local_arxiv","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:10:59.958220Z","title":"Fas t quantum algorithm for attention computation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:59.958220Z"},"links":{"citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:b4e9f033d76ef77870ff4174c076a49a461cf7302bc82b3e544cb50c94ec9e65","observation_id":"a8ae4233-160a-4312-9e3f-16c8a62b1ade","resolution":{"observed_at":"2026-08-07T15:10:59.958220Z","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":"2026-08-07T15:11:07.998743Z","title":"Differe ntially private attention computation","venue":null,"work_id":"d22b362e-19dd-4696-86e2-c4ff7f8fe7b9","year":2024},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:00.061873Z"},"links":{"citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:beaa139b5f01b776f39da53031368d0e28d1613f03d07485a345be3aa3283338","observation_id":"ad557723-f39f-41b5-b4f4-d268540ea384","resolution":{"observed_at":"2026-08-07T15:11:08.041139Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2303.06562","last_updated":"2023-05-02T13:38:34Z","snapshot_observed_at":"2026-07-06T15:01:49.803305Z","submitted_at":"2023-03-12T04:04:51Z","title":"ContraNorm: A Contrastive Learning Perspective on Oversmoothing and Beyond","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.06562","snapshot_observed_at":"2026-08-07T15:11:00.121842Z","title":"Contranorm: A contrastive learning perspective on oversmoothing and beyond","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:00.121842Z"},"links":{"cited_paper":"/paper/2303.06562","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:ea3bef8fe56c1e279c0905633f808ce82f814a09e45de790b9bc92d583681d82","observation_id":"b6920609-4c27-46fa-a82d-85e362eca3a6","resolution":{"observed_at":"2026-08-07T15:11:00.121842Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.15578","last_updated":"2024-10-21T01:55:52Z","snapshot_observed_at":"2026-07-06T19:36:45.701678Z","submitted_at":"2024-10-21T01:55:52Z","title":"Generalized Probabilistic Attention Mechanism in Transformers","version":1},"cited_work":{"arxiv_id":"2410.15578","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.15578","snapshot_observed_at":"2026-08-07T15:11:05.349209Z","title":"Generalized Probabilistic Attention Mechanism in Transformers","venue":"cs.LG","work_id":"3f2e4611-28eb-4fec-90ac-7cf7b20ed3d8","year":2024},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:00.180961Z"},"links":{"cited_paper":"/paper/2410.15578","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:e3a86616260a0e4f21402d3779a5459b7681799ad5d1951c06190f288778f6f8","observation_id":"f7a78c96-b6d3-45e2-b025-322c0481cef7","resolution":{"observed_at":"2026-08-07T15:11:05.477298Z","resolver_source":"local_arxiv","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":"2406.03136","last_updated":"2025-06-06T05:22:09Z","snapshot_observed_at":"2026-07-06T18:25:48.914502Z","submitted_at":"2024-06-05T10:44:08Z","title":"Computational Limits of Low-Rank Adaptation (LoRA) Fine-Tuning for Transformer Models","version":2},"cited_work":{"arxiv_id":"2406.03136","doi":null,"metadata_source":"pith","pith_arxiv_id":"2406.03136","snapshot_observed_at":"2026-08-07T15:11:05.145102Z","title":"Computational Limits of Low-Rank Adaptation (LoRA) Fine-Tuning for Transformer Models","venue":"cs.LG","work_id":"431d38bf-54fa-4280-b989-cfbc860a27d0","year":2024},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:00.238993Z"},"links":{"cited_paper":"/paper/2406.03136","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:4d81f18f1a79ba4edfdb586ab5dce6954074174d07b15df91beed3d2997c5bbd","observation_id":"3c3ed1ad-f5e9-435b-a09b-13604fc7fe22","resolution":{"observed_at":"2026-08-07T15:11:05.244812Z","resolver_source":"local_arxiv","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":"2407.01079","last_updated":"2024-10-31T16:59:13Z","snapshot_observed_at":"2026-07-06T18:39:24.513351Z","submitted_at":"2024-07-01T08:34:40Z","title":"On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs)","version":3},"cited_work":{"arxiv_id":"2407.01079","doi":null,"metadata_source":"pith","pith_arxiv_id":"2407.01079","snapshot_observed_at":"2026-08-07T15:11:05.025939Z","title":"On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs)","venue":"stat.ML","work_id":"b3264c38-2f73-40aa-ba07-306184521e96","year":2024},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:00.371342Z"},"links":{"cited_paper":"/paper/2407.01079","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:c067379be16c6e1d2ddc05d9ec5e4bee2570e91117437c1ad138de8b098345d4","observation_id":"691ba6f4-69df-461b-a360-6c0198c84da1","resolution":{"observed_at":"2026-08-07T15:11:05.074634Z","resolver_source":"local_arxiv","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":"2310.06927","last_updated":"2023-10-13T13:47:44Z","snapshot_observed_at":"2026-07-06T16:30:41.852589Z","submitted_at":"2023-10-10T18:28:38Z","title":"Sparse