{"as_of":"2026-08-09T21:42:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:69eaa7e3446cbb6d093fb77cbdf6431e04e1da7cfce62fe5ef9ae36b0e64edd7","coverage":[{"denominator":18,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":18,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-04T19:41:53.668529Z","state":"measured"},{"denominator":19,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":19,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+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":"2026-07-11T17:54:49.531461Z","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":[{"citation":{"cited_paper":{"arxiv_id":"2606.11211","last_updated":"2026-04-24T04:46:16Z","snapshot_observed_at":"2026-08-06T06:29:18.404870Z","submitted_at":"2026-04-24T04:46:16Z","title":"Calibration Drift Under Reasoning: How Chain-of-Thought Budgets Induce Overconfidence in Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2606.11211","snapshot_observed_at":"2026-07-11T17:54:49.531461Z","title":"arXiv preprint arXiv:2606.11211 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.04528","last_updated":"2026-07-05T22:22:39Z","snapshot_observed_at":"2026-08-06T09:31:33.885518Z","submitted_at":"2026-07-05T22:22:39Z","title":"Measuring Harness-Induced Belief Divergence in Multi-Step LLM Agents","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-07-11T17:54:49.531461Z"},"links":{"cited_paper":"/paper/2606.11211","citing_paper":"/paper/2607.04528"},"observation_digest":"sha256:e957fcabda5a5e1bd78f5ac521002ebd4ccff7abef177e07318d5f118ab6d55b","observation_id":"d8879794-a8c6-45f1-8b95-c0b2815085c5","resolution":{"observed_at":"2026-07-11T17:54:49.531461Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2606.11211/citation-record","integrity":"/paper/2606.11211/integrity","json":"/paper/2606.11211/citation-record.json","paper":"/paper/2606.11211"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-04T21:20:09.134271Z","title":"S., and Robbins, H","venue":null,"work_id":"46c72e07-c49e-412a-853c-dbeabd1295a0","year":1961},"citing_paper":{"arxiv_id":"2606.11211","last_updated":"2026-04-24T04:46:16Z","snapshot_observed_at":"2026-08-06T06:29:18.404870Z","submitted_at":"2026-04-24T04:46:16Z","title":"Calibration Drift Under Reasoning: How Chain-of-Thought Budgets Induce Overconfidence in Large Language Models","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-07-04T19:41:53.668529Z"},"links":{"citing_paper":"/paper/2606.11211"},"observation_digest":"sha256:94e2ede65904a7d5164c70b7ccd0a6a061ed3c2adc0aa1229670663a73adce56","observation_id":"f87eb00c-b55e-4074-aff3-ed7288f41cb4","resolution":{"observed_at":"2026-07-04T21:20:09.135397Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-04T21:20:09.130826Z","title":null,"venue":null,"work_id":"dd4e6291-9a93-40a9-a801-1194aab028d8","year":1983},"citing_paper":{"arxiv_id":"2606.11211","last_updated":"2026-04-24T04:46:16Z","snapshot_observed_at":"2026-08-06T06:29:18.404870Z","submitted_at":"2026-04-24T04:46:16Z","title":"Calibration Drift Under Reasoning: How Chain-of-Thought Budgets Induce Overconfidence in Large Language Models","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-07-04T19:41:53.668529Z"},"links":{"citing_paper":"/paper/2606.11211"},"observation_digest":"sha256:49cbf71a279b818dc59a9c20d9aa627448ad86196a1c51ffc88fa0ff9ce53d23","observation_id":"d6739967-4412-4e2a-9d37-28c8c6d44b2f","resolution":{"observed_at":"2026-07-04T21:20:09.131904Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-04T21:20:09.147279Z","title":"and Durrett, G","venue":null,"work_id":"a1774e95-4963-4bf9-bf78-a28b3f78a784","year":2020},"citing_paper":{"arxiv_id":"2606.11211","last_updated":"2026-04-24T04:46:16Z","snapshot_observed_at":"2026-08-06T06:29:18.404870Z","submitted_at":"2026-04-24T04:46:16Z","title":"Calibration Drift Under Reasoning: How Chain-of-Thought Budgets Induce Overconfidence in Large Language