{"as_of":"2026-08-19T14:11:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6c87df7b480e3c48052bf6da17a63448d0e51ed84a0989413886fad5b6c778bd","coverage":[{"denominator":48,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":48,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T18:20:49.663929Z","state":"measured"},{"denominator":50,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":50,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-03T19:52:11.018335Z","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":"2026-07-03T19:58:53.685679Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"cited_work":{"arxiv_id":"2507.18305","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2507.18305","snapshot_observed_at":"2026-07-03T19:58:53.685679Z","title":"Badreasoner: Planting tunable overthinking backdoors into large reasoning models for fun or profit,","venue":null,"work_id":"37641838-dbcd-4f4f-90b7-49412ccebfe4","year":2025},"citing_paper":{"arxiv_id":"2606.07968","last_updated":"2026-06-06T03:52:27Z","snapshot_observed_at":"2026-08-12T19:19:31.483970Z","submitted_at":"2026-06-06T03:52:27Z","title":"RecurGuard: Runtime Monitoring for Reasoning-Token Consumption Attacks","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-06-27T19:45:30.671490Z"},"links":{"cited_paper":"/paper/2507.18305","citing_paper":"/paper/2606.07968"},"observation_digest":"sha256:74c3406f2b40d832844f2882ac9150aa89c44486ecb53b7e952bd8ae43d954b6","observation_id":"914bc9d2-f0b4-42a4-9b2b-cdca0ed4450c","resolution":{"observed_at":"2026-07-02T21:27:24.560289Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"cited_work":{"arxiv_id":"2507.18305","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2507.18305","snapshot_observed_at":"2026-07-03T19:58:53.685679Z","title":"Badreasoner: Planting tunable overthinking backdoors into large reasoning models for fun or profit,","venue":null,"work_id":"37641838-dbcd-4f4f-90b7-49412ccebfe4","year":2025},"citing_paper":{"arxiv_id":"2607.01518","last_updated":"2026-07-01T22:31:10Z","snapshot_observed_at":"2026-08-12T15:56:48.128553Z","submitted_at":"2026-07-01T22:31:10Z","title":"Overthink-Triggered Slowdown Attacks on LVLM-Based Robotic Systems","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-07-03T19:52:11.018335Z"},"links":{"cited_paper":"/paper/2507.18305","citing_paper":"/paper/2607.01518"},"observation_digest":"sha256:836312fb5f6b6d35675df1715eb7f3066cb3450b00a7ad743bf51437ae9cb230","observation_id":"c03f65bb-bcf6-43be-adef-bf82afa81112","resolution":{"observed_at":"2026-07-03T19:58:53.687109Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2507.18305/citation-record","integrity":"/paper/2507.18305/integrity","json":"/paper/2507.18305/citation-record.json","paper":"/paper/2507.18305"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:20:50.538138Z","title":"Stealthy and persistent unalignment on large language models via backdoor injections","venue":null,"work_id":"f35fc3d1-0afa-4866-ac75-75c7a7a30c7e","year":2024},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.423120Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:92a83bb8ea82a327ad26bad671ce30d0e58aa4b1b972834a9d4542ada99bd02e","observation_id":"0e9db89c-04c3-4fca-84fd-ce7c031249f8","resolution":{"observed_at":"2026-08-15T18:20:50.542676Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.21187","last_updated":"2025-02-01T07:57:37Z","snapshot_observed_at":"2026-08-01T16:43:44.704797Z","submitted_at":"2024-12-30T18:55:12Z","title":"Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.21187","snapshot_observed_at":"2026-08-15T18:20:49.431194Z","title":"Do NOT think that much for 2+3=? on the overthinking of o1-like llms","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.431194Z"},"links":{"cited_paper":"/paper/2412.21187","citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:390aa7429cbc2911a42157830e8c5c0c88a7ee1e80521faf8226fbf6c27c0a0c","observation_id":"05476a2f-4644-4145-8486-8777fc9e4210","resolution":{"observed_at":"2026-08-15T18:20:49.431194Z","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":"2026-08-15T18:20:49.437459Z","title":"Training verifiers to solve math word problems","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.437459Z"},"links":{"cited_paper":"/paper/2110.14168","citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:0f6950be8354fd61110d913bec7215b7f4a5e4e836998aa2bf18834fd9496276","observation_id":"6a14410f-8e26-443e-9e39-321e2b9fc0a7","resolution":{"observed_at":"2026-08-15T18:20:49.437459Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.08235","last_updated":"2025-02-12T09:23:26Z","snapshot_observed_at":"2026-08-17T02:05:44.540631Z","submitted_at":"2025-02-12T09:23:26Z","title":"The