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Paper Citation Record · LEDGER

Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 25 inbound Pith citation observations for arXiv:2212.10001.

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

pith.paper-citation-record.v1
2212.10001 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 25 of 25 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:52:20.629456Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

9
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 573a0b81-4faa-45e2-b2fe-bb738b523942 · inbound

Towards Expert-Level Medical Question Answering with Large Language Models cites this paper.

Towards Expert-Level Medical Question Answering with Large Language Models Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 99

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arxiv_id, observed 2026-05-24T04:32:33.618342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-05-24T04:32:33.271634Z digest=sha256:7de64866eb26cb56952dd8460de0d3501bab236d645c19818902961d8c954188

Observation ba27426c-431b-42dd-827a-9b00cf0d4092 · inbound

RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback cites this paper.

RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 118

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arxiv_id, observed 2026-05-15T21:32:28.013923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-05-15T21:32:27.806494Z digest=sha256:7ba00629713b12d43cdc2a37d4cc935f806c1e159c6f74b17b0ae29feeaa1f06

Observation 5e1babae-523a-425d-8438-b31ab05443fe · inbound

Training Language Models to Self-Correct via Reinforcement Learning cites this paper.

Training Language Models to Self-Correct via Reinforcement Learning Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 125

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arxiv_id, observed 2026-05-17T12:04:10.652277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-05-17T12:04:10.210508Z digest=sha256:47e2068cdf24a59fe6bdbd404bfbe9a4d81dff67f0e5b4aa39eb92cdbe924c70

Observation 2bcf1209-3a31-4db7-8bb9-9b63c2e0e948 · inbound

Towards Specification-Driven LLM-Based Generation of Embedded Automotive Software cites this paper.

Towards Specification-Driven LLM-Based Generation of Embedded Automotive Software Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 37

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no resolver link, observed 2026-08-12T16:42:23.564934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:42:23.564934Z digest=sha256:732d00d8dcfdcc0ab2466a27a7813f1f4101a0ad69f1c3802575c6e2590073a4

Observation 2ca4db71-6e65-4b7c-a84b-57c8bbd7c04c · inbound

PhyT2V: LLM-Guided Iterative Self-Refinement for Physics-Grounded Text-to-Video Generation cites this paper.

PhyT2V: LLM-Guided Iterative Self-Refinement for Physics-Grounded Text-to-Video Generation Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 38

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no resolver link, observed 2026-08-12T05:16:59.595761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:16:59.595761Z digest=sha256:082cb82830aa6104038b82e4c76aac5a79d3b8e5b55b3743584eb72bb9ecbb72

Observation d8cbbbcd-cec7-408b-832f-a025516fb4fc · inbound

Training Large Language Models to Reason in a Continuous Latent Space cites this paper.

Training Large Language Models to Reason in a Continuous Latent Space Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-11T10:29:05.843182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation a34f3211-2349-41c9-b142-f2d2abf8f2c9 · inbound

A non-ergodic framework for understanding emergent capabilities in Large Language Models cites this paper.

A non-ergodic framework for understanding emergent capabilities in Large Language Models Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 124

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no resolver link, observed 2026-08-10T22:27:47.981731Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:27:47.981731Z digest=sha256:e0626e9f66bff676c619723d69fb9badeb1463218b71b210ff9e2faab25d1afe

Observation 762e25e8-34e0-428d-aba7-a6cc621749e5 · inbound

Large Language Models to Diffusion Finetuning cites this paper.

Large Language Models to Diffusion Finetuning Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 42

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no resolver link, observed 2026-08-10T14:01:55.635017Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:01:55.635017Z digest=sha256:5f09cb1c37f8575b76a0ba95c0bab3fb2a6ba3d69f93066d31e70eb297613534

Observation 909104fc-f6bc-403b-bcd1-2c34922e305e · inbound

Towards Sustainable NLP: Insights from Benchmarking Inference Energy in Large Language Models cites this paper.

Towards Sustainable NLP: Insights from Benchmarking Inference Energy in Large Language Models Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 47

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no resolver link, observed 2026-08-08T18:41:32.531338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T18:41:32.531338Z digest=sha256:3e0e0df5692bf16e9a4678be5745f48150341ab21afe4cb640647d5b248f0328

Observation 173ef2ff-54f8-439b-adec-bcbda335e871 · inbound

XiHeFusion: Harnessing Large Language Models for Science Communication in Nuclear Fusion cites this paper.

XiHeFusion: Harnessing Large Language Models for Science Communication in Nuclear Fusion Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 48

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no resolver link, observed 2026-08-08T18:39:26.873992Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:39:26.873992Z digest=sha256:5fdbe411d0ed0ec46db6b88f3fe9aa74ab27287f013d1f7431c878060973c817

Observation d2720872-3cda-4532-bf12-a9a4e8fc54e8 · inbound

Towards an AI co-scientist cites this paper.

Towards an AI co-scientist Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 181

Resolution
verified exact
arxiv_id, observed 2026-05-11T13:02:45.118046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-05-11T13:02:43.571234Z digest=sha256:12ce834cb1e3da54811fde0a2cd01eceadbbfb95cab6b4e01e3481385a9a9ea3

Observation c9b7f3f1-9ee2-4f7a-8190-72f813afaabc · inbound

From Evidence to Belief: A Bayesian Epistemology Approach to Language Models cites this paper.

