{"as_of":"2026-08-05T00:27:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:183e09edd4c3c613649456e83402c81bdb32ce5f9d771c0e1aae83b8c97ff38e","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":10,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":10,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-04T06:34:03.388597+00:00","state":"measured"},{"denominator":10,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":10,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T04:22:25.234646Z","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":"2026-07-10T06:15:00.866473Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2305.11860","last_updated":"2023-11-16T16:47:05Z","snapshot_observed_at":"2026-08-04T02:42:35.223564Z","submitted_at":"2023-05-19T17:49:25Z","title":"Let's Sample Step by Step: Adaptive-Consistency for Efficient Reasoning and Coding with LLMs","version":2},"cited_work":{"arxiv_id":"2305.11860","doi":"10.48550/arxiv.2305.11860","metadata_source":"arxiv_reference","pith_arxiv_id":"2305.11860","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"arXiv preprint arXiv:2305.11860 , year=","venue":null,"work_id":"254c2798-11d7-439d-ad41-9b6e1cb1d634","year":2023},"citing_paper":{"arxiv_id":"2509.11295","last_updated":"2026-04-29T13:18:01Z","snapshot_observed_at":"2026-07-06T22:29:58.066459Z","submitted_at":"2025-09-14T14:39:35Z","title":"The Prompt Engineering Report Distilled: Quick Start Guide for Life Sciences","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-18T16:39:03.794436Z"},"links":{"cited_paper":"/paper/2305.11860","citing_paper":"/paper/2509.11295"},"observation_digest":"sha256:12cce4c5d4dac21e61f751849cab8979f5daccbf37110d405ca5687ea569c658","observation_id":"77482dce-d72e-4bec-ad6d-abc07aa4ccf1","resolution":{"observed_at":"2026-05-18T16:41:38.018321Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.11860","last_updated":"2023-11-16T16:47:05Z","snapshot_observed_at":"2026-08-04T02:42:35.223564Z","submitted_at":"2023-05-19T17:49:25Z","title":"Let's Sample Step by Step: Adaptive-Consistency for Efficient Reasoning and Coding with LLMs","version":2},"cited_work":{"arxiv_id":"2305.11860","doi":"10.48550/arxiv.2305.11860","metadata_source":"arxiv_reference","pith_arxiv_id":"2305.11860","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"arXiv preprint arXiv:2305.11860 , year=","venue":null,"work_id":"254c2798-11d7-439d-ad41-9b6e1cb1d634","year":2023},"citing_paper":{"arxiv_id":"2509.11295","last_updated":"2026-04-29T13:18:01Z","snapshot_observed_at":"2026-07-06T22:29:58.066459Z","submitted_at":"2025-09-14T14:39:35Z","title":"The Prompt Engineering Report Distilled: Quick Start Guide for Life Sciences","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-18T16:39:03.794436Z"},"links":{"cited_paper":"/paper/2305.11860","citing_paper":"/paper/2509.11295"},"observation_digest":"sha256:a2f12d3934597c282901902fd9e953d41f4d4ab78b9a61098ecb6f5603b8f39c","observation_id":"d9d73f4a-10be-4aeb-a175-cd603e967964","resolution":{"observed_at":"2026-05-18T16:41:37.657361Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.11860","last_updated":"2023-11-16T16:47:05Z","snapshot_observed_at":"2026-08-04T02:42:35.223564Z","submitted_at":"2023-05-19T17:49:25Z","title":"Let's Sample Step by Step: Adaptive-Consistency for Efficient Reasoning and Coding with LLMs","version":2},"cited_work":{"arxiv_id":"2305.11860","doi":"10.48550/arxiv.2305.11860","metadata_source":"arxiv_reference","pith_arxiv_id":"2305.11860","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"arXiv preprint arXiv:2305.11860 , year=","venue":null,"work_id":"254c2798-11d7-439d-ad41-9b6e1cb1d634","year":2023},"citing_paper":{"arxiv_id":"2511.00751","last_updated":"2026-05-07T03:39:05Z","snapshot_observed_at":"2026-07-06T22:34:38.619949Z","submitted_at":"2025-11-02T00:36:49Z","title":"Self-Consistency Is Losing Its Edge: Diminishing Returns and Rising Costs in Modern LLMs","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-18T02:06:33.443026Z"},"links":{"cited_paper":"/paper/2305.11860","citing_paper":"/paper/2511.00751"},"observation_digest":"sha256:45ff50324f2c44602394eaf813b5afe52ad6b5f1a7805607cf768722ae999f27","observation_id":"31a6cf80-867c-4d7f-9d1d-edd98f841c4f","resolution":{"observed_at":"2026-05-18T02:10:39.007932Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.11860","last_updated":"2023-11-16T16:47:05Z","snapshot_observed_at":"2026-08-04T02:42:35.223564Z","submitted_at":"2023-05-19T17:49:25Z","title":"Let's