Danger of Overthinking: Examining the Reasoning-Action Dilemma in Agentic Tasks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.08235","snapshot_observed_at":"2026-08-15T18:20:49.442782Z","title":"The danger of overthinking: Examining the reasoning-action dilemma in agentic tasks","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.442782Z"},"links":{"cited_paper":"/paper/2502.08235","citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:936dd99bfd9f166e8a9fa968f752632086822b32d00598180338d049c837250c","observation_id":"bc8a09ea-4929-4fbb-b902-dc53d57c9605","resolution":{"observed_at":"2026-08-15T18:20:49.442782Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.12948","last_updated":"2026-01-04T03:57:36Z","snapshot_observed_at":"2026-08-15T12:33:55.451951Z","submitted_at":"2025-01-22T15:19:35Z","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.12948","snapshot_observed_at":"2026-08-15T18:20:49.447759Z","title":"Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.447759Z"},"links":{"cited_paper":"/paper/2501.12948","citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:c7f693f78b9fa817a41f8ad15ca772b3d89ce2de16abf8cfe7c7fa573459d3f9","observation_id":"88a98d13-ff2a-4a13-b9ed-92d9cb10a856","resolution":{"observed_at":"2026-08-15T18:20:49.447759Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.19394","last_updated":"2025-02-13T03:00:18Z","snapshot_observed_at":"2026-08-18T03:58:47.491620Z","submitted_at":"2024-12-27T01:00:23Z","title":"An Engorgio Prompt Makes Large Language Model Babble on","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.19394","snapshot_observed_at":"2026-08-15T18:20:49.453101Z","title":"An engorgio prompt makes large language model babble on","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.453101Z"},"links":{"cited_paper":"/paper/2412.19394","citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:1d24e813aa514e664b4f55fae9e78f617350313d4e1a573528ef645558b9c3c6","observation_id":"cea1374a-4435-4553-b2a7-4e123213753f","resolution":{"observed_at":"2026-08-15T18:20:49.453101Z","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":"2026-08-15T18:20:50.523594Z","title":"Towards revealing the mystery behind chain of thought: A theoretical perspective","venue":null,"work_id":"b5e639ec-f26d-4a63-ba9e-76ec78e6b48f","year":2023},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.459317Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:a51711113d39de5cbae905a1a0b03e22406294a9875c064dcdcc0e647e66b943","observation_id":"2235fb81-823b-40a7-a1b5-5953287965aa","resolution":{"observed_at":"2026-08-15T18:20:50.528869Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.10760","last_updated":"2024-10-14T17:39:31Z","snapshot_observed_at":"2026-08-18T19:04:38.861432Z","submitted_at":"2024-10-14T17:39:31Z","title":"Denial-of-Service Poisoning Attacks against Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.10760","snapshot_observed_at":"2026-08-15T18:20:49.463977Z","title":"Denial-of-service poisoning attacks against large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.463977Z"},"links":{"cited_paper":"/paper/2410.10760","citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:c0275fea7575cea0ee162898d882ace93cbb8e0b8204362e20949b807374b09f","observation_id":"c1e1610d-5587-4038-9dd7-70158ce52b39","resolution":{"observed_at":"2026-08-15T18:20:49.463977Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.14020","last_updated":"2024-02-21T18:59:13Z","snapshot_observed_at":"2026-08-19T10:59:20.646492Z","submitted_at":"2024-02-21T18:59:13Z","title":"Coercing LLMs to do and reveal (almost) anything","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.14020","snapshot_observed_at":"2026-08-15T18:20:49.469492Z","title":"Coercing llms to do and reveal (almost) anything","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.469492Z"},"links":{"cited_paper":"/paper/2402.14020","citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:e6887af9523348381f908d65c754c66c493129eeffa4e92daa45457bbefe5257","observation_id":"850ee62a-b512-42e6-adc0-e3c89b2f3dff","resolution":{"observed_at":"2026-08-15T18:20:49.469492Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02406","last_updated":"2024-04-03T02:16:53Z","snapshot_observed_at":"2026-08-19T10:59:21.367861Z","submitted_at":"2024-04-03T02:16:53Z","title":"Exploring