Models","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-07-04T19:41:53.668529Z"},"links":{"citing_paper":"/paper/2606.11211"},"observation_digest":"sha256:aa01ec5f83ef34d00a9a22ffbb93e185ce5eb4bab2daec599d29550655a60e27","observation_id":"2cde472d-7047-441a-a028-5554742abd39","resolution":{"observed_at":"2026-07-04T21:20:09.148597Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1603.08983","last_updated":"2017-02-21T16:21:21Z","snapshot_observed_at":"2026-08-04T14:24:45.814840Z","submitted_at":"2016-03-29T22:09:00Z","title":"Adaptive Computation Time for Recurrent Neural Networks","version":6},"cited_work":{"arxiv_id":"1603.08983","doi":"10.48550/arxiv.1603.08983","metadata_source":"pith","pith_arxiv_id":"1603.08983","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Adaptive Computation Time for Recurrent Neural Networks","venue":"cs.NE","work_id":"75565443-173e-479c-b0e7-d2464e7630be","year":2016},"citing_paper":{"arxiv_id":"2606.11211","last_updated":"2026-04-24T04:46:16Z","snapshot_observed_at":"2026-08-06T06:29:18.404870Z","submitted_at":"2026-04-24T04:46:16Z","title":"Calibration Drift Under Reasoning: How Chain-of-Thought Budgets Induce Overconfidence in Large Language Models","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-07-04T19:41:53.668529Z"},"links":{"cited_paper":"/paper/1603.08983","citing_paper":"/paper/2606.11211"},"observation_digest":"sha256:9af811ee05648978f68f3d09039ff4f2f01b3720c0e9379ee5604695f61b7a8d","observation_id":"9117c447-94d2-4404-8c11-30177d24e448","resolution":{"observed_at":"2026-07-04T19:50:10.032546Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-04T21:20:09.129050Z","title":null,"venue":null,"work_id":"2c79bbf8-cd67-4bfa-b8a2-c2aba3ca2df7","year":2017},"citing_paper":{"arxiv_id":"2606.11211","last_updated":"2026-04-24T04:46:16Z","snapshot_observed_at":"2026-08-06T06:29:18.404870Z","submitted_at":"2026-04-24T04:46:16Z","title":"Calibration Drift Under Reasoning: How Chain-of-Thought Budgets Induce Overconfidence in Large Language Models","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-07-04T19:41:53.668529Z"},"links":{"citing_paper":"/paper/2606.11211"},"observation_digest":"sha256:0d95b033718f900d59d1ff46550a12b4a61a659263ffab82d0cb73499752c05b","observation_id":"58863f1b-a17d-4ea0-aad8-f30999955fcb","resolution":{"observed_at":"2026-07-04T21:20:09.130285Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-04T21:20:09.145417Z","title":null,"venue":null,"work_id":"e269442d-c231-4be0-aa75-d497873b0dc7","year":2001},"citing_paper":{"arxiv_id":"2606.11211","last_updated":"2026-04-24T04:46:16Z","snapshot_observed_at":"2026-08-06T06:29:18.404870Z","submitted_at":"2026-04-24T04:46:16Z","title":"Calibration Drift Under Reasoning: How Chain-of-Thought Budgets Induce Overconfidence in Large Language Models","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-07-04T19:41:53.668529Z"},"links":{"citing_paper":"/paper/2606.11211"},"observation_digest":"sha256:36306e3bc15b28aebf2407ef603b2855902055f650383d515227b8024ebc0d8e","observation_id":"f5f11320-fba6-4092-8c37-1ae056d00f20","resolution":{"observed_at":"2026-07-04T21:20:09.146722Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2207.05221","last_updated":"2022-11-21T16:38:35Z","snapshot_observed_at":"2026-08-06T08:34:11.887259Z","submitted_at":"2022-07-11T22:59:39Z","title":"Language Models (Mostly) Know What They Know","version":4},"cited_work":{"arxiv_id":"2207.05221","doi":"10.1145/3618260.3649777","metadata_source":"pith","pith_arxiv_id":"2207.05221","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Models (Mostly) Know What They Know","venue":"cs.CL","work_id":"8ca58a10-da41-4f70-baae-7e449512e345","year":2022},"citing_paper":{"arxiv_id":"2606.11211","last_updated":"2026-04-24T04:46:16Z","snapshot_observed_at":"2026-08-06T06:29:18.404870Z","submitted_at":"2026-04-24T04:46:16Z","title":"Calibration Drift Under Reasoning: How Chain-of-Thought Budgets Induce Overconfidence in Large Language