{"as_of":"2026-08-09T17:22:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ebf93f2bb96cfc064ec9d3c1915698ec15c5b5a46710cafeca7265a997da18a4","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":24,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":24,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":24,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":24,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T20:44:48.443920Z","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":"2411.04330","last_updated":"2024-11-30T02:42:31Z","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision","version":2},"cited_work":{"arxiv_id":"2411.04330","doi":"10.48550/arxiv.2411.04330","metadata_source":"arxiv_reference","pith_arxiv_id":"2411.04330","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Spector, Blake Bordelon, Niklas Muennighoff, Mansheej Paul, Cengiz Pehlevan, Christopher Ré, and Aditi Raghunathan","venue":"arXiv (Cornell University)","work_id":"988bd25e-4ff9-47cd-89f4-f30e112706ec","year":2024},"citing_paper":{"arxiv_id":"2412.14590","last_updated":"2026-04-22T15:43:48Z","snapshot_observed_at":"2026-08-03T01:50:37.847212Z","submitted_at":"2024-12-19T07:15:15Z","title":"MixLLM: LLM Quantization with Global Mixed-precision between Output-features and Highly-efficient System Design","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-23T06:56:51.829741Z"},"links":{"cited_paper":"/paper/2411.04330","citing_paper":"/paper/2412.14590"},"observation_digest":"sha256:66233676132b4b6ef393955d8ed8dee8ff569940b4d0f6e7069963677f8318df","observation_id":"7ebcf684-9784-4b84-b16c-b8a1dc19ec57","resolution":{"observed_at":"2026-05-23T06:57:40.270961Z","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":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04330","last_updated":"2024-11-30T02:42:31Z","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.04330","snapshot_observed_at":"2026-08-08T20:44:48.443920Z","title":"F., Bordelon, B., Muen- nighoff, N., Paul, M., Pehlevan, C., R´e, C., and Raghu- nathan, A","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.05003","last_updated":"2025-06-10T18:01:40Z","snapshot_observed_at":"2026-08-09T10:27:19.269217Z","submitted_at":"2025-02-07T15:23:34Z","title":"QuEST: Stable Training of LLMs with 1-Bit Weights and Activations","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-08T20:44:48.443920Z"},"links":{"cited_paper":"/paper/2411.04330","citing_paper":"/paper/2502.05003"},"observation_digest":"sha256:0671b3f4b48097956d257676da22a5eb1c3955bcf92255b13f830065f353fda4","observation_id":"08afdb74-a924-4455-b045-0f40949cdcbd","resolution":{"observed_at":"2026-08-08T20:44:48.443920Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04330","last_updated":"2024-11-30T02:42:31Z","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.04330","snapshot_observed_at":"2026-08-08T20:06:23.536558Z","title":"F., Bordelon, B., Muennighoff, N., Paul, M., Pehlevan, C., Ré, C., and Raghunathan, A","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.05172","last_updated":"2025-02-19T14:36:33Z","snapshot_observed_at":"2026-08-09T03:47:32.466460Z","submitted_at":"2025-02-07T18:55:38Z","title":"Joint MoE Scaling Laws: Mixture of Experts Can Be Memory Efficient","version":2},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-08T20:06:23.536558Z"},"links":{"cited_paper":"/paper/2411.04330","citing_paper":"/paper/2502.05172"},"observation_digest":"sha256:723924ed4fa9692fc09dfd202ca42f63a92ff976df3291fd4f95245b22648b62","observation_id":"4132cec3-9b18-4494-9813-326748b70b12","resolution":{"observed_at":"2026-08-08T20:06:23.536558Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04330","last_updated":"2024-11-30T02:42:31Z","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.04330","snapshot_observed_at":"2026-08-07T15:41:07.082716Z","title":"Scaling