{"as_of":"2026-08-18T04:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:615e8191a7aaf1bcfd4ff727251fc7043454a826cd20ae92c183040939b4298c","coverage":[{"denominator":12,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":12,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-27T05:08:00.711576Z","state":"measured"},{"denominator":12,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":12,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2606.13280/citation-record","integrity":"/paper/2606.13280/integrity","json":"/paper/2606.13280/citation-record.json","paper":"/paper/2606.13280"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T05:08:00.711576Z","title":"[2]Anderson, T","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.13280","last_updated":"2026-06-11T12:34:47Z","snapshot_observed_at":"2026-08-16T19:59:58.219056Z","submitted_at":"2026-06-11T12:34:47Z","title":"Generalization Bounds for Transformer-Based Next-Token Prediction in a Language Model","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-06-27T05:08:00.711576Z"},"links":{"citing_paper":"/paper/2606.13280"},"observation_digest":"sha256:761cd593ccc32f9493ab813aa44a857dd464f440ad9932f9a1f26b24188b0456","observation_id":"c7e90caf-61e0-4e2e-821b-938a02463cb5","resolution":{"observed_at":"2026-06-27T05:08:00.711576Z","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":"2026-06-27T05:08:00.711576Z","title":"In2012 IEEE 53rd Annual Symposium on Foundations of Computer Science(2012), pp","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2606.13280","last_updated":"2026-06-11T12:34:47Z","snapshot_observed_at":"2026-08-16T19:59:58.219056Z","submitted_at":"2026-06-11T12:34:47Z","title":"Generalization Bounds for Transformer-Based Next-Token Prediction in a Language Model","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-27T05:08:00.711576Z"},"links":{"citing_paper":"/paper/2606.13280"},"observation_digest":"sha256:77bdb5f40b0c5ef021991a303ad02d9f49ea11fe94788944d1ae29708ecfef94","observation_id":"b62d4437-18d7-4ab2-bc63-08029b1fb99d","resolution":{"observed_at":"2026-06-27T05:08:00.711576Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2601.15014","last_updated":"2026-05-19T14:33:39Z","snapshot_observed_at":"2026-07-06T22:42:26.083572Z","submitted_at":"2026-01-21T14:13:38Z","title":"Efficient and Minimax Optimal In-context Nonparametric Regression with Transformers","version":2},"cited_work":{"arxiv_id":"2601.15014","doi":null,"metadata_source":"pith","pith_arxiv_id":"2601.15014","snapshot_observed_at":"2026-07-03T16:38:40.629999Z","title":"Efficient and Minimax Optimal In-context Nonparametric Regression with Transformers","venue":"stat.ML","work_id":"4f7d9c98-c878-4743-b00b-913074829a9d","year":2026},"citing_paper":{"arxiv_id":"2606.13280","last_updated":"2026-06-11T12:34:47Z","snapshot_observed_at":"2026-08-16T19:59:58.219056Z","submitted_at":"2026-06-11T12:34:47Z","title":"Generalization Bounds for Transformer-Based Next-Token Prediction in a Language Model","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-27T05:08:00.711576Z"},"links":{"cited_paper":"/paper/2601.15014","citing_paper":"/paper/2606.13280"},"observation_digest":"sha256:5cea3da74039b7be0845dda2e6e4d66a0c2570e713ee2941a69407b413e98d73","observation_id":"4e106056-835a-4c17-8d75-ecca0fb972cb","resolution":{"observed_at":"2026-07-03T16:38:40.632510Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2604.24878","last_updated":"2026-04-27T18:04:11Z","snapshot_observed_at":"2026-08-14T06:11:21.247516Z","submitted_at":"2026-04-27T18:04:11Z","title":"Transformer Approximations from ReLUs","version":1},"cited_work":{"arxiv_id":"2604.24878","doi":null,"metadata_source":"pith","pith_arxiv_id":"2604.24878","snapshot_observed_at":"2026-07-03T16:38:40.639612Z","title":"Transformer Approximations from ReLUs","venue":"cs.LG","work_id":"fd8714cc-6597-4295-9495-34bdc62b970e","year":2026},"citing_paper":{"arxiv_id":"2606.13280","last_updated":"2026-06-11T12:34:47Z","snapshot_observed_at":"2026-08-16T19:59:58.219056Z","submitted_at":"2026-06-11T12:34:47Z","title":"Generalization Bounds for Transformer-Based Next-Token Prediction in a Language