{"as_of":"2026-08-11T06:32:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:256b93d84c14e1aee33ae773922ed16909f15012697addad6e44665c931d676a","coverage":[{"denominator":37,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":37,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T04:54:26.433734Z","state":"measured"},{"denominator":37,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":37,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2506.09440/citation-record","integrity":"/paper/2506.09440/integrity","json":"/paper/2506.09440/citation-record.json","paper":"/paper/2506.09440"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:54:22.997412Z","title":"online\" 'onlinestring :=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:22.997412Z"},"links":{"citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:890ea831daca76180e5643275017d2509cd279e7b6324a69c40fde54d5ae57a9","observation_id":"d1960218-7be8-4d50-be33-ca5ebbac801c","resolution":{"observed_at":"2026-08-07T04:54:22.997412Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:54:23.061689Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:23.061689Z"},"links":{"citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:6118f7440b13756dac602fc4a0f1862e4ae7c9fcacf5673045e7ad5bb8af576d","observation_id":"d05dd2a5-edfe-4f21-9a25-4a9d8960fe7e","resolution":{"observed_at":"2026-08-07T04:54:23.061689Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.08905","last_updated":"2024-12-12T03:37:41Z","snapshot_observed_at":"2026-08-05T04:04:21.846023Z","submitted_at":"2024-12-12T03:37:41Z","title":"Phi-4 Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.08905","snapshot_observed_at":"2026-08-07T04:54:23.138790Z","title":"Hewett, Mojan Javaheripi, Piero Kauffmann, James R","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:23.138790Z"},"links":{"cited_paper":"/paper/2412.08905","citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:582d7fa5f7cfaaac4538111a91596dc9f216910d4db011aee93ea10d9276781e","observation_id":"77c791d2-a60e-4827-b438-cc5ff5c3e51e","resolution":{"observed_at":"2026-08-07T04:54:23.138790Z","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":"10.18653/v1/2024.emnlp-demo.48","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":null,"venue":null,"work_id":"192648d7-b23e-47b8-a65a-bed8983f09fd","year":2024},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:23.238365Z"},"links":{"citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:d41f3f974731e54ebc70dea8aabdc10ae4f2f6a259f7e3e99557d6e3a7a0da52","observation_id":"e173030b-2cb5-4a67-a84e-4e86f1a74348","resolution":{"observed_at":"2026-08-07T04:54:26.675401Z","resolver_source":"doi","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":"2308.14508","last_updated":"2024-06-19T04:00:32Z","snapshot_observed_at":"2026-08-08T03:49:18.086396Z","submitted_at":"2023-08-28T11:53:40Z","title":"LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.14508","snapshot_observed_at":"2026-08-07T04:54:23.322343Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:23.322343Z"},"links":{"cited_paper":"/paper/2308.14508","citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:df309e2970819f046d18be4e4066e7ecab30eca036d43ea41f9c55d2aa24ec49","observation_id":"c283a20a-9c31-4f19-8f4a-64ef1a4fc67a","resolution":{"observed_at":"2026-08-07T04:54:23.322343Z","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":"2026-08-07T04:54:28.346871Z","title":null,"venue":null,"work_id":"7dc087fb-23c7-4268-9c01-6b63313a346c","year":1997},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:23.449605Z"},"links":{"citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:7068cef12c52308954252bc8e0b030f3d5c58400fdb0c56840d55849427475e5","observation_id":"9db2f1d1-3646-425f-8e91-b19eb8054039","resolution":{"observed_at":"2026-08-07T04:54:28.439584Z","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":"2407.06204","last_updated":"2025-04-09T13:54:59Z","snapshot_observed_at":"2026-08-11T00:43:48.374986Z","submitted_at":"2024-06-26T16:34:33Z","title":"A Survey on Mixture of Experts in Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.06204","snapshot_observed_at":"2026-08-07T04:54:23.530398Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:23.530398Z"},"links":{"cited_paper":"/paper/2407.06204","citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:26abd653d61da795cbe95942f99e5b4cc8ddbd16a4d0beaf7e387058a038d35a","observation_id":"bff54777-d361-4081-bd35-90754809743a","resolution":{"observed_at":"2026-08-07T04:54:23.530398Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2107.03374","last_updated":"2021-07-14T17:16:02Z","snapshot_observed_at":"2026-08-08T11:58:24.516369Z","submitted_at":"2021-07-07T17:41:24Z","title":"Evaluating