{"as_of":"2026-08-14T17:29:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4e59654c074570be5f5ea54e01f32d06eaa46f8a9d5a95969ae399d52605d74e","coverage":[{"denominator":47,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":47,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T10:56:23.724916Z","state":"measured"},{"denominator":48,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":48,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+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":"2026-05-09T15:10:16.533927Z","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":"2026-05-11T16:46:06.338646Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"cited_work":{"arxiv_id":"2506.03978","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.03978","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"T., Nguyen, B., and Nguyen, V","venue":null,"work_id":"b1ab3503-d321-4c30-80b6-05a8d4037a01","year":null},"citing_paper":{"arxiv_id":"2605.01194","last_updated":"2026-05-02T02:13:11Z","snapshot_observed_at":"2026-07-06T23:14:29.125042Z","submitted_at":"2026-05-02T02:13:11Z","title":"VLA-ATTC: Adaptive Test-Time Compute for VLA Models with Relative Action Critic Model","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-09T15:10:16.533927Z"},"links":{"cited_paper":"/paper/2506.03978","citing_paper":"/paper/2605.01194"},"observation_digest":"sha256:5d7b0caf4a08c0f6085bce40f82e7b8b23a2b8689113b9acd582325f7a0fcd42","observation_id":"f2eb5284-573b-480c-82be-0e2dee524b12","resolution":{"observed_at":"2026-05-11T16:46:06.341363Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2506.03978/citation-record","integrity":"/paper/2506.03978/integrity","json":"/paper/2506.03978/citation-record.json","paper":"/paper/2506.03978"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:56:23.494589Z","title":"online\" 'onlinestring :=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.494589Z"},"links":{"citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:4d9d88690e890f8e1b030bacdacca2909f076e6d562b52369a9a495b3cd61104","observation_id":"42df121a-9ecc-48ae-85d3-a731c1ba4f3d","resolution":{"observed_at":"2026-08-07T10:56:23.494589Z","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":"2026-08-07T10:56:23.500169Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.500169Z"},"links":{"citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:d32f03b833e23ede07640ab0d5ed210d6a2a496bc35e00fddb87d5436b9f455f","observation_id":"32c5688f-8b83-4994-8418-a52884311498","resolution":{"observed_at":"2026-08-07T10:56:23.500169Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-07T10:56:23.506114Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.506114Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:13ff7e1647d2492bf7eefefec06adad355895d7d860f2be558026fe4e4c12fcf","observation_id":"ce4da5b5-bbe9-4222-8ba3-eb6c3ae63a3a","resolution":{"observed_at":"2026-08-07T10:56:23.506114Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.00157","last_updated":"2024-09-16T19:20:59Z","snapshot_observed_at":"2026-08-13T04:29:45.408362Z","submitted_at":"2024-01-31T20:26:32Z","title":"Large Language Models for Mathematical Reasoning: Progresses and Challenges","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.00157","snapshot_observed_at":"2026-08-07T10:56:23.511738Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.511738Z"},"links":{"cited_paper":"/paper/2402.00157","citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:d4c2e8a140d5107655d2b3bea3cec1caf2a910d4c90d96daeb5c616a1d4879ea","observation_id":"ecd86cd7-3a10-4636-b632-d0e84df0588b","resolution":{"observed_at":"2026-08-07T10:56:23.511738Z","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":"2026-08-07T10:56:23.517604Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.517604Z"},"links":{"citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:4317560c68a60259f8b5bca2e1e2fc83b0554b4887547845e8df9f1523ef41d7","observation_id":"c429718a-57d9-490b-99e3-36d7c0445f92","resolution":{"observed_at":"2026-08-07T10:56:23.517604Z","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":"2026-08-07T10:56:24.573101Z","title":null,"venue":null,"work_id":"7f5d3be4-2e01-436e-9c59-d70d9ee1995b","year":2024},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.522093Z"},"links":{"citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:8fc93cb4e4c23ac6f69f486cfa08948168705b46227b6eaca1f721af8ebf22f6","observation_id":"fc11bae8-450e-49f5-83fd-b3372c1fb40b","resolution":{"observed_at":"2026-08-07T10:56:24.577754Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.09078","last_updated":"2025-04-01T12:48:43Z","snapshot_observed_at":"2026-08-14T09:31:36.315665Z","submitted_at":"2024-12-12T09:01:18Z","title":"Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.09078","snapshot_observed_at":"2026-08-07T10:56:23.527265Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.527265Z"},"links":{"cited_paper":"/paper/2412.09078","citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:b3f9908b81b903a3b90ddeb59698af4e1dd07bc8ceae4062354a5cdec0dda0e7","observation_id":"f8e87d75-e03e-4ac8-9359-e921fa81b7d9","resolution":{"observed_at":"2026-08-07T10:56:23.527265Z","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":"2026-08-07T10:56:24.557561Z","title":"Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D","venue":null,"work_id":"02ea561a-3e42-4d34-a1c1-a20ff3314da8","year":2020},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.532406Z"},"links":{"citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:2d8ec5c223f52fbce7e583513938580f380c4bd7236c8e5ceceef711ded9e464","observation_id":"39c89130-fe3c-4b8a-af51-fb77807920f7","resolution":{"observed_at":"2026-08-07T10:56:24.562335Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.05019","last_updated":"2025-04-07T12:43:05Z","snapshot_observed_at":"2026-08-12T14:48:26.574235Z","submitted_at":"2025-04-07T12:43:05Z","title":"Mixture-of-Personas Language Models for Population Simulation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.05019","snapshot_observed_at":"2026-08-07T10:56:23.537422Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.537422Z"},"links":{"cited_paper":"/paper/2504.05019","citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:13c244c211aebc211ac8dd73ab0ef54a713676ec37b8de26091049acf929c639","observation_id":"5120c196-88c7-4c55-a20a-188d9b401c26","resolution":{"observed_at":"2026-08-07T10:56:23.537422Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.02311","last_updated":"2022-10-05T06:02:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-04-05T16:11:45Z","title":"PaLM: Scaling Language Modeling with Pathways","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.02311","snapshot_observed_at":"2026-08-07T10:56:23.542034Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.542034Z"},"links":{"cited_paper":"/paper/2204.02311","citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:e461317af5c1bdb45d5dc62ef48548d92c2ef342182f90f9691f71224b842978","observation_id":"72cbac44-31b0-4596-a4a3-7153fcf7b40b","resolution":{"observed_at":"2026-08-07T10:56:23.542034Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.14168","last_updated":"2021-11-18T00:23:45Z","snapshot_observed_at":"2026-08-14T02:43:01.480086Z","submitted_at":"2021-10-27T04:49:45Z","title":"Training Verifiers to Solve Math Word Problems","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.14168","snapshot_observed_at":"2026-08-07T10:56:23.546965Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.546965Z"},"links":{"cited_paper":"/paper/2110.14168","citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:12861acd0e5d9775019fda4813d9f22270abdca8a41913f617b05ae6a4d45e26","observation_id":"bc0cfc96-dbd2-42c0-96e1-959ac7e874d0","resolution":{"observed_at":"2026-08-07T10:56:23.546965Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04707","last_updated":"2024-10-07T02:52:30Z","snapshot_observed_at":"2026-08-14T11:31:33.903243Z","submitted_at":"2024-10-07T02:52:30Z","title":"Learning How Hard to Think: Input-Adaptive Allocation of LM Computation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.04707","snapshot_observed_at":"2026-08-07T10:56:23.551437Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.551437Z"},"links":{"cited_paper":"/paper/2410.04707","citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:85e0268cb6f8e0a991d0521acab721e320b89299281e5034db0b63dbf3cbab5b","observation_id":"77aebce6-4914-4c51-956f-81cdfa8e45c0","resolution":{"observed_at":"2026-08-07T10:56:23.551437Z","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":"2023.10560","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:56:24.234264Z","title":null,"venue":null,"work_id":"b479cbf7-2f4d-42e4-9603-6bc56ca62186","year":2023},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.555937Z"},"links":{"citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:d4fa804287e2272adfa04e2930e05e9982ed8bde4d75c76b916748203960b5ad","observation_id":"80701daf-968c-48d8-981e-738e0868a9e1","resolution":{"observed_at":"2026-08-07T10:56:24.242379Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.17179","last_updated":"2024-02-09T00:13:46Z","snapshot_observed_at":"2026-08-13T10:02:20.024046Z","submitted_at":"2023-09-29T12:20:19Z","title":"Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.17179","snapshot_observed_at":"2026-08-07T10:56:23.561140Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.561140Z"},"links":{"cited_paper":"/paper/2309.17179","citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:ece44e739a339a13a5a0a0ce3578f02d3cad59accf2a01b1770df33b8ac177a5","observation_id":"9ad7cede-ca98-4c61-8f14-ecbbdd2bc5ab","resolution":{"observed_at":"2026-08-07T10:56:23.561140Z","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":"2026-08-07T10:56:23.566443Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.566443Z"},"links":{"citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:e695516eff33cc9685796b2ff33a69c2e3d34496512509cc179b43ceef3dfce9","observation_id":"1f3fb80f-ac8a-4033-8f69-7f29db7a1694","resolution":{"observed_at":"2026-08-07T10:56:23.566443Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.04519","last_updated":"2025-01-08T14:12:57Z","snapshot_observed_at":"2026-08-14T00:11:28.443916Z","submitted_at":"2025-01-08T14:12:57Z","title":"rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.04519","snapshot_observed_at":"2026-08-07T10:56:23.571793Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.571793Z"},"links":{"cited_paper":"/paper/2501.04519","citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:09191fd7bc8a8cb2b41247011640951ddf3cdefb225d5a9fe28557c0f4607ad5","observation_id":"82381dd6-b3cb-4230-a172-84bd0c8bfe11","resolution":{"observed_at":"2026-08-07T10:56:23.571793Z","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":"2026-08-07T10:56:23.576323Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.576323Z"},"links":{"citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:b6ec547047c65b4d5f3d0a605a690c05016be2e2de25731b56aa98d0a68c2d10","observation_id":"78302c14-0f49-4ca3-a244-d6e1f80e0ed9","resolution":{"observed_at":"2026-08-07T10:56:23.576323Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"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":"2026-08-07T10:56:23.581265Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.581265Z"},"links":{"cited_paper":"/paper/2203.15556","citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:7023bc418e5b026ffe073e982bbae18a9b06773dba989a701d26cc8ea289c222","observation_id":"bc3b6116-a91a-450d-a03a-0133ccb05725","resolution":{"observed_at":"2026-08-07T10:56:23.581265Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.05398","last_updated":"2023-03-04T04:43:49Z","snapshot_observed_at":"2026-08-13T12:32:18.384526Z","submitted_at":"2023-03-04T04:43:49Z","title":"MathPrompter: Mathematical Reasoning using Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.05398","snapshot_observed_at":"2026-08-07T10:56:23.586385Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.586385Z"},"links":{"cited_paper":"/paper/2303.05398","citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:24e3014ca101d9c6b74c7e3fc0f0e5dd3eaddf79940b05951ef6d97164c9f02c","observation_id":"aae6248f-6c2e-4532-87d2-64b77b41c189","resolution":{"observed_at":"2026-08-07T10:56:23.586385Z","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":"2026-08-07T10:56:23.592177Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.592177Z"},"links":{"citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:79f7bfbdcd08700bcaab850b419f9161f28f389fefd783057f290bddb6016093","observation_id":"28b7c98f-4f41-4fe4-881a-1fc042192e88","resolution":{"observed_at":"2026-08-07T10:56:23.592177Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.04043","last_updated":"2025-02-06T13:03:05Z","snapshot_observed_at":"2026-08-09T19:26:39.230395Z","submitted_at":"2025-02-06T13:03:05Z","title":"Probe-Free Low-Rank Activation Intervention","version":1},"cited_work":{"arxiv_id":"2502.04043","doi":null,"metadata_source":"pith","pith_arxiv_id":"2502.04043","snapshot_observed_at":"2026-08-07T10:56:24.084381Z","title":"Probe-Free Low-Rank Activation Intervention","venue":"cs.LG","work_id":"69495cdb-cde8-4ef9-8078-96864c2fa059","year":2025},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.596584Z"},"links":{"cited_paper":"/paper/2502.04043","citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:90dfddb8f717ed2c027de79e471e47ce545c586ae45725f59aedf01e6d22b3be","observation_id":"f11a69db-faff-4ee5-9fd0-7c09f70356d5","resolution":{"observed_at":"2026-08-07T10:56:24.091130Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:56:23.601249Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.601249Z"},"links":{"citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:32bfd3c3f49e7396ed433092a022359e78d82442e875ac2e29c69fae959f1141","observation_id":"5c67747d-6d16-4702-82b3-9aeefe68da1c","resolution":{"observed_at":"2026-08-07T10:56:23.601249Z","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":"2026-08-07T10:56:24.510292Z","title":null,"venue":null,"work_id":"706ee0ab-8a55-4582-a2c7-b6a1faaafbab","year":2024},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.606951Z"},"links":{"citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:429308ff36f69e20cb9b67dfb43072524882db2fe6208f022925271fc6c08d30","observation_id":"9b2b6e33-1246-45e3-a89d-bccd21745386","resolution":{"observed_at":"2026-08-07T10:56:24.514957Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:56:24.490950Z","title":null,"venue":null,"work_id":"cffb8f9f-6e1f-477b-9e01-88ecdee9a7c2","year":2023},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.612530Z"},"links":{"citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:d4c4449a5f50ffb9f05a49a82940e701720341cadbff165bed3a866e20c8d95d","observation_id":"86711ff7-0587-4fe6-bd0b-0731f58c7cb8","resolution":{"observed_at":"2026-08-07T10:56:24.496026Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:56:24.474435Z","title":null,"venue":null,"work_id":"8724a7a6-4392-4d8a-9757-925070c1d1dc","year":2024},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.617394Z"},"links":{"citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:5a58a1b29c58858bd6d812de1af53dfc55eebef198be4e0cfd41be6c9bc8127e","observation_id":"ebbc9080-4d61-4a45-bb25-a013f2361eb1","resolution":{"observed_at":"2026-08-07T10:56:24.480103Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.20050","last_updated":"2023-05-31T17:24:00Z","snapshot_observed_at":"2026-08-11T17:22:43.545531Z","submitted_at":"2023-05-31T17:24:00Z","title":"Let's Verify Step by Step","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.20050","snapshot_observed_at":"2026-08-07T10:56:23.622242Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.622242Z"},"links":{"cited_paper":"/paper/2305.20050","citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:c54d5ae6a58253d4ea0fcee1f1fca3695222bd6e8f46892690ead8d9cba86cf7","observation_id":"6e612c67-50b6-4bc6-862e-d39ecdb0e944","resolution":{"observed_at":"2026-08-07T10:56:23.622242Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.06668","last_updated":"2024-02-13T22:37:39Z","snapshot_observed_at":"2026-08-14T16:06:18.731069Z","submitted_at":"2023-11-11T21:19:44Z","title":"In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.06668","snapshot_observed_at":"2026-08-07T10:56:23.627880Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.627880Z"},"links":{"cited_paper":"/paper/2311.06668","citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:be2c868ce751ba7b80cec5547eea4468da6df8597e75081ad6f4a8d0566a9343","observation_id":"f7ac5b78-383b-4761-9b8f-8c6144eb12a9","resolution":{"observed_at":"2026-08-07T10:56:23.627880Z","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":"2026-08-07T10:56:24.459809Z","title":null,"venue":null,"work_id":"b7fd2fa6-a837-464c-8aa7-7c68ad64fc5d","year":2023},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.632907Z"},"links":{"citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:4874be8d3325f2876e52384daf47017f934c2b2fa9d559ae6be500d676722bde","observation_id":"2dd8e2e5-73f4-477c-8c60-e060b92e4112","resolution":{"observed_at":"2026-08-07T10:56:24.464376Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:56:23.638227Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.638227Z"},"links":{"citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:99b2c8e1643a3e0d7d0f214a1e438eaa58ff3e1b2cb1a0a35f99b8b4198eb839","observation_id":"4bfa94e2-b6c3-44cb-981d-616a764d4b85","resolution":{"observed_at":"2026-08-07T10:56:23.638227Z","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":"2026-08-07T10:56:23.643292Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.643292Z"},"links":{"citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:c3ff2fa92ea4914729e885d328e87581621e8b91d0f1a8cb4794f9d6ea97012d","observation_id":"81db1bcb-e7bc-4db9-a483-985e2170a6d0","resolution":{"observed_at":"2026-08-07T10:56:23.643292Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12446","last_updated":"2026-07-10T01:07:20Z","snapshot_observed_at":"2026-08-11T15:58:24.281086Z","submitted_at":"2025-02-18T02:27:23Z","title":"Multi-Attribute Steering of Language Models via Targeted Intervention","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.12446","snapshot_observed_at":"2026-08-07T10:56:23.648530Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.648530Z"},"links":{"cited_paper":"/paper/2502.12446","citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:9d1b079d3b41bfae1bbc599116aa732e4a81e97a2125070235e7f0bff02471a2","observation_id":"149d62f1-7df5-4f97-abbc-846ded0c0ecb","resolution":{"observed_at":"2026-08-07T10:56:23.648530Z","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":"2026-08-07T10:56:24.435002Z","title":null,"venue":null,"work_id":"7e027027-b13e-40cb-b576-d93427ba74b3","year":2025},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.653075Z"},"links":{"citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:ea6d8dc77ee894c026b7527fcd50d84350e4b10efe59db4af55642c4e3e77642","observation_id":"69427ad5-9576-44f7-a758-22c3f3fa1706","resolution":{"observed_at":"2026-08-07T10:56:24.439676Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2112.11446","last_updated":"2022-01-21T18:39:38Z","snapshot_observed_at":"2026-08-09T14:52:01.161814Z","submitted_at":"2021-12-08T19:41:47Z","title":"Scaling