{"as_of":"2026-08-08T08:27:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:378a2d078de4bbf73d080b8c05fdb4e3a5ab93bce76c46573dbf34dd71752972","coverage":[{"denominator":62,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":62,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:13:25.493384Z","state":"measured"},{"denominator":63,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":63,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-26T21:25:15.709652Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-04T00:09:15.167070Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"cited_work":{"arxiv_id":"2505.22549","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.22549","snapshot_observed_at":"2026-07-04T00:09:15.167070Z","title":"F., Qiu, X., and Lane, N","venue":null,"work_id":"68723ad5-e131-4ba9-baff-a73c1f80738f","year":2025},"citing_paper":{"arxiv_id":"2606.19025","last_updated":"2026-06-20T12:18:17Z","snapshot_observed_at":"2026-08-04T11:35:50.051001Z","submitted_at":"2026-06-17T12:50:07Z","title":"FoMoE: Breaking the Full-Replica Barrier with a Federation of MoEs","version":2},"reference_index":110,"source":"arxiv_source","source_observed_at":"2026-06-26T21:25:15.709652Z"},"links":{"cited_paper":"/paper/2505.22549","citing_paper":"/paper/2606.19025"},"observation_digest":"sha256:9ec9c194f77737fc149f85799855b9eb83c72e079aa7dc52a1d8642d70483212","observation_id":"4e410f05-9633-4292-9045-ef6ea71e3455","resolution":{"observed_at":"2026-07-04T00:09:15.169175Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2505.22549/citation-record","integrity":"/paper/2505.22549/integrity","json":"/paper/2505.22549/citation-record.json","paper":"/paper/2505.22549"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.02737","last_updated":"2025-02-04T21:43:16Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-02-04T21:43:16Z","title":"SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.02737","snapshot_observed_at":"2026-08-07T13:13:20.016971Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:20.016971Z"},"links":{"cited_paper":"/paper/2502.02737","citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:6772abbd539df2b24728b7ef6b985501e6289f9cbadb9c02c29c2927a68e92cd","observation_id":"d2172a97-5db9-44bd-940e-f6e3a406a789","resolution":{"observed_at":"2026-08-07T13:13:20.016971Z","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":"2026-08-07T13:13:37.256753Z","title":"Arjevani, Y","venue":null,"work_id":"a2e89117-8f68-478b-934f-ac4b0fffe136","year":2023},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:20.076371Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:0d51bd916d9c93d873f6cc5454def94dc0430a4f95375c15eac2fb8c1b1f448f","observation_id":"1182027c-1689-4156-9684-b6ec03755afb","resolution":{"observed_at":"2026-08-07T13:13:37.319228Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:37.082707Z","title":"Balles and P","venue":null,"work_id":"31540797-9cba-45e4-a579-65b618ecb9c7","year":2018},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:20.189804Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:f1c925b69e776c731d6d702723503a3b20d9c8a0b95ba9fc4170be2469695697","observation_id":"06d66d0d-b985-48ff-b2f1-9020cf6ff699","resolution":{"observed_at":"2026-08-07T13:13:37.141686Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:36.929379Z","title":"Ben Allal, A","venue":null,"work_id":"350299ea-7b18-409a-8204-28d0219d9b76","year":2024},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:20.345120Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:f092b533b674642e2f207da6f38b2fcba5c873c2e584cd96d344cc4dadf960e3","observation_id":"c2fceca2-3682-44d7-ac14-742348bfe704","resolution":{"observed_at":"2026-08-07T13:13:37.023451Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:36.678199Z","title":null,"venue":null,"work_id":"93386166-41f1-4a4b-832f-290f419216e0","year":2020},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:20.505095Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:082d1435b864a0bcadfd95ffff5198e8346e91139dad75b8b279e15a3107d07a","observation_id":"1eeb5636-1ece-4a77-b008-610f822a643c","resolution":{"observed_at":"2026-08-07T13:13:36.818454Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:36.446398Z","title":"Brown, B","venue":null,"work_id":"1140a3d9-f9ff-4b0e-9f6d-454630a63e70","year":2020},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:20.584311Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:7c288e9f69059fa0235fe447e5424ec501703656839629c6e6c9e68f89668bae","observation_id":"f4aabb6e-e55f-47e6-80f0-2ee6a4b6b9ed","resolution":{"observed_at":"2026-08-07T13:13:36.553211Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.09799","last_updated":"2025-03-12T20:04:38Z","snapshot_observed_at":"2026-08-07T17:09:02.220829Z","submitted_at":"2025-03-12T20:04:38Z","title":"Communication-Efficient