{"as_of":"2026-08-08T03:39:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7e0b65b0cff4b01844a20767097263c73fb28c3d0b91a123bc1a4d31e26259a5","coverage":[{"denominator":29,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":29,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T15:08:29.799420Z","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":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-12T02:38:11.071221Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-12T07:31:26.282151Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"cited_work":{"arxiv_id":"2507.16933","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2507.16933","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Esser, Jeffrey L","venue":null,"work_id":"99049a18-b8f5-4de7-810c-40d71d077650","year":2025},"citing_paper":{"arxiv_id":"2605.09425","last_updated":"2026-05-10T08:56:08Z","snapshot_observed_at":"2026-07-06T23:21:30.897592Z","submitted_at":"2026-05-10T08:56:08Z","title":"AtteConDA: Attention-Based Conflict Suppression in Multi-Condition Diffusion Models and Synthetic Data Augmentation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-12T02:38:11.071221Z"},"links":{"cited_paper":"/paper/2507.16933","citing_paper":"/paper/2605.09425"},"observation_digest":"sha256:889503ed0dbd9a4c40b8a032ba114270aa9a79a054fc3b75d23d1f381d00784a","observation_id":"b227dcf7-2a16-480c-8cdd-fd94f39f1e9f","resolution":{"observed_at":"2026-05-12T07:31:26.284793Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2507.16933/citation-record","integrity":"/paper/2507.16933/integrity","json":"/paper/2507.16933/citation-record.json","paper":"/paper/2507.16933"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T15:08:33.151187Z","title":null,"venue":null,"work_id":"34f058a3-7b66-4545-b823-904521a115ed","year":2024},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:26.102850Z"},"links":{"citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:492bfcda5b9a483119e551223e918ee7cbb2343eec7a2a155ae95bee5348db27","observation_id":"5baac5d1-5fd9-4271-8ee8-bb50732ab57b","resolution":{"observed_at":"2026-08-06T15:08:33.301777Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:08:32.844340Z","title":null,"venue":null,"work_id":"aa1a5340-59c6-4365-8658-ad00bae446d4","year":2024},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:26.155176Z"},"links":{"citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:868c8b2b94dfe5bd92f7e0bc2a12432049740a5c75ee9d2959b328699fff0038","observation_id":"b7837cf5-cf70-47a6-9c0e-ca5cb06516b2","resolution":{"observed_at":"2026-08-06T15:08:32.987585Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1308.3432","last_updated":"2013-08-15T15:19:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2013-08-15T15:19:34Z","title":"Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1308.3432","snapshot_observed_at":"2026-08-06T15:08:26.301138Z","title":null,"venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:26.301138Z"},"links":{"cited_paper":"/paper/1308.3432","citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:c2cc4a079b323c85b8e8e036e7f4f68ab8b5ad5bc5bbdec5798e62402f1eb8f1","observation_id":"a790008b-46fd-4a59-ac4a-69a8f4706e9e","resolution":{"observed_at":"2026-08-06T15:08:26.301138Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.05265","last_updated":"2025-01-27T13:39:25Z","snapshot_observed_at":"2026-07-06T19:29:09.714725Z","submitted_at":"2024-10-07T17:59:35Z","title":"PrefixQuant: Eliminating Outliers by Prefixed Tokens for Large Language Models Quantization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.05265","snapshot_observed_at":"2026-08-06T15:08:26.413524Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:26.413524Z"},"links":{"cited_paper":"/paper/2410.05265","citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:3e56074f2b1d173f0b1f9a625b7576a854a7d616eebc3ec4e04737f2df5deebd","observation_id":"9bf823a9-ad89-4c39-99d7-368d25843d7f","resolution":{"observed_at":"2026-08-06T15:08:26.413524Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.11062","last_updated":"2025-05-19T06:20:01Z","snapshot_observed_at":"2026-08-08T01:47:51.652242Z","submitted_at":"2024-07-10T17:53:30Z","title":"EfficientQAT: Efficient Quantization-Aware Training for Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.11062","snapshot_observed_at":"2026-08-06T15:08:26.568508Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:26.568508Z"},"links":{"cited_paper":"/paper/2407.11062","citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:d6f75b3bb4bb5178e1b4a7da53c7db7fd73ec623d30ed2e0d4ec38185574252d","observation_id":"fd84d796-2cf5-4b7f-8e53-5a75ae456c08","resolution":{"observed_at":"2026-08-06T15:08:26.568508Z","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":"2026-08-06T15:08:32.625016Z","title":"Fu, Stefano