Fine-tuning for Inference Acceleration of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.06927","snapshot_observed_at":"2026-08-07T15:11:00.461703Z","title":"Sparse finetuning for inference acceleration of large langu age models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:00.461703Z"},"links":{"cited_paper":"/paper/2310.06927","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:23f18f473b1bb9582b499982c3bf6608dcd9ff94acbb7b7d313372fb81bab25d","observation_id":"63b4de37-4f7c-4241-87f0-0acefa71aede","resolution":{"observed_at":"2026-08-07T15:11:00.461703Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.02834","last_updated":"2024-06-23T08:45:33Z","snapshot_observed_at":"2026-08-07T23:10:12.222808Z","submitted_at":"2024-02-05T09:44:49Z","title":"Shortened LLaMA: Depth Pruning for Large Language Models with Comparison of Retraining Methods","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.02834","snapshot_observed_at":"2026-08-07T15:11:00.526233Z","title":"Shortened llama: A simple d epth pruning for large language models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:00.526233Z"},"links":{"cited_paper":"/paper/2402.02834","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:07728b821f19318b11937070d7edd52c4e3cbce5c07a9b849e1835796b670d8b","observation_id":"464956f2-9dab-4c33-8b65-ad6b6ac61434","resolution":{"observed_at":"2026-08-07T15:11:00.526233Z","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":"2026-08-07T15:11:07.907183Z","title":"On the power of preconditioning in sparse linear regression","venue":null,"work_id":"690a41fd-3491-46ab-8bdc-40011a0dcf59","year":2021},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:00.609105Z"},"links":{"citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:58cfce9b769e1cc12521f29c720233c40ad55de37a0204eb2f40c1b8c04c9941","observation_id":"ed37a3ed-7e14-4fe9-9882-4952eb62ff98","resolution":{"observed_at":"2026-08-07T15:11:07.955089Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2212.14024","last_updated":"2023-01-23T17:00:01Z","snapshot_observed_at":"2026-08-06T22:47:15.172350Z","submitted_at":"2022-12-28T18:52:44Z","title":"Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.14024","snapshot_observed_at":"2026-08-07T15:11:00.664900Z","title":"Demonstrate-search-predict: Composing retrieval and language models for knowledge-intensive nlp","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:00.664900Z"},"links":{"cited_paper":"/paper/2212.14024","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:9f7d0479b85eedac63076e9dd97be5b1b8220077f3da8e727bd9bbc45ebfce77","observation_id":"2087cf65-9e10-43ee-a267-af8e5681e1d0","resolution":{"observed_at":"2026-08-07T15:11:00.664900Z","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":"2026-08-07T15:11:00.703848Z","title":"Simulation of hypergraph algorithms with looped tr ansformers","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:00.703848Z"},"links":{"citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:4112275ece2b0aef4e9b208c72d6bbd153050d9627218daca48bd5d0649fa986","observation_id":"83447a50-a4aa-43d9-9d23-c448ddf74ac0","resolution":{"observed_at":"2026-08-07T15:11:00.703848Z","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":"2405.03251","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:11:04.506316Z","title":"Exploring the frontiers of softmax: Provable optimization, applications in diffusion m odel, and beyond","venue":null,"work_id":"4c4c39db-a56b-47d0-810d-5868ee89825b","year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:00.905892Z"},"links":{"citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:2e082bb7edbc42957f006f27d199b5887ae9a70d947d52319997275ffaed1a04","observation_id":"8c653ab5-95e6-40f2-9e5e-82bd315108e2","resolution":{"observed_at":"2026-08-07T15:11:04.574245Z","resolver_source":"raw_fallback","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":"2408.12151","last_updated":"2024-10-18T03:36:03Z","snapshot_observed_at":"2026-07-06T19:04:26.917233Z","submitted_at":"2024-08-22T06:40:32Z","title":"A