Model","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-27T05:08:00.711576Z"},"links":{"cited_paper":"/paper/2604.24878","citing_paper":"/paper/2606.13280"},"observation_digest":"sha256:dc622585f1be9b6f8106b69302f182b95076b40c471ce65e4308a92055a94d15","observation_id":"f1d4879a-a851-498b-a8aa-0c87d41b0441","resolution":{"observed_at":"2026-07-03T16:38:40.640997Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-06-27T05:08:00.711576Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.13280","last_updated":"2026-06-11T12:34:47Z","snapshot_observed_at":"2026-08-16T19:59:58.219056Z","submitted_at":"2026-06-11T12:34:47Z","title":"Generalization Bounds for Transformer-Based Next-Token Prediction in a Language Model","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-27T05:08:00.711576Z"},"links":{"citing_paper":"/paper/2606.13280"},"observation_digest":"sha256:b2a65aa7e7f1c1e2c298456e6088096257d330acd6008fa6f7aab4bc1a5bff94","observation_id":"ba9df328-6b4f-4b4d-b013-faa3b0d79172","resolution":{"observed_at":"2026-06-27T05:08:00.711576Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2602.20555","last_updated":"2026-07-28T04:45:18Z","snapshot_observed_at":"2026-08-16T10:54:23.387763Z","submitted_at":"2026-02-24T05:14:01Z","title":"Standard Transformers Achieve the Minimax Rate in Nonparametric Regression with $C^{s,\\lambda}$ Targets","version":2},"cited_work":{"arxiv_id":"2602.20555","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2602.20555","snapshot_observed_at":"2026-07-29T02:24:15.834827Z","title":"[46]Lai, Y., and Sun, D.Standard transformers achieve the minimax rate in nonparametric regression withC s,λ targets.arXiv e-prints(2026), arXiv:2602.20555","venue":null,"work_id":"88261e55-9bbf-4309-955e-0d77a7905ca9","year":2025},"citing_paper":{"arxiv_id":"2606.13280","last_updated":"2026-06-11T12:34:47Z","snapshot_observed_at":"2026-08-16T19:59:58.219056Z","submitted_at":"2026-06-11T12:34:47Z","title":"Generalization Bounds for Transformer-Based Next-Token Prediction in a Language Model","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-27T05:08:00.711576Z"},"links":{"cited_paper":"/paper/2602.20555","citing_paper":"/paper/2606.13280"},"observation_digest":"sha256:6a7bc79e1946fb4fc7a94b16e00161a13889a4686d53107e9ca97cbf8383aa7c","observation_id":"68c41094-657e-4173-97e4-2c0684c89151","resolution":{"observed_at":"2026-07-29T02:24:15.834827Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-06-27T05:08:00.711576Z","title":"T.Optimal convergence rates of deep neural networks in a classification setting.Electronic Journal of Statistics 17, 2 (2023), 3613 –","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.13280","last_updated":"2026-06-11T12:34:47Z","snapshot_observed_at":"2026-08-16T19:59:58.219056Z","submitted_at":"2026-06-11T12:34:47Z","title":"Generalization Bounds for Transformer-Based Next-Token Prediction in a Language Model","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-27T05:08:00.711576Z"},"links":{"citing_paper":"/paper/2606.13280"},"observation_digest":"sha256:3275b43c6c477b4f54c71e529b49e680df898cb67ff2d8fbb8a434aa1ed3aa6c","observation_id":"64386fe3-6f1b-4140-be9e-ca41db70a115","resolution":{"observed_at":"2026-06-27T05:08:00.711576Z","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":"2026-06-27T05:08:00.711576Z","title":"InPro- ceedings of the 24th international conference on Machine learning(2007), pp","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2606.13280","last_updated":"2026-06-11T12:34:47Z","snapshot_observed_at":"2026-08-16T19:59:58.219056Z","submitted_at":"2026-06-11T12:34:47Z","title":"Generalization Bounds for Transformer-Based Next-Token Prediction in a Language Model","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-27T05:08:00.711576Z"},"links":{"citing_paper":"/paper/2606.13280"},"observation_digest":"sha256:389778280ed82e684fb0a7c7c408eaf74d489c74a41e84657756ce535855a0f9","observation_id":"4ebdc87d-7ea4-4d16-9d6c-444e9340a4d6","resolution":{"observed_at":"2026-06-27T05:08:00.711576Z","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":"2026-06-27T05:08:00.711576Z","title":"[60]Sanford, C., Hsu, D., and Telgarsky, M.Representational strengths and limitations of trans- formers","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.13280","last_updated":"2026-06-11T12:34:47Z","snapshot_observed_at":"2026-08-16T19:59:58.219056Z","submitted_at":"2026-06-11T12:34:47Z","title":"Generalization Bounds for Transformer-Based Next-Token Prediction in a