Pith. sign in

Paper Citation Record · LEDGER

SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 27 inbound Pith citation observations for arXiv:2308.00436.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2308.00436 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 27 of 27 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T20:00:33.976818Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-06-28T22:32:44.141882Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 0e837d28-bad0-4b0c-a1f2-b45ca36ebb8c · inbound

The Rise and Potential of Large Language Model Based Agents: A Survey cites this paper.

The Rise and Potential of Large Language Model Based Agents: A Survey SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 193

Resolution
verified exact
arxiv_id, observed 2026-05-11T10:47:46.222821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-11T10:47:44.152066Z digest=sha256:a647f851708554127d2b7a6fcd69052070894b1c41b1396a6aa680d78215ba3b

Observation 38dcbf99-1582-4781-b99f-9986dc30edf1 · inbound

Chain-of-Verification Reduces Hallucination in Large Language Models cites this paper.

Chain-of-Verification Reduces Hallucination in Large Language Models SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 157

Resolution
verified exact
arxiv_id, observed 2026-05-18T01:06:50.409824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-18T01:06:49.811982Z digest=sha256:d11e9482978042b81baa4b17df083c22ca9d585207cefc4469542b514abd295e

Observation 46e09913-0d9e-4aa5-b7d5-7881ad19b495 · inbound

A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions cites this paper.

A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 222

Resolution
verified exact
arxiv_id, observed 2026-05-13T02:46:27.809338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-13T02:46:26.957539Z digest=sha256:140dae273ce7f1c032edd0b831427aedc96cb8b6c5b2292260d0a11be9e9caaa

Observation 209c1360-4b4d-42f4-a4bd-288159a192dc · inbound

Generating on Generated: An Approach Towards Self-Evolving Diffusion Models cites this paper.

Generating on Generated: An Approach Towards Self-Evolving Diffusion Models SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T20:00:33.976818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T20:00:33.976818Z digest=sha256:d876d61a8aa01cd66925d9708d3964a917cff1837626d0275bfae5962c653b49

Observation 5e402d76-4edb-4091-8121-0de4d404c0bc · inbound

From System 1 to System 2: A Survey of Reasoning Large Language Models cites this paper.

From System 1 to System 2: A Survey of Reasoning Large Language Models SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 225

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T01:36:24.353297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-13T01:36:23.845366Z digest=sha256:ffb3ac47a9f0ff47ca7a3bb5aa066cd1e329347c1779cb675dc63f4dc23e8232

Observation 51c50869-8ef4-42d7-9746-4530cff6eec3 · inbound

Hume: Introducing System-2 Thinking in Visual-Language-Action Model cites this paper.

Hume: Introducing System-2 Thinking in Visual-Language-Action Model SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T13:33:52.387699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:33:52.387699Z digest=sha256:e6bad9c92157e6c0c75526725e9123688407110e2423962651533134db1ab693

Observation 6524e2e9-6c6e-473d-a380-152a3b2dc499 · inbound

Do We Know What LLMs Don't Know? A Study of Consistency in Knowledge Probing cites this paper.

Do We Know What LLMs Don't Know? A Study of Consistency in Knowledge Probing SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T13:30:23.435924Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:30:23.435924Z digest=sha256:d5510af6d5cb97070ec2ad49378982a38286089d70f984448296778478114c07

Observation d46cbc78-a18d-4a5e-8f48-114d9fbd4dd6 · inbound

Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs cites this paper.

Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T10:19:34.293483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:19:34.293483Z digest=sha256:fb49b8282ab31f4c8a077981c88245696f3209a58a8bb0db0d0297db5eef9697

Observation 577bdf80-2172-450c-ae09-bc05272ed337 · inbound

Your Agent Can Defend Itself against Backdoor Attacks cites this paper.

Your Agent Can Defend Itself against Backdoor Attacks SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T05:20:51.450599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:20:51.450599Z digest=sha256:868dd8a5f1cf9c80a90d07c3eaaa9575e987533c949c088c4ad840bac5272b06

Observation 10e19b5b-e007-47c4-bf0a-f615dafda644 · inbound

InfoFlood: Jailbreaking Large Language Models with Information Overload cites this paper.