Large Language Models Trained on Code","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.03374","snapshot_observed_at":"2026-08-07T04:54:23.630412Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:23.630412Z"},"links":{"cited_paper":"/paper/2107.03374","citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:51fcab0a322387a30c56967cf63e9c3f8cd40b7bfdbd4cd687f418576d61ee22","observation_id":"6a4456f6-2201-4876-86a7-04085ac85997","resolution":{"observed_at":"2026-08-07T04:54:23.630412Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.14168","last_updated":"2021-11-18T00:23:45Z","snapshot_observed_at":"2026-08-07T01:45:38.840969Z","submitted_at":"2021-10-27T04:49:45Z","title":"Training Verifiers to Solve Math Word Problems","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.14168","snapshot_observed_at":"2026-08-07T04:54:23.764716Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:23.764716Z"},"links":{"cited_paper":"/paper/2110.14168","citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:72a43346a60b4473bbf40465409c4050f46b3c664bf5b0bd87971e364c76e808","observation_id":"cbec733d-d3fb-4918-86f5-597a695e02f0","resolution":{"observed_at":"2026-08-07T04:54:23.764716Z","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":"2026-08-07T04:54:28.186610Z","title":null,"venue":null,"work_id":"6828947a-0b59-4511-b869-45f5d61ec22b","year":2024},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:23.869393Z"},"links":{"citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:8e87ae97176094904bc841fa879f7e3a7131b87e8cb321be6ff8d463acad4e0e","observation_id":"5fe02ab7-b60e-440e-a3dd-dab0fe981a34","resolution":{"observed_at":"2026-08-07T04:54:28.273604Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:54:24.038901Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:24.038901Z"},"links":{"citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:69e432c6b401f8f657a4056caf0ead5c579a40bf3f4d6ee6e4552345dc9a74d1","observation_id":"a709a3fe-a62f-4a91-a2cb-0616d16b64c7","resolution":{"observed_at":"2026-08-07T04:54:24.038901Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2101.00027","last_updated":"2020-12-31T19:00:10Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-12-31T19:00:10Z","title":"The Pile: An 800GB Dataset of Diverse Text for Language Modeling","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2101.00027","snapshot_observed_at":"2026-08-07T04:54:24.198498Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:24.198498Z"},"links":{"cited_paper":"/paper/2101.00027","citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:a2f9ca0ae14b414bc9f696e5ff55f1a1ab3e74b1b791a41f7f958c8bb2982a00","observation_id":"78a08b1d-c9d6-41e5-9900-1292f74989ce","resolution":{"observed_at":"2026-08-07T04:54:24.198498Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.20094","last_updated":"2025-05-08T00:24:02Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-06-28T17:59:01Z","title":"Scaling Synthetic Data Creation with 1,000,000,000 Personas","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.20094","snapshot_observed_at":"2026-08-07T04:54:24.345161Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:24.345161Z"},"links":{"cited_paper":"/paper/2406.20094","citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:a1cb89c75063fa7c87c7af7cb2d991ec65a4c650c112dd412c6ea92e8765140e","observation_id":"0437ff8b-b52b-49ad-ad38-fad67ba0a247","resolution":{"observed_at":"2026-08-07T04:54:24.345161Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-08-10T16:40:37.411115Z","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":"2026-08-07T04:54:24.445219Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:24.445219Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:28aade6a69869cfd9dd79f505ce461726ba4533a95827ba72c4242c19b3b9a07","observation_id":"27481c61-8029-4626-9f60-ced87a16705e","resolution":{"observed_at":"2026-08-07T04:54:24.445219Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.03300","last_updated":"2021-01-12T18:57:11Z","snapshot_observed_at":"2026-08-10T12:35:09.020030Z","submitted_at":"2020-09-07T17:59:25Z","title":"Measuring Massive Multitask Language