Language Models: Methods, Analysis & Insights from Training Gopher","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.11446","snapshot_observed_at":"2026-08-07T10:56:23.657578Z","title":"Rae, Sebastian Borgeaud, Trevor Cai, Katie Millican, Jordan Hoffmann, Francis Song, John Aslanides, Sarah Henderson, Roman Ring, Susannah Young, and 1 others","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.657578Z"},"links":{"cited_paper":"/paper/2112.11446","citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:aca1b6fcc28423123cc0bcc6bf9657112cdbd0f8d7927cfbd84af9e8482b37f5","observation_id":"ed34106c-d1e6-48d7-8e3e-b1bd90cb1d30","resolution":{"observed_at":"2026-08-07T10:56:23.657578Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10683","last_updated":"2023-09-19T15:14:48Z","snapshot_observed_at":"2026-08-14T16:16:21.567225Z","submitted_at":"2019-10-23T17:37:36Z","title":"Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10683","snapshot_observed_at":"2026-08-07T10:56:23.663999Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.663999Z"},"links":{"cited_paper":"/paper/1910.10683","citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:21303c1c42d7978b731e3bc006c1626f689e8721a397b5b8948fc225886380f2","observation_id":"365e22e5-afd8-44a5-a2bc-31f8d817dddc","resolution":{"observed_at":"2026-08-07T10:56:23.663999Z","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":"2026-08-07T10:56:24.420519Z","title":null,"venue":null,"work_id":"03ce5d1d-af9c-4421-968d-1351212e1ec5","year":2024},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.669381Z"},"links":{"citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:c82fa01550ca41e3b9687c1553efb1ec283fc6e6c0bda54e1139de37ac8d2911","observation_id":"f2274c59-ed8e-44f6-8ce1-4ef20f49c568","resolution":{"observed_at":"2026-08-07T10:56:24.425071Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.2196/53225","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":null,"venue":"Journal of Medical Internet Research","work_id":"1423855b-9465-4533-8f6f-894913608792","year":2024},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.673796Z"},"links":{"citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:ecad43b6017e36a8218b379e08108bc11933d1a8fef559136dce4de805384da8","observation_id":"36e5c216-9c16-4998-b314-93c0397c033c","resolution":{"observed_at":"2026-08-07T10:56:23.763350Z","resolver_source":"doi_truncated","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:56:23.678567Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.678567Z"},"links":{"citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:4dd5bed8f6e260675f0b5f56312421f81a2054664f1db86bd6434abffa59cb19","observation_id":"31dc3fa7-ac99-4d16-884d-613fd4f608b3","resolution":{"observed_at":"2026-08-07T10:56:23.678567Z","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":"2026-08-07T10:56:23.682679Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.682679Z"},"links":{"citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:afdc56c32fbcf7987a6a53d26a735f64d4888ea5387a91dfcc71b504dbb2afc6","observation_id":"ead33bc5-858b-4c5e-9020-becb0992c12a","resolution":{"observed_at":"2026-08-07T10:56:23.682679Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"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":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.11171","snapshot_observed_at":"2026-08-07T10:56:23.687038Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.687038Z"},"links":{"cited_paper":"/paper/2203.11171","citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:c33c36083cc966f535269f5f1bf5c9c438fda42c771ae2ebe8bac202e0168f3b","observation_id":"930052e9-18cb-41b6-b5b3-ab42355fd4be","resolution":{"observed_at":"2026-08-07T10:56:23.687038Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.04732","last_updated":"2021-03-28T19:04:25Z","snapshot_observed_at":"2026-08-14T00:39:23.744952Z","submitted_at":"2019-10-10T17:44:18Z","title":"Structured Pruning