From Evidence to Belief: A Bayesian Epistemology Approach to Language Models Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 38

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unresolved
no resolver link, observed 2026-08-16T05:52:20.629456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T05:52:20.629456Z digest=sha256:d00fc37ca3b9a1546f31fa3f88ed3d6116e8345efc592131a7d0b9a30d754124

Observation aa40e47a-7999-4e18-b18a-4452f49aab27 · inbound

Benchmarking LLMs in an Embodied Environment for Blue Team Threat Hunting cites this paper.

Benchmarking LLMs in an Embodied Environment for Blue Team Threat Hunting Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 92

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no resolver link, observed 2026-08-15T20:50:08.318950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:50:08.318950Z digest=sha256:74af57a94cd6fd7ae25c576b0e4da87fd04fdf80c91e14e9863b113876ae6d46

Observation b91d63d8-6028-4394-83f3-e7d694b1c80f · inbound

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects cites this paper.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 44

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no resolver link, observed 2026-08-07T14:02:54.752609Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:54.752609Z digest=sha256:f57de8fc0b859327b214dc411ddb5a688c7a67220b9507bf7d3ddbbe89d127da

Observation 54c04625-fb6d-4afd-a67b-5184e21149d3 · inbound

Toward Structured Knowledge Reasoning: Contrastive Retrieval-Augmented Generation on Experience cites this paper.

Toward Structured Knowledge Reasoning: Contrastive Retrieval-Augmented Generation on Experience Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 44

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no resolver link, observed 2026-08-07T12:02:01.203439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:02:01.203439Z digest=sha256:cd5445e7f7fe46defba1a2a71e1be8b05008b88edb10037cf57af67ca2bc981c

Observation e489ebc3-cc2f-4070-8a70-64637c89b932 · inbound

SuperRL: Reinforcement Learning with Supervision to Boost Language Model Reasoning cites this paper.

SuperRL: Reinforcement Learning with Supervision to Boost Language Model Reasoning Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 4

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no resolver link, observed 2026-08-07T11:55:03.162009Z

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Unavailable: canonical work link unavailable.

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Observation b820f736-39c1-48c9-8252-0031a060102b · inbound

A Statistical Physics of Language Model Reasoning cites this paper.

A Statistical Physics of Language Model Reasoning Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 37

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no resolver link, observed 2026-08-07T10:50:54.238608Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:50:54.238608Z digest=sha256:521905303590915eb21e66f77d95134bb7cfdedffbce3a290f4782296af16dce

Observation baf7a07b-7520-4b4b-ad2f-faac2d4e86b9 · inbound

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models cites this paper.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 41

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no resolver link, observed 2026-08-07T06:09:18.865615Z

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Observation dada2299-e478-4505-a5b2-83ec775c3ed9 · inbound

Distinct Computations Emerge From Compositional Curricula in In-Context Learning cites this paper.

Distinct Computations Emerge From Compositional Curricula in In-Context Learning Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 48

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no resolver link, observed 2026-08-07T00:41:59.042862Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3bbc517c-394d-4f27-b53a-39185559dc19 · inbound

WebGuard: Building a Generalizable Guardrail for Web Agents cites this paper.

WebGuard: Building a Generalizable Guardrail for Web Agents Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-06T16:12:50.719954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:12:50.719954Z digest=sha256:b1eae01ca37f62081174ad3e540536b2e5abf922cb0d2c050774059177e8739a

Observation 327841fc-0247-4d77-829c-1b6491e081e8 · inbound

GenoMAS: A Multi-Agent Framework for Scientific Discovery via Code-Driven Gene Expression Analysis cites this paper.

GenoMAS: A Multi-Agent Framework for Scientific Discovery via Code-Driven Gene Expression Analysis Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 117

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verified exact
arxiv_id, observed 2026-05-22T00:40:50.852037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 24a463b9-bcb9-479c-9c74-10d3354b88aa · inbound

Benchmarking LLM-Assisted Blue Teaming via Standardized Threat Hunting cites this paper.

Benchmarking LLM-Assisted Blue Teaming via Standardized Threat Hunting Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 28

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no resolver link, observed 2026-08-04T14:42:59.598970Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:42:59.598970Z digest=sha256:83d62b979a85c582c194892473350642aebe1229256b24f8f32529b70dc89c69

Observation 9f7f78bc-dc1d-4a6c-9f4d-158b6e3b13e7 · inbound

Attention Illuminates LLM Reasoning: The Preplan-and-Anchor Rhythm Enables Fine-Grained Policy Optimization cites this paper.

Attention Illuminates LLM Reasoning: The Preplan-and-Anchor Rhythm Enables Fine-Grained Policy Optimization Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 60

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no resolver link, observed 2026-08-04T09:48:09.510930Z

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Unavailable: canonical work link unavailable.

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Observation e8b922bd-8073-489b-a3a2-d81e7b72e211 · inbound

NoisyCoconut: Counterfactual Consensus via Latent Space Reasoning cites this paper.

NoisyCoconut: Counterfactual Consensus via Latent Space Reasoning Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 46

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arxiv_id, observed 2026-05-12T08:41:24.332031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-05-12T00:51:40.815981Z digest=sha256:479275144a8125847368f422ea2830eced912f149666cd87c995ff54ea590321

Observation e41c3365-be8c-4bf5-9f48-9af7ae4b5467 · inbound

DICE: Entropy-Regularized Equilibrium Selection for Stable Multi-Agent LLM Coordination cites this paper.

DICE: Entropy-Regularized Equilibrium Selection for Stable Multi-Agent LLM Coordination Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 66

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arxiv_id, observed 2026-07-02T21:07:23.529620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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