Understanding","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.03300","snapshot_observed_at":"2026-08-07T04:54:24.495478Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:24.495478Z"},"links":{"cited_paper":"/paper/2009.03300","citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:2b06f0311c6a7345532153008ea6d9ac563418f02ba5e3454dad858c96a036b7","observation_id":"176d693d-9b43-48cc-9cd7-d2676f7b2a56","resolution":{"observed_at":"2026-08-07T04:54:24.495478Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2103.03874","last_updated":"2021-11-08T21:30:18Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2021-03-05T18:59:39Z","title":"Measuring Mathematical Problem Solving With the MATH Dataset","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2103.03874","snapshot_observed_at":"2026-08-07T04:54:24.594503Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:24.594503Z"},"links":{"cited_paper":"/paper/2103.03874","citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:11830b931543179fa47d6415f14872a472353da51fe5356a0a897b4f33069320","observation_id":"2bee7052-0bab-4b8b-8e9c-11273d30d4aa","resolution":{"observed_at":"2026-08-07T04:54:24.594503Z","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":"2026-08-07T04:54:28.014480Z","title":null,"venue":null,"work_id":"e3f19117-e2aa-402c-bef1-11a7697b2256","year":2024},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:24.665709Z"},"links":{"citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:0bc4aa8ad1c7c8f6cb19fe01c80067a1e779f19005267d39e7bd791738c22ed1","observation_id":"608bb7d3-06df-4877-858f-f301bc0c286b","resolution":{"observed_at":"2026-08-07T04:54:28.100571Z","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":"2310.06825","last_updated":"2023-10-10T17:54:58Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-10T17:54:58Z","title":"Mistral 7B","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.06825","snapshot_observed_at":"2026-08-07T04:54:24.733180Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:24.733180Z"},"links":{"cited_paper":"/paper/2310.06825","citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:bd5f152868b7910fe2ff86f317cf914a1992b82a978d452a1270f05660fa5254","observation_id":"497bf157-0983-4007-af47-5c2fde61d2e2","resolution":{"observed_at":"2026-08-07T04:54:24.733180Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.04088","last_updated":"2024-01-08T18:47:34Z","snapshot_observed_at":"2026-08-08T06:16:25.839566Z","submitted_at":"2024-01-08T18:47:34Z","title":"Mixtral of Experts","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.04088","snapshot_observed_at":"2026-08-07T04:54:24.815818Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:24.815818Z"},"links":{"cited_paper":"/paper/2401.04088","citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:1d9627af2c6fdb0bad5b1764917f6836d8e8448d8e8788d9f93f36bed115c46d","observation_id":"a375a437-6dd1-4c10-a491-3e03fd2ba55e","resolution":{"observed_at":"2026-08-07T04:54:24.815818Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1607.01759","last_updated":"2016-08-09T17:38:43Z","snapshot_observed_at":"2026-07-06T05:02:39.487370Z","submitted_at":"2016-07-06T19:40:15Z","title":"Bag of Tricks for Efficient Text Classification","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1607.01759","snapshot_observed_at":"2026-08-07T04:54:24.908267Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:24.908267Z"},"links":{"cited_paper":"/paper/1607.01759","citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:6d6ba32a10fd705a987e3dfe5d5b15af81cac2dbc993648a656f280c7eae1e30","observation_id":"de6c9cf9-25f0-4f67-ba3f-cf020a7f322b","resolution":{"observed_at":"2026-08-07T04:54:24.908267Z","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":"2026-08-07T04:54:27.781136Z","title":null,"venue":null,"work_id":"9a0349c2-bf2d-4b78-8961-e397dcb6a6fd","year":2020},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:24.981439Z"},"links":{"citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:77a9e3429e87ac96d8fc3777fa0a12287f63c78bfc850a90ac39f3e2eaf0c722","observation_id":"29055dc6-88ab-4192-b1d5-577d23d780d7","resolution":{"observed_at":"2026-08-07T04:54:27.914378Z","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":"2406.11794","last_updated":"2025-04-21T17:48:15Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-06-17T17:42:57Z","title":"DataComp-LM: In search of the next generation of training sets for language models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.11794","snapshot_observed_at":"2026-08-07T04:54:25.054281Z","title":"Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke S","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:25.054281Z"},"links":{"cited_paper":"/paper/2406.11794","citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:3d14c25e36bdbe6a901837f60b10b09dd4c5d88a7e445502f37ab88412dbece6","observation_id":"38b31b8b-d30f-4a1c-acde-9b896657cdba","resolution":{"observed_at":"2026-08-07T04:54:25.054281Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.06161","last_updated":"2023-12-13T14:44:10Z","snapshot_observed_at":"2026-07-06T15:25:35.930688Z","submitted_at":"2023-05-09T08:16:42Z","title":"StarCoder: may the source be with you!","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.06161","snapshot_observed_at":"2026-08-07T04:54:25.105456Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:25.105456Z"},"links":{"cited_paper":"/paper/2305.06161","citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:908204867d267300f788a073818b29842b87a33fe5a413e7994a0b8405770c51","observation_id":"d2fceb72-c3c9-47ed-ad1d-93589bedc573","resolution":{"observed_at":"2026-08-07T04:54:25.105456Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.10814","last_updated":"2024-10-16T02:00:24Z","snapshot_observed_at":"2026-08-10T16:59:36.795964Z","submitted_at":"2024-10-14T17:59:44Z","title":"Your Mixture-of-Experts LLM Is Secretly an Embedding Model For Free","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.10814","snapshot_observed_at":"2026-08-07T04:54:25.205882Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:25.205882Z"},"links":{"cited_paper":"/paper/2410.10814","citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:c125a2aaf77781fa72984d7aa434ffcfd8988ed34b52026faee5b614c6949b4d","observation_id":"041d7761-56f6-4aac-bcf9-b37fbaa20d19","resolution":{"observed_at":"2026-08-07T04:54:25.205882Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.19173","last_updated":"2024-02-29T13:53:35Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-02-29T13:53:35Z","title":"StarCoder 2 and The Stack v2: The Next Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.19173","snapshot_observed_at":"2026-08-07T04:54:25.310986Z","title":"Risdal, Jia Li, Jian Zhu, Terry Yue Zhuo, Evgenii Zheltonozhskii, Nii Osae Osae Dade, W","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:25.310986Z"},"links":{"cited_paper":"/paper/2402.19173","citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:c6011640af7b3b83c9af4c319fa08b81152eca5157e8aa5cf7523496be8910b9","observation_id":"6183365f-d0e9-4430-b012-3d9aae0f9b74","resolution":{"observed_at":"2026-08-07T04:54:25.310986Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.01116","last_updated":"2023-06-01T20:03:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-06-01T20:03:56Z","title":"The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Only","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.01116","snapshot_observed_at":"2026-08-07T04:54:25.466243Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:25.466243Z"},"links":{"cited_paper":"/paper/2306.01116","citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:f67ed10fb0c4a1111e35f3f661a198cdb162629e0645f30639488d15c317e5e1","observation_id":"d39ddb0e-46c5-475b-a0de-8483946f8c56","resolution":{"observed_at":"2026-08-07T04:54:25.466243Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:54:25.561210Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:25.561210Z"},"links":{"citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:72b0525fa36cff89682ee59e161693c0bec07c38e714098a03889a645ed7ffa7","observation_id":"e7190bd3-0a64-4977-bfbb-13bcbc5d5476","resolution":{"observed_at":"2026-08-07T04:54:25.561210Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:54:25.661353Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:25.661353Z"},"links":{"citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:5c5ba428c6de046b2611aad99d9eb72a4a0878eb1cff85ab1cad08c5d6c1faaf","observation_id":"4cd03c79-7dba-4388-af05-9548fd33218d","resolution":{"observed_at":"2026-08-07T04:54:25.661353Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:54:25.742833Z","title":"Le, Geoffrey