Ermon, Atri Rudra, and Christopher R \\'e","venue":null,"work_id":"6c4520a6-12e5-4ac8-8833-f99555b960eb","year":2022},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:26.717618Z"},"links":{"citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:105c1bd17ddb35ac8c139b81c5a87541a3cf7945aa842baceae2da9d2064feba","observation_id":"c296ec80-830a-4812-b5ae-1a6d519a41d8","resolution":{"observed_at":"2026-08-06T15:08:32.690384Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.10631","last_updated":"2024-02-16T12:27:15Z","snapshot_observed_at":"2026-07-06T17:31:08.762955Z","submitted_at":"2024-02-16T12:27:15Z","title":"BitDistiller: Unleashing the Potential of Sub-4-Bit LLMs via Self-Distillation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.10631","snapshot_observed_at":"2026-08-06T15:08:26.859827Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:26.859827Z"},"links":{"cited_paper":"/paper/2402.10631","citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:a3db79bf3e0237f7718f54d4ed9a6bb2219e911b2dafffb74ed22d1148a562c2","observation_id":"8f314e75-ca3b-447b-9648-af25be343cd5","resolution":{"observed_at":"2026-08-06T15:08:26.859827Z","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":"2026-08-06T15:08:32.352459Z","title":null,"venue":null,"work_id":"03b9c5fa-5c1b-499e-bceb-8c09f02aa62d","year":2019},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:26.982294Z"},"links":{"citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:06e9f332e7b46b4a4f27129c9b90b33dac3ae27e5adbf90b7bb5c88a1f0596cc","observation_id":"c9a89695-b5ca-400c-b104-94990150d472","resolution":{"observed_at":"2026-08-06T15:08:32.496434Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.17323","last_updated":"2023-03-22T13:10:47Z","snapshot_observed_at":"2026-08-07T08:38:54.025062Z","submitted_at":"2022-10-31T13:42:40Z","title":"GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.17323","snapshot_observed_at":"2026-08-06T15:08:27.101492Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:27.101492Z"},"links":{"cited_paper":"/paper/2210.17323","citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:87038b0a39dea445a9b3275bf6ca2afc7933d31510120eb1a12e600d9ac4ec07","observation_id":"fdb6a6e9-43eb-4baa-b7f4-a187957cefe4","resolution":{"observed_at":"2026-08-06T15:08:27.101492Z","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":"2026-08-06T15:08:27.217357Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:27.217357Z"},"links":{"citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:169650ad6d9aa23cf50dbd6addb2a147a9fb1be31a67ce67bce65a4d2c48600d","observation_id":"2b4fe852-b01c-4541-8072-0ee8f6b4f777","resolution":{"observed_at":"2026-08-06T15:08:27.217357Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1503.02531","last_updated":"2015-03-09T15:44:49Z","snapshot_observed_at":"2026-07-06T04:11:24.157003Z","submitted_at":"2015-03-09T15:44:49Z","title":"Distilling the Knowledge in a Neural Network","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1503.02531","snapshot_observed_at":"2026-08-06T15:08:27.368246Z","title":null,"venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:27.368246Z"},"links":{"cited_paper":"/paper/1503.02531","citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:d79e894f2591bb07913a8f83320304841bc8874a835015990997c0dcbea47d64","observation_id":"3d87b40c-8c32-4e05-94ea-bea2f0f8b03d","resolution":{"observed_at":"2026-08-06T15:08:27.368246Z","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":"2026-08-06T15:08:32.034474Z","title":null,"venue":null,"work_id":"ff0d19b2-409b-4e08-af40-b583162f58ea","year":2024},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:27.480150Z"},"links":{"citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:3a0d3e0fa93ee98df543179e9124fdd562c442aa80d1e0307117b78599fc0de5","observation_id":"79f4bc61-c53a-47b4-9e38-511059cd917d","resolution":{"observed_at":"2026-08-06T15:08:32.227892Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:08:31.757880Z","title":"Sft trainer — trl documentation","venue":null,"work_id":"ed3c4cf3-35aa-4c4b-ae70-7b725ac14589","year":2025},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:27.570609Z"},"links":{"citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:ba80f043664c8837c5ffcaf4de938eaa73c453c3cc4481a91d832ecf01abd07e","observation_id":"f209ca72-dfb3-4a03-a87c-73965a29ea66","resolution":{"observed_at":"2026-08-06T15:08:31.886610Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.15124","last_updated":"2025-04-14T22:39:09Z","snapshot_observed_at":"2026-07-06T19:55:37.400185Z","submitted_at":"2024-11-22T18:44:04Z","title":"Tulu 3: Pushing Frontiers in Open Language Model