{"as_of":"2026-08-09T23:32:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:89a3d1c7ade229771d03a2d4b3d3848a14df7013c54ad7b4a7f12813cf535cc7","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":30,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":30,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":30,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":30,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T21:56:50.749126Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":"2404.10102","doi":"10.48550/arxiv.2404.10102","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Besiroglu, E","venue":"arXiv (Cornell University)","work_id":"1867d308-052b-4c44-a1e7-4ccc9ea2869b","year":2024},"citing_paper":{"arxiv_id":"2409.04777","last_updated":"2026-05-20T09:55:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-09-07T09:37:19Z","title":"Optimization Hyper-parameter Laws for Large Language Models","version":4},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-23T20:45:31.427677Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2409.04777"},"observation_digest":"sha256:56671bf7392cdcd7095ee3182c9d788a35cbde6d3379811da505e80bd657b970","observation_id":"9d989cec-7771-41d1-a130-01b1618bc8a9","resolution":{"observed_at":"2026-05-23T20:45:48.784575Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-09T21:56:50.749126Z","title":"Chinchilla scaling: A replication attempt","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.18965","last_updated":"2025-07-23T13:03:41Z","snapshot_observed_at":"2026-08-09T21:45:42.546566Z","submitted_at":"2025-01-31T08:55:56Z","title":"The Surprising Agreement Between Convex Optimization Theory and Learning-Rate Scheduling for Large Model Training","version":2},"reference_index":2003,"source":"pdf_text","source_observed_at":"2026-08-09T21:56:50.749126Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2501.18965"},"observation_digest":"sha256:e8f4e769f1858526a007dba41d813ab63f19c6001020bc364a0c29591d7cf358","observation_id":"8d100234-d5ee-4cf5-ae7b-91a8a8b4af6a","resolution":{"observed_at":"2026-08-09T21:56:50.749126Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-08T17:01:36.058241Z","title":"Chinchilla scaling: A replication attempt","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06042","last_updated":"2025-05-26T18:48:37Z","snapshot_observed_at":"2026-08-09T10:18:57.511599Z","submitted_at":"2025-02-09T21:44:27Z","title":"Scaling Laws for Forgetting during Finetuning with Pretraining Data Injection","version":2},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-08T17:01:36.058241Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2502.06042"},"observation_digest":"sha256:50a92a9db55f3ea33ea2847af2bb157872b8b4f1c05b4469dfb16d75d90c55bb","observation_id":"5ad549d4-7fac-4b5a-90c7-53a13cc61fbb","resolution":{"observed_at":"2026-08-08T17:01:36.058241Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":"2404.10102","doi":"10.48550/arxiv.2404.10102","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Besiroglu, E","venue":"arXiv (Cornell University)","work_id":"1867d308-052b-4c44-a1e7-4ccc9ea2869b","year":2024},"citing_paper":{"arxiv_id":"2505.10465","last_updated":"2025-11-29T21:39:27Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-05-15T16:18:13Z","title":"Superposition Yields Robust Neural Scaling","version":4},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-22T14:38:44.789822Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2505.10465"},"observation_digest":"sha256:56db5374ff9a185224eab9a87bfc9bd7462ca4c414cf673230e6284ce4ee1511","observation_id":"7c7bd792-94c3-45a6-9bb4-2e7f9ac512d9","resolution":{"observed_at":"2026-05-09T06:36:25.448330Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-07T12:45:26.228230Z","title":"Chinchilla scaling: A replication attempt","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23725","last_updated":"2026-06-02T01:19:21Z","snapshot_observed_at":"2026-08-07T12:36:41.591936Z","submitted_at":"2025-05-29T17:55:37Z","title":"MuLoCo: Muon is a practical inner optimizer for