Backdoor Vulnerabilities of Chat Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02406","snapshot_observed_at":"2026-08-15T18:20:49.474056Z","title":"Exploring backdoor vulnerabilities of chat models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.474056Z"},"links":{"cited_paper":"/paper/2404.02406","citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:d461fc379c3bf09eb74f5c7678e435c40e42b17e9f0a27f6d9a612d4e2bd8055","observation_id":"71332089-ec13-4514-8671-cbafae29be19","resolution":{"observed_at":"2026-08-15T18:20:49.474056Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-08-19T11:46:55.171293Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-08-15T18:20:49.479378Z","title":"Openai o1 system card","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.479378Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:bbceabc29cd7239d458d74f4ba98376b79c6bf6ebf7585bec280fb9043770f10","observation_id":"29a178d2-4c44-4ab4-9d9a-14e37bc5287e","resolution":{"observed_at":"2026-08-15T18:20:49.479378Z","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":"2026-08-15T18:20:49.485425Z","title":"Overthink: Slowdown attacks on reasoning llms","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.485425Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:c3cabb377bf14a01106d7e6131824e0fe0a1eea133cb2fe4f13d1a76504f43eb","observation_id":"b5bf3fd7-1785-4157-aefc-552a07118c2d","resolution":{"observed_at":"2026-08-15T18:20:49.485425Z","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":"2026-08-15T18:20:50.510025Z","title":"Weight poisoning attacks on pretrained models","venue":null,"work_id":"a07b9ca6-523a-4984-b152-35039096fdbd","year":2020},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.490150Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:9d4acfdb0f0c515a465c265b7cef59759f6190898bd6616d9e43f34422b870ea","observation_id":"de4f0b73-234c-4d4f-9d23-eb456cb562a6","resolution":{"observed_at":"2026-08-15T18:20:50.514430Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.12798","last_updated":"2025-05-19T04:34:50Z","snapshot_observed_at":"2026-08-18T17:45:39.866113Z","submitted_at":"2024-08-23T02:21:21Z","title":"BackdoorLLM: A Comprehensive Benchmark for Backdoor Attacks and Defenses on Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.12798","snapshot_observed_at":"2026-08-15T18:20:49.495320Z","title":"Backdoorllm: A comprehensive benchmark for backdoor attacks on large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.495320Z"},"links":{"cited_paper":"/paper/2408.12798","citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:efbb7b679bc2e5074dd08e1fb7e5064cf30bbcc9b9573a123e059f351714b5f7","observation_id":"6d85ab41-edc1-4926-aad2-adf69e31d024","resolution":{"observed_at":"2026-08-15T18:20:49.495320Z","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":"2026-08-15T18:20:50.496359Z","title":"Backdoor learning: A survey","venue":null,"work_id":"4ca782e9-3329-4daa-8b3d-d23b99862f85","year":2022},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.500149Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:8231351e82191646521284f950afbdf101eb45edc0e5b5d4f1c449f53791299c","observation_id":"9deca424-1994-4363-829d-107b2ae1d246","resolution":{"observed_at":"2026-08-15T18:20:50.500821Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T18:20:50.482610Z","title":"Let's verify step by step","venue":null,"work_id":"d3ec2323-ebb3-4f66-86bc-24d9f4e40401","year":2023},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.505494Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:fada805b908ac880d37ace1b915abda620156ad28f920ce9fc02fcfd451d1eb7","observation_id":"83df5e0f-cd74-48b4-8c20-d1a3fe2cf019","resolution":{"observed_at":"2026-08-15T18:20:50.487332Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T18:20:50.468313Z","title":"Fine-pruning: Defending against backdooring attacks on deep neural networks","venue":null,"work_id":"9e8ed918-9370-4b4a-8cd3-71b3126cb7ad","year":2018},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.510294Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:2caa2c8bf9bc64b65a78ed1ab030fba5800721d0f6ba2478ad52fff71c891762","observation_id":"ffbb9464-34be-4c31-8aa4-85017f8dd4a9","resolution":{"observed_at":"2026-08-15T18:20:50.473134Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T18:20:50.453955Z","title":"Trojtext: Test-time invisible textual trojan