Paper Citation Record · LEDGER

TRUE: A Trustworthy Unified Explanation Framework for Large Language Model Reasoning

As of 17 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2602.18905.

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

pith.paper-citation-record.v1
2602.18905 v2

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T21:53:26.918890Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

17 of 17 outbound references displayed

verified exact0
verified fuzzy0
unresolved17
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 178a37ca-225c-41e1-8c05-63bdb7df4e4a · outbound

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

TRUE: A Trustworthy Unified Explanation Framework for Large Language Model Reasoning Measuring Faithfulness in Chain-of-Thought Reasoning

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T21:53:24.903462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b79a54e8-234a-45cf-8d40-d9ec911f0aba · outbound

This paper cites AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution.

TRUE: A Trustworthy Unified Explanation Framework for Large Language Model Reasoning AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T21:53:25.433447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 719ad747-8669-4c1f-b302-b89cfef2fc96 · outbound

This paper cites MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution.

TRUE: A Trustworthy Unified Explanation Framework for Large Language Model Reasoning MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T21:53:25.695298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0bf3130b-d837-4ac3-ba11-95891ddf2a2f · outbound

This paper cites Understanding Data Influence with Differential Approximation.

TRUE: A Trustworthy Unified Explanation Framework for Large Language Model Reasoning Understanding Data Influence with Differential Approximation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T21:53:25.839638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b1c14b0-7fb9-4a9b-bb1b-d35069f12709 · outbound

This paper cites llmshap: A principled approach to llm explainability.arXiv preprint arXiv:2511.01311,.

TRUE: A Trustworthy Unified Explanation Framework for Large Language Model Reasoning llmshap: A principled approach to llm explainability.arXiv preprint arXiv:2511.01311,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T21:53:25.968279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6dc2c33-d46c-4013-a9cf-62ff463f5d47 · outbound

This paper cites Larger language models do in-context learning differently.

TRUE: A Trustworthy Unified Explanation Framework for Large Language Model Reasoning Larger language models do in-context learning differently

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T21:53:26.043170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c31a810-4ffa-4c96-a9bc-0a806aef9f15 · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

TRUE: A Trustworthy Unified Explanation Framework for Large Language Model Reasoning Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T21:53:26.080314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47c4f35a-133d-492a-90c2-582a2617b741 · outbound

This paper cites Language models of code are few-shot commonsense learners.

TRUE: A Trustworthy Unified Explanation Framework for Large Language Model Reasoning Language models of code are few-shot commonsense learners

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T21:53:26.411356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 466587b8-1e77-4ea7-ae6e-057e7cdf0fc1 · outbound

This paper cites Context-faithful prompting for large language models.

TRUE: A Trustworthy Unified Explanation Framework for Large Language Model Reasoning Context-faithful prompting for large language models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T21:53:26.547495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81635b25-69fe-4d6e-8719-a41922030d22 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

TRUE: A Trustworthy Unified Explanation Framework for Large Language Model Reasoning Training Verifiers to Solve Math Word Problems

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T21:53:26.704754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a60cc988-f525-405d-a5d0-2857875fcd15 · outbound

This paper cites Challenging big-bench tasks and whether chain-of-thought can solve them.

TRUE: A Trustworthy Unified Explanation Framework for Large Language Model Reasoning Challenging big-bench tasks and whether chain-of-thought can solve them

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T21:53:26.918890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 353abfd0-4eb9-4e02-8e93-5118b77db2bf · outbound

This paper cites Noiser: Bounded Input Perturbations for Attributing Large Language Models.

TRUE: A Trustworthy Unified Explanation Framework for Large Language Model Reasoning Noiser: Bounded Input Perturbations for Attributing Large Language Models

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-02T21:53:25.165120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60568377-3447-4f88-92a0-aa7ee8ace0f9 · outbound

This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

TRUE: A Trustworthy Unified Explanation Framework for Large Language Model Reasoning Measuring Mathematical Problem Solving With the MATH Dataset

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-02T21:53:26.864750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8644593c-653a-42f7-b151-1ceb6376b2d5 · outbound

This paper cites SelfCite: Self-Supervised Alignment for Context Attribution in Large Language Models.

TRUE: A Trustworthy Unified Explanation Framework for Large Language Model Reasoning SelfCite: Self-Supervised Alignment for Context Attribution in Large Language Models

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-02T21:53:26.265790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d80453e-784a-450e-bec2-efb344f83f32 · outbound

This paper cites Making reasoning matter: Measuring and improving faithfulness of chain-of-thought reasoning.

TRUE: A Trustworthy Unified Explanation Framework for Large Language Model Reasoning Making reasoning matter: Measuring and improving faithfulness of chain-of-thought reasoning

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-02T21:53:25.015440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a3741a4-0b01-4754-9dff-5780c5ea5d0c · outbound

This paper cites Token- shapley: Token level context attribution with shapley value.

TRUE: A Trustworthy Unified Explanation Framework for Large Language Model Reasoning Token- shapley: Token level context attribution with shapley value

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-02T21:53:25.324750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 634ec39a-2a5b-44ed-9e38-0301e73496dc · outbound

This paper cites Faithfulness vs. Plausibility: On the (Un)Reliability of Explanations from Large Language Models.

TRUE: A Trustworthy Unified Explanation Framework for Large Language Model Reasoning Faithfulness vs. Plausibility: On the (Un)Reliability of Explanations from Large Language Models

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-02T21:53:25.091493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.