DiLoCo","version":3},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-07T12:45:26.228230Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2505.23725"},"observation_digest":"sha256:300598cf9ccb9563835d1960d089c485b53be7d152c9faf8a453824757b92715","observation_id":"4401eddd-a9a3-452e-b4c9-229dfdb62623","resolution":{"observed_at":"2026-08-07T12:45:26.228230Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-07T11:18:05.875330Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03101","last_updated":"2025-06-03T17:35:56Z","snapshot_observed_at":"2026-08-08T07:38:04.360811Z","submitted_at":"2025-06-03T17:35:56Z","title":"Beyond Text Compression: Evaluating Tokenizers Across Scales","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-07T11:18:05.875330Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2506.03101"},"observation_digest":"sha256:05aa88de1c6cbbbedb15302870c8a43882d0683248464d57d84162822fc8cc14","observation_id":"448cd705-652d-45d9-b596-7f5c2e36200b","resolution":{"observed_at":"2026-08-07T11:18:05.875330Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-07T04:21:29.262637Z","title":"Chinchilla scaling: A replication attempt.arXiv preprint arXiv:2404.10102, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10972","last_updated":"2025-07-16T07:09:02Z","snapshot_observed_at":"2026-08-09T19:09:19.738358Z","submitted_at":"2025-06-12T17:59:23Z","title":"Predictable Scale: Part II, Farseer: A Refined Scaling Law in Large Language Models","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T04:21:29.262637Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2506.10972"},"observation_digest":"sha256:267666599cedc3da59698a2ecc06d4a73773eed124f924511c3e21d4179daaed","observation_id":"ac512a91-f9ef-4f58-b9d1-981c11415bfe","resolution":{"observed_at":"2026-08-07T04:21:29.262637Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-07T05:07:39.948694Z","title":"Chinchilla scaling: A replication attempt,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.00004","last_updated":"2025-07-10T17:08:40Z","snapshot_observed_at":"2026-08-08T16:04:02.052629Z","submitted_at":"2025-06-10T14:47:48Z","title":"A Theory of Inference Compute Scaling: Reasoning through Directed Stochastic Skill Search","version":2},"reference_index":110,"source":"pdf_text","source_observed_at":"2026-08-07T05:07:39.948694Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2507.00004"},"observation_digest":"sha256:717ceb3b8cff33ff7f472a56d6d43ca75e3eb341024c059a31fd2f08ebe2be00","observation_id":"bd45fb1a-1888-4f8f-ab8c-f8fde07665ae","resolution":{"observed_at":"2026-08-07T05:07:39.948694Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-06T16:53:08.286130Z","title":"Chinchilla scaling: A replication attempt","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.12466","last_updated":"2025-07-16T17:59:45Z","snapshot_observed_at":"2026-08-09T12:12:41.025897Z","submitted_at":"2025-07-16T17:59:45Z","title":"Language Models Improve When Pretraining Data Matches Target Tasks","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-06T16:53:08.286130Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2507.12466"},"observation_digest":"sha256:1ea78b4b9425a2da8d0f774951bf04a35a27b9414e3e4ac53753e035f7e7d08c","observation_id":"f6e24277-4ffe-4c8e-a410-ed578df587e1","resolution":{"observed_at":"2026-08-06T16:53:08.286130Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-03T04:07:45.197041Z","title":"Chin- chilla scaling: A replication attempt.arXiv preprint arXiv:2404.10102,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.05970","last_updated":"2026-05-31T19:48:07Z","snapshot_observed_at":"2026-08-07T15:15:21.459993Z","submitted_at":"2026-02-05T18:22:41Z","title":"Inverse Depth Scaling From Most Layers Being Similar","version":2},"reference_index":2009,"source":"pdf_text","source_observed_at":"2026-08-03T04:07:45.197041Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2602.05970"},"observation_digest":"sha256:9a6fe40c27496eb8c9b4a9f6864b66f645dd1d2051a511f57062d0dbfd2715aa","observation_id":"e702ae16-0621-4282-b387-61a0c3b6388e","resolution":{"observed_at":"2026-08-03T04:07:45.197041Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":"2404.10102","doi":"10.48550/arxiv.2404.10102","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Besiroglu, E","venue":"arXiv (Cornell University)","work_id":"1867d308-052b-4c44-a1e7-4ccc9ea2869b","year":2024},"citing_paper":{"arxiv_id":"2604.21106","last_updated":"2026-05-07T08:18:20Z","snapshot_observed_at":"2026-07-06T23:07:47.244208Z","submitted_at":"2026-04-22T21:51:11Z","title":"How Much Is One Recurrence Worth? Iso-Depth