Language Model","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-27T05:08:00.711576Z"},"links":{"citing_paper":"/paper/2606.13280"},"observation_digest":"sha256:06eb4cc58fdc6c78b9c5994346b88d6c8476545fafc5553c8b45361839cb769e","observation_id":"a032cd47-e354-49a2-ace3-488da6d12ce6","resolution":{"observed_at":"2026-06-27T05:08:00.711576Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.03205","last_updated":"2026-05-17T05:57:50Z","snapshot_observed_at":"2026-08-15T00:54:03.489652Z","submitted_at":"2025-05-06T05:41:46Z","title":"Transformers for Learning on Noisy and Task-Level Manifolds: Approximation and Generalization Insights","version":3},"cited_work":{"arxiv_id":"2505.03205","doi":null,"metadata_source":"pith","pith_arxiv_id":"2505.03205","snapshot_observed_at":"2026-07-03T16:38:40.639778Z","title":"Transformers for Learning on Noisy and Task-Level Manifolds: Approximation and Generalization Insights","venue":"cs.LG","work_id":"7fce5064-ff22-4c96-a066-055ed6194bd4","year":2025},"citing_paper":{"arxiv_id":"2606.13280","last_updated":"2026-06-11T12:34:47Z","snapshot_observed_at":"2026-08-16T19:59:58.219056Z","submitted_at":"2026-06-11T12:34:47Z","title":"Generalization Bounds for Transformer-Based Next-Token Prediction in a Language Model","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-27T05:08:00.711576Z"},"links":{"cited_paper":"/paper/2505.03205","citing_paper":"/paper/2606.13280"},"observation_digest":"sha256:ea7860e575699ec732660affa4fcb04c8636efabb36ea0ebb7b37336a984a9b3","observation_id":"eb2ef265-4f51-4b7a-b474-2096563d0769","resolution":{"observed_at":"2026-07-03T16:38:40.641256Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2510.10981","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-03T16:38:40.636590Z","title":"In-context learning is provably bayesian inference: a generalization theory for meta-learning","venue":null,"work_id":"220cfa18-fc85-4d03-89bf-fea204874158","year":2025},"citing_paper":{"arxiv_id":"2606.13280","last_updated":"2026-06-11T12:34:47Z","snapshot_observed_at":"2026-08-16T19:59:58.219056Z","submitted_at":"2026-06-11T12:34:47Z","title":"Generalization Bounds for Transformer-Based Next-Token Prediction in a Language Model","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-27T05:08:00.711576Z"},"links":{"citing_paper":"/paper/2606.13280"},"observation_digest":"sha256:7aa43f35069d4e56ccc52245b2fb39e1475eb9bdd01ce6b9971b2f38aed7f287","observation_id":"fca37527-c335-4aa9-b868-83d92a1fd0de","resolution":{"observed_at":"2026-07-03T16:38:40.638322Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02724","last_updated":"2025-02-02T15:57:01Z","snapshot_observed_at":"2026-08-16T13:12:52.000653Z","submitted_at":"2024-10-03T17:45:31Z","title":"Large Language Models as Markov Chains","version":2},"cited_work":{"arxiv_id":"2410.02724","doi":"10.48550/arxiv.2410.02724","metadata_source":"pith","pith_arxiv_id":"2410.02724","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Large language models as markov chains","venue":"stat.ML","work_id":"f8875763-7cfb-4c8f-9c30-9026fc9667a3","year":2024},"citing_paper":{"arxiv_id":"2606.13280","last_updated":"2026-06-11T12:34:47Z","snapshot_observed_at":"2026-08-16T19:59:58.219056Z","submitted_at":"2026-06-11T12:34:47Z","title":"Generalization Bounds for Transformer-Based Next-Token Prediction in a Language Model","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-06-27T05:08:00.711576Z"},"links":{"cited_paper":"/paper/2410.02724","citing_paper":"/paper/2606.13280"},"observation_digest":"sha256:0996dce1d16506a2e238a54b4460a9484ca31818be3e8a4741ed7092c8edbddb","observation_id":"52811563-5949-4ce2-8cfa-793b11350af1","resolution":{"observed_at":"2026-07-03T16:38:40.644732Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2606.13280","last_updated":"2026-06-11T12:34:47Z","latest_version":1,"primary_category":"math.ST","snapshot_observed_at":"2026-08-16T19:59:58.219056Z","submitted_at":"2026-06-11T12:34:47Z","title":"Generalization Bounds for Transformer-Based Next-Token Prediction in a Language Model"},"reference_resolution":{"displayed":12,"state_counts":{"malformed_identifier":0,"metadata_mismatch":3,"parse_uncertain":0,"unresolved":6,"verified_exact":3,"verified_fuzzy":0},"total_outbound_references":12},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2606.13280."}