Sample Step by Step: Adaptive-Consistency for Efficient Reasoning and Coding with LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.11860","snapshot_observed_at":"2026-08-03T04:22:25.234646Z","title":"Let's sample step by step: Adaptive-consistency for efficient reasoning and coding with llms","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2602.05395","last_updated":"2026-05-31T20:25:40Z","snapshot_observed_at":"2026-08-03T04:22:22.864641Z","submitted_at":"2026-02-05T07:22:00Z","title":"Optimal Bayesian Stopping for Efficient Inference of Consistent LLM Answers","version":2},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-03T04:22:25.234646Z"},"links":{"cited_paper":"/paper/2305.11860","citing_paper":"/paper/2602.05395"},"observation_digest":"sha256:0c1ddcd018fe1f6eae191c2e3d04caae8e6803ae0081c536ded4c5140d5f2561","observation_id":"3f50c792-2e0e-4644-87ca-06f9d999f335","resolution":{"observed_at":"2026-08-03T04:22:25.234646Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.11860","last_updated":"2023-11-16T16:47:05Z","snapshot_observed_at":"2026-08-04T02:42:35.223564Z","submitted_at":"2023-05-19T17:49:25Z","title":"Let's Sample Step by Step: Adaptive-Consistency for Efficient Reasoning and Coding with LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.11860","snapshot_observed_at":"2026-08-03T02:22:14.487651Z","title":"Let’s sample step by step: Adaptive-consistency for efficient reasoning and coding with llms, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2605.15100","last_updated":"2026-07-31T12:11:10Z","snapshot_observed_at":"2026-08-05T00:12:10.090141Z","submitted_at":"2026-05-14T17:19:37Z","title":"Dual-Dimensional Consistency: Balancing Budget and Quality in Adaptive Inference-Time Scaling","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-03T02:22:14.487651Z"},"links":{"cited_paper":"/paper/2305.11860","citing_paper":"/paper/2605.15100"},"observation_digest":"sha256:6d0846dc4ab480841fd6d860790d955bf8cea15c04c79d37a19497cedffb168f","observation_id":"165cfffe-8c5b-47b6-a431-9fdcfddfbc21","resolution":{"observed_at":"2026-08-03T02:22:14.487651Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.11860","last_updated":"2023-11-16T16:47:05Z","snapshot_observed_at":"2026-08-04T02:42:35.223564Z","submitted_at":"2023-05-19T17:49:25Z","title":"Let's Sample Step by Step: Adaptive-Consistency for Efficient Reasoning and Coding with LLMs","version":2},"cited_work":{"arxiv_id":"2305.11860","doi":"10.48550/arxiv.2305.11860","metadata_source":"arxiv_reference","pith_arxiv_id":"2305.11860","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"arXiv preprint arXiv:2305.11860 , year=","venue":null,"work_id":"254c2798-11d7-439d-ad41-9b6e1cb1d634","year":2023},"citing_paper":{"arxiv_id":"2606.03102","last_updated":"2026-06-02T03:42:04Z","snapshot_observed_at":"2026-08-03T04:21:57.609394Z","submitted_at":"2026-06-02T03:42:04Z","title":"Small RL Controller, Large Language Model: RL-Guided Adaptive Sampling for Test-Time Scaling","version":1},"reference_index":72,"source":"arxiv_source","source_observed_at":"2026-06-28T10:25:10.559953Z"},"links":{"cited_paper":"/paper/2305.11860","citing_paper":"/paper/2606.03102"},"observation_digest":"sha256:cf6fc947d71c0b19d4a84c566b1983d1703a11b46fc4268de63ceac169ad1d5e","observation_id":"f188aa0c-6fad-4d39-aa14-f09bbeb990bb","resolution":{"observed_at":"2026-07-02T02:56:29.960817Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.11860","last_updated":"2023-11-16T16:47:05Z","snapshot_observed_at":"2026-08-04T02:42:35.223564Z","submitted_at":"2023-05-19T17:49:25Z","title":"Let's Sample Step by Step: Adaptive-Consistency for Efficient Reasoning and Coding with LLMs","version":2},"cited_work":{"arxiv_id":"2305.11860","doi":"10.48550/arxiv.2305.11860","metadata_source":"arxiv_reference","pith_arxiv_id":"2305.11860","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"arXiv preprint arXiv:2305.11860 , year=","venue":null,"work_id":"254c2798-11d7-439d-ad41-9b6e1cb1d634","year":2023},"citing_paper":{"arxiv_id":"2607.01612","last_updated":"2026-07-02T02:29:33Z","snapshot_observed_at":"2026-07-07T00:07:08.919017Z","submitted_at":"2026-07-02T02:29:33Z","title":"Scaling with Confidence: Calibrating Confidence of LLMs for Adaptive Test Time