laws for precision.arXiv preprint arXiv:2411.04330, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.14302","last_updated":"2025-05-20T12:54:43Z","snapshot_observed_at":"2026-08-07T15:43:23.244437Z","submitted_at":"2025-05-20T12:54:43Z","title":"Scaling Law for Quantization-Aware Training","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T15:41:07.082716Z"},"links":{"cited_paper":"/paper/2411.04330","citing_paper":"/paper/2505.14302"},"observation_digest":"sha256:05c48b3de33d156109d9a9aad45cc0ce8e19fbaef054c887be8f98bb058764b8","observation_id":"5ce689b7-426f-4e5f-8f35-fb0f2daa6f2d","resolution":{"observed_at":"2026-08-07T15:41:07.082716Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04330","last_updated":"2024-11-30T02:42:31Z","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.04330","snapshot_observed_at":"2026-08-07T12:06:24.610518Z","title":"Scaling laws for precision.arXiv preprint arXiv:2411.04330, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.00577","last_updated":"2025-05-31T14:22:40Z","snapshot_observed_at":"2026-08-07T22:33:33.136985Z","submitted_at":"2025-05-31T14:22:40Z","title":"Reasoning Like an Economist: Post-Training on Economic Problems Induces Strategic Generalization in LLMs","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T12:06:24.610518Z"},"links":{"cited_paper":"/paper/2411.04330","citing_paper":"/paper/2506.00577"},"observation_digest":"sha256:fb59e6a3e7628c13b3eeac7f3aafd1df9911b601356ef806e01af4042b1ecde0","observation_id":"4c7422eb-915f-4c85-9266-3449b88e1a37","resolution":{"observed_at":"2026-08-07T12:06:24.610518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04330","last_updated":"2024-11-30T02:42:31Z","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.04330","snapshot_observed_at":"2026-08-07T11:40:07.103756Z","title":"F., Bordelon, B., Muennighoff, N., Paul, M., Pehlevan, C., Ré, C., and Raghunathan, A","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.01863","last_updated":"2025-06-02T16:52:51Z","snapshot_observed_at":"2026-08-07T23:41:22.236547Z","submitted_at":"2025-06-02T16:52:51Z","title":"Unified Scaling Laws for Compressed Representations","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T11:40:07.103756Z"},"links":{"cited_paper":"/paper/2411.04330","citing_paper":"/paper/2506.01863"},"observation_digest":"sha256:530174b8579f8d11033b5f217525e88b65646d80c47b9d7715b65626552fe640","observation_id":"be96af55-4446-4678-965c-8464ab15f5b4","resolution":{"observed_at":"2026-08-07T11:40:07.103756Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04330","last_updated":"2024-11-30T02:42:31Z","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.04330","snapshot_observed_at":"2026-08-07T10:30:34.276380Z","title":"Scaling laws for precision.arXiv preprint arXiv:2411.04330,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.05333","last_updated":"2025-06-20T01:25:25Z","snapshot_observed_at":"2026-08-07T10:18:59.977399Z","submitted_at":"2025-06-05T17:59:24Z","title":"Kinetics: Rethinking Test-Time Scaling Laws","version":3},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:34.276380Z"},"links":{"cited_paper":"/paper/2411.04330","citing_paper":"/paper/2506.05333"},"observation_digest":"sha256:d0e3d7a33d90f8bfd61bfe364081b9cc7fa61c594e33350494008e3f3ebeaf31","observation_id":"1d234a47-80c2-4656-af6e-d0da2da7c236","resolution":{"observed_at":"2026-08-07T10:30:34.276380Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04330","last_updated":"2024-11-30T02:42:31Z","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.04330","snapshot_observed_at":"2026-08-07T04:21:29.346210Z","title":"Scaling laws for precision.arXiv preprint