Models","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-07-04T19:41:53.668529Z"},"links":{"cited_paper":"/paper/2207.05221","citing_paper":"/paper/2606.11211"},"observation_digest":"sha256:e6d7bc2e0d0bb8a5a3a7dba5e04fe14460dbd67c8c541763b5afa1eef295a5ff","observation_id":"37b82850-abff-4f42-9480-14f87e70ef49","resolution":{"observed_at":"2026-07-04T19:50:10.026754Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-21T07:53:13.382372+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-21T07:53:13.382372+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-07-04T21:20:09.149158Z","title":"S., Reid, M., Matsuo, Y., and Iwasawa, Y","venue":null,"work_id":"806a4bae-6bd1-4948-a4fd-42984db0fde2","year":2022},"citing_paper":{"arxiv_id":"2606.11211","last_updated":"2026-04-24T04:46:16Z","snapshot_observed_at":"2026-08-06T06:29:18.404870Z","submitted_at":"2026-04-24T04:46:16Z","title":"Calibration Drift Under Reasoning: How Chain-of-Thought Budgets Induce Overconfidence in Large Language Models","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-07-04T19:41:53.668529Z"},"links":{"citing_paper":"/paper/2606.11211"},"observation_digest":"sha256:d0886cf1f5aac3b1790150d744e9f4dbe74a4039ab80fd2798884f824257d164","observation_id":"ed7b77ce-7994-4b10-bdae-54e15a80edb4","resolution":{"observed_at":"2026-07-04T21:20:09.153386Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.20050","last_updated":"2023-05-31T17:24:00Z","snapshot_observed_at":"2026-08-05T13:11:04.104454Z","submitted_at":"2023-05-31T17:24:00Z","title":"Let's Verify Step by Step","version":1},"cited_work":{"arxiv_id":"2305.20050","doi":"10.1007/bf00262952","metadata_source":"pith","pith_arxiv_id":"2305.20050","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Let's Verify Step by Step","venue":"cs.LG","work_id":"6d05b790-04c5-4fd2-91b2-ba1dfdd5770f","year":2023},"citing_paper":{"arxiv_id":"2606.11211","last_updated":"2026-04-24T04:46:16Z","snapshot_observed_at":"2026-08-06T06:29:18.404870Z","submitted_at":"2026-04-24T04:46:16Z","title":"Calibration Drift Under Reasoning: How Chain-of-Thought Budgets Induce Overconfidence in Large Language Models","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-07-04T19:41:53.668529Z"},"links":{"cited_paper":"/paper/2305.20050","citing_paper":"/paper/2606.11211"},"observation_digest":"sha256:19e4077a4e88b094f83b14c265f92cf21a573be9f2db7c50640f2c9f90b07b28","observation_id":"8313b1c8-b01b-4d4f-84be-d8627593d63a","resolution":{"observed_at":"2026-07-04T19:50:10.016854Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-04T21:20:09.139366Z","title":null,"venue":null,"work_id":"f011de60-b76f-4cfe-9d9d-ef34de514aa5","year":1977},"citing_paper":{"arxiv_id":"2606.11211","last_updated":"2026-04-24T04:46:16Z","snapshot_observed_at":"2026-08-06T06:29:18.404870Z","submitted_at":"2026-04-24T04:46:16Z","title":"Calibration Drift Under Reasoning: How Chain-of-Thought Budgets Induce Overconfidence in Large Language Models","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-07-04T19:41:53.668529Z"},"links":{"citing_paper":"/paper/2606.11211"},"observation_digest":"sha256:87df7d9037efd3ad4566f433030fde0e4421ab5184a4e5ab291eca4dc6bcc521","observation_id":"38b7dd66-97df-498f-ae7c-2816b5a5c5d9","resolution":{"observed_at":"2026-07-04T21:20:09.140748Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-04T21:20:09.141528Z","title":null,"venue":null,"work_id":"5f4227d0-c1ed-46ab-8dd6-c6e4d5619d89","year":2022},"citing_paper":{"arxiv_id":"2606.11211","last_updated":"2026-04-24T04:46:16Z","snapshot_observed_at":"2026-08-06T06:29:18.404870Z","submitted_at":"2026-04-24T04:46:16Z","title":"Calibration Drift Under Reasoning: How Chain-of-Thought Budgets Induce Overconfidence in Large Language