Language Model Training Scales Reliably and Robustly: Scaling Laws for DiLoCo","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.09799","snapshot_observed_at":"2026-08-07T13:13:20.674049Z","title":"Charles, G","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:20.674049Z"},"links":{"cited_paper":"/paper/2503.09799","citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:724fb8a2ff14a414f8f6fd7d4410740780611d7d3dcedf86f96e170bd7c132a4","observation_id":"85f54d5b-9c0d-4c0a-915c-3e936ec6cb40","resolution":{"observed_at":"2026-08-07T13:13:20.674049Z","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":"2026-08-07T13:13:36.157545Z","title":null,"venue":null,"work_id":"23a0dd86-7220-4faf-a059-cc67fd64b7a5","year":2023},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:20.819250Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:81412fa96e45bfbdad6e5258fc6d3b8b596e4c670c5f1cfc3a030cda572bacdf","observation_id":"7dcaaa74-a7ad-4b7e-8a40-33a8c294e375","resolution":{"observed_at":"2026-08-07T13:13:36.299354Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:35.875755Z","title":"Cheng and M","venue":null,"work_id":"73880cfb-aaa9-47e5-960b-6fe4499efd42","year":2025},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:20.901750Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:2a2490eec53c83183401f8cef710cebd5404fb515ef874e90c490bb3fc58620c","observation_id":"e397315e-a9c3-4ad6-b551-2f29fe8c7e29","resolution":{"observed_at":"2026-08-07T13:13:35.995718Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:35.606016Z","title":"Chowdhery, S","venue":null,"work_id":"c4adae8b-c398-460d-b4d9-e1ba19122d37","year":2023},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:21.001201Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:0fdb8fe28e37999a950cb8bece229086e2a0e83495ee0e0f2bdce6d0ad5d08a4","observation_id":"e3cbe639-80a1-4d91-9dfd-0cc96524c175","resolution":{"observed_at":"2026-08-07T13:13:35.728657Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1803.05457","last_updated":"2018-03-14T18:04:21Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2018-03-14T18:04:21Z","title":"Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1803.05457","snapshot_observed_at":"2026-08-07T13:13:21.076522Z","title":"Clark, I","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:21.076522Z"},"links":{"cited_paper":"/paper/1803.05457","citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:5476250ccfe1801cb0324cc7aa79c031de5003edcae10074d058676ca2eb8f6d","observation_id":"56c4c9b9-d72e-4cab-95bf-0ca6cfe59eab","resolution":{"observed_at":"2026-08-07T13:13:21.076522Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.08105","last_updated":"2024-09-23T10:41:27Z","snapshot_observed_at":"2026-08-04T10:53:01.395272Z","submitted_at":"2023-11-14T12:05:45Z","title":"DiLoCo: Distributed Low-Communication Training of Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.08105","snapshot_observed_at":"2026-08-07T13:13:21.194758Z","title":"Douillard, Q","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:21.194758Z"},"links":{"cited_paper":"/paper/2311.08105","citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:cbbeb9e7210d585d6ab4245d1f3039c1be91950424f04b01b711d5cb853b6928","observation_id":"ec5ff9dd-d323-429c-b9ae-5d73bd6acdd0","resolution":{"observed_at":"2026-08-07T13:13:21.194758Z","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":"2026-08-07T13:13:21.241231Z","title":"Dubey, A","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:21.241231Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:6864faaa16087dcb88e65f19231b6c3fb28186dde44e47ef7ecaf11758de1a99","observation_id":"dc2aca47-b452-4bb7-9d1f-c8ec3322efaa","resolution":{"observed_at":"2026-08-07T13:13:21.241231Z","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":"2026-08-07T13:13:35.370727Z","title":"Hägele, E","venue":null,"work_id":"47b3ff52-90cc-49cf-8f3b-b017e3ea7961","year":2024},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:21.347722Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:a787a3c86aa2076ff21aad3f1245514fef1730487a41577db2f546a33e27004f","observation_id":"fa042afe-7b73-4a30-ba41-43604c9a1a77","resolution":{"observed_at":"2026-08-07T13:13:35.471669Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.15556","last_updated":"2022-03-29T13:38:03Z","snapshot_observed_at":"2026-07-06T12:54:11.616335Z","submitted_at":"2022-03-29T13:38:03Z","title":"Training