Paper Citation Record · LEDGER

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning

As of 4 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 1 inbound Pith citation observation for arXiv:2606.03503.

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

pith.paper-citation-record.v1
2606.03503 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T10:07:16.700499Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-14T02:43:21.225324Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

44 of 44 outbound references displayed

verified exact21
verified fuzzy0
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch19

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6a17d518-577d-485f-93ec-a358ec9531a0 · outbound

This paper cites L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-07-02T03:26:28.727043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f49cf19f-65d6-4322-bcfc-d2f993da2c88 · outbound

This paper cites Training language models to reason efficiently.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Training language models to reason efficiently

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-07-02T03:26:28.749820Z

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Observation b90073b6-9a96-4cb8-80e1-c83b82a53349 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Evaluating Large Language Models Trained on Code

Reference 3

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T03:26:28.742888Z

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Observation a08c83bf-c2b8-453c-9c63-8599e7c17ba4 · outbound

This paper cites Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs

Reference 4

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T03:26:28.695641Z

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Observation 424624be-bd9d-4c71-9937-eacdacd03bca · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Training Verifiers to Solve Math Word Problems

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-07-02T03:26:28.682833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 00d49656-5c80-4b7c-a988-356d2dd7e3bd · outbound

This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 6

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T03:26:28.711411Z

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Observation 5df9ee55-0072-4fd6-bfff-245c931b6251 · outbound

This paper cites S-GRPO: Early Exit via Reinforcement Learning in Reasoning Models.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning S-GRPO: Early Exit via Reinforcement Learning in Reasoning Models

Reference 7

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T03:26:28.760292Z

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Observation 3b9681ed-768e-4778-b904-b2b54736f487 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 8

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T03:26:28.775702Z

Source-reported events for the cited work

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Observation 456ea93d-5648-4ef8-b3e9-cf9f254949de · outbound

This paper cites Mask-DPO: Generalizable Fine-grained Factuality Alignment of LLMs.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Mask-DPO: Generalizable Fine-grained Factuality Alignment of LLMs

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-07-02T03:26:28.742129Z

Source-reported events for the cited work

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Observation b1985960-767d-4637-8247-67a50ccada79 · outbound

This paper cites Learning to reason faithfully through step-level faithful- ness maximization.arXiv preprint arXiv:2602.03507, 2026a.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Learning to reason faithfully through step-level faithful- ness maximization.arXiv preprint arXiv:2602.03507, 2026a

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-07-02T03:26:28.758857Z

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Observation 7fb7b005-ff50-4cc2-a597-31b394148e56 · outbound

This paper cites DeepMath-103K: A Large-Scale, Challenging, Decontaminated, and Verifiable Mathematical Dataset for Advancing Reasoning.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning DeepMath-103K: A Large-Scale, Challenging, Decontaminated, and Verifiable Mathematical Dataset for Advancing Reasoning

Reference 11

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T03:26:28.773294Z

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Observation 26cf7ce9-43bb-4cb4-a279-853901432f8d · outbound

This paper cites How Well do LLMs Compress Their Own Chain-of-Thought? A Token Complexity Approach.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning How Well do LLMs Compress Their Own Chain-of-Thought? A Token Complexity Approach

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-07-02T03:26:28.750825Z

Source-reported events for the cited work

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Observation 6e195617-8c4b-4b9e-9fa8-cf4dc2706ae0 · outbound

This paper cites Drpo: Efficient reasoning via decoupled reward policy optimization.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Drpo: Efficient reasoning via decoupled reward policy optimization

Reference 13

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T03:26:28.744968Z

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Observation 8c66803d-ef90-423c-94bd-8205ca26b35d · outbound

This paper cites Reward-Guided Speculative Decoding for Efficient LLM Reasoning.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Reward-Guided Speculative Decoding for Efficient LLM Reasoning

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-07-02T03:26:28.717883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation fd6a2328-aa74-4ade-942f-ff01d09b57fc · outbound

This paper cites Bridging the Semantic-Action Gap in Visual Token Pruning for Efficient VLA Inference.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Bridging the Semantic-Action Gap in Visual Token Pruning for Efficient VLA Inference

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-07-02T03:26:28.729967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 07c7eee8-2297-4021-9873-67667021732c · outbound

This paper cites Meta-Cognitive Memory Policy Optimization for Long-Horizon LLM Agents.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Meta-Cognitive Memory Policy Optimization for Long-Horizon LLM Agents

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-07-02T03:26:28.757256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation c9ec2970-a2df-4853-99da-8c2886a0abc0 · outbound

This paper cites O1-Pruner: Length-Harmonizing Fine-Tuning for O1-Like Reasoning Pruning.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning O1-Pruner: Length-Harmonizing Fine-Tuning for O1-Like Reasoning Pruning