Post-Training","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.15124","snapshot_observed_at":"2026-08-06T15:08:27.751884Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:27.751884Z"},"links":{"cited_paper":"/paper/2411.15124","citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:f163c52aa80490ecc9f2f720f45286d58291ddc153e6a73a8b2b5b5ab4dec806","observation_id":"1fcfa5a1-2395-4d70-85a3-0cc4378b5a08","resolution":{"observed_at":"2026-08-06T15:08:27.751884Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.11055","last_updated":"2025-06-04T01:15:49Z","snapshot_observed_at":"2026-08-06T14:52:52.028018Z","submitted_at":"2024-09-17T10:31:37Z","title":"Exploring the Trade-Offs: Quantization Methods, Task Difficulty, and Model Size in Large Language Models From Edge to Giant","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.11055","snapshot_observed_at":"2026-08-06T15:08:27.899104Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:27.899104Z"},"links":{"cited_paper":"/paper/2409.11055","citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:48c2974a1b3ca5db5d96a7ba636d10a5e41ddd456cac65c0654f4364d2d1f1de","observation_id":"3ed256d7-a068-4937-89fa-bdd3fa7edddd","resolution":{"observed_at":"2026-08-06T15:08:27.899104Z","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":"2026-08-06T15:08:31.377972Z","title":null,"venue":null,"work_id":"cc1351bb-89a1-4f03-ae4d-e0ce4a4cb696","year":2024},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:28.009238Z"},"links":{"citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:97a8075ca86ba39f6902faf2bbae42229afe57fe7c6e6f6d75d3b02bf2ba4f9d","observation_id":"8badd7f2-ff3d-435e-a3a0-49886357854a","resolution":{"observed_at":"2026-08-06T15:08:31.537278Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.17888","last_updated":"2023-05-29T05:22:11Z","snapshot_observed_at":"2026-08-07T18:58:35.737110Z","submitted_at":"2023-05-29T05:22:11Z","title":"LLM-QAT: Data-Free Quantization Aware Training for Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.17888","snapshot_observed_at":"2026-08-06T15:08:28.125268Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:28.125268Z"},"links":{"cited_paper":"/paper/2305.17888","citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:82bd8f10ab298814fae9851e31fee9f51a4d68b4e365fc17dbb4a927f1e07aca","observation_id":"b814e3ab-99ec-4300-aa5e-a2060109a7fe","resolution":{"observed_at":"2026-08-06T15:08:28.125268Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.16406","last_updated":"2025-02-20T06:07:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-05-26T02:15:49Z","title":"SpinQuant: LLM quantization with learned rotations","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.16406","snapshot_observed_at":"2026-08-06T15:08:28.214739Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:28.214739Z"},"links":{"cited_paper":"/paper/2405.16406","citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:e1df4454cde46bd65fa6b8a9a96647dca4442951f6f26c761b00c808f0dbfa66","observation_id":"eaeed9bd-da10-446b-bd69-1300b891e7d1","resolution":{"observed_at":"2026-08-06T15:08:28.214739Z","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":"2026-08-06T15:08:28.368262Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:28.368262Z"},"links":{"citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:b0997134dda01f79adcee57b0c80c94905339f956a335e06d832c607f541858f","observation_id":"e6295020-d45f-4060-8428-b6db17d85d41","resolution":{"observed_at":"2026-08-06T15:08:28.368262Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1711.05101","last_updated":"2019-01-04T21:01:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-11-14T14:24:06Z","title":"Decoupled Weight Decay Regularization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.05101","snapshot_observed_at":"2026-08-06T15:08:28.517646Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:28.517646Z"},"links":{"cited_paper":"/paper/1711.05101","citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:27f2d988f5294f85f9db1c152ff893c8c578c66c1d6c4e6176dacb08508452dd","observation_id":"33c9b6d1-415c-4699-826d-8458d6bb6ac7","resolution":{"observed_at":"2026-08-06T15:08:28.517646Z","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":"2026-08-06T15:08:31.133475Z","title":null,"venue":null,"work_id":"e6eb6aff-e707-4f7c-9c78-c80596b8df29","year":2023},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:28.719583Z"},"links":{"citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:83e9785403a5228000f31b6dfa05518f33d65624013d6403b6fa70f4d1249e11","observation_id":"466df803-ac7c-425d-8cf3-20e2321972d8","resolution":{"observed_at":"2026-08-06T15:08:31.259306Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:08:30.961751Z","title":null,"venue":null,"work_id":"c7a66bd3-7aaf-411a-95fb-4004718e93d4","year":1966},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:28.800600Z"},"links":{"citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:03fdef9f45cbcba69724cd2838764a15a2a8d2cc2d773276f4cc5b6f9336d37f","observation_id":"8f1fc671-7f1f-4f48-89f3-2ea61bae8bbe","resolution":{"observed_at":"2026-08-06T15:08:31.037446Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.13359","last_updated":"2024-09-11T20:48:05Z","snapshot_observed_at":"2026-07-06T19:05:18.260091Z","submitted_at":"2024-08-23T20:22:20Z","title":"Power