arXiv:2411.04330, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10972","last_updated":"2025-07-16T07:09:02Z","snapshot_observed_at":"2026-08-07T04:10:32.350663Z","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":23,"source":"pdf_text","source_observed_at":"2026-08-07T04:21:29.346210Z"},"links":{"cited_paper":"/paper/2411.04330","citing_paper":"/paper/2506.10972"},"observation_digest":"sha256:24ad7afc2b9c4edf56471f5e991d3c6753152e951a9b0691978b742afe168987","observation_id":"d7e4579b-32d9-4e9f-88f3-5b8ebf06383d","resolution":{"observed_at":"2026-08-07T04:21:29.346210Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04330","last_updated":"2024-11-30T02:42:31Z","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.04330","snapshot_observed_at":"2026-08-06T22:47:52.235193Z","title":"F., Bordelon, B., Muennighoff, N., Paul, M., Pehlevan, C., R \\'e , C., and Raghunathan, A","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20752","last_updated":"2025-06-25T18:25:08Z","snapshot_observed_at":"2026-08-09T12:08:21.616173Z","submitted_at":"2025-06-25T18:25:08Z","title":"Characterization and Mitigation of Training Instabilities in Microscaling Formats","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-06T22:47:52.235193Z"},"links":{"cited_paper":"/paper/2411.04330","citing_paper":"/paper/2506.20752"},"observation_digest":"sha256:a7357c185b687b8371286efd1aed9f4a60487c2815db301344c4c88a80e9585a","observation_id":"4380e891-2ae2-4b64-a401-36da515700d0","resolution":{"observed_at":"2026-08-06T22:47:52.235193Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04330","last_updated":"2024-11-30T02:42:31Z","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.04330","snapshot_observed_at":"2026-08-06T20:20:44.174979Z","title":"Scaling laws for precision","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.03300","last_updated":"2025-07-04T05:10:20Z","snapshot_observed_at":"2026-08-08T21:21:24.114593Z","submitted_at":"2025-07-04T05:10:20Z","title":"LRM-1B: Towards Large Routing Model","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T20:20:44.174979Z"},"links":{"cited_paper":"/paper/2411.04330","citing_paper":"/paper/2507.03300"},"observation_digest":"sha256:08ac965c940b08413af072ac99ddd1b5e86a530b30c2de6b7cdf7ae4e96283f0","observation_id":"896b51bb-cf59-40a2-ac90-ec1d324084a8","resolution":{"observed_at":"2026-08-06T20:20:44.174979Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04330","last_updated":"2024-11-30T02:42:31Z","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.04330","snapshot_observed_at":"2026-08-06T19:16:25.036428Z","title":"F., Bordelon, B., Muennighoff, N., Paul, M., Pehlevan, C., R \\'e , C., & Raghunathan, A","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.06079","last_updated":"2025-07-08T15:19:14Z","snapshot_observed_at":"2026-08-09T15:13:00.134450Z","submitted_at":"2025-07-08T15:19:14Z","title":"QS4D: Quantization-aware training for efficient hardware deployment of structured state-space sequential models","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-06T19:16:25.036428Z"},"links":{"cited_paper":"/paper/2411.04330","citing_paper":"/paper/2507.06079"},"observation_digest":"sha256:9973d08165b7259e623b9d1e965fbdb94d032a46ad6e496391fc736f5251622f","observation_id":"4926aa8e-9bf8-4ca7-8267-7d332fcbfd78","resolution":{"observed_at":"2026-08-06T19:16:25.036428Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04330","last_updated":"2024-11-30T02:42:31Z","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.04330","snapshot_observed_at":"2026-08-06T11:15:33.959039Z","title":"Scaling laws for