{"as_of":"2026-08-10T15:16:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ee3ddabe2aa7c17d0018313a77266518392456dc8614043a6da0b9ee29f8b6bc","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":"2026-08-10T06:31:04.303077+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":"2026-08-09T15:57:12.071768Z","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":"sha256:43d79547cede6cfad2b9c391750d211a2f94f1220a0f6a8d838bb0ba6e2980b3","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"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":"2026-08-10T04:07:56.506438Z","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":"2026-08-09T15:57:12.071768Z","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:e301c174150ab1749bf9622ec2025e2960de55cc7c689252493f5e8259d75ed8","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":"2026-08-09T15:57:12.071768Z","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:e4883015c4599f4a4258678341606351d59f350a554a1206620b99d90c7c3d84","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:18433f45e296a519810fa481b7b99d5efef3a43589e15bcb56c6e996a3009e53","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:96759903e8eb078a83dee4d9fe76b0bbb72ac94245707538ca6315111cb8ed31","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:482a91970640920291a81b9439c071f8844caade38da20a3d5f27a217bb52917","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:8c7119c8b7fdb369fc1e8e7ec803c2dd02890a19a75d8095ecc2350f8da62345","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"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":"2026-08-09T15:57:12.071768Z","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":"sha256:3f70378e71113c2f90a5791379e9f10748819522be3a71c791990c38d9c9b5d1","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":"2026-08-09T15:57:12.071768Z","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":"sha256:17932be4c35d15be68aaa19de3e192931af165cc7a354205c128c3021a837b30","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:0b9cb7d5848c8413aacba9c72df465e2df556dcec0f02bc979fa481901628f63","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:2beca7cce7dbec95b76fee6a4d8dc5b678737a624691e7fc9b04bdbf637ba88d","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"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":"2026-08-09T15:57:12.071768Z","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":"sha256:427fff6226293514b772e81bc7fdbf95bb2379a92e2515e6f448132b663deac1","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":"2026-08-09T15:57:12.071768Z","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:d20d7655577452db1dce53b92edd9023a01a5c63dec96319058d196ec39268c2","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":"2026-08-09T15:57:12.071768Z","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":"sha256:91be9ef22838ba18aa38d1e099051b871270d3c88e78f36d7bbdb6a71895f3da","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":"2026-08-09T15:57:12.071768Z","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":"sha256:9b5e9912c8a59147143291b35b8916de6012b8b802e2b52622f0a623b20c72cf","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.15556","last_updated":"2022-03-29T13:38:03Z","snapshot_observed_at":"2026-08-09T19:52:33.533277Z","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":"2026-08-09T15:57:12.071768Z","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":"sha256:4e2b677a528ec77a1b8db4fb6e13c3e173ef3308cb3f15c4dec1284f467aac04","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":"2026-08-09T15:57:12.071768Z","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:b8887a78db12c90a397ee7eaed28f785202f2b2a42ef966582999223f3540279","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:4aa768d84b7f8ad98b1e709a3ba225a9c1359ae4863b545a61e8a8a6aca851da","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"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":"2026-08-09T15:57:12.071768Z","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":"sha256:7b57b4070cc21a63727012d4adb4e4e400e1be751466823e7bdaeec4ac5dcd36","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":"2026-08-09T15:57:12.071768Z","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":"sha256:43d4c09c1f13ca1eef13cd1163c3594a04381302e7299008970ed493bd422b5c","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:8cbadbab83cbb5cfb99eb4c2c98ebba742f66dc18a1c997b1be599f6f6a6a2c9","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:7fb82f24bf2ddac69de53223c5819b03d1e93dcbd410f65d4147b4275c794508","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:2a0938040310c622b065c21cdb24536b60758e3096aae5d1553a37f22d9185f8","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"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":"2026-08-09T15:57:12.071768Z","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":"sha256:015162d5ff3d7f4e01891fd8815628e4a752c9a33644ddf904724d53ade41f2e","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"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":"2026-08-09T15:57:12.071768Z","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":"sha256:1fbf235797462bb6b6ca45c76b92e60ff8b742ebec17a7b892aae2be549947a6","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":"2026-08-09T16:41:23.255054Z","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":"2026-08-09T15:57:12.071768Z","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":"sha256:392397239738e46c3fd26d46e79f29d25b75ad1a54000990e8e497090bb0f125","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":"2026-08-09T15:57:12.071768Z","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":"sha256:1296db2b2d2b4d2e44f3ca8f46082c0436f9a9112333cc1524788c80c847f9c9","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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:d60719fdb1b1ea8277c2d6e6d144344fce82a547968d0a8fa9cca1c4b5ec3c2b","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:632ba94560c4ca5c3bafe442aad4753431f666e21588ca1ee1b