insertion","venue":null,"work_id":"3aea539f-e54c-459a-ae30-fc43cd54e6b4","year":2023},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.515544Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:78c17e75cc401bdda36de992b3fb2a9b3f81afc6fe13968a3e48f2f7df7773f4","observation_id":"596ab527-3771-40e3-9f56-550348c959b8","resolution":{"observed_at":"2026-08-15T18:20:50.458671Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T18:20:50.439463Z","title":"Hidden trigger backdoor attack on NLP models via linguistic style manipulation","venue":null,"work_id":"3918380b-e923-4624-94af-1fba75606b46","year":2022},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.521367Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:cb6055535103f1e3fcea4749d26d5c49128de8ada72770a874dbb400d97b72b4","observation_id":"3a302ec1-bfc6-461d-b731-a2d9a1f29fec","resolution":{"observed_at":"2026-08-15T18:20:50.443856Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T18:20:50.425466Z","title":"Mind the style of text! adversarial and backdoor attacks based on text style transfer","venue":null,"work_id":"be94a65d-cc1c-4dae-ba44-a2002ab80287","year":2021},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.527177Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:a24c8014aee9b1574a4ab10cd3bb6e61bdd38b5773d3a3a796b5923950c78263","observation_id":"19f36903-bca8-4b29-86ba-9ddc63c9d3ac","resolution":{"observed_at":"2026-08-15T18:20:50.429979Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T18:20:50.411124Z","title":"Hidden killer: Invisible textual backdoor attacks with syntactic trigger","venue":null,"work_id":"34a82208-a892-485a-923d-8198d883eb3d","year":2021},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.532014Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:15e6d9c3c639093528313ac92e8893b8be5c55377a3c15710dc4a9cd7a41284f","observation_id":"b83080ef-a1b3-461d-9355-93ad4d46edc4","resolution":{"observed_at":"2026-08-15T18:20:50.415606Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T18:20:50.395673Z","title":"Fine-tuning aligned language models compromises safety, even when users do not intend to! In ICLR, 2024","venue":null,"work_id":"e9650613-09ae-4e7f-bf72-37d573c82360","year":2024},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.536661Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:e3239bede910bfe8914ef0e3a6789321d036df13f278228d430cdaa60e488c19","observation_id":"5fceee3e-6d24-40a9-af70-36ea43b310dd","resolution":{"observed_at":"2026-08-15T18:20:50.401404Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T18:20:50.380774Z","title":"Hello qwen2","venue":null,"work_id":"83896449-9861-4a3d-b1a5-41cf3ef985dd","year":2024},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.540840Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:b46056dd38ff9c0a931ac1d7652889c0ed7fe03f82df382f3058e5f2a1253176","observation_id":"9e988b3f-8c7f-42ce-a4a2-6187d0df488f","resolution":{"observed_at":"2026-08-15T18:20:50.385345Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T18:20:50.366859Z","title":"Qwq-32b: Embracing the power of reinforcement learning","venue":null,"work_id":"43b68161-8990-40ab-965d-cc2d7fc580a6","year":2025},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.545878Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:5ab769676ab59091f80c9e09b9b649b07a65c813b0ec0491a6c80116a97e64fc","observation_id":"6261e850-aea0-4bc2-bf6a-d00574ed861f","resolution":{"observed_at":"2026-08-15T18:20:50.371514Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T18:20:50.352627Z","title":"Universal jailbreak backdoors from poisoned human feedback","venue":null,"work_id":"12458407-22d2-4690-a36b-ea6a71d2bafb","year":2024},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.550611Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:3a56e054cc5c3fa33d6ac3686c9a3de09d923e291fa3c51a51d3cd2cd912c42a","observation_id":"e739cdbc-4858-4626-9d23-3e8d9fc18233","resolution":{"observed_at":"2026-08-15T18:20:50.357322Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T18:20:50.338807Z","title":"On the exploitability of instruction tuning","venue":null,"work_id":"6f71502a-c8d4-4d75-9a35-a9ee0494b85f","year":2023},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.555721Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:23314730da494631c5f8de40db71aeeb0c279b10912c8b4c364ea083457d6e5f","observation_id":"436d4c44-e35d-4e1e-903f-231f42b98d67","resolution":{"observed_at":"2026-08-15T18:20:50.343158Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T18:20:50.324239Z","title":"Sponge examples: Energy-latency attacks on