of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.04732","snapshot_observed_at":"2026-08-07T10:56:23.691771Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.691771Z"},"links":{"cited_paper":"/paper/1910.04732","citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:6c49840d20a3275d5780d23c1c68ab393e2a4289a54cc89c7c7bf49684ad5c23","observation_id":"f5582c5c-dcae-4d72-8da3-fccbca0da466","resolution":{"observed_at":"2026-08-07T10:56:23.691771Z","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":"2026-08-07T10:56:23.696419Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.696419Z"},"links":{"citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:1bed74c16c722421e3d1aa706b0ee3dfae30e2c121e46d6c6fdc05e01e9897ae","observation_id":"5d2707f1-78ec-4aca-ada5-feee52475f05","resolution":{"observed_at":"2026-08-07T10:56:23.696419Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.07809","last_updated":"2024-03-12T16:46:54Z","snapshot_observed_at":"2026-08-13T00:55:53.795755Z","submitted_at":"2024-03-12T16:46:54Z","title":"pyvene: A Library for Understanding and Improving PyTorch Models via Interventions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.07809","snapshot_observed_at":"2026-08-07T10:56:23.700909Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.700909Z"},"links":{"cited_paper":"/paper/2403.07809","citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:771ac24d6f0165f5324070e7ecd03d42183f9bf39f1b037b76537108e994dfd8","observation_id":"5cd69a75-741c-4ee8-8b26-70958fa4e55a","resolution":{"observed_at":"2026-08-07T10:56:23.700909Z","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":"2026-08-07T10:56:24.373832Z","title":null,"venue":null,"work_id":"4bf96c01-7243-4347-81fe-b7dcd200399f","year":2024},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.705624Z"},"links":{"citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:e6dd70fc237f5458ffdbb0cfc7fc867a6dba128a18570b5a113e9b5440a78241","observation_id":"7cf271b7-f4af-4be4-bb61-17474afdf319","resolution":{"observed_at":"2026-08-07T10:56:24.378473Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.11817","last_updated":"2025-02-13T08:11:25Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-01-22T10:26:14Z","title":"Hallucination is Inevitable: An Innate Limitation of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.11817","snapshot_observed_at":"2026-08-07T10:56:23.710024Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.710024Z"},"links":{"cited_paper":"/paper/2401.11817","citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:d02ee04cec86b3b8118768c3855e19bfba254868ade7a89532a309048aa6f8c8","observation_id":"699b1cbb-b6b8-45e4-8cfa-f920e731e695","resolution":{"observed_at":"2026-08-07T10:56:23.710024Z","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":"2026-08-07T10:56:23.714788Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.714788Z"},"links":{"citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:27fd8b8c973d5dedce4684302d91721e4e66bb3ee4543cb97cf385229e31be49","observation_id":"51583e54-c09d-44a6-a68a-99eda60ac814","resolution":{"observed_at":"2026-08-07T10:56:23.714788Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.07191","last_updated":"2025-07-07T17:42:19Z","snapshot_observed_at":"2026-08-13T14:55:20.001264Z","submitted_at":"2024-11-11T18:05:48Z","title":"The Super Weight in Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.07191","snapshot_observed_at":"2026-08-07T10:56:23.719496Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.719496Z"},"links":{"cited_paper":"/paper/2411.07191","citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:fc58956e5e4b25cb4e0dade9b2e26a66e34d1c7ae06903c22bfb6019a65692d8","observation_id":"b341e365-fea9-4d4b-b0fd-168881919bec","resolution":{"observed_at":"2026-08-07T10:56:23.719496Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.03816","last_updated":"2024-11-18T05:36:16Z","snapshot_observed_at":"2026-08-14T03:57:25.019190Z","submitted_at":"2024-06-06T07:40:00Z","title":"ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.03816","snapshot_observed_at":"2026-08-07T10:56:23.724916Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization","version":2},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:23.724916Z"},"links":{"cited_paper":"/paper/2406.03816","citing_paper":"/paper/2506.03978"},"observation_digest":"sha256:4e289715102fb6caa72bac7a03fdd42d92e91baf885692c4523bb80eb73ccc4a","observation_id":"b468fc3c-b25a-4c5b-9425-e2a8afe5b8c3","resolution":{"observed_at":"2026-08-07T10:56:23.724916Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.03978","last_updated":"2025-06-09T04:15:05Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-12T02:45:06.429220Z","submitted_at":"2025-06-04T14:08:44Z","title":"Structured Pruning for Diverse Best-of-N Reasoning Optimization"},"reference_resolution":{"displayed":47,"state_counts":{"malformed_identifier":1,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":43,"verified_exact":1,"verified_fuzzy":1},"total_outbound_references":47},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 1 inbound Pith citation observation for arXiv:2506.03978."}