{"as_of":"2026-08-19T13:46:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0ea3639c567c8333d6ed60b6f8e1cd342a02a51ea95ac1ac08bebd36d4304ce9","coverage":[{"denominator":28,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":28,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T20:00:05.212675Z","state":"measured"},{"denominator":29,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":29,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+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":"2026-05-15T00:56:04.958757Z","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":"2026-05-15T00:58:25.671460Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"cited_work":{"arxiv_id":"2508.11551","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.11551","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Available: https://arxiv.org/abs/2508.11551","venue":null,"work_id":"47984959-ecc8-423f-9cba-88162167b6d3","year":null},"citing_paper":{"arxiv_id":"2604.16380","last_updated":"2026-03-25T13:30:40Z","snapshot_observed_at":"2026-08-15T22:16:01.152280Z","submitted_at":"2026-03-25T13:30:40Z","title":"Data Mixing for Large Language Models Pretraining: A Survey and Outlook","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-15T00:56:04.958757Z"},"links":{"cited_paper":"/paper/2508.11551","citing_paper":"/paper/2604.16380"},"observation_digest":"sha256:a3b8b33dca04075dbaadc02fc23f2efb3d988da2702e3713deee3b6c076dfd12","observation_id":"60955298-e064-4ccd-a7df-660b8f73dd1f","resolution":{"observed_at":"2026-05-15T00:58:25.673307Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2508.11551/citation-record","integrity":"/paper/2508.11551/integrity","json":"/paper/2508.11551/citation-record.json","paper":"/paper/2508.11551"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:00:05.490079Z","title":null,"venue":null,"work_id":"14d2c63c-28de-4cc8-b902-b6d5c6edda80","year":2024},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.138265Z"},"links":{"citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:91a155e76903351193c729ca76508e570e501f2a4192642168914286a08dc354","observation_id":"992ab8fa-70e3-44bf-8f1d-c4f4fd6e5f72","resolution":{"observed_at":"2026-08-05T20:00:05.492442Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.16827","last_updated":"2024-08-02T17:59:31Z","snapshot_observed_at":"2026-08-16T14:15:11.706978Z","submitted_at":"2024-02-26T18:54:35Z","title":"A Survey on Data Selection for Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.16827","snapshot_observed_at":"2026-08-05T20:00:05.148049Z","title":"org/abs/2402.16827,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.148049Z"},"links":{"cited_paper":"/paper/2402.16827","citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:c44824e1c922fcfdabdca3cd472c09d1025d3383a1ddc27935691e5d0adb1805","observation_id":"f9b58d95-95ed-4b05-bbe6-f282d743f47e","resolution":{"observed_at":"2026-08-05T20:00:05.148049Z","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":"2026-08-05T20:00:05.154184Z","title":"Language models are few-shot learners","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.154184Z"},"links":{"citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:24bdf3e3af28781de19f09d98458aec8abc4e4d30446493aef3f4b2e8a0121c4","observation_id":"a2c24579-23ff-46ea-b269-7ed67150f765","resolution":{"observed_at":"2026-08-05T20:00:05.154184Z","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":"2026-08-05T20:00:05.157109Z","title":"Bert: Pre-training of deep bidirectional transformers for language understanding","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.157109Z"},"links":{"citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:4ed1022cff295859293bbb1c4f72b6dfe752628bf1dd06022538180294e4ea68","observation_id":"21e3063c-fc7b-4d0a-9b79-596e3d650818","resolution":{"observed_at":"2026-08-05T20:00:05.157109Z","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":"2026-08-05T20:00:05.475113Z","title":"Combining hyperband and bayesian optimization","venue":null,"work_id":"eeccb9ab-3409-4229-b5ea-19652146a3dc","year":2017},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.160306Z"},"links":{"citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:e11f801aa9ad82ff2c25690015a5858a2d64320bc7283e7011868d96b7ad513e","observation_id":"d32d30f7-ce73-4321-908f-558d67814117","resolution":{"observed_at":"2026-08-05T20:00:05.477342Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1807.02811","last_updated":"2018-07-08T13:06:26Z","snapshot_observed_at":"2026-08-18T00:58:48.914606Z","submitted_at":"2018-07-08T13:06:26Z","title":"A