Compute-Optimal Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.15556","snapshot_observed_at":"2026-08-07T13:13:21.432532Z","title":"Hoffmann, S","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:21.432532Z"},"links":{"cited_paper":"/paper/2203.15556","citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:77590ada57b9f80b1559ea9a8a7d64cc7bff3efe530019ae3ca4a3c5f450e229","observation_id":"d3ec821f-913d-4e5c-8e05-df2105ea2c9f","resolution":{"observed_at":"2026-08-07T13:13:21.432532Z","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":"2026-08-07T13:13:35.221544Z","title":"Iacob, L","venue":null,"work_id":"734d7d6c-453f-4921-aeb8-3f326926818f","year":2025},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:21.502087Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:c3b559f473593095f66e63bd5a3d14a68139a4cc02071c042bc99310be49ada8","observation_id":"02244ee3-5359-4aac-a49f-4620c7a164eb","resolution":{"observed_at":"2026-08-07T13:13:35.289962Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:35.044033Z","title":"Kairouz, H","venue":null,"work_id":"1be29c6e-9d93-4fa9-bf58-fd9ad0f36c52","year":2021},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:21.584559Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:10af212ee423ac192b67f6a4a2f6c296d544eb64508662ee7e57f52a88574e66","observation_id":"b70640e3-b4a8-44a8-bcc5-5658b1bedac2","resolution":{"observed_at":"2026-08-07T13:13:35.138200Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2001.08361","last_updated":"2020-01-23T03:59:20Z","snapshot_observed_at":"2026-07-06T08:52:12.656082Z","submitted_at":"2020-01-23T03:59:20Z","title":"Scaling Laws for Neural Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2001.08361","snapshot_observed_at":"2026-08-07T13:13:21.616016Z","title":"Kaplan, S","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:21.616016Z"},"links":{"cited_paper":"/paper/2001.08361","citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:6eb9bcb26de6f2ff401725d72bd89d2d7eb81fa4257e194448b30e656382d15b","observation_id":"acbbcfa6-4117-4adf-9623-1b9f978c102d","resolution":{"observed_at":"2026-08-07T13:13:21.616016Z","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":"2026-08-07T13:13:34.853461Z","title":null,"venue":null,"work_id":"f1393aed-cfb5-41f7-aa4f-243e3423d318","year":2020},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:21.719820Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:d957815954af771cf579b20caaf923d9e0562e15a663d526d8aaea2c068770b6","observation_id":"376832bb-4af6-4c5e-8318-9b5c83f6dc18","resolution":{"observed_at":"2026-08-07T13:13:34.958988Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:34.544910Z","title":null,"venue":null,"work_id":"2319659a-e37f-49da-96a2-4b399f4afa74","year":2015},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:21.798715Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:e4c4d1c61ab6ad071f1495decc9dd06392813a12feb800533b192ac6664c9794","observation_id":"e6b5315a-c6d4-4ce1-a797-9a502e0854e0","resolution":{"observed_at":"2026-08-07T13:13:34.694578Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:34.308261Z","title":"Kunstner, J","venue":null,"work_id":"90f4b49a-7656-4117-994d-7acadeadd8cb","year":2023},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:21.885888Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:5dfbd8d7cf7d105b6c9d9b2473f4be08e3dc10d6c1b9bea30afa8c77cc6c4fcf","observation_id":"02b638ad-33a7-4afb-9204-5936a9e00396","resolution":{"observed_at":"2026-08-07T13:13:34.397500Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:34.078915Z","title":null,"venue":null,"work_id":"d2b20aae-6dd6-4428-b1c3-980faa58e9a4","year":2020},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:21.972625Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:9e9abf7ae54356eee97378241b8e61e9b6e5cc581a5fcc8442e607f544d7adaf","observation_id":"9ac251c1-d723-4cb9-8bbe-b6c7b1434dd3","resolution":{"observed_at":"2026-08-07T13:13:34.195239Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2205.05632","last_updated":"2022-05-11T17:02:07Z","snapshot_observed_at":"2026-07-06T13:08:59.614061Z","submitted_at":"2022-05-11T17:02:07Z","title":"On Distributed Adaptive Optimization with Gradient