Scheduler: A Batch Size and Token Number Agnostic Learning Rate Scheduler","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.13359","snapshot_observed_at":"2026-08-06T15:08:28.936813Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:28.936813Z"},"links":{"cited_paper":"/paper/2408.13359","citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:c20269473f3aaf06f5dd65501edd617fcb3423b489e6503669ff54d476885cda","observation_id":"3bfa4de5-803d-429d-827b-ac5a995d7023","resolution":{"observed_at":"2026-08-06T15:08:28.936813Z","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":"2026-08-06T15:08:30.612337Z","title":"https://github.com/facebookresearch/LLM-QAT, Accessed: 2025-06-19","venue":null,"work_id":"727328e3-b4e5-4922-aec1-382265083703","year":2025},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:29.093041Z"},"links":{"citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:3235f5903bb5de332b261a9d4790e7a4cd75f621f15fe25433b720475faa5fef","observation_id":"04573746-73c2-4467-921f-fc0156a45b36","resolution":{"observed_at":"2026-08-06T15:08:30.762839Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04965","last_updated":"2024-11-07T18:41:50Z","snapshot_observed_at":"2026-08-04T09:57:22.968756Z","submitted_at":"2024-11-07T18:41:50Z","title":"BitNet a4.8: 4-bit Activations for 1-bit LLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.04965","snapshot_observed_at":"2026-08-06T15:08:29.258048Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:29.258048Z"},"links":{"cited_paper":"/paper/2411.04965","citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:77c2a0b495e2efe40e2a3560facc9e5a2cbe92cd07d8890f26b85e9a7aee64af","observation_id":"c968c840-9b15-4a3b-ab6d-fa46d242edff","resolution":{"observed_at":"2026-08-06T15:08:29.258048Z","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":"2026-08-06T15:08:30.238281Z","title":null,"venue":null,"work_id":"1b12b534-de2b-4d6c-b577-7ba0738e746c","year":2024},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:29.431011Z"},"links":{"citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:5270faf1b1361a78a654792f561ec4350f768f994032b74a2ad95f6d7182793e","observation_id":"e16ef3ae-d6ec-40c1-a0b7-235198e21f99","resolution":{"observed_at":"2026-08-06T15:08:30.388348Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:08:29.530102Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:29.530102Z"},"links":{"citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:c6d5b25686df54ed1ef5d5ac6c4aaa326ea3faa9e9e2fbc9dbccc5663ec7ca36","observation_id":"24e555cf-f4aa-4ff6-a58a-63884a6dbeeb","resolution":{"observed_at":"2026-08-06T15:08:29.530102Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.14717","last_updated":"2023-10-09T07:39:04Z","snapshot_observed_at":"2026-08-03T21:40:53.000035Z","submitted_at":"2023-09-26T07:22:23Z","title":"QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.14717","snapshot_observed_at":"2026-08-06T15:08:29.673002Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:29.673002Z"},"links":{"cited_paper":"/paper/2309.14717","citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:b1295193ad418fbd0c88e225307758f812cf7d6e331244efd0369caa635af09c","observation_id":"3a3a095f-eda8-41a2-a546-7817e53568a1","resolution":{"observed_at":"2026-08-06T15:08:29.673002Z","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":"2026-08-06T15:08:29.799420Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-06T15:08:29.799420Z"},"links":{"citing_paper":"/paper/2507.16933"},"observation_digest":"sha256:4aba28900246613c0ce44e540c087d8e6b2ab4095b543ff0fdfe90ec6fb13c1e","observation_id":"d1122fd9-4d29-43fe-96f4-d99741b8e8b8","resolution":{"observed_at":"2026-08-06T15:08:29.799420Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2507.16933","last_updated":"2025-07-22T18:17:53Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-06T14:58:05.838241Z","submitted_at":"2025-07-22T18:17:53Z","title":"SiLQ: Simple Large Language Model Quantization-Aware Training"},"reference_resolution":{"displayed":29,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":26,"verified_exact":0,"verified_fuzzy":3},"total_outbound_references":29},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 1 inbound Pith citation observation for arXiv:2507.16933."}