neural networks","venue":null,"work_id":"f9cef280-46a3-4e37-8f21-736b1e4e00df","year":2021},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.560647Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:bbace7853bd9b25097c16a3d2effd5f171f98076c5045ad9b17a7c80df600835","observation_id":"eb149dfb-2d8c-4568-a9a3-65ed1dcfc025","resolution":{"observed_at":"2026-08-15T18:20:50.328871Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T18:20:49.565294Z","title":"Qwq: Reflect deeply on the boundaries of the unknown, November 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.565294Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:5200c5d81e2ccce1082c352372267fcd1d89cc25b550d55d84d456d253678463","observation_id":"6b88ae2f-777b-4a88-8113-3dcdfde3e529","resolution":{"observed_at":"2026-08-15T18:20:49.565294Z","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":"2026-08-15T18:20:50.300636Z","title":"Poisoning language models during instruction tuning","venue":null,"work_id":"dd50a4f6-0bbd-4aef-a5bf-e1a4e3dcc88a","year":2023},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.569710Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:161154c8cf453b083e5e7913398eaf9df8b84b264e23931743f43c0ad4eb937c","observation_id":"cae08903-eb78-4bf4-bd90-224d2f779b22","resolution":{"observed_at":"2026-08-15T18:20:50.305793Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.01652","last_updated":"2022-02-08T20:26:45Z","snapshot_observed_at":"2026-08-14T06:11:14.515796Z","submitted_at":"2021-09-03T17:55:52Z","title":"Finetuned Language Models Are Zero-Shot Learners","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.01652","snapshot_observed_at":"2026-08-15T18:20:49.574216Z","title":"Finetuned language models are zero-shot learners","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.574216Z"},"links":{"cited_paper":"/paper/2109.01652","citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:85af5972507632598d22dfef46a0ca3daafbb08b0c2cb1f1310746a288c7a573","observation_id":"21a37586-89b4-4b74-8fb5-c7cc82d90536","resolution":{"observed_at":"2026-08-15T18:20:49.574216Z","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":"2026-08-15T18:20:50.286415Z","title":"Chain-of-thought prompting elicits reasoning in large language models","venue":null,"work_id":"30da12ec-4657-4d75-ad36-0b942e045794","year":2022},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.579105Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:600dfa995c4fa2e077ffe761b64ee74daf4d72a0c51e15e32ef34eb4009943b6","observation_id":"7072eb48-4fa2-42b6-bf16-4d25f12f84a6","resolution":{"observed_at":"2026-08-15T18:20:50.291205Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.12242","last_updated":"2024-01-20T04:53:35Z","snapshot_observed_at":"2026-08-18T10:22:57.249193Z","submitted_at":"2024-01-20T04:53:35Z","title":"BadChain: Backdoor Chain-of-Thought Prompting for Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.12242","snapshot_observed_at":"2026-08-15T18:20:49.583507Z","title":"Badchain: Backdoor chain-of-thought prompting for large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.583507Z"},"links":{"cited_paper":"/paper/2401.12242","citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:f9b18b84ff09ddf03b500cd927dd892928a0fb682679b864b45204014688fdc1","observation_id":"7598b979-7287-4949-9f1d-b5c6051d8f66","resolution":{"observed_at":"2026-08-15T18:20:49.583507Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.09686","last_updated":"2025-01-23T08:44:44Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-01-16T17:37:58Z","title":"Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.09686","snapshot_observed_at":"2026-08-15T18:20:49.588169Z","title":"Towards large reasoning models: A survey of reinforced reasoning with large language models","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.588169Z"},"links":{"cited_paper":"/paper/2501.09686","citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:9ea4b2e8dd869cf32cf9616d43c7f191b00604a33942e3741c234dab98284059","observation_id":"db743a0c-585f-473a-8abf-e34ec0f01146","resolution":{"observed_at":"2026-08-15T18:20:49.588169Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.18600","last_updated":"2025-03-03T17:08:21Z","snapshot_observed_at":"2026-08-18T14:29:54.622995Z","submitted_at":"2025-02-25T19:36:06Z","title":"Chain of Draft: Thinking Faster by Writing Less","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.18600","snapshot_observed_at":"2026-08-15T18:20:49.592495Z","title":"Chain