Compression","version":1},"cited_work":{"arxiv_id":"2205.05632","doi":null,"metadata_source":"pith","pith_arxiv_id":"2205.05632","snapshot_observed_at":"2026-08-07T13:13:26.241383Z","title":"On Distributed Adaptive Optimization with Gradient Compression","venue":"stat.ML","work_id":"615ec5f8-00f9-4070-9f43-801b1db61361","year":2022},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:22.047003Z"},"links":{"cited_paper":"/paper/2205.05632","citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:a57488e4cbcbe983f0c1a74bbe356492db911da24e2e413e689b910a0cff6b3b","observation_id":"553ec41f-12ed-4230-8365-2b04178fd61e","resolution":{"observed_at":"2026-08-07T13:13:26.318258Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.09135","last_updated":"2024-09-23T10:49:33Z","snapshot_observed_at":"2026-07-06T17:16:47.315706Z","submitted_at":"2024-01-17T11:17:04Z","title":"Asynchronous Local-SGD Training for Language Modeling","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.09135","snapshot_observed_at":"2026-08-07T13:13:22.137707Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:22.137707Z"},"links":{"cited_paper":"/paper/2401.09135","citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:c0352c447de0bfa1d9c70b729cc1fd5b7af2a35b07b2f7f43b5d4e91f5681b47","observation_id":"9070db0e-b562-4e6e-95cd-a603cefe4134","resolution":{"observed_at":"2026-08-07T13:13:22.137707Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2007.07989","last_updated":"2020-08-18T03:55:26Z","snapshot_observed_at":"2026-08-05T11:18:58.735828Z","submitted_at":"2020-07-15T20:49:35Z","title":"An Improved Analysis of Stochastic Gradient Descent with Momentum","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2007.07989","snapshot_observed_at":"2026-08-07T13:13:22.271416Z","title":null,"venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:22.271416Z"},"links":{"cited_paper":"/paper/2007.07989","citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:62443dbd10a71e07ddf939db80b19a282f9fdaf9ce1d4d7890764b7af1b3827d","observation_id":"5b730c6a-0274-4a67-89cc-ec0346934cfd","resolution":{"observed_at":"2026-08-07T13:13:22.271416Z","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":"2026-08-07T13:13:33.827102Z","title":"McMahan, E","venue":null,"work_id":"8e8b2026-dd1e-47c6-8d34-e34ad3b60489","year":2017},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:22.356385Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:0eecdaf736f6030d12ef49baf2eb3c25d7edfbe823da808e2b9cae1478ead6fa","observation_id":"1ba3bc43-cbaf-4110-8490-f59d8522d991","resolution":{"observed_at":"2026-08-07T13:13:33.934171Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:33.616013Z","title":"Pagliardini, P","venue":null,"work_id":"bf353c2d-d892-45c7-9b84-db1d79c05b7a","year":2025},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:22.421704Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:b3f0359a6cb87992abd3658d0f68b0066c740afa179b604ecc89be1f332c327f","observation_id":"0fdc09ab-3052-41d3-b99f-ce62e1a5d987","resolution":{"observed_at":"2026-08-07T13:13:33.696273Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:33.426093Z","title":"Pascanu, T","venue":null,"work_id":"ab5994bb-41a0-4b5a-9ebf-9c689d6fc707","year":2013},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:22.510089Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:cbf69a12637dc45368a75260ed440cd2dac7e7c1594d3a13e39174e5d97230ca","observation_id":"56b6d560-0ace-49c7-a97d-8e2ebdf0eb02","resolution":{"observed_at":"2026-08-07T13:13:33.513449Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:33.240843Z","title":"Penedo, H","venue":null,"work_id":"367fde64-d403-40b5-ad0b-974fa2787f93","year":2024},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:22.599548Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:726abd49c9406f38f2cd273a8832a84c9d7d2c2bd0d840660a1c7194c4020b1d","observation_id":"c38cac2e-3901-4c06-9d7c-510c33131ad8","resolution":{"observed_at":"2026-08-07T13:13:33.317576Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:33.044809Z","title":"Rajbhandari, J","venue":null,"work_id":"9d826e7e-5fac-4731-9b34-0d19f5685765","year":2020},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:22.735762Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:a22a4de8535a80603764d80e93791f16a4b1f58d01520975d9628d8c9ba790b7","observation_id":"31724ded-a253-4b0a-82e1-f6fc126e04cd","resolution":{"observed_at":"2026-08-07T13:13:33.137571Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