Tighter Complexity Analysis of SparseGPT","version":2},"cited_work":{"arxiv_id":"2408.12151","doi":null,"metadata_source":"pith","pith_arxiv_id":"2408.12151","snapshot_observed_at":"2026-08-07T15:11:04.208435Z","title":"A Tighter Complexity Analysis of SparseGPT","venue":"cs.DS","work_id":"3e9aac7b-c4a2-40ab-9f40-4d11d41f614e","year":2024},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:01.006242Z"},"links":{"cited_paper":"/paper/2408.12151","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:8ee05ca1e269c5a02a0a3027e382d88110dc59150d4e9d9a0462fdd96a5a32b6","observation_id":"526a9e26-0eb2-4d0d-8877-990071229060","resolution":{"observed_at":"2026-08-07T15:11:04.312562Z","resolver_source":"local_arxiv","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":"2407.13621","last_updated":"2024-11-02T05:30:20Z","snapshot_observed_at":"2026-08-04T10:32:09.349940Z","submitted_at":"2024-07-18T15:57:55Z","title":"Differential Privacy Mechanisms in Neural Tangent Kernel Regression","version":2},"cited_work":{"arxiv_id":"2407.13621","doi":null,"metadata_source":"pith","pith_arxiv_id":"2407.13621","snapshot_observed_at":"2026-08-07T15:11:03.876031Z","title":"Differential Privacy Mechanisms in Neural Tangent Kernel Regression","venue":"cs.LG","work_id":"82390ad3-c409-4d89-a36c-f6f54f8d1bbb","year":2024},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:01.150538Z"},"links":{"cited_paper":"/paper/2407.13621","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:7af3a291bdfebcd23c3a1a0b92e431a8923112c88d87e375973648a4a6c521e8","observation_id":"30edbdec-b0be-4440-a910-3012d405961f","resolution":{"observed_at":"2026-08-07T15:11:04.047829Z","resolver_source":"local_arxiv","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:11:01.201154Z","title":"Differential privacy of cross- attention with provable guarantee","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:01.201154Z"},"links":{"citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:c23fb0f1871d505b74a58014ee6bf6f39d379d0bb7417c7b72a9242e77ae124c","observation_id":"60c79b3b-fe08-41d0-bdc4-ba09ac61ec76","resolution":{"observed_at":"2026-08-07T15:11:01.201154Z","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":"2026-08-07T15:11:01.239808Z","title":"Tensor attention train- ing: Provably efficient learning of higher-order transforme rs","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:01.239808Z"},"links":{"citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:50d50152081a3bd3713ba5d396ccfdf6d666a385709c4653f09cef6a985af638","observation_id":"ba38dcfe-ef43-4302-a0fc-d4154dc35afb","resolution":{"observed_at":"2026-08-07T15:11:01.239808Z","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":"2026-07-06T18:55:11.576666Z","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":"2026-08-07T15:11:01.298262Z","title":"The llama 3 herd of models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:01.298262Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:45039e5971d0b12d804f9c923394ffc2bdf8a2f77fa871cd36c172de0cbb1dce","observation_id":"a74be657-abfe-442b-b68a-6eaf51535d38","resolution":{"observed_at":"2026-08-07T15:11:01.298262Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.15579","last_updated":"2025-08-27T08:40:47Z","snapshot_observed_at":"2026-07-06T20:10:41.978020Z","submitted_at":"2024-12-20T05:23:45Z","title":"Score-based Generative Diffusion Models for Social Recommendations","version":2},"cited_work":{"arxiv_id":"2412.15579","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.15579","snapshot_observed_at":"2026-08-07T15:11:03.503634Z","title":"Score-based Generative Diffusion Models for Social Recommendations","venue":"cs.SI","work_id":"cedd1f7f-89cb-4b2d-9da9-04493d7d473a","year":2024},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:01.383054Z"},"links":{"cited_paper":"/paper/2412.15579","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:35ab72cd74dbcb9dded7fb38e6ee9d86bc11f1d06648933927490e9804d77808","observation_id":"44f97945-08e5-4721-867a-522f7f925b30","resolution":{"observed_at":"2026-08-07T15:11:03.578696Z","resolver_source":"local_arxiv","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":"2501.09038","last_updated":"2025-02-27T15:10:51Z","snapshot_observed_at":"2026-08-02T17:18:33.867969Z","submitted_at":"2025-01-14T20:59:37Z","title":"Do generative video models understand physical principles?