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Paper Citation Record · LEDGER

On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 21 inbound Pith citation observations for arXiv:2406.10625.

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

pith.paper-citation-record.v1
2406.10625 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 21 of 21 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:24:17.290151Z

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

  • verified exact0
  • verified fuzzy0
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  • malformed identifier0
  • metadata mismatch0

External citation measurements

1
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 09c9f66b-716a-465e-83de-76649220c553 · inbound

On the Impact of Fine-Tuning on Chain-of-Thought Reasoning cites this paper.

On the Impact of Fine-Tuning on Chain-of-Thought Reasoning On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-12T14:24:17.290151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T14:24:17.290151Z digest=sha256:26fdb1a2729f9a9700136344bdba9266e9b7efe57d085421249b4245299caaf3

Observation a8c562b6-bcec-484d-988c-bea27dfae1f9 · inbound

Chain-of-Thought in Large Language Models: Decoding, Projection, and Activation cites this paper.

Chain-of-Thought in Large Language Models: Decoding, Projection, and Activation On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-11T21:59:01.483095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T21:59:01.483095Z digest=sha256:4c6db91071dc427b823f2f70ef5094e77cc953631a00e25585bcdfe5d21eafd0

Observation 3075a40c-559d-4350-aab4-89c5e76f6332 · inbound

OpenAI o1 System Card cites this paper.

OpenAI o1 System Card On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-23T06:42:39.624072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-23T06:39:44.542350Z digest=sha256:725ae7974b26b6c4a20826226a53c1d7beed3301d6434e5e169c8d17fbbb0585

Observation 685fdebd-4b31-4b5b-8663-4919d8317334 · inbound

How Chain-of-Thought Works? Tracing Information Flow from Decoding, Projection, and Activation cites this paper.

How Chain-of-Thought Works? Tracing Information Flow from Decoding, Projection, and Activation On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-06T13:22:37.060218Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:22:37.060218Z digest=sha256:bc5229c32e9e95a1738079d2785d52ca093bd7cb5cc5a6aa00ffe656795aad23

Observation 4a0070ed-d8e2-4d98-a3da-f25a6077f16a · inbound

Do Cognitively Interpretable Reasoning Traces Improve LLM Performance? cites this paper.

Do Cognitively Interpretable Reasoning Traces Improve LLM Performance? On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-05T17:40:54.643811Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:40:54.643811Z digest=sha256:f95cdf822836d78614732395812c0e2b54deb80dca5ca686be2ec5822c1d962d

Observation bf208120-e27a-4f5a-a3f3-df5416e19825 · inbound

Parallel-R1: Towards Parallel Thinking via Reinforcement Learning cites this paper.

Parallel-R1: Towards Parallel Thinking via Reinforcement Learning On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-04T21:28:50.022641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:28:50.022641Z digest=sha256:8ec8fcac0cb34b242a413833f71ce39020e71b8451e7728d6b897ee9787002bd

Observation bfadc3db-912c-454d-9ceb-07050e484bf6 · inbound

Can Aha Moments Be Fake? Towards Quantifying Decorative and True Thinking in Chain-of-Thought cites this paper.

Can Aha Moments Be Fake? Towards Quantifying Decorative and True Thinking in Chain-of-Thought On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-18T02:45:46.126691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-18T02:44:48.729794Z digest=sha256:bd2dc26ccbacaa011bd255fbd2b2e7b83a8ed7eafe8b90aad6890440d35b45f6

Observation ea9d2334-50ef-4184-ba31-2bf74abbf2a3 · inbound

Can Aha Moments Be Fake? Towards Quantifying Decorative and True Thinking in Chain-of-Thought cites this paper.

Can Aha Moments Be Fake? Towards Quantifying Decorative and True Thinking in Chain-of-Thought On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-04T07:43:11.160170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T07:43:11.160170Z digest=sha256:ed6f907f745eb3c4975a2f2bc794763cc82350732857981fa316f5baf9473636

Observation 418d1d95-c935-41dd-ab12-9a2063e9e52a · inbound

Compared to What? Baselines and Metrics for Counterfactual Prompting cites this paper.

Compared to What? Baselines and Metrics for Counterfactual Prompting On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-05-09T19:05:10.553352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-05-09T19:02:46.991897Z digest=sha256:13f329ce976b68ffaac74549897b29131681f6940541f2a2adf865295e92edea

Observation be89165d-874e-42e3-b8ce-0a2518606612 · inbound

The Reasoning Trap: An Information-Theoretic Bound on Closed-System Multi-Step LLM Reasoning cites this paper.

The Reasoning Trap: An Information-Theoretic Bound on Closed-System Multi-Step LLM Reasoning On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models

Reference 25

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T09:41:03.943052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-05-10T15:52:43.274993Z digest=sha256:9fd7be8886dc9db21ece7520783424750f61e91b1a41ef0ebeb185d6b3660333

Observation f3d213dc-ec91-4cb9-84ea-6ff04762b66b · inbound

Understanding Annotator Safety Policy with Interpretability cites this paper.