:31.469915Z","title":null,"venue":null,"work_id":"6a9a8e02-7a64-4daa-bd34-64f2936e6cae","year":2018},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:22.838407Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:779e123fbca8a54c581642f4b5c34c42794d8fdf204bf1966bdb9f812d2fb0c3","observation_id":"de86753f-45cd-41d4-a142-a31a4eb5fa0f","resolution":{"observed_at":"2026-08-07T13:13:31.849223Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:31.034768Z","title":"Romero, J","venue":null,"work_id":"cb2d8571-f239-42de-88dd-9228d0fa98f7","year":2022},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:22.915688Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:543c7c6c1a85b62b624eb685e2cf037f8ce9aa5d3d51becc861a2863fe4321fe","observation_id":"dd1bc151-ab41-426d-81d6-81c6d1a113fa","resolution":{"observed_at":"2026-08-07T13:13:31.172018Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.10853","last_updated":"2024-10-14T16:37:29Z","snapshot_observed_at":"2026-08-07T22:00:01.952070Z","submitted_at":"2024-05-17T15:27:52Z","title":"The Future of Large Language Model Pre-training is Federated","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.10853","snapshot_observed_at":"2026-08-07T13:13:23.000067Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:23.000067Z"},"links":{"cited_paper":"/paper/2405.10853","citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:d98f1581c0550bff4eff0f88de70d5981579d0a33102435cd3fb552423fc8393","observation_id":"9670be89-79d8-4266-9918-a33f2a890c84","resolution":{"observed_at":"2026-08-07T13:13:23.000067Z","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":"2026-08-07T13:13:30.861295Z","title":null,"venue":null,"work_id":"cfb6fbf8-db0a-4617-a273-e86194f7fbdc","year":2025},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:23.091906Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:0f50f34e63c8f3df3c711185744c47209698940b0e14389621e7f8c352e35fca","observation_id":"f35efcc2-b8a9-4ef4-9009-2212069bb9b6","resolution":{"observed_at":"2026-08-07T13:13:30.926712Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:30.397547Z","title":"Sardana, J","venue":null,"work_id":"57e8937e-53ff-49db-b860-23e58bd71fea","year":2024},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:23.138477Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:66471654ffc7d2c3b35dd46c2ef9594b633b2b98594f8224ebd934c61467c5f7","observation_id":"7dc45ccc-7726-4c18-be64-1d6f46d010bd","resolution":{"observed_at":"2026-08-07T13:13:30.730065Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2211.05100","last_updated":"2023-06-27T09:57:58Z","snapshot_observed_at":"2026-08-04T18:56:03.233715Z","submitted_at":"2022-11-09T18:48:09Z","title":"BLOOM: A 176B-Parameter Open-Access Multilingual Language Model","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.05100","snapshot_observed_at":"2026-08-07T13:13:23.210344Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:23.210344Z"},"links":{"cited_paper":"/paper/2211.05100","citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:f5ac530d3d068e63f884a9150f01c21c29eaa41715e3751853b5811996646a12","observation_id":"1633bc0d-b3c6-455e-9726-e95d9252e04f","resolution":{"observed_at":"2026-08-07T13:13:23.210344Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1802.05799","last_updated":"2018-02-21T04:30:30Z","snapshot_observed_at":"2026-07-06T06:23:45.215820Z","submitted_at":"2018-02-15T23:36:51Z","title":"Horovod: fast and easy distributed deep learning in TensorFlow","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1802.05799","snapshot_observed_at":"2026-08-07T13:13:23.272737Z","title":"Sergeev and M","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:23.272737Z"},"links":{"cited_paper":"/paper/1802.05799","citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:caa3102e5918e158395468b9f28970f229537b577d83b35c784c14aba4d2ed48","observation_id":"0edd5e36-f54c-4ea8-9d15-ad58925c83a3","resolution":{"observed_at":"2026-08-07T13:13:23.272737Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1909.08053","last_updated":"2020-03-13T23:45:18Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-09-17T19:42:54Z","title":"Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1909.08053","snapshot_observed_at":"2026-08-07T13:13:23.388282Z","title":"Shoeybi, M","venue":null,"work_id":null,"year":1909},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:23.388282Z"},"links":{"cited_paper":"/paper/1909.08053","citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