Tutorial on Bayesian Optimization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.02811","snapshot_observed_at":"2026-08-05T20:00:05.167395Z","title":"A tutorial on bayesian optimization.arXiv preprint arXiv:1807.02811,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.167395Z"},"links":{"cited_paper":"/paper/1807.02811","citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:32e2bd4d752cedd15528ab86f16da58c2ac5fec2c29ad1b6511c6d100376e293","observation_id":"c5c288e4-2328-4ad0-a6fd-c8a4d9f146b4","resolution":{"observed_at":"2026-08-05T20:00:05.167395Z","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":"2026-08-05T20:00:05.459262Z","title":"Bayesian optimization with inequality constraints","venue":null,"work_id":"76c2ef8d-0716-48cc-af6f-764414fde48c","year":2014},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.172999Z"},"links":{"citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:83b9e11cd72d1d79e1055411d58f42cd6192f03791f640bf34394cdd29f71549","observation_id":"be84c658-4fd4-4785-aa96-07f7a98602e9","resolution":{"observed_at":"2026-08-05T20:00:05.462508Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.15556","last_updated":"2022-03-29T13:38:03Z","snapshot_observed_at":"2026-08-09T19:52:33.533277Z","submitted_at":"2022-03-29T13:38:03Z","title":"Training Compute-Optimal Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.15556","snapshot_observed_at":"2026-08-05T20:00:05.178399Z","title":"Training compute-optimal large language models.arXiv preprint arXiv:2203.15556,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.178399Z"},"links":{"cited_paper":"/paper/2203.15556","citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:5d207a0fe5f6733d5ba57236187824388fccbd5b748f465e09194a7aff2f1089","observation_id":"59045464-aca8-40ee-a890-6e3718097d7d","resolution":{"observed_at":"2026-08-05T20:00:05.178399Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-08-17T19:26:44.032537Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-05T20:00:05.183737Z","title":"Adam: A method for stochastic optimization","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.183737Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:3439906dffa5d41177b9957469ac599c530d5b8c7453ced02aaba36aef24eaa2","observation_id":"ba99ab58-2f64-4d55-8e9c-eb66dbd10cb9","resolution":{"observed_at":"2026-08-05T20:00:05.183737Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.15124","last_updated":"2025-04-14T22:39:09Z","snapshot_observed_at":"2026-08-17T14:11:00.232598Z","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":"2026-08-05T20:00:05.186346Z","title":"T�\" ulu 3: Pushing frontiers in open language model post-training","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.186346Z"},"links":{"cited_paper":"/paper/2411.15124","citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:f7e66be148c5ee8840399d81d5bd4c56f334149835365a60f797cb6ec150085a","observation_id":"6ffb9e73-c18a-441c-9525-85af377e37b0","resolution":{"observed_at":"2026-08-05T20:00:05.186346Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1603.06560","last_updated":"2018-06-18T23:01:43Z","snapshot_observed_at":"2026-08-14T22:05:06.791163Z","submitted_at":"2016-03-21T19:51:04Z","title":"Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1603.06560","snapshot_observed_at":"2026-08-05T20:00:05.189826Z","title":"Jamieson, Giulia DeSalvo, Afshin Rostamizadeh, and Ameet Talwalkar","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.189826Z"},"links":{"cited_paper":"/paper/1603.06560","citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:cd7e876f940cbc16bce3015da8a5fdc1ca63941cac9eab85ed16915c934b74c2","observation_id":"8af0b646-d623-4753-bb51-36ee09704f6f","resolution":{"observed_at":"2026-08-05T20:00:05.189826Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.04564","last_updated":"2023-09-08T19:34:05Z","snapshot_observed_at":"2026-08-16T15:02:10.343729Z","submitted_at":"2023-09-08T19:34:05Z","title":"When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.04564","snapshot_observed_at":"2026-08-05T20:00:05.194995Z","title":"When