Understanding Annotator Safety Policy with Interpretability On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models

Reference 22

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T17:21:08.581008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-05-08T17:41:00.933594Z digest=sha256:c18faa49cd09588a7f206075de2192d71b50d3c1be907d0d36295d661ee8e275

Observation a0b2ec31-d6c9-4cfe-80c3-2f8211f39817 · inbound

Reasoning emerges from constrained inference manifolds in large language models cites this paper.

Reasoning emerges from constrained inference manifolds in large language models On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-12T02:01:15.359715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-12T01:58:30.713839Z digest=sha256:ce74fb2da81e2d46483933f7f21e1c3629deaf8353349e3298df7b23cbfd1322

Observation db79d215-bee5-4f19-a6e5-215e6c350eba · inbound

Decomposing and Steering Functional Metacognition in Large Language Models cites this paper.

Decomposing and Steering Functional Metacognition in Large Language Models On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:26:28.349602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-12T02:57:09.180530Z digest=sha256:e21b79ffcb95297e525f74fc7b79d4cc432331341d1e387582a8004079d935b2

Observation aed4e205-da54-466c-81ac-258f17331303 · inbound

When Reasoning Traces Become Performative: Step-Level Evidence that Chain-of-Thought Is an Imperfect Oversight Channel cites this paper.

When Reasoning Traces Become Performative: Step-Level Evidence that Chain-of-Thought Is an Imperfect Oversight Channel On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-05-13T06:32:24.369983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-13T06:30:12.558660Z digest=sha256:5a0cf20fd9ad0175caae31761e7cdf3bdcfb5745357c969b690a1653dbdbe573

Observation 519f611e-490e-4134-9feb-23ab5e7ed729 · inbound

Understanding and Mitigating Premature Confidence for Better LLM Reasoning cites this paper.

Understanding and Mitigating Premature Confidence for Better LLM Reasoning On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-06-30T14:04:44.398281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-06-30T14:03:25.913615Z digest=sha256:7508d7b5e753321f6ee08040ca80142109662d6ee5ed1755cbe6b9c9e2d34e13

Observation 81d069ed-7a04-4c54-8b07-e963ac9e01c4 · inbound

Forecasting Future Behavior as a Learning Task cites this paper.

Forecasting Future Behavior as a Learning Task On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models

Reference 71

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T06:07:41.344564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-06-27T12:55:39.494339Z digest=sha256:3ec863c02c729fec54f20dfb0fccb75305c1b3b012f247141671cd21371ce840

Observation d91446b2-3930-47a8-a6dc-db1b9363932b · inbound

HANSEL: Extracting Breadcrumbs from Web Agent Trajectories for Interactive Verification cites this paper.

HANSEL: Extracting Breadcrumbs from Web Agent Trajectories for Interactive Verification On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-07-04T02:09:22.804433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-26T19:58:23.151980Z digest=sha256:3cde9f3bb12197b648ba8cd8d34f549a401c0899bd5896a8292810b87f4ed5cd

Observation 9a3a2b1c-d55d-4355-8974-10c51ef2e445 · inbound

Decodable but Not Faithful: Coupling Natural-Language Rationales to Programmatic Verifiers cites this paper.

Decodable but Not Faithful: Coupling Natural-Language Rationales to Programmatic Verifiers On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models

Reference 17

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T06:19:38.712958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-26T14:33:39.060591Z digest=sha256:ee3eac6a4412ea59cac4b935d4734e7c25916a026f771d2441da188b3dbfc254

Observation c420f8e8-fc27-40f4-bba4-defb566881fc · inbound

To Isolate or to Score? Model-Adaptive Assessment for Cost-Efficient Multi-Agent RAG cites this paper.

To Isolate or to Score? Model-Adaptive Assessment for Cost-Efficient Multi-Agent RAG On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models

Reference 44

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T18:40:02.370778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-06-25T22:44:43.951083Z digest=sha256:cac2186f8f949bb25ad04844565a6c8383766b9bb705e45c6f3d5af59701a2a9

Observation d79368c3-76ed-4246-a60f-e4ba47e22590 · inbound

Graph-Native Reinforcement Learning Enables Traceable Scientific Hypothesis Generation through Conceptual Recombination cites this paper.

Graph-Native Reinforcement Learning Enables Traceable Scientific Hypothesis Generation through Conceptual Recombination On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models

Reference 59

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T12:26:55.864269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-02T12:26:46.384850Z digest=sha256:b912531cec2e5b1d2c86d271dbb9c4f7f6b30aa79ae3523f03053cddbd1f87f7

Observation 02031709-db34-43fc-a0f6-b4c754478249 · inbound

CASE: Causal Alignment and Structural Enforcement for Improving Chain-of-Thought Faithfulness cites this paper.

CASE: Causal Alignment and Structural Enforcement for Improving Chain-of-Thought Faithfulness On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-01T14:17:27.493514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T14:17:27.493514Z digest=sha256:963a402be0596c0cc829eb894fc5e664a03c048f88dc3acf87482361ae699e59