InfoFlood: Jailbreaking Large Language Models with Information Overload SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T01:02:29.757780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:29.757780Z digest=sha256:69c448d35a23734063688bd2cfb993f8019149c45536f5127b8ea33737485e8f

Observation 16d0f8f9-75ae-4667-bab6-dc0ebb366f70 · inbound

AdapThink: Adaptive Thinking Preferences for Reasoning Language Model cites this paper.

AdapThink: Adaptive Thinking Preferences for Reasoning Language Model SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T23:28:38.512970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:28:38.512970Z digest=sha256:7d16451dd11f8f44e3f9ae6ac66a64edda98782c150b865256a834bd2544f615

Observation b31ad758-aa48-443f-a570-3f45cd2915c6 · inbound

Leveraging Large Language Models for Tacit Knowledge Discovery in Organizational Contexts cites this paper.

Leveraging Large Language Models for Tacit Knowledge Discovery in Organizational Contexts SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T20:06:02.668456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:06:02.668456Z digest=sha256:9900c869801b0c9c2def692fe5f961d13c7dd5c2c44b2889d67c8c487325297d

Observation 73e5af91-525a-42e2-ac73-452c42689805 · inbound

MIND: A Multi-agent Framework for Zero-shot Harmful Meme Detection cites this paper.

MIND: A Multi-agent Framework for Zero-shot Harmful Meme Detection SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T18:56:56.865888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:56:56.865888Z digest=sha256:42b928ebf18f26936f14bfe4dbbe3491a8cd3c0cb1b1bb356c77b757942046ee

Observation 93896a37-39d3-4c5e-8033-f9456b9ac425 · inbound

I2CR: Intra- and Inter-modal Collaborative Reflections for Multimodal Entity Linking cites this paper.

I2CR: Intra- and Inter-modal Collaborative Reflections for Multimodal Entity Linking SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-06T05:11:13.114523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:11:13.114523Z digest=sha256:955bb698feab1eb03fb5584c94081d4bfd0de09cda9b325afa37e8053348b919

Observation 6b45c962-e0ab-40b9-8b22-7fa97c468793 · inbound

Beyond ROUGE: N-Gram Subspace Features for LLM Hallucination Detection cites this paper.

Beyond ROUGE: N-Gram Subspace Features for LLM Hallucination Detection SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-05T10:50:32.085327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:50:32.085327Z digest=sha256:eb8177b899f10632e21ca7a8275d5edf83992420245aa27b1aed9fe2d01f218a

Observation f232e0bd-caa4-42ea-941f-10928430d000 · inbound

Automatic Failure Attribution and Critical Step Prediction Method for Multi-Agent Systems Based on Causal Inference cites this paper.

Automatic Failure Attribution and Critical Step Prediction Method for Multi-Agent Systems Based on Causal Inference SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-04T20:21:21.815399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T20:21:21.815399Z digest=sha256:36651528f4d4099a0d48ea4d16ecc05c6076c62e4b0f81e2a0951a76dafae672

Observation 54fef558-5377-49d7-b80b-18e1e2a046a8 · inbound

ReMedi: Reasoner for Medical Clinical Prediction cites this paper.

ReMedi: Reasoner for Medical Clinical Prediction SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 65

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:01:06.018535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-09T14:20:29.672994Z digest=sha256:ac4494d2f0c9447b4e550cdbb14422d72e5d80a463dbfec687f187fb7bc8cfc2

Observation 85a09185-04ef-46eb-8b4c-252abddade3a · inbound

UnAC: Adaptive Visual Prompting with Abstraction and Stepwise Checking for Complex Multimodal Reasoning cites this paper.

UnAC: Adaptive Visual Prompting with Abstraction and Stepwise Checking for Complex Multimodal Reasoning SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-11T23:16:37.377658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-07T17:35:28.050906Z digest=sha256:6a54e5ed33b318c0645a6be5985881758c9fd8191d2958d287f2cac02abe89f8

Observation 2fd8b03d-6929-49a7-9060-ad9d60e770b6 · inbound

AgentForesight: Online Auditing for Early Failure Prediction in Multi-Agent Systems cites this paper.