Scaling Laws for Looped Language Models","version":3},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-10T00:08:21.385512Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2604.21106"},"observation_digest":"sha256:f10aa1ef200b58ea3476f92283bb2a8b558e0f2cb00827c5d53ec72a0266a1b4","observation_id":"b1525955-5590-43a4-aeaf-7aa0dcb00ef6","resolution":{"observed_at":"2026-05-10T00:19:47.323235Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":"2404.10102","doi":"10.48550/arxiv.2404.10102","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Besiroglu, E","venue":"arXiv (Cornell University)","work_id":"1867d308-052b-4c44-a1e7-4ccc9ea2869b","year":2024},"citing_paper":{"arxiv_id":"2604.24037","last_updated":"2026-06-22T01:13:01Z","snapshot_observed_at":"2026-07-06T23:10:12.016186Z","submitted_at":"2026-04-27T04:43:42Z","title":"A Limit Theory of Foundation Models: A Mathematical Approach to Understanding Emergent Intelligence and Scaling Laws","version":3},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-13T07:27:21.118156Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2604.24037"},"observation_digest":"sha256:7997ace9f4246cd45eabd60a06333e5ec43ad0e1cac2fcdde986080f113e0188","observation_id":"0b70aedf-3606-47dc-8cc0-8990dc73df1e","resolution":{"observed_at":"2026-05-13T07:27:28.975922Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":"2404.10102","doi":"10.48550/arxiv.2404.10102","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Besiroglu, E","venue":"arXiv (Cornell University)","work_id":"1867d308-052b-4c44-a1e7-4ccc9ea2869b","year":2024},"citing_paper":{"arxiv_id":"2604.24037","last_updated":"2026-06-22T01:13:01Z","snapshot_observed_at":"2026-07-06T23:10:12.016186Z","submitted_at":"2026-04-27T04:43:42Z","title":"A Limit Theory of Foundation Models: A Mathematical Approach to Understanding Emergent Intelligence and Scaling Laws","version":4},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-07-01T09:03:59.522516Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2604.24037"},"observation_digest":"sha256:7ab27fd55cd3e940e50aece90cc6b22ca12ae6a80b3705009094ef4b17b72b97","observation_id":"e11477ab-2a84-442b-b7dd-c2dac43d37d7","resolution":{"observed_at":"2026-07-01T09:05:36.318692Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":"2404.10102","doi":"10.48550/arxiv.2404.10102","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Besiroglu, E","venue":"arXiv (Cornell University)","work_id":"1867d308-052b-4c44-a1e7-4ccc9ea2869b","year":2024},"citing_paper":{"arxiv_id":"2605.09154","last_updated":"2026-05-09T20:35:09Z","snapshot_observed_at":"2026-07-06T23:21:16.454273Z","submitted_at":"2026-05-09T20:35:09Z","title":"Predicting Large Model Test Losses with a Noisy Quadratic System","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-05-12T04:40:05.006583Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2605.09154"},"observation_digest":"sha256:7af4f8b872aa70a6665ac289bef158f59d71243f7567a859aec01c0d4601333d","observation_id":"ea57ab62-0ad0-429c-9653-0610045ca839","resolution":{"observed_at":"2026-05-12T06:01:25.519173Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":"2404.10102","doi":"10.48550/arxiv.2404.10102","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Besiroglu, E","venue":"arXiv (Cornell University)","work_id":"1867d308-052b-4c44-a1e7-4ccc9ea2869b","year":2024},"citing_paper":{"arxiv_id":"2605.09189","last_updated":"2026-05-09T22:07:01Z","snapshot_observed_at":"2026-07-06T23:21:21.560069Z","submitted_at":"2026-05-09T22:07:01Z","title":"Practical Scaling Laws: Converting Compute into Performance in a Data-Constrained World","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-12T02:58:26.656927Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2605.09189"},"observation_digest":"sha256:6db04f43362949f2a86b9da065cf7b49bc801329cc6092a5751054a4f8786c9f","observation_id":"2e9dc927-d7bc-40e6-a29f-b9438e301603","resolution":{"observed_at":"2026-05-12T03:01:18.395295Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":"2404.10102","doi":"10.48550/arxiv.2404.10102","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Besiroglu, E","venue":"arXiv (Cornell