of draft: Thinking faster by writing less","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.592495Z"},"links":{"cited_paper":"/paper/2502.18600","citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:6489247d0734471eef327566f06337a02756b83ab431047be599820c0c409f8d","observation_id":"ec9420a7-05cc-4cd9-8f40-da17212da17e","resolution":{"observed_at":"2026-08-15T18:20:49.592495Z","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":"2026-08-15T18:20:50.271373Z","title":"BITE: textual backdoor attacks with iterative trigger injection","venue":null,"work_id":"2d011ec3-f3eb-42f9-9516-fb5ad7feeec7","year":2023},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.597671Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:8e75876fedd3e1716017ab68953a81eb4df971f7d98001d76009c1cfe277f7c1","observation_id":"6f3de590-9b2e-4c03-8d98-87b8a9f116e4","resolution":{"observed_at":"2026-08-15T18:20:50.276326Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T18:20:50.255527Z","title":"Backdooring instruction-tuned large language models with virtual prompt injection","venue":null,"work_id":"576cf454-8565-42d5-8c9c-32065c43ed04","year":2024},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.602338Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:07b39397a1b6767a675a97c37be6d6f46decb6e4040726010160e19a849b9088","observation_id":"d06cc7f9-9462-4017-9923-7428cdd9cf94","resolution":{"observed_at":"2026-08-15T18:20:50.260384Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T18:20:50.240890Z","title":"Backdooring instruction-tuned large language models with virtual prompt injection","venue":null,"work_id":"876696e5-b304-4db1-87c6-04eb6a87edde","year":2024},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.607653Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:6d55aeedaf1345fc1529652e338bb2ba9b5d112ab42574af60fbc3c05d1263d8","observation_id":"91dd9df1-80bf-4207-b76d-413407b1b99b","resolution":{"observed_at":"2026-08-15T18:20:50.245379Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.15115","last_updated":"2025-01-03T02:18:21Z","snapshot_observed_at":"2026-08-17T18:50:07.059564Z","submitted_at":"2024-12-19T17:56:09Z","title":"Qwen2.5 Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.15115","snapshot_observed_at":"2026-08-15T18:20:49.612101Z","title":"Qwen2.5 technical report","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.612101Z"},"links":{"cited_paper":"/paper/2412.15115","citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:336f6678ee989c2acdd4af92731476495869c73a010987b337833a2d6996c515","observation_id":"718fec48-86f6-4531-9e8b-3674139bef97","resolution":{"observed_at":"2026-08-15T18:20:49.612101Z","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":"2026-08-15T18:20:50.226133Z","title":"Be careful about poisoned word embeddings: Exploring the vulnerability of the embedding layers in NLP models","venue":null,"work_id":"5b704648-a4a0-4c6e-a859-6876b81e635a","year":2021},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.616989Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:5aa45b169e142acd44530d0fde295ae5ab407800a0abbb07a149cfbb62deae0c","observation_id":"1d8c7103-e43d-4af1-944e-a8f7e8b733a6","resolution":{"observed_at":"2026-08-15T18:20:50.231034Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T18:20:50.210429Z","title":"Probe before you talk: Towards black-box defense against backdoor unalignment for large language models","venue":null,"work_id":"a3d7ef9a-3718-48cd-831b-587372cec0b1","year":2025},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.621892Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:0d5b2b6c740c6494418720cebe534680921288ecb3878b14d79f014576addfb3","observation_id":"575769ce-f656-4d14-a12c-0e9e2cf6b97a","resolution":{"observed_at":"2026-08-15T18:20:50.215247Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.17092","last_updated":"2024-06-24T19:29:47Z","snapshot_observed_at":"2026-08-18T18:56:36.965879Z","submitted_at":"2024-06-24T19:29:47Z","title":"BEEAR: Embedding-based Adversarial Removal of Safety Backdoors in Instruction-tuned Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.17092","snapshot_observed_at":"2026-08-15T18:20:49.627441Z","title":"BEEAR: embedding-based adversarial removal of safety backdoors in instruction-tuned