8787ae1776b0d","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:6dcb8e99f996b5946fb37d214aa98e7801a5e7ca5a00387feb372bf7d494f238","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:38ca67ca4bb1203f51caca9c3c9c53aa94f86206bdc0fe2420f58ea149404532","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:4740fde69dbd53ab752d969fff7163a5f6d2f7898a2a6bf6f31e6fa4493a95c2","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:6d7125e1cbe9627f0496f177db1f040131713af25367efaa6a0c7ee0860d034d","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"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":"2026-08-09T15:57:12.071768Z","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":"sha256:00e4a54d12a9fc68dc9da5d9f793df32c15b567449a2d85401e30e92587a17c0","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":"2026-08-09T15:57:12.071768Z","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:dad3cc69fb3b82cedab67a29a21241107a6aa4d348cfe9e23391e23b60118cc4","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:01ebb870d5c480b87913080c061b0e20d0d1b16698d333a26772b6a61eb5879c","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"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":"2026-08-09T15:57:12.071768Z","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":"sha256:3021342dedbe8d28ef81625b1ae9b2354137031994f57b15750a5b14e5a53cfb","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":"2026-08-09T15:57:12.071768Z","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":"sha256:6ed144a4a3aa52c7a2eea9b60424559483b174b4e9829888d7869c21a6e4adc4","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":"2026-08-09T15:57:12.071768Z","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:c1f7b35badb0b815c95682a7fc8fe354622a6a058c42760e12884f1a0e317938","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":"2026-08-09T15:57:12.071768Z","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":"sha256:6675c46c66bf9b82e2a383db4353e43e1a875c0c002fb6e3c20ebfc37a5d29b3","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:96fce5fc13651e4a805eaba7b73a1d50eed3a6a4aeb82beb9d93613523f728e4","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:2548f9931c84bb3a3c108e7d289926d145c8b43e19efa43829a73c325e4f6739","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:60b569ae2ba0b297d14965015c573d31a2caa3db025a3676a12236be5faef7b4","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:1dba419a25c856273811ebf8b815f66b1b14dffcf46b1e68c2533a6193425672","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:2d8ea8135450b63193cf01fd38c64b3c0139c4f6bccb75e7ede2b32de0e26cf6","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":"2026-08-09T15:57:12.071768Z","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:bb85119b1fdd3005ae47acee25fee240e1cf418cf071138f9bc97e7316d3ee04","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":"2026-08-09T15:57:12.071768Z","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:e0f12aff5501cedcfcba6fd835d50b0d2ccd540c525fa9a1fcb293b235d73303","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:1721a91526182d0d6e6086bb5c0c2bb518179b9a9faa756be0e5b0412ef0d992","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"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":"2026-08-09T15:57:12.071768Z","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":"sha256:77a8f87fa3c9ef825e68bcc83ca1572e9e40467c4e278080f2b840f5a957ea11","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07863","last_updated":"2022-10-14T14:34:32Z","snapshot_observed_at":"2026-08-10T00:30:27.345306Z","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":"2026-08-09T15:57:12.071768Z","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":"sha256:1ce01a5b9bebc0b76aaceb18b41d4c2c96ecbb485be90dfd9f44ab1daef56545","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:071a52a320f5be25766b2c098b23019984fb8d33eb01e4c38153c5dd11c84c9c","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:746b4d6d9c1df2224a0634086f78712107828e0d00e74d705084389cc08457a0","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:1960a3e3d74905e594fa64acf24eda1fe478d6034c9fd9415047aaf12b844d4d","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:08b3b993bd3c9d58b3a2594f87024bdbd7bb1fc6a2e93400b5fe0bede90e1d4b","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:37a1ee71af15abe26da7a1279e9e756a18e216cf5a694d0200f17f5c2c54a0ce","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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:dcc91160f04baaffbfaf4afd4c22f50bc23d6edd96992cfdd5f68ccefcfac15e","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:123f1937ac810b63a6c9c4815037a09fc75caa9495103342649bb1527c46334f","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:502c9c63b58e30ba190245f91bbdb8501e1128c9ee2eebccf92f6cb02e40076f","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:708f31ee755d32197c276f30a7118c0c2058b8e66e367480cd08a46dbb0ac1d2","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:2115d9f364cf11950bfd49dd9e044ab12871c507e8ca7dc6822e61b85c634a90","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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":"sha256:1ed00e80246e69b57ba789d3367c1d91501a296bfa2b56956f7dc130f68b3296","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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:ddce8c335ad7e753f03f43c1f6bba73944d7bbd8ba050947c827279568ed8543","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":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":"2026-08-09T15:57:12.071768Z","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:b4cef5b12430efedd44de6371db6f0e5c098c0f57591db72c6a070c850fe50da","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.22549","last_updated":"2025-05-28T16:32:33Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-09T15:57:12.071768Z","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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 1 inbound Pith citation observation for arXiv:2505.22549."}