precision,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.23035","last_updated":"2026-06-02T03:48:06Z","snapshot_observed_at":"2026-08-08T23:08:59.153618Z","submitted_at":"2025-07-30T19:01:25Z","title":"OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration","version":4},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T11:15:33.959039Z"},"links":{"cited_paper":"/paper/2411.04330","citing_paper":"/paper/2507.23035"},"observation_digest":"sha256:e81fe5ef78ab53551a8b84404d46ab82d861c06db68551cba2eefaa9e0b4e4d6","observation_id":"0e91b256-0d82-4bcd-ad0d-353c4c24d757","resolution":{"observed_at":"2026-08-06T11:15:33.959039Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04330","last_updated":"2024-11-30T02:42:31Z","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision","version":2},"cited_work":{"arxiv_id":"2411.04330","doi":"10.48550/arxiv.2411.04330","metadata_source":"arxiv_reference","pith_arxiv_id":"2411.04330","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Spector, Blake Bordelon, Niklas Muennighoff, Mansheej Paul, Cengiz Pehlevan, Christopher Ré, and Aditi Raghunathan","venue":"arXiv (Cornell University)","work_id":"988bd25e-4ff9-47cd-89f4-f30e112706ec","year":2024},"citing_paper":{"arxiv_id":"2510.18245","last_updated":"2026-05-13T04:16:31Z","snapshot_observed_at":"2026-08-08T00:42:38.787054Z","submitted_at":"2025-10-21T03:08:48Z","title":"Scaling Laws Meet Model Architecture: Toward Inference-Efficient LLMs","version":3},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-18T05:30:11.389756Z"},"links":{"cited_paper":"/paper/2411.04330","citing_paper":"/paper/2510.18245"},"observation_digest":"sha256:b8ee6520939ad0bf51e5f3497a8bc04aac4fa30916e20fd89841f612d7676b94","observation_id":"77a1a9f5-b51f-4a18-b02d-d7fb973e58e6","resolution":{"observed_at":"2026-05-18T05:30:55.061410Z","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":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04330","last_updated":"2024-11-30T02:42:31Z","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.04330","snapshot_observed_at":"2026-08-04T08:50:46.192841Z","title":"F., Bordelon, B., Muen- nighoff, N., Paul, M., Pehlevan, C., R´e, C., and Raghu- nathan, A","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2510.18784","last_updated":"2026-06-18T13:37:57Z","snapshot_observed_at":"2026-08-07T23:40:25.133967Z","submitted_at":"2025-10-21T16:33:57Z","title":"CAGE: Curvature-Aware Gradient Estimation For Accurate Quantization-Aware Training","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-04T08:50:46.192841Z"},"links":{"cited_paper":"/paper/2411.04330","citing_paper":"/paper/2510.18784"},"observation_digest":"sha256:72b6afba2e1e1d66c2aacd6067ee19a8501c53bb32d6ceb61ea1f7ed6d55f4b2","observation_id":"55f10632-c74f-4610-a32d-ddbc3da57613","resolution":{"observed_at":"2026-08-04T08:50:46.192841Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04330","last_updated":"2024-11-30T02:42:31Z","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision","version":2},"cited_work":{"arxiv_id":"2411.04330","doi":"10.48550/arxiv.2411.04330","metadata_source":"arxiv_reference","pith_arxiv_id":"2411.04330","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Spector, Blake Bordelon, Niklas Muennighoff, Mansheej Paul, Cengiz Pehlevan, Christopher Ré, and Aditi Raghunathan","venue":"arXiv (Cornell University)","work_id":"988bd25e-4ff9-47cd-89f4-f30e112706ec","year":2024},"citing_paper":{"arxiv_id":"2603.28507","last_updated":"2026-04-09T16:35:51Z","snapshot_observed_at":"2026-07-30T03:18:14.362050Z","submitted_at":"2026-03-30T14:42:53Z","title":"Continued AI Scaling Requires Repeated Efficiency