University)","work_id":"1867d308-052b-4c44-a1e7-4ccc9ea2869b","year":2024},"citing_paper":{"arxiv_id":"2605.10933","last_updated":"2026-05-20T17:26:14Z","snapshot_observed_at":"2026-08-03T07:36:40.918472Z","submitted_at":"2026-05-11T17:58:28Z","title":"DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices","version":1},"reference_index":140,"source":"arxiv_source","source_observed_at":"2026-05-12T03:36:12.915133Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2605.10933"},"observation_digest":"sha256:a097b73cae8a12d0b56ab598327087d50c825775c5437ed91b8e006e2af06d01","observation_id":"2fb46b4b-b7a0-4536-b49c-b75ff6e873f6","resolution":{"observed_at":"2026-05-12T03:36:19.882972Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":"2404.10102","doi":"10.48550/arxiv.2404.10102","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Besiroglu, E","venue":"arXiv (Cornell University)","work_id":"1867d308-052b-4c44-a1e7-4ccc9ea2869b","year":2024},"citing_paper":{"arxiv_id":"2605.10933","last_updated":"2026-05-20T17:26:14Z","snapshot_observed_at":"2026-08-03T07:36:40.918472Z","submitted_at":"2026-05-11T17:58:28Z","title":"DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices","version":2},"reference_index":140,"source":"arxiv_source","source_observed_at":"2026-05-13T07:29:14.545746Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2605.10933"},"observation_digest":"sha256:ee7a8ca1becc08e3a89b52f2a468a0d5df1eecc0e70614feae1139b92c432e0e","observation_id":"277aa453-afdb-4133-84c4-4a0b7739aa22","resolution":{"observed_at":"2026-05-13T07:32:30.191022Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":"2404.10102","doi":"10.48550/arxiv.2404.10102","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Besiroglu, E","venue":"arXiv (Cornell University)","work_id":"1867d308-052b-4c44-a1e7-4ccc9ea2869b","year":2024},"citing_paper":{"arxiv_id":"2605.10933","last_updated":"2026-05-20T17:26:14Z","snapshot_observed_at":"2026-08-03T07:36:40.918472Z","submitted_at":"2026-05-11T17:58:28Z","title":"DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices","version":3},"reference_index":140,"source":"arxiv_source","source_observed_at":"2026-05-21T07:57:49.746594Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2605.10933"},"observation_digest":"sha256:1b14a8f057d7cccf39564ea77f0186d988090f4ad4d3585a2baacb1b0eae95d5","observation_id":"3f97b60e-3b74-4d0d-8144-ba705336e3e4","resolution":{"observed_at":"2026-05-21T07:59:50.256621Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":"2404.10102","doi":"10.48550/arxiv.2404.10102","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Besiroglu, E","venue":"arXiv (Cornell University)","work_id":"1867d308-052b-4c44-a1e7-4ccc9ea2869b","year":2024},"citing_paper":{"arxiv_id":"2605.14200","last_updated":"2026-05-13T23:32:00Z","snapshot_observed_at":"2026-07-06T23:25:39.415637Z","submitted_at":"2026-05-13T23:32:00Z","title":"How to Scale Mixture-of-Experts: From muP to the Maximally Scale-Stable Parameterization","version":1},"reference_index":92,"source":"arxiv_source","source_observed_at":"2026-05-15T04:45:20.091598Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2605.14200"},"observation_digest":"sha256:402692426051dfa9834db2c143df97c0bf1279e58bd1bd7293f6ecb79cd44552","observation_id":"5b14b588-77d5-4b18-87a5-92b3eb0d7746","resolution":{"observed_at":"2026-05-15T04:49:44.747649Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":"2404.10102","doi":"10.48550/arxiv.2404.10102","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Besiroglu, E","venue":"arXiv (Cornell University)","work_id":"1867d308-052b-4c44-a1e7-4ccc9ea2869b","year":2024},"citing_paper":{"arxiv_id":"2605.16430","last_updated":"2026-06-11T06:12:30Z","snapshot_observed_at":"2026-08-08T01:14:17.512228Z","submitted_at":"2026-05-14T18:57:40Z","title":"A Theory of Training Profit-Optimal LLMs","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-05-20T20:13:35.954495Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2605.16430"},"observation_digest":"sha256:30f8ac40fa7b77e2532e9b2e9ed131f03bc989a8302e0f74ba1fedab1ab6848d","observation_id":"4cfface1-c5bc-47f5-84be-00733c69024f","resolution":{"observed_at":"2026-05-20T20:13:42.734033Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":"2404.10102","doi":"10.48550/arxiv.2404.10102","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Besiroglu, E","venue":"arXiv (Cornell