less is more: Investigating data pruning for pretraining llms at scale.arXiv preprint arXiv:2309.04564,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.194995Z"},"links":{"cited_paper":"/paper/2309.04564","citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:c0a60bcd5c6a6eea965f45501771566d79772e780cd23415c07e770ec236042c","observation_id":"f1ed7484-fbb0-434d-9557-1e0cf813a131","resolution":{"observed_at":"2026-08-05T20:00:05.194995Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.11805","last_updated":"2025-05-09T21:04:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-19T02:39:27Z","title":"Gemini: A Family of Highly Capable Multimodal Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.11805","snapshot_observed_at":"2026-08-05T20:00:05.201722Z","title":"Gemini: a family of highly capable multimodal models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.201722Z"},"links":{"cited_paper":"/paper/2312.11805","citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:518b6bdb272ebfcfcfe14918206a457021b6216b2bfad3f7156ccf5f754f2eb5","observation_id":"183520e0-bbd0-4283-9ebf-ee878a9c09ec","resolution":{"observed_at":"2026-08-05T20:00:05.201722Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.04333","last_updated":"2024-06-13T03:42:02Z","snapshot_observed_at":"2026-08-16T14:20:52.583862Z","submitted_at":"2024-02-06T19:18:04Z","title":"LESS: Selecting Influential Data for Targeted Instruction Tuning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.04333","snapshot_observed_at":"2026-08-05T20:00:05.206082Z","title":"Less: Selecting influential data for targeted instruction tuning.arXiv preprint arXiv:2402.04333,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.206082Z"},"links":{"cited_paper":"/paper/2402.04333","citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:1b9b81c1973211877266a9e2a59d167ea3ac4cb0e943963da5943f1083d281f5","observation_id":"e2651289-819d-4323-8f74-b7faa459aef5","resolution":{"observed_at":"2026-08-05T20:00:05.206082Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.15115","last_updated":"2025-01-03T02:18:21Z","snapshot_observed_at":"2026-08-17T18:50:07.059564Z","submitted_at":"2024-12-19T17:56:09Z","title":"Qwen2.5 Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.15115","snapshot_observed_at":"2026-08-05T20:00:05.209560Z","title":"Qwen2.5 technical report","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.209560Z"},"links":{"cited_paper":"/paper/2412.15115","citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:740aef2c93c93181e2bd1e2c018331d9feb8ebb5f5b5fba5497530ceb7a44643","observation_id":"7ca1d358-1968-4515-bfc6-70544c98ed9e","resolution":{"observed_at":"2026-08-05T20:00:05.209560Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.21023","last_updated":"2025-03-26T22:19:47Z","snapshot_observed_at":"2026-08-16T12:46:28.873775Z","submitted_at":"2025-03-26T22:19:47Z","title":"Data Mixture Optimization: A Multi-fidelity Multi-scale Bayesian Framework","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.21023","snapshot_observed_at":"2026-08-05T20:00:05.212675Z","title":"Data mixture optimization: A multi-fidelity multi-scale bayesian framework.arXiv preprint arXiv:2503.21023,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.212675Z"},"links":{"cited_paper":"/paper/2503.21023","citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:e0375e21826bf13c1e48421cbe5fac8702636e971de7002c4306e101b2d9609b","observation_id":"88e84c6b-0e85-482e-81b5-4b792acbeb72","resolution":{"observed_at":"2026-08-05T20:00:05.212675Z","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":"2026-08-05T20:00:05.451325Z","title":"Simopt: A library of simulation optimization problems","venue":null,"work_id":"9685cce1-7bf2-40e0-bdf7-3981e6bba875","year":2011},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":1998,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.197150Z"},"links":{"citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:5fbc23e0d47e90c4bce00f17a664c0b258c3f1302964a8cb57798e4750041e63","observation_id":"38e5ff1e-2338-46a1-b064-4acecbbebc77","resolution":{"observed_at":"2026-08-05T20:00:05.453734Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2101.00027","last_updated":"2020-12-31T19:00:10Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-12-31T19:00:10Z","title":"The