Doublings","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-14T21:31:05.116491Z"},"links":{"cited_paper":"/paper/2411.04330","citing_paper":"/paper/2603.28507"},"observation_digest":"sha256:85e9d6d63ec13f8e9eb54b13959927306bbefb20af1c8bbaa09c918e94799a2d","observation_id":"7737ce5a-5f63-4d95-a054-21c4bf0edb50","resolution":{"observed_at":"2026-05-14T21:32:58.868260Z","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":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04330","last_updated":"2024-11-30T02:42:31Z","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision","version":2},"cited_work":{"arxiv_id":"2411.04330","doi":"10.48550/arxiv.2411.04330","metadata_source":"arxiv_reference","pith_arxiv_id":"2411.04330","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Spector, Blake Bordelon, Niklas Muennighoff, Mansheej Paul, Cengiz Pehlevan, Christopher Ré, and Aditi Raghunathan","venue":"arXiv (Cornell University)","work_id":"988bd25e-4ff9-47cd-89f4-f30e112706ec","year":2024},"citing_paper":{"arxiv_id":"2604.14629","last_updated":"2026-04-16T05:13:57Z","snapshot_observed_at":"2026-07-06T23:02:22.790426Z","submitted_at":"2026-04-16T05:13:57Z","title":"Switch-KD: Visual-Switch Knowledge Distillation for Vision-Language Models","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-10T11:23:46.371799Z"},"links":{"cited_paper":"/paper/2411.04330","citing_paper":"/paper/2604.14629"},"observation_digest":"sha256:5a8ac29565eec27989b0dd2da64b086ba5d41b9e912481b17dd0d19bdcd34e61","observation_id":"91c0a9ba-9230-4ba0-a128-f219dd32f689","resolution":{"observed_at":"2026-05-10T11:25:18.548606Z","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":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04330","last_updated":"2024-11-30T02:42:31Z","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision","version":2},"cited_work":{"arxiv_id":"2411.04330","doi":"10.48550/arxiv.2411.04330","metadata_source":"arxiv_reference","pith_arxiv_id":"2411.04330","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Spector, Blake Bordelon, Niklas Muennighoff, Mansheej Paul, Cengiz Pehlevan, Christopher Ré, and Aditi Raghunathan","venue":"arXiv (Cornell University)","work_id":"988bd25e-4ff9-47cd-89f4-f30e112706ec","year":2024},"citing_paper":{"arxiv_id":"2604.20079","last_updated":"2026-04-22T00:53:43Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-22T00:53:43Z","title":"On the Quantization Robustness of Diffusion Language Models in Coding Benchmarks","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-10T00:21:30.101748Z"},"links":{"cited_paper":"/paper/2411.04330","citing_paper":"/paper/2604.20079"},"observation_digest":"sha256:0296fa9047dd60a997e9a82f8cfa61acca73d71386e0c4553daefdb870166a69","observation_id":"d48861ed-1443-4717-97ae-9a85b91220e1","resolution":{"observed_at":"2026-05-10T00:24:47.008477Z","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":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04330","last_updated":"2024-11-30T02:42:31Z","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision","version":2},"cited_work":{"arxiv_id":"2411.04330","doi":"10.48550/arxiv.2411.04330","metadata_source":"arxiv_reference","pith_arxiv_id":"2411.04330","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Spector, Blake Bordelon, Niklas Muennighoff, Mansheej Paul, Cengiz Pehlevan, Christopher Ré, and Aditi Raghunathan","venue":"arXiv (Cornell University)","work_id":"988bd25e-4ff9-47cd-89f4-f30e112706ec","year":2024},"citing_paper":{"arxiv_id":"2605.14929","last_updated":"2026-05-14T15:03:58Z","snapshot_observed_at":"2026-07-06T23:26:18.733776Z","submitted_at":"2026-05-14T15:03:58Z","title":"A Hardware-Aware, Per-Layer Methodology for Post-Training Quantization of Large Language