{"as_of":"2026-08-08T16:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2353e8119ace613ec9610cf1a62bb3d70470276d4f014ade9391603a4abc1f1e","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":8,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":8,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":8,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T13:02:23.592574Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2503.11314","last_updated":"2025-06-11T03:55:09Z","snapshot_observed_at":"2026-08-07T17:04:15.538727Z","submitted_at":"2025-03-14T11:30:37Z","title":"Unlocking General Long Chain-of-Thought Reasoning Capabilities of Large Language Models via Representation Engineering","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.11314","snapshot_observed_at":"2026-08-08T13:02:23.592574Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2502.07365","last_updated":"2025-05-28T08:04:23Z","snapshot_observed_at":"2026-08-08T12:56:03.378384Z","submitted_at":"2025-02-11T08:37:16Z","title":"LongReD: Mitigating Short-Text Degradation of Long-Context Large Language Models via Restoration Distillation","version":3},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-08-08T13:02:23.592574Z"},"links":{"cited_paper":"/paper/2503.11314","citing_paper":"/paper/2502.07365"},"observation_digest":"sha256:579f98a1905701a7509519b42ce32b81c373165427c8c9d0284b0b1b592a3fef","observation_id":"e01e48f6-a94f-49db-87f0-a0ca6bb51e23","resolution":{"observed_at":"2026-08-08T13:02:23.592574Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.11314","last_updated":"2025-06-11T03:55:09Z","snapshot_observed_at":"2026-08-07T17:04:15.538727Z","submitted_at":"2025-03-14T11:30:37Z","title":"Unlocking General Long Chain-of-Thought Reasoning Capabilities of Large Language Models via Representation Engineering","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.11314","snapshot_observed_at":"2026-08-07T15:05:18.186011Z","title":"Unlocking General Long Chain-of-Thought Reasoning Capabilities of Large Language Models via Representation Engineering, March 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.17153","last_updated":"2025-05-22T11:27:01Z","snapshot_observed_at":"2026-08-08T08:42:49.400073Z","submitted_at":"2025-05-22T11:27:01Z","title":"Amplify Adjacent Token Differences: Enhancing Long Chain-of-Thought Reasoning with Shift-FFN","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T15:05:18.186011Z"},"links":{"cited_paper":"/paper/2503.11314","citing_paper":"/paper/2505.17153"},"observation_digest":"sha256:fa72b2bedd4afe4b085259e457e588b59a1815427ae7cda5df4e60d22f9309dc","observation_id":"9d3f7704-a80b-4415-81ab-03d1b3823450","resolution":{"observed_at":"2026-08-07T15:05:18.186011Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.11314","last_updated":"2025-06-11T03:55:09Z","snapshot_observed_at":"2026-08-07T17:04:15.538727Z","submitted_at":"2025-03-14T11:30:37Z","title":"Unlocking General Long Chain-of-Thought Reasoning Capabilities of Large Language Models via Representation Engineering","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.11314","snapshot_observed_at":"2026-08-07T14:46:17.456419Z","title":"Unlocking general long chain-of-thought reasoning capabilities of large language models via representation engineering.arXiv preprint arXiv:2503.11314, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.17697","last_updated":"2025-05-23T10:07:18Z","snapshot_observed_at":"2026-08-07T21:54:30.483014Z","submitted_at":"2025-05-23T10:07:18Z","title":"Activation Control for Efficiently Eliciting Long Chain-of-thought Ability of Language Models","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T14:46:17.456419Z"},"links":{"cited_paper":"/paper/2503.11314","citing_paper":"/paper/2505.17697"},"observation_digest":"sha256:bc0e949a4c7376e9f9adc3c4c318dc86dd68c200d60fe4be7d5f71c90a200846","observation_id":"5a9080bb-fe0a-4a60-b29a-2bdaf9a9141c","resolution":{"observed_at":"2026-08-07T14:46:17.456419Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.11314","last_updated":"2025-06-11T03:55:09Z","snapshot_observed_at":"2026-08-07T17:04:15.538727Z","submitted_at":"2025-03-14T11:30:37Z","title":"Unlocking General Long Chain-of-Thought Reasoning Capabilities of Large Language Models via Representation Engineering","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.11314","snapshot_observed_at":"2026-08-06T16:45:59.645017Z","title":"Unlocking general long chain-of-thought reasoning capabilities of large language models via representation engineering","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.12759","last_updated":"2025-07-17T03:31:36Z","snapshot_observed_at":"2026-08-07T21:57:01.893066Z","submitted_at":"2025-07-17T03:31:36Z","title":"Logit Arithmetic Elicits Long Reasoning Capabilities Without Training","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-06T16:45:59.645017Z"},"links":{"cited_paper":"/paper/2503.11314","citing_paper":"/paper/2507.12759"},"observation_digest":"sha256:a471f21344e2ceedb77a7c23b91187bd35ac36e94f9e93841e9079f5f5e1b4ca","observation_id":"52fc4979-7cf7-4065-99ee-5faba847a214","resolution":{"observed_at":"2026-08-06T16:45:59.645017Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.11314","last_updated":"2025-06-11T03:55:09Z","snapshot_observed_at":"2026-08-07T17:04:15.538727Z","submitted_at":"2025-03-14T11:30:37Z","title":"Unlocking