Pile: An 800GB Dataset of Diverse Text for Language Modeling","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2101.00027","snapshot_observed_at":"2026-08-05T20:00:05.170020Z","title":"The pile: An 800gb dataset of diverse text for language modeling","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":1999,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.170020Z"},"links":{"cited_paper":"/paper/2101.00027","citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:c879dd3b66d6b8fc5c74db7b128557a6066abb73a0358aa1a03ed5dc4cf18626","observation_id":"889ad05c-ccf5-418a-a16e-b1a5d9de7ad1","resolution":{"observed_at":"2026-08-05T20:00:05.170020Z","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":"2026-08-05T20:00:05.165014Z","title":"Alexander IJ Forrester, András Sóbester, and Andy J Keane","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":2007,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.165014Z"},"links":{"citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:78a408db3d87b6bb3c2343a5355bb91b07d251f2e8c7b040c53bc2882d15be89","observation_id":"60f797a8-8e7b-4116-83f5-e9485a4aac11","resolution":{"observed_at":"2026-08-05T20:00:05.165014Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.09288","last_updated":"2023-07-19T17:08:59Z","snapshot_observed_at":"2026-08-07T12:56:43.323460Z","submitted_at":"2023-07-18T14:31:57Z","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.09288","snapshot_observed_at":"2026-08-05T20:00:05.203962Z","title":"Llama 2: Open foundation and fine-tuned chat models.arXiv preprint arXiv:2307.09288,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":2013,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.203962Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:3554f49c87f79c0493a0dfbc49a0ca7c4a31c52a130ad02f7b8f53ef0aec72f9","observation_id":"27041d16-5151-433a-8803-604874533759","resolution":{"observed_at":"2026-08-05T20:00:05.203962Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-08-13T17:20:44.002518Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-08-05T20:00:05.175666Z","title":"The llama 3 herd of models.arXiv preprint arXiv:2407.21783,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":2014,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.175666Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:a8acfbc07bea69e7f93fabec37cab51d12ea046281703acd8e568faacdab0767","observation_id":"ff3491db-eec4-4eea-805e-323a6168b148","resolution":{"observed_at":"2026-08-05T20:00:05.175666Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2001.08361","last_updated":"2020-01-23T03:59:20Z","snapshot_observed_at":"2026-08-13T17:41:53.092611Z","submitted_at":"2020-01-23T03:59:20Z","title":"Scaling Laws for Neural Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2001.08361","snapshot_observed_at":"2026-08-05T20:00:05.181143Z","title":"Scaling laws for neural language models.arXiv preprint arXiv:2001.08361,","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.181143Z"},"links":{"cited_paper":"/paper/2001.08361","citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:caf755811d903a0313d989284d203b21b7c5eb9c4467e43a38d2b6930e09c740","observation_id":"596e1c54-d351-4367-937c-2c1c2e662d9c","resolution":{"observed_at":"2026-08-05T20:00:05.181143Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.01492","last_updated":"2025-01-23T17:35:43Z","snapshot_observed_at":"2026-08-18T18:58:59.065205Z","submitted_at":"2024-07-01T17:31:03Z","title":"RegMix: Data Mixture as Regression for Language Model Pre-training","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.01492","snapshot_observed_at":"2026-08-05T20:00:05.192800Z","title":"Regmix: Data mixture as regression for language model