Paper Citation Record · LEDGER

Faithful Reasoning Using Large Language Models

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:2208.14271.

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

pith.paper-citation-record.v1
2208.14271 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 19 of 19 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T05:35:51.228537Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T08:56:06.366379Z

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 999b0d38-48c2-4287-959e-379758affc6d · inbound

Language Models can Solve Computer Tasks cites this paper.

Language Models can Solve Computer Tasks Faithful Reasoning Using Large Language Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-17T12:17:26.808894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 74584527-13e7-44a6-a9d0-097b895abf5e · inbound

Tree of Thoughts: Deliberate Problem Solving with Large Language Models cites this paper.

Tree of Thoughts: Deliberate Problem Solving with Large Language Models Faithful Reasoning Using Large Language Models

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:36:42.549023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 36cec669-0e30-408e-b77f-a4540d8d5eee · inbound

Measuring Faithfulness in Chain-of-Thought Reasoning cites this paper.

Measuring Faithfulness in Chain-of-Thought Reasoning Faithful Reasoning Using Large Language Models

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:51:39.889349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6a550327-3d8f-4e36-9c7e-8bb57dd93b08 · inbound

TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis cites this paper.

TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis Faithful Reasoning Using Large Language Models

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-05-23T19:45:47.200018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 911bbbca-0825-4cfd-aebe-06eb822312c4 · inbound

Human-Like Code Quality Evaluation through LLM-based Recursive Semantic Comprehension cites this paper.

Human-Like Code Quality Evaluation through LLM-based Recursive Semantic Comprehension Faithful Reasoning Using Large Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T05:35:51.228537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ed755b8-7569-4ff0-89d1-601a80a9f9b5 · inbound

An Analysis for Reasoning Bias of Language Models with Small Initialization cites this paper.

An Analysis for Reasoning Bias of Language Models with Small Initialization Faithful Reasoning Using Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-09T05:28:51.257146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7740c2f-69f3-4a16-a198-602dd61e6a97 · inbound

Mechanistic Unveiling of Transformer Circuits: Self-Influence as a Key to Model Reasoning cites this paper.

Mechanistic Unveiling of Transformer Circuits: Self-Influence as a Key to Model Reasoning Faithful Reasoning Using Large Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T22:56:40.202648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0336c431-6fb7-4935-8201-33b9ddb6991d · inbound

Standardizing Intelligence: Aligning Generative AI for Regulatory and Operational Compliance cites this paper.

Standardizing Intelligence: Aligning Generative AI for Regulatory and Operational Compliance Faithful Reasoning Using Large Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-09T15:05:24.098531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 224d2730-c59d-4adc-8035-094f2b806e3d · inbound

Two-way Evidence self-Alignment based Dual-Gated Reasoning Enhancement cites this paper.

Two-way Evidence self-Alignment based Dual-Gated Reasoning Enhancement Faithful Reasoning Using Large Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T14:58:54.911313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a08dd8f6-c46d-439f-8826-c1fd52b48c8c · inbound

Interpretation Meets Safety: A Survey on Interpretation Methods and Tools for Improving LLM Safety cites this paper.

Interpretation Meets Safety: A Survey on Interpretation Methods and Tools for Improving LLM Safety Faithful Reasoning Using Large Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T10:24:26.340928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 266207b5-609b-4fec-853e-c460d0e88e97 · inbound

PuzzleWorld: A Benchmark for Multimodal, Open-Ended Reasoning in Puzzlehunts cites this paper.

PuzzleWorld: A Benchmark for Multimodal, Open-Ended Reasoning in Puzzlehunts Faithful Reasoning Using Large Language Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-19T10:47:15.185351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 994ffe3c-dd44-48b7-8e78-2cea2b753d93 · inbound

Visual Perceptual to Conceptual First-Order Rule Learning Networks cites this paper.

Visual Perceptual to Conceptual First-Order Rule Learning Networks Faithful Reasoning Using Large Language Models

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:41:01.127976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3c486980-7f17-4886-8626-76ba8409097b · inbound

Learning to Draw ASCII Improves Spatial Reasoning in Language Models cites this paper.

Learning to Draw ASCII Improves Spatial Reasoning in Language Models Faithful Reasoning Using Large Language Models

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T10:55:03.993838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5552ea0f-f286-4baf-9d37-a60e1fc1d5e0 · inbound

LLM Reasoning Is Latent, Not the Chain of Thought cites this paper.

LLM Reasoning Is Latent, Not the Chain of Thought Faithful Reasoning Using Large Language Models

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-10T08:53:04.670214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b5e98ca7-0a94-45df-8c9f-af2c4a8f84d5 · 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 Faithful Reasoning Using Large Language Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-13T06:32:24.363421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c7d6ca47-c488-4de3-9c8a-3b43b97f92d1 · inbound

Intelligence as Managed Autonomy: Failure, Escalation, and Governance for Agentic AI Systems cites this paper.

Intelligence as Managed Autonomy: Failure, Escalation, and Governance for Agentic AI Systems Faithful Reasoning Using Large Language Models

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-06-29T16:53:41.387455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 61f1df2f-a16e-49e4-9abe-51ac5fda19da · inbound

Know Your Limits : On the Faithfulness of LLMs as Solvers and Autoformalizers in Legal Reasoning cites this paper.

Know Your Limits : On the Faithfulness of LLMs as Solvers and Autoformalizers in Legal Reasoning Faithful Reasoning Using Large Language Models

Reference 25

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T17:18:43.467069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3087c3ed-e92c-4eb8-9d4d-cc945795c384 · inbound

Finetuning Lightweight LLMs for Control Flow Graph Generation cites this paper.

Finetuning Lightweight LLMs for Control Flow Graph Generation Faithful Reasoning Using Large Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-11T16:55:02.189375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 654002f1-471c-49dc-9952-ac1282d91091 · inbound

HIVE: Understanding Post-Hallucination Reasoning in Vision Language Models cites this paper.

HIVE: Understanding Post-Hallucination Reasoning in Vision Language Models Faithful Reasoning Using Large Language Models

Reference 5

Resolution: metadata mismatch; local_arxiv, observed 2026-07-09T08:56:06.370342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.