Models","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-06-30T21:03:05.361805Z"},"links":{"cited_paper":"/paper/2411.04330","citing_paper":"/paper/2605.14929"},"observation_digest":"sha256:8fe5c4f3aa82c0433d341caa9372e80a8a4b1c8aea2f8d5662971999fbdeac60","observation_id":"c4223ed8-f9e8-4f6a-8761-3b3611edde8c","resolution":{"observed_at":"2026-06-30T21:05:03.951165Z","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":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04330","last_updated":"2024-11-30T02:42:31Z","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision","version":2},"cited_work":{"arxiv_id":"2411.04330","doi":"10.48550/arxiv.2411.04330","metadata_source":"arxiv_reference","pith_arxiv_id":"2411.04330","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Spector, Blake Bordelon, Niklas Muennighoff, Mansheej Paul, Cengiz Pehlevan, Christopher Ré, and Aditi Raghunathan","venue":"arXiv (Cornell University)","work_id":"988bd25e-4ff9-47cd-89f4-f30e112706ec","year":2024},"citing_paper":{"arxiv_id":"2605.23591","last_updated":"2026-05-22T13:00:52Z","snapshot_observed_at":"2026-08-02T07:23:00.263762Z","submitted_at":"2026-05-22T13:00:52Z","title":"Asymmetric Scaling Laws from Sparse Features","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-05-25T03:16:34.488732Z"},"links":{"cited_paper":"/paper/2411.04330","citing_paper":"/paper/2605.23591"},"observation_digest":"sha256:234ae011ade4806441f70fbdcd209527496cc9ff1808aeb5e97dd9e999c7d231","observation_id":"508a95a2-2afe-4c7e-94d1-46f23da5fa1a","resolution":{"observed_at":"2026-05-25T03:20:16.932922Z","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":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04330","last_updated":"2024-11-30T02:42:31Z","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision","version":2},"cited_work":{"arxiv_id":"2411.04330","doi":"10.48550/arxiv.2411.04330","metadata_source":"arxiv_reference","pith_arxiv_id":"2411.04330","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Spector, Blake Bordelon, Niklas Muennighoff, Mansheej Paul, Cengiz Pehlevan, Christopher Ré, and Aditi Raghunathan","venue":"arXiv (Cornell University)","work_id":"988bd25e-4ff9-47cd-89f4-f30e112706ec","year":2024},"citing_paper":{"arxiv_id":"2605.23901","last_updated":"2026-05-22T17:59:38Z","snapshot_observed_at":"2026-07-06T23:34:03.934151Z","submitted_at":"2026-05-22T17:59:38Z","title":"LLMs as Noisy Channels: A Shannon Perspective on Model Capacity and Scaling Laws","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:35.962947Z"},"links":{"cited_paper":"/paper/2411.04330","citing_paper":"/paper/2605.23901"},"observation_digest":"sha256:a7a5070559cab4a10d01f1104f181500c1084d26d3a96d0b4268129cd1374763","observation_id":"23864b76-d090-4a95-b643-dd81ceecb4cb","resolution":{"observed_at":"2026-05-25T04:35:21.781093Z","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":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04330","last_updated":"2024-11-30T02:42:31Z","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision","version":2},"cited_work":{"arxiv_id":"2411.04330","doi":"10.48550/arxiv.2411.04330","metadata_source":"arxiv_reference","pith_arxiv_id":"2411.04330","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Spector, Blake Bordelon, Niklas Muennighoff, Mansheej Paul, Cengiz Pehlevan, Christopher Ré, and Aditi Raghunathan","venue":"arXiv (Cornell University)","work_id":"988bd25e-4ff9-47cd-89f4-f30e112706ec","year":2024},"citing_paper":{"arxiv_id":"2605.27435","last_updated":"2026-05-22T10:39:35Z","snapshot_observed_at":"2026-08-08T01:27:25.329843Z","submitted_at":"2026-05-22T10:39:35Z","title":"When NPUs Are Not Always Faster: A Stage-Level Analysis of Mobile LLM