:75e6fc3bc3816714e7c364081b941d9176313db37aa3d694247f8ee7e49ad525","observation_id":"dcc13d16-0859-42b1-878a-2b6d86398f7b","resolution":{"observed_at":"2026-08-07T13:13:23.388282Z","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":"2026-08-07T13:13:30.193455Z","title":null,"venue":null,"work_id":"6de0cf8c-7da5-4e3a-aa59-2545bf9780c7","year":2018},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:23.472300Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:416a02b7382258095805c14bcb4e9194ddcba8c7d545cccbb7e2f88176f82582","observation_id":"fc3c1ede-4716-4da3-a7af-1cd3deb103ae","resolution":{"observed_at":"2026-08-07T13:13:30.297874Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:30.003543Z","title":null,"venue":null,"work_id":"bc0a02c5-9b33-46c4-8632-4caf0684d97c","year":2019},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:23.544757Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:398223adacd6382205edac8182d81ef6acb766c9f55bd3ccdbdabbb2289157af","observation_id":"1c8d626d-472d-4307-b3eb-49323cc5fe02","resolution":{"observed_at":"2026-08-07T13:13:30.060945Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:29.839664Z","title":null,"venue":null,"work_id":"ca7abae8-a412-4625-915e-c377db4b01e8","year":2024},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:23.591593Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:2d04a37d80b6d1eb208ab1ab750f1c6346d39a6bace77487ef6b96dcf53cddb2","observation_id":"fae14c7f-d9e3-4107-9ccf-58096e679471","resolution":{"observed_at":"2026-08-07T13:13:29.939892Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:29.548722Z","title":"Sutskever, J","venue":null,"work_id":"41f9604c-525d-4743-b7aa-35f9476cef8b","year":2013},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:23.721571Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:e80e8d10f5e46e6d358ca4a39fed8888dbb675cb9098890d0f22b57f3ffd9a7e","observation_id":"3e0828f0-b59b-4972-9592-a2c521a7d14a","resolution":{"observed_at":"2026-08-07T13:13:29.727166Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:29.371343Z","title":"Taniguchi, K","venue":null,"work_id":"53a304ad-89f7-423d-8184-df1894d193d7","year":2024},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:23.778017Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:95dde2e5cf25d1859263c1fd47cf797f2780b588f04664a7e4ce16443b2e675d","observation_id":"284a3f56-ed13-49ee-b690-91e29127956b","resolution":{"observed_at":"2026-08-07T13:13:29.456801Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:23.868628Z","title":"Touvron, L","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:23.868628Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:f3a5151544f0664ec7dfa8cd051fe84d6361c383d21373106f6e0ef60040e69b","observation_id":"1e361132-4e09-46ec-b25e-2197c8203fa1","resolution":{"observed_at":"2026-08-07T13:13:23.868628Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2107.06917","last_updated":"2021-07-14T18:09:08Z","snapshot_observed_at":"2026-07-31T18:13:22.254060Z","submitted_at":"2021-07-14T18:09:08Z","title":"A Field Guide to Federated Optimization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.06917","snapshot_observed_at":"2026-08-07T13:13:23.936074Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:23.936074Z"},"links":{"cited_paper":"/paper/2107.06917","citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:7a33d6f8f59991d02443203a9181efbb8a46ecdee8e526b41fc1e4b8de40bc09","observation_id":"11adccbd-73df-459a-b8f8-7ffb50aaaf5d","resolution":{"observed_at":"2026-08-07T13:13:23.936074Z","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":"2026-08-07T13:13:29.176892Z","title":"Wortsman, T","venue":null,"work_id":"b5b3ec5c-52d4-46bc-8663-498c40c454a3","year":2023},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:24.003640Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:a9f38119f85f27126983dfd20e1b079afc05c48db8fe229e2925d0fc3e2d4dc4","observation_id":"4b52a0a3-13e7-4cda-8ad3-3c5fbfa43fb7","resolution":{"observed_at":"2026-08-07T13:13:29.272497Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:28.953948Z","title":null,"venue":null,"work_id":"4eb0f2ac-19d2-41cf-a52b-949a2abf942f","year":2020},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:24.104412Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:826ba452d604fcc623ac5d87977b1387df7b7df1db9f4eb18656f77091f9486f","observation_id":"9b8a6365-cff8-4b6e-94ef-da7de7d9d3d3","resolution":{"observed_at":"2026-08-07T13:13:29.040628Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1905.03817","last_updated":"2019-05-09T19:06:47Z","snapshot_observed_at":"2026-07-06T07:51:59.788418Z","submitted_at":"2019-05-09T19:06:47Z","title":"On