General Long Chain-of-Thought Reasoning Capabilities of Large Language Models via Representation Engineering","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.11314","snapshot_observed_at":"2026-08-06T16:31:51.350436Z","title":"Unlocking general long chain-of-thought reasoning capabilities of large language models via representation engineering","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.13236","last_updated":"2025-07-17T15:47:22Z","snapshot_observed_at":"2026-08-07T18:24:30.449370Z","submitted_at":"2025-07-17T15:47:22Z","title":"Enhancing Cross-task Transfer of Large Language Models via Activation Steering","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T16:31:51.350436Z"},"links":{"cited_paper":"/paper/2503.11314","citing_paper":"/paper/2507.13236"},"observation_digest":"sha256:3df5f3c2e9a17e11a4cc6eb67f904993185b1c6cec4b4f187384998625c7c434","observation_id":"34ec79ad-94b0-41b6-8ca0-aacc6ccaf376","resolution":{"observed_at":"2026-08-06T16:31:51.350436Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.11314","last_updated":"2025-06-11T03:55:09Z","snapshot_observed_at":"2026-08-07T17:04:15.538727Z","submitted_at":"2025-03-14T11:30:37Z","title":"Unlocking General Long Chain-of-Thought Reasoning Capabilities of Large Language Models via Representation Engineering","version":2},"cited_work":{"arxiv_id":"2503.11314","doi":"10.48550/arxiv.2503.11314","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.11314","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://arxiv.org/abs/2503.11314","venue":"ArXiv.org","work_id":"8d1cf7a1-53e1-401d-b16b-f342bcf0e84c","year":null},"citing_paper":{"arxiv_id":"2510.24941","last_updated":"2026-05-26T22:58:09Z","snapshot_observed_at":"2026-08-08T14:16:18.113872Z","submitted_at":"2025-10-28T20:14:02Z","title":"Can Aha Moments Be Fake? Towards Quantifying Decorative and True Thinking in Chain-of-Thought","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-18T02:44:48.729794Z"},"links":{"cited_paper":"/paper/2503.11314","citing_paper":"/paper/2510.24941"},"observation_digest":"sha256:1a361fcb88031c3998141bf1c86a4700ec0c1cf951e6c9d0cb0e183bf3be2b85","observation_id":"44664614-d825-4fc8-8455-6fe5e4bea3fe","resolution":{"observed_at":"2026-05-18T02:45:46.080045Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.11314","last_updated":"2025-06-11T03:55:09Z","snapshot_observed_at":"2026-08-07T17:04:15.538727Z","submitted_at":"2025-03-14T11:30:37Z","title":"Unlocking General Long Chain-of-Thought Reasoning Capabilities of Large Language Models via Representation Engineering","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.11314","snapshot_observed_at":"2026-08-04T07:43:11.054073Z","title":"URLhttps://arxiv.org/abs/2503.11314","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2510.24941","last_updated":"2026-05-26T22:58:09Z","snapshot_observed_at":"2026-08-08T14:16:18.113872Z","submitted_at":"2025-10-28T20:14:02Z","title":"Can Aha Moments Be Fake? Towards Quantifying Decorative and True Thinking in Chain-of-Thought","version":4},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-04T07:43:11.054073Z"},"links":{"cited_paper":"/paper/2503.11314","citing_paper":"/paper/2510.24941"},"observation_digest":"sha256:55f9777f5fbe4bf1bdb21fc251eb25b39861950d70c224fcd3a95988dfbab84b","observation_id":"5052dfba-e5e8-402a-8bcf-9454afe32956","resolution":{"observed_at":"2026-08-04T07:43:11.054073Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.11314","last_updated":"2025-06-11T03:55:09Z","snapshot_observed_at":"2026-08-07T17:04:15.538727Z","submitted_at":"2025-03-14T11:30:37Z","title":"Unlocking General Long Chain-of-Thought Reasoning Capabilities of Large Language Models via Representation Engineering","version":2},"cited_work":{"arxiv_id":"2503.11314","doi":"10.48550/arxiv.2503.11314","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.11314","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://arxiv.org/abs/2503.11314","venue":"ArXiv.org","work_id":"8d1cf7a1-53e1-401d-b16b-f342bcf0e84c","year":null},"citing_paper":{"arxiv_id":"2606.06188","last_updated":"2026-06-04T13:59:07Z","snapshot_observed_at":"2026-07-06T23:46:05.829177Z","submitted_at":"2026-06-04T13:59:07Z","title":"The Tell-Tale Norm: $\\ell_2$ Magnitude as a Signal for Reasoning Dynamics in Large Language Models","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-06-28T02:07:49.501480Z"},"links":{"cited_paper":"/paper/2503.11314","citing_paper":"/paper/2606.06188"},"observation_digest":"sha256:d6d58e943499bd72a798e1f1da90fe0e26f7b82fca5b845e0902e7bcddb8109c","observation_id":"f1083680-137e-4169-b8f9-addc06fcf258","resolution":{"observed_at":"2026-07-02T12:26:56.915789Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2503.11314/citation-record","integrity":"/paper/2503.11314/integrity","json":"/paper/2503.11314/citation-record.json","paper":"/paper/2503.11314"},"outbound":[],"paper":{"arxiv_id":"2503.11314","last_updated":"2025-06-11T03:55:09Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-07T17:04:15.538727Z","submitted_at":"2025-03-14T11:30:37Z","title":"Unlocking General Long Chain-of-Thought Reasoning Capabilities of Large Language Models via Representation Engineering"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2503.11314."}