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.09038","snapshot_observed_at":"2026-08-07T15:11:01.498098Z","title":"Do generative video models learn physical principles from w atching videos? arXiv preprint arXiv:2501.09038,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:01.498098Z"},"links":{"cited_paper":"/paper/2501.09038","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:6299341a689279c8b5403a6080c5d8ef47cf793f97b731d6747376216870d4a7","observation_id":"65b39b20-75e1-490c-978a-93dcf0f60872","resolution":{"observed_at":"2026-08-07T15:11:01.498098Z","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":"2026-08-07T15:11:07.676733Z","title":"Great power, great responsibility: Recom mendations for reducing energy for training language models","venue":null,"work_id":"be27197c-7adf-488f-ad00-273434a96965","year":2022},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:01.552238Z"},"links":{"citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:afbe128495491f506631468bd3f64661d9c5d3bd3c467679e32b497d26aef1df","observation_id":"d8606f76-e9f0-4b7a-b3b2-c20108d802a0","resolution":{"observed_at":"2026-08-07T15:11:07.796116Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2112.13310","last_updated":"2021-12-26T03:23:59Z","snapshot_observed_at":"2026-07-06T12:22:24.025336Z","submitted_at":"2021-12-26T03:23:59Z","title":"Miti-DETR: Object Detection based on Transformers with Mitigatory Self-Attention Convergence","version":1},"cited_work":{"arxiv_id":"2112.13310","doi":null,"metadata_source":"pith","pith_arxiv_id":"2112.13310","snapshot_observed_at":"2026-08-07T15:11:03.371404Z","title":"Miti-DETR: Object Detection based on Transformers with Mitigatory Self-Attention Convergence","venue":"cs.CV","work_id":"805c7ca1-893c-4c93-b71d-3cd29bc78422","year":2021},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:01.642887Z"},"links":{"cited_paper":"/paper/2112.13310","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:0d1c98635a7270b306e0d3ac188676c067640a4cbdbefe85b2925f518c78e823","observation_id":"343f9c74-55d3-4fe5-9512-99b86e813985","resolution":{"observed_at":"2026-08-07T15:11:03.404449Z","resolver_source":"local_arxiv","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:11:07.478921Z","title":"Osnap: Faster numerical linear algebra algorithms via sparser subspace embeddings","venue":null,"work_id":"58c588a5-1b52-48cd-9a42-083f8880068c","year":2013},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:01.694596Z"},"links":{"citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:78283e26eaa5d6d3affaa82fb0749e7c5bcb45045443b758ec89f048d71c8bd7","observation_id":"dc4723b6-eb58-4978-9a39-59a8c1a66f23","resolution":{"observed_at":"2026-08-07T15:11:07.588867Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-07T15:11:01.774327Z","title":"Gpt-4 technical report","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:01.774327Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:ddf2006d6271531e6585faded709a37ad44389c3a91010ff1b740b3b8a442142","observation_id":"e37d840e-7c8b-4656-8c25-2aac22c38233","resolution":{"observed_at":"2026-08-07T15:11:01.774327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.08621","last_updated":"2023-08-09T08:53:08Z","snapshot_observed_at":"2026-08-02T13:21:32.251959Z","submitted_at":"2023-07-17T16:40:01Z","title":"Retentive Network: A Successor to Transformer for Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.08621","snapshot_observed_at":"2026-08-07T15:11:01.812673Z","title":"Retentive network: A successor to tra nsformer for large language models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:01.812673Z"},"links":{"cited_paper":"/paper/2307.08621","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:e167d1a69f37fceee63d5629e2c388462517f99976bb9753cc5652954cd2c15f","observation_id":"1c17b35d-389a-4543-8371-b819c13259c4","resolution":{"observed_at":"2026-08-07T15:11:01.812673Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.12441","last_updated":"2024-12-17T01:09:23Z","snapshot_observed_at":"2026-07-06T20:08:12.033767Z","submitted_at":"2024-12-17T01:09:23Z","title":"Numerical Pruning for Efficient Autoregressive Models","version":1},"cited_work":{"arxiv_id":"2412.12441","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.12441","snapshot_observed_at":"2026-08-07T15:11:03.194661Z","title":"Numerical