University)","work_id":"1867d308-052b-4c44-a1e7-4ccc9ea2869b","year":2024},"citing_paper":{"arxiv_id":"2605.16430","last_updated":"2026-06-11T06:12:30Z","snapshot_observed_at":"2026-08-08T01:14:17.512228Z","submitted_at":"2026-05-14T18:57:40Z","title":"A Theory of Training Profit-Optimal LLMs","version":3},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-06-30T21:08:15.159805Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2605.16430"},"observation_digest":"sha256:34eb229bec7631522388c12b1a11f45318bb6012ea6676c5749f11f7e9bc7199","observation_id":"7ced08cd-0e04-4596-90a2-dd329eb418a8","resolution":{"observed_at":"2026-06-30T21:15:03.635405Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":"2404.10102","doi":"10.48550/arxiv.2404.10102","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Besiroglu, E","venue":"arXiv (Cornell University)","work_id":"1867d308-052b-4c44-a1e7-4ccc9ea2869b","year":2024},"citing_paper":{"arxiv_id":"2605.24316","last_updated":"2026-06-25T06:26:55Z","snapshot_observed_at":"2026-08-01T14:56:15.713802Z","submitted_at":"2026-05-23T00:48:36Z","title":"From One-Pass SGD to Data Reuse: Mini-Batch Scaling Laws in Sketched Linear Regression","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-30T14:09:52.456340Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2605.24316"},"observation_digest":"sha256:24da3e820f07ba0aedb09177b05d95ed4850ef171cf6ccc835d2346226cd6d02","observation_id":"c08e6761-26c7-4216-94ca-ab3328d384a9","resolution":{"observed_at":"2026-06-30T14:14:45.569884Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":"2404.10102","doi":"10.48550/arxiv.2404.10102","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Besiroglu, E","venue":"arXiv (Cornell University)","work_id":"1867d308-052b-4c44-a1e7-4ccc9ea2869b","year":2024},"citing_paper":{"arxiv_id":"2606.01302","last_updated":"2026-05-31T15:44:57Z","snapshot_observed_at":"2026-08-08T15:43:46.371002Z","submitted_at":"2026-05-31T15:44:57Z","title":"Structure and Scale in Simplicial Sequence Modelling","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-28T17:13:00.475488Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2606.01302"},"observation_digest":"sha256:86f42b1fce3d8d735397bf3c960dffa38bbd795a263c2d9c511c4a3c00a85b5d","observation_id":"4fbfef15-b471-467a-a419-c299b28b2d66","resolution":{"observed_at":"2026-07-01T21:26:13.631536Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":"2404.10102","doi":"10.48550/arxiv.2404.10102","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Besiroglu, E","venue":"arXiv (Cornell University)","work_id":"1867d308-052b-4c44-a1e7-4ccc9ea2869b","year":2024},"citing_paper":{"arxiv_id":"2606.10127","last_updated":"2026-06-08T20:00:42Z","snapshot_observed_at":"2026-07-06T23:49:22.753911Z","submitted_at":"2026-06-08T20:00:42Z","title":"Data-Driven Automation","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-06-27T13:58:40.370152Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2606.10127"},"observation_digest":"sha256:d6cb2e1d799a085ed66a6867d639d302859b74f744a5b9ceaf98064f830ca2b1","observation_id":"2a6a66c0-5eb8-44df-b73a-b64f87e8590b","resolution":{"observed_at":"2026-07-03T04:27:36.184415Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":"2404.10102","doi":"10.48550/arxiv.2404.10102","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Besiroglu, E","venue":"arXiv (Cornell University)","work_id":"1867d308-052b-4c44-a1e7-4ccc9ea2869b","year":2024},"citing_paper":{"arxiv_id":"2606.24998","last_updated":"2026-06-23T16:02:40Z","snapshot_observed_at":"2026-07-31T12:51:11.444875Z","submitted_at":"2026-06-23T16:02:40Z","title":"Internal Data Repetition Destroys Language Models","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-06-26T00:12:56.745617Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2606.24998"},"observation_digest":"sha256:1ad40d8494e9de5fd2185e582d3e2e8ff0ac127c118d3e449460b6351748bd39","observation_id":"89dc0d15-b731-46ce-a4b8-33f4a30c44e9","resolution":{"observed_at":"2026-07-04T16:49:57.915883Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":"2404.10102","doi":"10.48550/arxiv.2404.10102","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Besiroglu, E","venue":"arXiv (Cornell University)","work_id":"1867d308-052b-4c44-a1e7-4ccc9ea2869b","year":2024},"citing_paper":{"arxiv_id":"2606.25008","last_updated":"2026-06-23T17:46:30Z","snapshot_observed_at":"2026-07-31T03:01:22.674756Z","submitted_at":"2026-06-23T17:46:30Z","title":"Neural