language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.627441Z"},"links":{"cited_paper":"/paper/2406.17092","citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:072919b7f1f7fc980c7c50d371f96171fc02cbedcb05a730fed674ff846beeba","observation_id":"662347fe-9e12-4593-b3d8-38a0dea076d8","resolution":{"observed_at":"2026-08-15T18:20:49.627441Z","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":"2026-08-15T18:20:50.193611Z","title":"Automatic chain of thought prompting in large language models","venue":null,"work_id":"bcb6fff2-67c9-4574-9bf9-228a403647a8","year":2023},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.632187Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:15af63ad5d557f2b7a18215089049446fc532ab39fcc57c30f1a2676e3e843cc","observation_id":"77cf6d71-6d0d-4126-96aa-5e31e15efa1b","resolution":{"observed_at":"2026-08-15T18:20:50.200113Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.14405","last_updated":"2024-11-25T17:57:55Z","snapshot_observed_at":"2026-08-18T11:40:03.096849Z","submitted_at":"2024-11-21T18:37:33Z","title":"Marco-o1: Towards Open Reasoning Models for Open-Ended Solutions","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.14405","snapshot_observed_at":"2026-08-15T18:20:49.637557Z","title":"Marco-o1: Towards open reasoning models for open-ended solutions","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.637557Z"},"links":{"cited_paper":"/paper/2411.14405","citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:326708f4fd20f0c8f242e98c728513fd5e51daa5fee887713848ccf43a8457ac","observation_id":"e685d0c6-60e3-409e-8859-4f2d0d800e80","resolution":{"observed_at":"2026-08-15T18:20:49.637557Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12202","last_updated":"2025-05-16T19:32:49Z","snapshot_observed_at":"2026-08-19T10:59:16.058886Z","submitted_at":"2025-02-16T10:45:56Z","title":"To Think or Not to Think: Exploring the Unthinking Vulnerability in Large Reasoning Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.12202","snapshot_observed_at":"2026-08-15T18:20:49.643167Z","title":"Bot: Breaking long thought processes of o1-like large language models through backdoor attack","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.643167Z"},"links":{"cited_paper":"/paper/2502.12202","citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:4b4873447cd0a1e7d07f700e9c85a6bb6841a903ced152ee56230bcb234c84e2","observation_id":"f4e22911-436d-4517-bfa7-23c32906200f","resolution":{"observed_at":"2026-08-15T18:20:49.643167Z","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":"2026-08-15T18:20:49.648136Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.648136Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:5527e9c2dd51532723eee5ddbadff7e9caf881b4f5db267f6692d7566f6fad40","observation_id":"c1c16fd0-ae33-45e1-80e5-c052dbe4dbce","resolution":{"observed_at":"2026-08-15T18:20:49.648136Z","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":"2026-08-15T18:20:49.653847Z","title":"@esa (Ref","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.653847Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:f5c4ff5a1072c655af1ec3d735c748c900ad31c420f8916ceb8c759620f703b3","observation_id":"c552472a-930c-4ec9-955d-4672982e9d1c","resolution":{"observed_at":"2026-08-15T18:20:49.653847Z","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":"2026-08-15T18:20:49.658895Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.658895Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:f1e2a9e71c38f239daa4d132a421e2b7b9784d622a0ed3c7242c7db7edb8314d","observation_id":"fa93ebb4-275e-4ecc-b4f9-b186b0963bb8","resolution":{"observed_at":"2026-08-15T18:20:49.658895Z","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":"2026-08-15T18:20:49.663929Z","title":"r 9gRam. (` : lB1.D[ٕZJ>]7O J]HDl G","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-15T18:20:49.663929Z"},"links":{"citing_paper":"/paper/2507.18305"},"observation_digest":"sha256:99daf38040cf7b2189687e5082f051075bcc8c18806c46b9df8068d144d8601f","observation_id":"df8ca008-18a7-4a0c-80ba-efebbb4504c0","resolution":{"observed_at":"2026-08-15T18:20:49.663929Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2507.18305","last_updated":"2025-07-24T11:24:35Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-19T06:14:27.620092Z","submitted_at":"2025-07-24T11:24:35Z","title":"BadReasoner: Planting Tunable Overthinking Backdoors into Large Reasoning Models for Fun or Profit"},"reference_resolution":{"displayed":48,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":24,"verified_exact":0,"verified_fuzzy":24},"total_outbound_references":48},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 2 inbound Pith citation observations for arXiv:2507.18305."}