Models","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-07-04T19:41:53.668529Z"},"links":{"citing_paper":"/paper/2606.11211"},"observation_digest":"sha256:065cac12da0acaf276e2a29c9c22ef71eff133ff8499db79929dd83d04b45763","observation_id":"0fe2b956-6397-4cd3-b797-8236d84f9571","resolution":{"observed_at":"2026-07-04T21:20:09.142893Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.03314","last_updated":"2024-08-06T17:35:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-08-06T17:35:05Z","title":"Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters","version":1},"cited_work":{"arxiv_id":"2408.03314","doi":"10.18653/v1/2025.acl-long.1486","metadata_source":"pith","pith_arxiv_id":"2408.03314","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters","venue":"cs.LG","work_id":"a8d50b24-bdf5-46ed-bc4f-2927dfd81f1d","year":2024},"citing_paper":{"arxiv_id":"2606.11211","last_updated":"2026-04-24T04:46:16Z","snapshot_observed_at":"2026-08-06T06:29:18.404870Z","submitted_at":"2026-04-24T04:46:16Z","title":"Calibration Drift Under Reasoning: How Chain-of-Thought Budgets Induce Overconfidence in Large Language Models","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-07-04T19:41:53.668529Z"},"links":{"cited_paper":"/paper/2408.03314","citing_paper":"/paper/2606.11211"},"observation_digest":"sha256:194baa48b5032696a392d647c15815ebcfe6a2eb804850aa77b04e0f0d180713","observation_id":"2ed1e3c5-4b8f-4763-bf78-62e6dae5475e","resolution":{"observed_at":"2026-07-04T19:50:10.019780Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.04388","last_updated":"2023-12-09T21:25:02Z","snapshot_observed_at":"2026-08-02T07:12:38.105035Z","submitted_at":"2023-05-07T22:44:25Z","title":"Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting","version":2},"cited_work":{"arxiv_id":"2305.04388","doi":"10.1109/cdics61497.2023.00014","metadata_source":"pith","pith_arxiv_id":"2305.04388","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting","venue":"cs.CL","work_id":"6ed38946-7275-41a4-91b9-b9f7fa043250","year":2023},"citing_paper":{"arxiv_id":"2606.11211","last_updated":"2026-04-24T04:46:16Z","snapshot_observed_at":"2026-08-06T06:29:18.404870Z","submitted_at":"2026-04-24T04:46:16Z","title":"Calibration Drift Under Reasoning: How Chain-of-Thought Budgets Induce Overconfidence in Large Language Models","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-07-04T19:41:53.668529Z"},"links":{"cited_paper":"/paper/2305.04388","citing_paper":"/paper/2606.11211"},"observation_digest":"sha256:bbb4b97f64e3cf3f3db1a0078bbd37e533d2be8a41956ade454d519c1dde6f59","observation_id":"3e18dc46-94a8-40de-818b-c45bd05f6cca","resolution":{"observed_at":"2026-07-04T19:50:10.029851Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-04T21:20:09.143494Z","title":null,"venue":null,"work_id":"6bb0f910-8557-46eb-a7f9-5e0be460e8d8","year":1947},"citing_paper":{"arxiv_id":"2606.11211","last_updated":"2026-04-24T04:46:16Z","snapshot_observed_at":"2026-08-06T06:29:18.404870Z","submitted_at":"2026-04-24T04:46:16Z","title":"Calibration Drift Under Reasoning: How Chain-of-Thought Budgets Induce Overconfidence in Large Language Models","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-07-04T19:41:53.668529Z"},"links":{"citing_paper":"/paper/2606.11211"},"observation_digest":"sha256:d0f0065514c3ddf4515495ff6fefda60f4f138583cbfd761ecd21759453dbcae","observation_id":"ed5194e4-7b5e-4a83-a55d-206447994df0","resolution":{"observed_at":"2026-07-04T21:20:09.144853Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.11171","last_updated":"2023-03-07T17:57:37Z","snapshot_observed_at":"2026-07-06T12:50:22.773056Z","submitted_at":"2022-03-21T17:48:52Z","title":"Self-Consistency Improves Chain of Thought Reasoning in Language Models","version":4},"cited_work":{"arxiv_id":"2203.11171","doi":"10.1101/2025.04.03.646459","metadata_source":"pith","pith_arxiv_id":"2203.11171","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Self-Consistency Improves Chain of Thought Reasoning in Language Models","venue":"cs.CL","work_id":"8c6d5a6b-b5cc-4105-9c84-9c34bb9375bb","year":2022},"citing_paper":{"arxiv_id":"2606.11211","last_updated":"2026-04-24T04:46:16Z","snapshot_observed_at":"2026-08-06T06:29:18.404870Z","submitted_at":"2026-04-24T04:46:16Z","title":"Calibration Drift Under Reasoning: How Chain-of-Thought Budgets Induce Overconfidence in Large Language