Pruning for Efficient Autoregressive Models","venue":"cs.LG","work_id":"5a8b954d-00b1-471c-a860-e147b544e454","year":2024},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:01.891088Z"},"links":{"cited_paper":"/paper/2412.12441","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:51fbe693097b9034b8054a82d8cea1d671d50c4fa0673943a8cf9bb764b4458e","observation_id":"2ab26d5d-2cb1-4703-8da2-06c387b504c4","resolution":{"observed_at":"2026-08-07T15:11:03.228296Z","resolver_source":"local_arxiv","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":"2311.14823","last_updated":"2023-11-24T19:41:28Z","snapshot_observed_at":"2026-07-06T16:52:07.175998Z","submitted_at":"2023-11-24T19:41:28Z","title":"Revisiting Quantum Algorithms for Linear Regressions: Quadratic Speedups without Data-Dependent Parameters","version":1},"cited_work":{"arxiv_id":"2311.14823","doi":null,"metadata_source":"pith","pith_arxiv_id":"2311.14823","snapshot_observed_at":"2026-08-07T15:11:03.065178Z","title":"Revisiting Quantum Algorithms for Linear Regressions: Quadratic Speedups without Data-Dependent Parameters","venue":"quant-ph","work_id":"99714c31-087b-4ce6-9565-7dcac8de2e7f","year":2023},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:01.948127Z"},"links":{"cited_paper":"/paper/2311.14823","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:eb6f2a9963dbf6df47129efea3f5c649714996cb6792bae01a5046fab4825521","observation_id":"46724db5-2cc8-4452-bf5a-0b194988abe5","resolution":{"observed_at":"2026-08-07T15:11:03.127847Z","resolver_source":"local_arxiv","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":"1908.11775","last_updated":"2019-11-11T21:51:11Z","snapshot_observed_at":"2026-08-07T12:23:46.977643Z","submitted_at":"2019-08-30T15:05:02Z","title":"Transformer Dissection: A Unified Understanding of Transformer's Attention via the Lens of Kernel","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1908.11775","snapshot_observed_at":"2026-08-07T15:11:01.988890Z","title":"Transformer dissection: a unified un derstanding of trans- former’s attention via the lens of kernel","venue":null,"work_id":null,"year":1908},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:01.988890Z"},"links":{"cited_paper":"/paper/1908.11775","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:190b4f7956c116f8e529db0bf57da2e64824bc2a3583ee2fa264a899f54da803","observation_id":"d5c18a48-6338-426b-9fe2-8e0adb748371","resolution":{"observed_at":"2026-08-07T15:11:01.988890Z","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":"2412.20984","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:11:02.843635Z","title":"Alignab: Pareto- optimal energy alignment for designing nature-like antibo dies","venue":null,"work_id":"143c46ce-1205-4b99-ab4a-16019afded4b","year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:02.048288Z"},"links":{"citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:160a4619f795b9a82debe7bcfffacf738cad4ca69b801b8d36e9203c2cdc303c","observation_id":"c1b239f0-a21f-4541-9e4c-a89e5007a8a8","resolution":{"observed_at":"2026-08-07T15:11:02.930307Z","resolver_source":"raw_fallback","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:11:07.277451Z","title":"Ev idence-aware fake news detection with graph neural networks","venue":null,"work_id":"26124c0e-71c1-41ec-9ed2-cf48429fdcb4","year":2022},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:02.105664Z"},"links":{"citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:8f555db32fc7f336d7fe1fe4a82636d87d88eb03b317796106a882278079bf64","observation_id":"d2582f56-ee71-44af-b8c9-9908d113dc60","resolution":{"observed_at":"2026-08-07T15:11:07.381558Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2410.10914","last_updated":"2024-10-14T06:28:40Z","snapshot_observed_at":"2026-07-06T19:33:21.541657Z","submitted_at":"2024-10-14T06:28:40Z","title":"Towards Better Multi-head Attention via Channel-wise Sample Permutation","version":1},"cited_work":{"arxiv_id":"2410.10914","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.10914","snapshot_observed_at":"2026-08-07T15:11:02.598513Z","title":"Towards Better Multi-head Attention via Channel-wise Sample