Inference","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-30T15:03:31.289211Z"},"links":{"cited_paper":"/paper/2411.04330","citing_paper":"/paper/2605.27435"},"observation_digest":"sha256:757c3c027d0a8fe12d2cd54cb171918f816d2edd6441aed543f02743f698cae7","observation_id":"d56d4330-afff-4cf2-b55b-6864e4d2789b","resolution":{"observed_at":"2026-06-30T15:04:46.177292Z","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":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04330","last_updated":"2024-11-30T02:42:31Z","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision","version":2},"cited_work":{"arxiv_id":"2411.04330","doi":"10.48550/arxiv.2411.04330","metadata_source":"arxiv_reference","pith_arxiv_id":"2411.04330","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Spector, Blake Bordelon, Niklas Muennighoff, Mansheej Paul, Cengiz Pehlevan, Christopher Ré, and Aditi Raghunathan","venue":"arXiv (Cornell University)","work_id":"988bd25e-4ff9-47cd-89f4-f30e112706ec","year":2024},"citing_paper":{"arxiv_id":"2606.05017","last_updated":"2026-06-22T12:03:17Z","snapshot_observed_at":"2026-08-08T21:46:25.128578Z","submitted_at":"2026-06-03T15:41:16Z","title":"GoldenFloat: A Phi-Derived Static-Split Floating-Point Family from GF4 to GF1024 with a Lucas-Exact Integer Identity","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-06-28T03:47:27.000639Z"},"links":{"cited_paper":"/paper/2411.04330","citing_paper":"/paper/2606.05017"},"observation_digest":"sha256:bd316451ee0ed57485fc1c1d8c97f833830a2e75d51dbfd2486c3992219bdffe","observation_id":"0f74a084-582a-4c67-a1d0-66f1e3bcb47c","resolution":{"observed_at":"2026-07-02T11:26:54.600469Z","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":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04330","last_updated":"2024-11-30T02:42:31Z","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.04330","snapshot_observed_at":"2026-07-14T15:32:26.691504Z","title":"Scaling laws for precision,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.09800","last_updated":"2026-07-28T02:32:08Z","snapshot_observed_at":"2026-08-08T04:58:48.026355Z","submitted_at":"2026-07-09T15:23:42Z","title":"Reference Traces for Auditing Invisible Weight Updates and Guiding Exact-Budget Protection","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-07-14T15:32:26.691504Z"},"links":{"cited_paper":"/paper/2411.04330","citing_paper":"/paper/2607.09800"},"observation_digest":"sha256:5f9ab318da0f92fa31b9589e2739a08c6183d50790b643187a37ef3d77360777","observation_id":"3207bbad-cee5-467a-a870-de7e887ed7f3","resolution":{"observed_at":"2026-07-14T15:32:26.691504Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04330","last_updated":"2024-11-30T02:42:31Z","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.04330","snapshot_observed_at":"2026-07-14T08:45:52.855783Z","title":"arXiv preprint arXiv:2411.04330 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10855","last_updated":"2026-07-12T17:39:09Z","snapshot_observed_at":"2026-08-06T03:10:18.618115Z","submitted_at":"2026-07-12T17:39:09Z","title":"Reliability Scaling Laws for Quantized Large Language Models","version":1},"reference_index":136,"source":"arxiv_source","source_observed_at":"2026-07-14T08:45:52.855783Z"},"links":{"cited_paper":"/paper/2411.04330","citing_paper":"/paper/2607.10855"},"observation_digest":"sha256:ee008eeef5a7e66ced158508dda5298e81dba920551be82aa3e6c91dae0db443","observation_id":"72ce8324-0291-4f38-b0b6-71069e02c81b","resolution":{"observed_at":"2026-07-14T08:45:52.855783Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2411.04330/citation-record","integrity":"/paper/2411.04330/integrity","json":"/paper/2411.04330/citation-record.json","paper":"/paper/2411.04330"},"outbound":[],"paper":{"arxiv_id":"2411.04330","last_updated":"2024-11-30T02:42:31Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-04T07:47:22.112536Z","submitted_at":"2024-11-07T00:10:10Z","title":"Scaling Laws for Precision"},"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 24 inbound Pith citation observations for arXiv:2411.04330."}