Models","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-07-04T19:41:53.668529Z"},"links":{"cited_paper":"/paper/2203.11171","citing_paper":"/paper/2606.11211"},"observation_digest":"sha256:1e9db7c28d95e5e3104585540bb7ebf07ea5c6cf3ae0c88b3800fcd15f581834","observation_id":"b5230aa5-0d4a-4a49-98b8-714690069b05","resolution":{"observed_at":"2026-07-04T19:50:10.013847Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-05-21T18:52:42.88633+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-21T18:52:42.88633+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-07-04T21:20:09.134915Z","title":null,"venue":null,"work_id":"4c3db79e-8850-4d17-9c63-72b12adc3f6f","year":2022},"citing_paper":{"arxiv_id":"2606.11211","last_updated":"2026-04-24T04:46:16Z","snapshot_observed_at":"2026-08-06T06:29:18.404870Z","submitted_at":"2026-04-24T04:46:16Z","title":"Calibration Drift Under Reasoning: How Chain-of-Thought Budgets Induce Overconfidence in Large Language Models","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-07-04T19:41:53.668529Z"},"links":{"citing_paper":"/paper/2606.11211"},"observation_digest":"sha256:0b1b47b3487fa601352870cd9c5974905dacbda30f421f62763e2cf61cd41f94","observation_id":"2e6fd3ac-b290-4930-9c4e-029cc767df3a","resolution":{"observed_at":"2026-07-04T21:20:09.136380Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-04T21:20:09.137149Z","title":null,"venue":null,"work_id":"b184d218-80d7-4505-802e-0c81dd8b89a3","year":2024},"citing_paper":{"arxiv_id":"2606.11211","last_updated":"2026-04-24T04:46:16Z","snapshot_observed_at":"2026-08-06T06:29:18.404870Z","submitted_at":"2026-04-24T04:46:16Z","title":"Calibration Drift Under Reasoning: How Chain-of-Thought Budgets Induce Overconfidence in Large Language Models","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-07-04T19:41:53.668529Z"},"links":{"citing_paper":"/paper/2606.11211"},"observation_digest":"sha256:465c84840b1817b046a7367ea40a54576aa6cfe685e8167ed38f86be1fab6caa","observation_id":"95b704c1-5d80-455c-b195-1aea19123b79","resolution":{"observed_at":"2026-07-04T21:20:09.138840Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.13439","last_updated":"2023-11-13T18:10:16Z","snapshot_observed_at":"2026-07-06T14:56:01.000439Z","submitted_at":"2023-02-26T23:46:29Z","title":"Navigating the Grey Area: How Expressions of Uncertainty and Overconfidence Affect Language Models","version":2},"cited_work":{"arxiv_id":"2302.13439","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2302.13439","snapshot_observed_at":"2026-07-04T19:50:10.021449Z","title":"Navigating the grey area: Expressions of overconfidence and uncertainty in language models","venue":null,"work_id":"e139643d-b682-4790-b67f-fcc8c6af726a","year":2023},"citing_paper":{"arxiv_id":"2606.11211","last_updated":"2026-04-24T04:46:16Z","snapshot_observed_at":"2026-08-06T06:29:18.404870Z","submitted_at":"2026-04-24T04:46:16Z","title":"Calibration Drift Under Reasoning: How Chain-of-Thought Budgets Induce Overconfidence in Large Language Models","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-07-04T19:41:53.668529Z"},"links":{"cited_paper":"/paper/2302.13439","citing_paper":"/paper/2606.11211"},"observation_digest":"sha256:8fe443fcfa2471eae7e914a20cb7dae4e2179b9a72fbacfc195f2fc8461c40d0","observation_id":"a6d37504-b47c-46b1-9600-88db77864a59","resolution":{"observed_at":"2026-07-04T19:50:10.023261Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2606.11211","last_updated":"2026-04-24T04:46:16Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-06T06:29:18.404870Z","submitted_at":"2026-04-24T04:46:16Z","title":"Calibration Drift Under Reasoning: How Chain-of-Thought Budgets Induce Overconfidence in Large Language Models"},"reference_resolution":{"displayed":18,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":8,"verified_exact":7,"verified_fuzzy":3},"total_outbound_references":18},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 1 inbound Pith citation observation for arXiv:2606.11211."}