pre-training","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.192800Z"},"links":{"cited_paper":"/paper/2407.01492","citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:8eea553e1188d9e7ecc2267d0b994617938d13368b71bee495583697c2f36c64","observation_id":"d73c048d-d6c4-4f09-82bf-b70b01bc3636","resolution":{"observed_at":"2026-08-05T20:00:05.192800Z","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":"2026-08-05T20:00:05.466689Z","title":null,"venue":null,"work_id":"a014cb31-846e-42b3-b3bd-e83f43be93c8","year":2088},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.162284Z"},"links":{"citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:2d9ed169fc7b09fb43d2b0f7cc2a1eab353a2845366aac6e099e6303d32fe2f4","observation_id":"f7be3829-ade4-4610-9608-e568875b0d0a","resolution":{"observed_at":"2026-08-05T20:00:05.469596Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2002.09996","last_updated":"2020-11-02T21:21:40Z","snapshot_observed_at":"2026-08-11T00:25:20.947790Z","submitted_at":"2020-02-23T22:06:26Z","title":"Practical Bayesian Optimization of Objectives with Conditioning Variables","version":2},"cited_work":{"arxiv_id":"2002.09996","doi":null,"metadata_source":"pith","pith_arxiv_id":"2002.09996","snapshot_observed_at":"2026-08-05T20:00:05.262358Z","title":"Practical Bayesian Optimization of Objectives with Conditioning Variables","venue":"stat.ML","work_id":"f55df53d-52a1-4714-a444-3af2f45d1cc1","year":2020},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.199429Z"},"links":{"cited_paper":"/paper/2002.09996","citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:6b0356c90bca07539d61c1198eaf5d7a0a1985dfddffa4700ae01508efe75a26","observation_id":"01a013cf-8eba-4c67-abb1-2282c39750ce","resolution":{"observed_at":"2026-08-05T20:00:05.267547Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.20541","last_updated":"2024-05-30T23:50:20Z","snapshot_observed_at":"2026-08-16T13:47:32.772922Z","submitted_at":"2024-05-30T23:50:20Z","title":"Perplexed by Perplexity: Perplexity-Based Data Pruning With Small Reference Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.20541","snapshot_observed_at":"2026-08-05T20:00:05.150955Z","title":"Perplexed by perplexity: Perplexity-based data pruning with small reference models.arXiv preprint arXiv:2405.20541,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.150955Z"},"links":{"cited_paper":"/paper/2405.20541","citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:70b24f6e51b1ad5a889b29a91eacf4b4fef39391f2d9b64bb17fd0f891c25368","observation_id":"0837b721-ed95-446b-88a2-f733f390296a","resolution":{"observed_at":"2026-08-05T20:00:05.150955Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.08905","last_updated":"2024-12-12T03:37:41Z","snapshot_observed_at":"2026-08-14T03:45:52.225630Z","submitted_at":"2024-12-12T03:37:41Z","title":"Phi-4 Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.08905","snapshot_observed_at":"2026-08-05T20:00:05.145239Z","title":"Phi-4 technical report.arXiv preprint arXiv:2412.08905,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.145239Z"},"links":{"cited_paper":"/paper/2412.08905","citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:ccb14f44dfb734d88b5888a106f1738332a991cdb62cad1f58f674aed90bd3cd","observation_id":"2e93fe54-a6ec-4b7f-8d35-654dd892368d","resolution":{"observed_at":"2026-08-05T20:00:05.145239Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.09540","last_updated":"2023-03-22T17:22:35Z","snapshot_observed_at":"2026-08-06T15:07:40.203199Z","submitted_at":"2023-03-16T17:53:24Z","title":"SemDeDup: Data-efficient learning at web-scale through semantic deduplication","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.09540","snapshot_observed_at":"2026-08-05T20:00:05.141967Z","title":"Amro Abbas, Kushal Tirumala, Dániel Simig, Surya Ganguli, and Ari S Morcos","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-05T20:00:05.141967Z"},"links":{"cited_paper":"/paper/2303.09540","citing_paper":"/paper/2508.11551"},"observation_digest":"sha256:eb9164c345999d71b81f966e1a82812aceffdbc453ddb5f85257a514e2e6c3a3","observation_id":"22f8f90b-1709-44f4-ae2e-c6d3cb420cde","resolution":{"observed_at":"2026-08-05T20:00:05.141967Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2508.11551","last_updated":"2025-08-18T06:38:38Z","latest_version":2,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-13T22:41:43.529278Z","submitted_at":"2025-08-15T15:53:09Z","title":"ADMIRE-BayesOpt: Accelerated Data MIxture RE-weighting for Language Models with Bayesian Optimization"},"reference_resolution":{"displayed":28,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":24,"verified_exact":1,"verified_fuzzy":3},"total_outbound_references":28},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 1 inbound Pith citation observation for arXiv:2508.11551."}