Permutation","venue":"cs.LG","work_id":"aaf2426b-c9cc-41f1-bddc-806c86f995cb","year":2024},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:02.195072Z"},"links":{"cited_paper":"/paper/2410.10914","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:ee4ed0e7cc9b0a4acb25a68ee8373f247e91c40015e440bc87c46211f0cce053","observation_id":"bcb163b4-5db3-4f3a-b791-e068cd32876f","resolution":{"observed_at":"2026-08-07T15:11:02.647244Z","resolver_source":"local_arxiv","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":"2306.09927","last_updated":"2023-10-19T20:31:32Z","snapshot_observed_at":"2026-07-06T15:43:31.881201Z","submitted_at":"2023-06-16T15:50:03Z","title":"Trained Transformers Learn Linear Models In-Context","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.09927","snapshot_observed_at":"2026-08-07T15:11:02.235661Z","title":"Tra ined transformers learn linear models in-context","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:02.235661Z"},"links":{"cited_paper":"/paper/2306.09927","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:0cf3e7b711c49f388be005bfa6f87734b50e8fa00d14c9479e0a2bdd7c1e52b9","observation_id":"726141bb-2a40-426a-9ef6-1ff457cecb61","resolution":{"observed_at":"2026-08-07T15:11:02.235661Z","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":"2026-08-07T15:11:07.130118Z","title":"Graph unlearning with efficient partia l retraining","venue":null,"work_id":"4f003cad-6073-4eaf-accb-860d97b6a922","year":2024},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:02.295900Z"},"links":{"citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:6ec44cf5b1272f4afc06c341126ad1261479439ec72aac41173c125f96d7aff9","observation_id":"7d75fe4a-da1d-4538-ab86-86b1db4109cd","resolution":{"observed_at":"2026-08-07T15:11:07.171546Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2302.02451","last_updated":"2023-06-29T17:51:10Z","snapshot_observed_at":"2026-08-01T17:14:19.934588Z","submitted_at":"2023-02-05T18:23:49Z","title":"KDEformer: Accelerating Transformers via Kernel Density Estimation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.02451","snapshot_observed_at":"2026-08-07T15:11:02.385646Z","title":"Kdeformer: Ac- celerating transformers via kernel density estimation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:02.385646Z"},"links":{"cited_paper":"/paper/2302.02451","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:153e29612e2809a2657a3d1a798fd68f363b4d3758488629f5c673ba5a3cbe11","observation_id":"bdbbbe23-e1a9-435c-a933-f82ae54b19ee","resolution":{"observed_at":"2026-08-07T15:11:02.385646Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.16199","last_updated":"2024-09-18T23:54:36Z","snapshot_observed_at":"2026-08-06T06:36:02.994951Z","submitted_at":"2023-03-28T17:59:12Z","title":"LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.16199","snapshot_observed_at":"2026-08-07T15:11:02.432690Z","title":"Llama-adapter: Efficient fine- tuning of language models with zero-init attention","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:02.432690Z"},"links":{"cited_paper":"/paper/2303.16199","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:139e8ed5b8441561492038530f261d05427bcd7f0a9d2cf5d1e66bfa53369723","observation_id":"caa6a95b-2b78-41d0-b4bd-0eb87c82a535","resolution":{"observed_at":"2026-08-07T15:11:02.432690Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.07799","last_updated":"2025-06-16T12:30:24Z","snapshot_observed_at":"2026-07-06T19:31:05.226753Z","submitted_at":"2024-10-10T10:34:18Z","title":"Mind the Gap: a Spectral Analysis of Rank Collapse and Signal Propagation in Attention Layers","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.07799","snapshot_observed_at":"2026-08-07T15:11:01.736227Z","title":"Mind the gap: a spectral analysis of rank collapse and signal propagation in transfo rmers","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":2013,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:01.736227Z"},"links":{"cited_paper":"/paper/2410.07799","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:a4ba6884124af8fdcb2f4bb14bead46ac53c63d1c465af2d5421909e254762de","observation_id":"03341e0c-7b97-43e3-aef5-43a475fe8e1e","resolution":{"observed_at":"2026-08-07T15:11:01.736227Z","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":"2026-08-07T15:10:57.684027Z","title":"Text-to-image diffusion models canno t count, and prompt refinement cannot