Scaling","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-07-03T14:49:33.364596Z"},"links":{"cited_paper":"/paper/2305.11860","citing_paper":"/paper/2607.01612"},"observation_digest":"sha256:65f6d00809074c8d8ab1b0fe3ac91ba2f36bb4b38caf1887566d18efacb76a2c","observation_id":"e82367d1-01e7-4781-9046-8d32160e301b","resolution":{"observed_at":"2026-07-03T14:58:32.558038Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.11860","last_updated":"2023-11-16T16:47:05Z","snapshot_observed_at":"2026-08-04T02:42:35.223564Z","submitted_at":"2023-05-19T17:49:25Z","title":"Let's Sample Step by Step: Adaptive-Consistency for Efficient Reasoning and Coding with LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.11860","snapshot_observed_at":"2026-07-13T05:38:27.357469Z","title":"Let’s sample step by step: Adaptive- consistency for efficient reasoning and coding with llms.arXiv preprint arXiv:2305.11860,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.08940","last_updated":"2026-07-18T17:05:31Z","snapshot_observed_at":"2026-08-02T07:51:10.193975Z","submitted_at":"2026-07-09T21:09:05Z","title":"TSRouter: Dynamic Modality-Model Selection for Time Series Reasoning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-13T05:38:27.357469Z"},"links":{"cited_paper":"/paper/2305.11860","citing_paper":"/paper/2607.08940"},"observation_digest":"sha256:6067f47f36c52feeabf01534efb5cb33c7d9ea6e46a48abc2fb91265168475e3","observation_id":"5cebccdc-5c1a-44c6-a090-b8066630cdc0","resolution":{"observed_at":"2026-07-13T05:38:27.357469Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.11860","last_updated":"2023-11-16T16:47:05Z","snapshot_observed_at":"2026-08-04T02:42:35.223564Z","submitted_at":"2023-05-19T17:49:25Z","title":"Let's Sample Step by Step: Adaptive-Consistency for Efficient Reasoning and Coding with LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.11860","snapshot_observed_at":"2026-08-02T07:51:11.404084Z","title":"Let’s sample step by step: Adaptive- consistency for efficient reasoning and coding with llms.arXiv preprint arXiv:2305.11860,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.08940","last_updated":"2026-07-18T17:05:31Z","snapshot_observed_at":"2026-08-02T07:51:10.193975Z","submitted_at":"2026-07-09T21:09:05Z","title":"TSRouter: Dynamic Modality-Model Selection for Time Series Reasoning","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-02T07:51:11.404084Z"},"links":{"cited_paper":"/paper/2305.11860","citing_paper":"/paper/2607.08940"},"observation_digest":"sha256:4187080caa441a352a1f4208064242cc772c5c64e2d5e98ebfb9cc9941348ca4","observation_id":"9236b78a-69af-4b58-a81c-2414b1d9caf3","resolution":{"observed_at":"2026-08-02T07:51:11.404084Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.11860","last_updated":"2023-11-16T16:47:05Z","snapshot_observed_at":"2026-08-04T02:42:35.223564Z","submitted_at":"2023-05-19T17:49:25Z","title":"Let's Sample Step by Step: Adaptive-Consistency for Efficient Reasoning and Coding with LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.11860","snapshot_observed_at":"2026-08-01T18:40:02.653070Z","title":"arXiv preprint arXiv:2305.11860 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.17251","last_updated":"2026-07-19T13:41:38Z","snapshot_observed_at":"2026-08-04T18:28:47.060592Z","submitted_at":"2026-07-19T13:41:38Z","title":"VecFontLLM: Anchor-Guided Direct Synthesis of Chinese Vector Fonts","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-01T18:40:02.653070Z"},"links":{"cited_paper":"/paper/2305.11860","citing_paper":"/paper/2607.17251"},"observation_digest":"sha256:014dab48366c7db0bceedccebe004e66cb358adfb9e61719094e641a83c15d3b","observation_id":"b1d72d05-e334-4d28-9a5b-7b69d8dff096","resolution":{"observed_at":"2026-08-01T18:40:02.653070Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2305.11860/citation-record","integrity":"/paper/2305.11860/integrity","json":"/paper/2305.11860/citation-record.json","paper":"/paper/2305.11860"},"outbound":[],"paper":{"arxiv_id":"2305.11860","last_updated":"2023-11-16T16:47:05Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-04T02:42:35.223564Z","submitted_at":"2023-05-19T17:49:25Z","title":"Let's Sample Step by Step: Adaptive-Consistency for Efficient Reasoning and Coding with LLMs"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"thesis":"As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2305.11860."}