E","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:25.742833Z"},"links":{"citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:a69b5e903fd6f26b1d210b818d746f3bf342bed716fa86f5a56564c6fd7ab3f7","observation_id":"48e77b93-9cde-4433-977d-0165485b5c91","resolution":{"observed_at":"2026-08-07T04:54:25.742833Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:54:25.846578Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:25.846578Z"},"links":{"citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:1014ecb4ea42e9439b881084e7fd10f627db2d0876381278b4101c1eea3322f8","observation_id":"99ee46ad-9ef3-44da-a016-43347e558660","resolution":{"observed_at":"2026-08-07T04:54:25.846578Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:54:25.914156Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:25.914156Z"},"links":{"citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:a53c38a59f6d33d3456a4976793c5599ddf3361e34e7b2b96be51811455c182e","observation_id":"3bbedc6f-367a-4a54-aab6-75aceabf224b","resolution":{"observed_at":"2026-08-07T04:54:25.914156Z","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":"2026-08-07T04:54:27.572928Z","title":null,"venue":null,"work_id":"e3ad22fe-4ae4-4422-baa2-dbebdf09a255","year":2024},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:25.979644Z"},"links":{"citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:023fc003b6ebf8dafcbfe672659d0721f9383247def50162425bf9baf0b0757c","observation_id":"be0750e3-2d5e-46f7-9de2-639e4b5cd10a","resolution":{"observed_at":"2026-08-07T04:54:27.664115Z","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":"2026-08-07T04:54:27.387753Z","title":"https://github.com/togethercomputer/RedPajama-Data Redpajama: An open source recipe to reproduce llama training dataset [online]","venue":null,"work_id":"a804b546-a910-4b62-93fb-57b9fa9c2bc2","year":2023},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:26.058753Z"},"links":{"citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:cef19e50a47d450b3afacea28b0f56eccfe3b4386a7044cc569c9f9c3d230aa0","observation_id":"34234a0f-eddf-4831-8fd8-7c48b71f12fa","resolution":{"observed_at":"2026-08-07T04:54:27.489591Z","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":"2026-08-07T04:54:27.199277Z","title":null,"venue":null,"work_id":"adc276b2-ecf9-4271-abb5-86557d1dfc95","year":2024},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:26.159929Z"},"links":{"citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:d2addcb124c59f14aa81ffcfe4c7431c9a58b6696c20f1bda3f91d9b9b10f14b","observation_id":"7e38f49d-4450-4dfb-b8c4-103bb76f842a","resolution":{"observed_at":"2026-08-07T04:54:27.302373Z","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":"2309.16039","last_updated":"2023-11-14T01:40:13Z","snapshot_observed_at":"2026-08-10T13:57:05.071602Z","submitted_at":"2023-09-27T21:41:49Z","title":"Effective Long-Context Scaling of Foundation Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.16039","snapshot_observed_at":"2026-08-07T04:54:26.223746Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:26.223746Z"},"links":{"cited_paper":"/paper/2309.16039","citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:92deb666741a6d43184b9aee162ac6a88385af437353c8597048164d322a3870","observation_id":"5ea00957-85e6-4111-9afa-d33b3265181d","resolution":{"observed_at":"2026-08-07T04:54:26.223746Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.07911","last_updated":"2023-11-14T05:13:55Z","snapshot_observed_at":"2026-07-06T16:47:08.877195Z","submitted_at":"2023-11-14T05:13:55Z","title":"Instruction-Following Evaluation for Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.07911","snapshot_observed_at":"2026-08-07T04:54:26.335882Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:26.335882Z"},"links":{"cited_paper":"/paper/2311.07911","citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:97a086649ff5642b2e56e4eb23ce93fe7ccf28c60db9f5f7b70e37f9df0559b5","observation_id":"d9cb6e0f-b3d7-49d1-bf9d-a460c1b3da58","resolution":{"observed_at":"2026-08-07T04:54:26.335882Z","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":"2026-08-07T04:54:27.019142Z","title":null,"venue":null,"work_id":"23e91943-1496-4360-8f27-ab94c1173929","year":2024},"citing_paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:26.433734Z"},"links":{"citing_paper":"/paper/2506.09440"},"observation_digest":"sha256:88383442e50695014ecb2c6dd51e3d7ed37bff4948e23ba6c9d7fc3f75c03493","observation_id":"786e529e-232b-4cf7-9d72-f3c3f0df4e07","resolution":{"observed_at":"2026-08-07T04:54:27.089925Z","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"}}],"paper":{"arxiv_id":"2506.09440","last_updated":"2025-06-11T06:46:49Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-09T03:35:26.746241Z","submitted_at":"2025-06-11T06:46:49Z","title":"GigaChat Family: Efficient Russian Language Modeling Through Mixture of Experts Architecture"},"reference_resolution":{"displayed":37,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":35,"verified_exact":1,"verified_fuzzy":1},"total_outbound_references":37},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2506.09440."}