the Linear Speedup Analysis of Communication Efficient Momentum SGD for Distributed Non-Convex Optimization","version":1},"cited_work":{"arxiv_id":"1905.03817","doi":null,"metadata_source":"pith","pith_arxiv_id":"1905.03817","snapshot_observed_at":"2026-08-07T13:13:25.892162Z","title":"On the Linear Speedup Analysis of Communication Efficient Momentum SGD for Distributed Non-Convex Optimization","venue":"math.OC","work_id":"6fd76e64-282a-4622-a3c6-c2887ce8b754","year":2019},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:24.215335Z"},"links":{"cited_paper":"/paper/1905.03817","citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:f408c36c1ae830eb5284d0c1aacda2a774278ccc14e59f806024e672418624f6","observation_id":"cd03e95e-8439-4bc0-a05e-d05eed787a6f","resolution":{"observed_at":"2026-08-07T13:13:26.051565Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07863","last_updated":"2022-10-14T14:34:32Z","snapshot_observed_at":"2026-08-02T19:34:55.809125Z","submitted_at":"2022-10-14T14:34:32Z","title":"Revisiting Optimal Convergence Rate for Smooth and Non-convex Stochastic Decentralized Optimization","version":1},"cited_work":{"arxiv_id":"2210.07863","doi":null,"metadata_source":"pith","pith_arxiv_id":"2210.07863","snapshot_observed_at":"2026-08-07T13:13:25.659749Z","title":"Revisiting Optimal Convergence Rate for Smooth and Non-convex Stochastic Decentralized Optimization","venue":"cs.LG","work_id":"9e7e7600-89c2-42ea-a345-a9b329119a10","year":2022},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:24.274554Z"},"links":{"cited_paper":"/paper/2210.07863","citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:1145b0a0d66f690d1e498e20410ab95a52c6991871315c04f0c9d5943403dac5","observation_id":"5b0172b0-644d-41ee-a673-1a941bf38ccd","resolution":{"observed_at":"2026-08-07T13:13:25.744102Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:28.786614Z","title":"Zellers, A","venue":null,"work_id":"1447773c-89ea-41af-bbc1-db0deb4c5ac2","year":2019},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:24.383352Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:6327feb26661a651030b8c983fbda3ae7f5212f313c84c6a69c6202bb9ad168e","observation_id":"6eef702e-2002-468c-8be1-d59019a01988","resolution":{"observed_at":"2026-08-07T13:13:28.884976Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:28.590679Z","title":"Zhang, D","venue":null,"work_id":"45b570ba-10a2-4acc-a799-bfd823f45d0b","year":2025},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:24.463744Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:162612b5796b34d373e39e841521bc8efa017b5f6e3897d27040f58ff4774fe3","observation_id":"9baf1577-4e6d-4ae4-ae60-cbfa1c113c7b","resolution":{"observed_at":"2026-08-07T13:13:28.718210Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:28.356724Z","title":"Zhang, C","venue":null,"work_id":"725f29ab-03bb-4f45-9666-cdf1af786b9b","year":2022},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:24.547386Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:ff4a47d5d365a1660e28de718d5b14c3c4acdf4648d31f2dab16c7fde6d9a5e5","observation_id":"d1fc6803-060c-4bd3-b437-6bf27ee7b888","resolution":{"observed_at":"2026-08-07T13:13:28.462537Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:28.137404Z","title":null,"venue":null,"work_id":"4245794a-ff28-455f-9f09-a88ccd6f9871","year":2023},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:24.644047Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:7010ee73d97f899b1765fa88135c206a71e35c27810d9a147999f33f33d76e0d","observation_id":"3cfae97b-22f2-47a0-887e-05acd4d4b233","resolution":{"observed_at":"2026-08-07T13:13:28.241838Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:28.008369Z","title":"Starting from the recommended baseline learning rate (η0) from Allal et al","venue":null,"work_id":"1e7450aa-09e9-4e87-acc9-e47b7168ab1e","year":null},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:24.769520Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:bcb823fcaac778e737b8c763615dd4bb727cd319b182787df58536aa625a41a8","observation_id":"4130c04a-182c-4b4f-9db3-1f4c5cded0bb","resolution":{"observed_at":"2026-08-07T13:13:28.064042Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:27.815902Z","title":"We then repeat this procedure for Local Adam , using η∗ DDP as the new