AgentForesight: Online Auditing for Early Failure Prediction in Multi-Agent Systems SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-12T08:06:27.529436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-12T01:19:49.062330Z digest=sha256:3cc730ae735413d6717d9dcc7e48e16ae9fdb7f7b68340f147e5d02673f50011

Observation 2369fa24-1d32-4f0a-a595-b17acd3afbe8 · inbound

AgentForesight: Online Auditing for Early Failure Prediction in Multi-Agent Systems cites this paper.

AgentForesight: Online Auditing for Early Failure Prediction in Multi-Agent Systems SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-15T05:25:03.851275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T05:24:54.265411Z digest=sha256:9a8489bb5a3dfa7231cbe59c8bb889947f54bed297563559787cd1ff793b32aa

Observation 4b0b5e31-f5cd-450c-b036-1d7e88de0909 · inbound

Scalable Token-Level Hallucination Detection in Large Language Models cites this paper.

Scalable Token-Level Hallucination Detection in Large Language Models SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-05-13T05:52:22.379615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-13T05:49:23.534294Z digest=sha256:c3479c700f7d7516dd93007f592b0846e252c669bc271f28899618c413cfa67e

Observation cc76b331-db08-4ae1-9581-d981ca6f5540 · inbound

EvoGens: A Population-Based Heuristic Search Framework for Scientific Idea Generation cites this paper.

EvoGens: A Population-Based Heuristic Search Framework for Scientific Idea Generation SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-06-28T22:32:44.143341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-28T22:29:44.078911Z digest=sha256:21f08f5d946dee94c37b6dbffb61441bc5638faff4c898dc1fd4c19bbc4e8ff8

Observation cb6e3098-75a2-4ff6-ac78-20a386c36644 · inbound

Latent Reward Steering: An Adaptive Inference-Time Framework that Implicitly Promotes Cognitive Behaviors in Reasoning LLMs cites this paper.

Latent Reward Steering: An Adaptive Inference-Time Framework that Implicitly Promotes Cognitive Behaviors in Reasoning LLMs SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 67

Resolution
verified exact
arxiv_id, observed 2026-06-28T19:52:35.482916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-28T18:49:56.917505Z digest=sha256:b6c3403aee6fce69106525fdb88134cb2c4550d9267650bbf3c491d8e59d1b46

Observation 94c17467-d6c8-48e8-8adb-279432afb72f · inbound

Latent Reward Steering: An Adaptive Inference-Time Framework that Implicitly Promotes Cognitive Behaviors in Reasoning LLMs cites this paper.

Latent Reward Steering: An Adaptive Inference-Time Framework that Implicitly Promotes Cognitive Behaviors in Reasoning LLMs SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 1

Resolution
unresolved
no resolver link, observed 2026-07-13T07:46:18.094867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T07:46:18.094867Z digest=sha256:447e8755e98c2ee6bc76ba04283b8dd209b6fe99beabccc9d4f97f9457bd0f91

Observation ffa6d392-98c8-4243-9a3b-637d26879f03 · inbound

MentalThink: Shaping Thoughts in Mental SVG World cites this paper.

MentalThink: Shaping Thoughts in Mental SVG World SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 214

Resolution
unresolved
no resolver link, observed 2026-07-12T01:50:59.184754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T01:50:59.184754Z digest=sha256:f15b1372264dbfe4d89efcae7c89abc21af422ec6151e18a14bb7aff0e4f8cdc

Observation e255b79c-4dc2-48a3-ae0b-a520e5f64046 · inbound

Beyond Semantic Equivalence: Logical Graphs for LLM Uncertainty Quantification cites this paper.

Beyond Semantic Equivalence: Logical Graphs for LLM Uncertainty Quantification SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-01T19:46:59.475358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T19:46:59.475358Z digest=sha256:de91126b774d686c0c4d10d2498a9b1772083cd02e8db1cbacd597cae032a2ba

Observation 6fdd39e5-693e-4429-b245-b151e34af687 · inbound

Using LLMs for Explainable, Data-Driven Insight Generation from Time Series cites this paper.

Using LLMs for Explainable, Data-Driven Insight Generation from Time Series SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-02T12:15:24.501118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T12:15:24.501118Z digest=sha256:fafe70e6a6401cbb035017731c6c6d2b5b73e8f09393b0737c8c4e54e0f95c54