help","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":2014,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:57.684027Z"},"links":{"citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:dad44b6b43bc8912f83d7d933613f68f00aef07cbc0c34e55dc092bfe1706d97","observation_id":"02f9f4f3-7bc7-4560-968c-67a3b5d2ffa0","resolution":{"observed_at":"2026-08-07T15:10:57.684027Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.05219","last_updated":"2024-10-16T06:55:47Z","snapshot_observed_at":"2026-07-06T18:11:38.755996Z","submitted_at":"2024-05-08T17:11:38Z","title":"Conv-Basis: A New Paradigm for Efficient Attention Inference and Gradient Computation in Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.05219","snapshot_observed_at":"2026-08-07T15:11:00.842439Z","title":"Conv-basis: A new paradigm for efficient attention inference and gradient computation in trans- formers","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":2016,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:00.842439Z"},"links":{"cited_paper":"/paper/2405.05219","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:46d0fd8d1ae1178fa42d33b2ed6012d7ce00ef3040667fe579e5455008e27e5b","observation_id":"7810ca21-9f36-4c33-9a35-b3b10170829d","resolution":{"observed_at":"2026-08-07T15:11:00.842439Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.01996","last_updated":"2025-08-19T02:38:59Z","snapshot_observed_at":"2026-08-07T15:56:40.603444Z","submitted_at":"2025-05-04T05:42:21Z","title":"Always Skip Attention","version":3},"cited_work":{"arxiv_id":"2505.01996","doi":null,"metadata_source":"pith","pith_arxiv_id":"2505.01996","snapshot_observed_at":"2026-08-07T15:11:04.853437Z","title":"Always Skip Attention","venue":"cs.LG","work_id":"a6ff14a4-e081-4df5-8115-04a05e26ee50","year":2025},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:00.419826Z"},"links":{"cited_paper":"/paper/2505.01996","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:817df271ae2059c9de52c04645828c89b896e6cdd1a2365cd182afe2ff8bba14","observation_id":"21c247cb-52a6-4447-9879-a090bceb86d2","resolution":{"observed_at":"2026-08-07T15:11:04.926625Z","resolver_source":"local_arxiv","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":"2303.04555","last_updated":"2023-03-08T13:13:33Z","snapshot_observed_at":"2026-08-07T05:04:46.567391Z","submitted_at":"2023-03-08T13:13:33Z","title":"Streaming Kernel PCA Algorithm With Small Space","version":1},"cited_work":{"arxiv_id":"2303.04555","doi":null,"metadata_source":"pith","pith_arxiv_id":"2303.04555","snapshot_observed_at":"2026-08-07T15:11:06.517239Z","title":"Streaming Kernel PCA Algorithm With Small Space","venue":"cs.LG","work_id":"fdbd4630-a70c-4b59-b713-584422ab2a51","year":2023},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:58.597364Z"},"links":{"cited_paper":"/paper/2303.04555","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:34a4cda4a3d229201e8670b394276eeaaa34ae192c093d679bc8fbded6edc407","observation_id":"7c0421dc-ad71-43c5-9657-25175df3b7a0","resolution":{"observed_at":"2026-08-07T15:11:06.573307Z","resolver_source":"local_arxiv","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":"2210.11416","last_updated":"2022-12-06T21:39:48Z","snapshot_observed_at":"2026-07-06T14:08:18.855958Z","submitted_at":"2022-10-20T16:58:32Z","title":"Scaling Instruction-Finetuned Language Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.11416","snapshot_observed_at":"2026-08-07T15:10:57.952918Z","title":"Scaling instruction-finetuned language models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:57.952918Z"},"links":{"cited_paper":"/paper/2210.11416","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:9f1bdb784d82a8cc9ed81c3832b5202c70113176c18072079c85bc20b7ea1ef4","observation_id":"f096e649-0a24-48b1-9744-c62ca73fa541","resolution":{"observed_at":"2026-08-07T15:10:57.952918Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.07602","last_updated":"2024-12-01T06:39:41Z","snapshot_observed_at":"2026-08-07T22:02:40.620185Z","submitted_at":"2024-11-12T07:24:41Z","title":"Circuit Complexity Bounds for RoPE-based Transformer Architecture","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.07602","snapshot_observed_at":"2026-08-07T15:10:58.286424Z","title":"Circuit complexity bounds for rope-based transformer arch itecture","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:58.286424Z"},"links":{"cited_paper":"/paper/2411.07602","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:8f10d97bd913edeeb2c7d1465c35970d475a2f11b26d331f3f76aa71dd4d8c85","observation_id":"b55a5859-5eb5-4dbc-a6fe-bcefce5b82ba","resolution":{"observed_at":"2026-08-07T15:10:58.286424Z","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":"2026-08-07T15:11:08.494117Z","title":"Videophy: Eval- uating physical commonsense for video generation","venue":null,"work_id":"ad2b29c2-998a-4c37-b28d-f75dddb14a3d","year":2024},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:57.497069Z"},"links":{"citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:494d3f8c017ee887bb9493b775919c9192b8aed62a26e1147773f46d4375a45f","observation_id":"8383b2aa-946e-441e-8191-310cea6f1728","resolution":{"observed_at":"2026-08-07T15:11:08.542715Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2408.13233","last_updated":"2024-10-15T04:11:19Z","snapshot_observed_at":"2026-07-06T19:05:14.227812Z","submitted_at":"2024-08-23T17:16:43Z","title":"Multi-Layer Transformers Gradient Can be Approximated in Almost Linear Time","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.13233","snapshot_observed_at":"2026-08-07T15:11:01.085476Z","title":"Multi-layer transformers gradient can be approximated in almost linear time","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-07T15:11:01.085476Z"},"links":{"cited_paper":"/paper/2408.13233","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:09ba4285f5109eb38bcc8a002b33a908284765dc15853bc4716c7f2fc260ba2a","observation_id":"27335392-8eab-45ff-b9d4-e10df6807577","resolution":{"observed_at":"2026-08-07T15:11:01.085476Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12033","last_updated":"2025-02-17T17:03:12Z","snapshot_observed_at":"2026-08-07T18:11:42.641366Z","submitted_at":"2025-02-17T17:03:12Z","title":"The geometry of BERT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.12033","snapshot_observed_at":"2026-08-07T15:10:57.334960Z","title":"The geometry of bert","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:57.334960Z"},"links":{"cited_paper":"/paper/2502.12033","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:56b655d61cc8bb95db9e510dfc55c21cbeb1217c376a3ed4c29a9102afe03990","observation_id":"a591c357-6ffc-4e07-8735-366c68f1ed82","resolution":{"observed_at":"2026-08-07T15:10:57.334960Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.11892","last_updated":"2025-05-17T08:03:50Z","snapshot_observed_at":"2026-08-07T15:44:24.823336Z","submitted_at":"2025-05-17T08:03:50Z","title":"Fast RoPE Attention: Combining the Polynomial Method and Fast Fourier Transform","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.11892","snapshot_observed_at":"2026-08-07T15:10:57.183708Z","title":"Fast rope attention: Combin ing the polynomial method and fast fourier transform","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:57.183708Z"},"links":{"cited_paper":"/paper/2505.11892","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:e3a2a8778cf0ead38cecb5881936f85180e37d715cd3842c259a2d9b9e469a2b","observation_id":"621ca083-c8d5-43ac-958c-942fd50c1dbb","resolution":{"observed_at":"2026-08-07T15:10:57.183708Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.02732","last_updated":"2025-08-05T16:43:21Z","snapshot_observed_at":"2026-08-08T16:05:45.479083Z","submitted_at":"2025-04-03T16:17:55Z","title":"Why do LLMs attend to the first token?","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.02732","snapshot_observed_at":"2026-08-07T15:10:57.273068Z","title":"Why do llms attend to the fir st token? arXiv preprint arXiv:2504.02732,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-07T15:10:57.273068Z"},"links":{"cited_paper":"/paper/2504.02732","citing_paper":"/paper/2505.16284"},"observation_digest":"sha256:643ddb8e482b4a86e8dd3a5a5282758142b9fb06ff046c3bae35371028b9cd4b","observation_id":"0b777600-3eb0-4152-a720-4b038b431ba4","resolution":{"observed_at":"2026-08-07T15:10:57.273068Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2505.16284","last_updated":"2025-05-22T06:26:28Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T22:03:10.571335Z","submitted_at":"2025-05-22T06:26:28Z","title":"Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse"},"reference_resolution":{"displayed":66,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":40,"verified_exact":16,"verified_fuzzy":10},"total_outbound_references":66},"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 9 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 2 inbound Pith citation observations for arXiv:2505.16284."}