baseline","venue":null,"work_id":"a9066e44-8941-4051-86e1-9c440e67797c","year":null},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:24.889199Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:691f5927070688b06768929dc0f3608ca32b063b5575568f1bb2c11d5a5569b5","observation_id":"2f86a6c2-fac7-40d6-8d20-bcb3e60a948c","resolution":{"observed_at":"2026-08-07T13:13:27.910261Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:27.550959Z","title":"2a by including results on the heterogeneous data dis- tribution described in Section 4.1","venue":null,"work_id":"3427f682-2e9f-46f1-a15b-50299f51d24f","year":null},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:24.969874Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:82c04e974e2f211d15d545cd1093509138171ee34186b3c059b7bc93f8cb1557","observation_id":"a47370d2-6703-46b3-a6ba-9cb97ecfc5dd","resolution":{"observed_at":"2026-08-07T13:13:27.665023Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:27.287557Z","title":"4 by showing the separate impact of varying synchro- nization frequencies for parameters and the second momentum when the base frequency is Kb = 16","venue":null,"work_id":"7f74f67f-4603-4426-9bd0-5693d1348c5e","year":null},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:25.034417Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:fe3ce1170fdf53fd9bf051e37000459a13e5507d4c425dcb4d74d63b245a3447","observation_id":"84a2cd1c-e0d3-4019-bc13-1279e37a1492","resolution":{"observed_at":"2026-08-07T13:13:27.393938Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:27.085246Z","title":"4 by evaluatingDES-LOC-Adam","venue":null,"work_id":"74ed5d81-daf2-428f-b95f-4711df5b3572","year":null},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:25.108096Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:a2e603701cc6a2a5e469663dd00401ebe12da64878b7fd127e7512583a41932a","observation_id":"072682f0-0c24-4435-8b21-291f702ca700","resolution":{"observed_at":"2026-08-07T13:13:27.177192Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:26.906930Z","title":"5 by showing DES-LOC-ADOPT’s perplexity against baseline methods on heterogeneous data (as defined in Section 4.1)","venue":null,"work_id":"eb6fdbed-1608-41f6-84b8-0077df4d039e","year":null},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:25.240333Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:c226282cf629c4e8be5090a31c708209a9612f80fb53ebbea51db8bb7959147e","observation_id":"adafeeb5-6161-44ab-9cd6-4ed87e2d9bed","resolution":{"observed_at":"2026-08-07T13:13:26.988547Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:26.765598Z","title":null,"venue":null,"work_id":"22bdcd98-329e-4190-9514-1329509636ec","year":null},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:25.314478Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:ce127bfd31ff78cb22177fc3e69b96d8fb4cf296014f174cbabaf58226b7a7e6","observation_id":"fdb9cb9d-a4d9-4009-bb60-b631ec4d23a1","resolution":{"observed_at":"2026-08-07T13:13:26.837297Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:26.615142Z","title":"5 for DES-LOC-Adam, demon- strating that DES-LOC achieves similar communication reductions and performance when using Adam instead of ADOPT","venue":null,"work_id":"dfef06f4-2186-444a-b71f-5426d55e16ea","year":null},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:25.393918Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:de90fe898c5a49cf895891c543ced77435c7ac13485164daf60efe07cb11b250","observation_id":"c596c3a4-92a7-41c7-ab4b-b3e0fe3fafd1","resolution":{"observed_at":"2026-08-07T13:13:26.688336Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:13:26.448304Z","title":"standard","venue":null,"work_id":"51e5a13a-127c-4c9f-8c88-08a403cd4e0b","year":2000},"citing_paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:25.493384Z"},"links":{"citing_paper":"/paper/2505.22549"},"observation_digest":"sha256:3b4ca6c6592ff1efd80d35458bb7c0cded38586be3870283bf77d99bf91995b6","observation_id":"60c5d486-d6dd-416d-9b5e-8ebfe01f3065","resolution":{"observed_at":"2026-08-07T13:13:26.537852Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T22:00:36.809838Z","submitted_at":"2025-05-28T16:32:33Z","title":"DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models"},"reference_resolution":{"displayed":62,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":28,"verified_exact":3,"verified_fuzzy":30},"total_outbound_references":62},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 1 inbound Pith citation observation for arXiv:2505.22549."}