Scaling Universality: If Exponents Are Fixed, Time to Understand Coefficients","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-06-25T23:45:54.283436Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2606.25008"},"observation_digest":"sha256:7fc9612585d8088d99470fae57beb060dd7513a45458d4d1e53009405c3602c8","observation_id":"7ecd69d7-5771-43fe-a248-5f891bd1ff34","resolution":{"observed_at":"2026-07-04T17:20:00.859901Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":"2404.10102","doi":"10.48550/arxiv.2404.10102","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Besiroglu, E","venue":"arXiv (Cornell University)","work_id":"1867d308-052b-4c44-a1e7-4ccc9ea2869b","year":2024},"citing_paper":{"arxiv_id":"2606.31345","last_updated":"2026-06-30T08:43:32Z","snapshot_observed_at":"2026-08-06T06:26:56.243148Z","submitted_at":"2026-06-30T08:43:32Z","title":"Automated High-Precision Extraction and Forensic Verification of Data-Bearing Vector Figures","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-01T05:39:36.615035Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2606.31345"},"observation_digest":"sha256:c4d5dd5ac751d5d12a8f8f2a9540546e0f0b4a8cdb6874021359a6691b822678","observation_id":"ad124522-31bd-4782-aa14-b30a8e765702","resolution":{"observed_at":"2026-07-01T10:15:44.791996Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":"2404.10102","doi":"10.48550/arxiv.2404.10102","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Besiroglu, E","venue":"arXiv (Cornell University)","work_id":"1867d308-052b-4c44-a1e7-4ccc9ea2869b","year":2024},"citing_paper":{"arxiv_id":"2607.01487","last_updated":"2026-07-01T21:32:14Z","snapshot_observed_at":"2026-08-07T20:18:36.914216Z","submitted_at":"2026-07-01T21:32:14Z","title":"How to Allocate Your Tokens? Scaling Laws with Training Steps and Batch Size","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-07-03T21:02:31.246432Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2607.01487"},"observation_digest":"sha256:5caef43e16169b949c70681f6c711e793ca054838a851ac6db24dc6b3db2bbd1","observation_id":"23bec904-74ad-4f1b-964d-867691c5c602","resolution":{"observed_at":"2026-07-03T21:08:57.610654Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T13:53:49.530466+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-02T14:45:35.151566Z","title":"Besiroglu, E","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.14112","last_updated":"2026-05-08T06:06:18Z","snapshot_observed_at":"2026-08-08T13:14:34.827542Z","submitted_at":"2026-05-08T06:06:18Z","title":"Information-Theoretic Limits of Reliability and Scaling in Language Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-02T14:45:35.151566Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2607.14112"},"observation_digest":"sha256:ac0c617bb1a925e225fae2ec191d14518f9dd4b2447e042231b34a54165ba811","observation_id":"1b01e3b2-e5a8-44ea-b374-b56d6f92ccaf","resolution":{"observed_at":"2026-08-02T14:45:35.151566Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.10102","snapshot_observed_at":"2026-08-01T03:01:55.590291Z","title":"arXiv preprint arXiv:2404.10102 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25271","last_updated":"2026-07-28T04:18:49Z","snapshot_observed_at":"2026-08-08T08:44:07.330246Z","submitted_at":"2026-07-28T04:18:49Z","title":"Bridging Compute- and Data-Optimal Pretraining","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-01T03:01:55.590291Z"},"links":{"cited_paper":"/paper/2404.10102","citing_paper":"/paper/2607.25271"},"observation_digest":"sha256:2595e458a891e1668d575b9cf28476cac832ff5a4ce2967d67d94e338f5a05e2","observation_id":"ee69bacb-afb1-40b6-bb33-8e9adc1539e6","resolution":{"observed_at":"2026-08-01T03:01:55.590291Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2404.10102/citation-record","integrity":"/paper/2404.10102/integrity","json":"/paper/2404.10102/citation-record.json","paper":"/paper/2404.10102"},"outbound":[],"paper":{"arxiv_id":"2404.10102","last_updated":"2024-05-15T00:57:23Z","latest_version":2,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-08T21:54:19.231644Z","submitted_at":"2024-04-15T19:19:56Z","title":"Chinchilla Scaling: A replication attempt"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 30 inbound Pith citation observations for arXiv:2404.10102."}