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-07-02T03:26:28.714337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b86c0352-790e-429e-90fc-b886c36b1cfc · outbound

This paper cites Frost: Filtering reasoning outliers with attention for efficient reasoning,.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Frost: Filtering reasoning outliers with attention for efficient reasoning,

Reference 18

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T03:26:28.667074Z

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Observation 66151ee2-93b0-491c-af25-4bdabfcd5357 · outbound

This paper cites Improve Mathematical Reasoning in Language Models by Automated Process Supervision.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Improve Mathematical Reasoning in Language Models by Automated Process Supervision

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-07-02T03:26:28.663008Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 977a99e0-495d-45ce-8a61-167a6847f610 · outbound

This paper cites Reasoning Models Can Be Effective Without Thinking.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Reasoning Models Can Be Effective Without Thinking

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-07-02T03:26:28.714701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation dc880a4a-ee00-4cfb-bbb6-da8304e9a34d · outbound

This paper cites Topology of reasoning: Understanding large reasoning models through reasoning graph properties.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Topology of reasoning: Understanding large reasoning models through reasoning graph properties

Reference 21

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T03:26:28.736408Z

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Observation ead1920a-fd43-4a17-acb3-f7ceeb88bbd4 · outbound

This paper cites Qwen2.5 Technical Report.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Qwen2.5 Technical Report

Reference 22

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T03:26:28.780710Z

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Observation 58b9f8cf-c810-4e1f-a792-f6977e045ab2 · outbound

This paper cites Direct Preference Optimization: Your Language Model is Secretly a Reward Model.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-07-02T03:26:28.730179Z

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Observation 7747edd6-a26e-4d2c-bc2f-f7bae1c63685 · outbound

This paper cites GPQA: A Graduate-Level Google-Proof Q&A Benchmark.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning GPQA: A Graduate-Level Google-Proof Q&A Benchmark

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-07-02T03:26:28.770755Z

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Observation fb18b22d-e0e1-4696-8d94-68b31877574e · outbound

This paper cites Proximal Policy Optimization Algorithms.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Proximal Policy Optimization Algorithms

Reference 25

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T03:26:28.684199Z

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Observation 1a668184-5526-4283-b467-d483156f3efb · outbound

This paper cites Chain of Thoughtlessness? An Analysis of CoT in Planning.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Chain of Thoughtlessness? An Analysis of CoT in Planning

Reference 26

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T03:26:28.768340Z

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Observation 3f6dd0e9-963e-4cbf-8c38-76b256353d4f · outbound

This paper cites Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-07-02T03:26:28.778357Z

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Observation 7972abe0-66d3-437d-abbe-99fa35460622 · outbound

This paper cites Kimi k1.5: Scaling Reinforcement Learning with LLMs.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-07-02T03:26:28.747660Z

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Observation dee13020-45f3-4eb0-a6f7-6ecf490e045e · outbound

This paper cites Qwen3 Technical Report.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Qwen3 Technical Report

Reference 29

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T03:26:28.762668Z

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Observation d572c47d-b0fd-4fb3-84d6-b4530c9b83af · outbound

This paper cites Solving math word problems with process- and outcome-based feedback.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Solving math word problems with process- and outcome-based feedback

Reference 30

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T03:26:28.765345Z

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Observation 39722990-0ca4-4561-97f6-690734e12278 · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 31

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T03:26:28.747394Z

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Observation ae4513e5-c3c9-4c0e-aed9-990bd0152ffa · outbound

This paper cites Memory Networks.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Memory Networks

Reference 32

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T03:26:28.785354Z

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Observation 6535bcd3-7f99-4609-b5a4-28c92b11fa9e · outbound

This paper cites Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-07-02T03:26:28.703870Z

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Observation 3c4100a4-29da-44cd-b19e-b60ca32712d6 · outbound

This paper cites HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

Reference 34

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T03:26:28.739598Z

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Observation 465725f1-26d7-4222-91bd-8585078bb725 · outbound

This paper cites Distilling System 2 into System 1.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Distilling System 2 into System 1

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-07-02T03:26:28.717125Z

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Observation 023cf850-694b-4f31-97dc-469375cd5844 · outbound

This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-07-02T03:26:28.733463Z

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Observation 277f1f2b-2cac-4fcd-95de-d094d35fc5de · outbound

This paper cites Efficient rl training for reasoning models via length-aware optimization.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Efficient rl training for reasoning models via length-aware optimization

Reference 37

Resolution: unresolved; no resolver link, observed 2026-06-28T10:07:16.700499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdade60b-217c-4cc8-8d78-7d16e40bf6c8 · outbound

This paper cites Promoting Efficient Reasoning with Verifiable Stepwise Reward.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Promoting Efficient Reasoning with Verifiable Stepwise Reward

Reference 38

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T03:26:28.773789Z

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Observation 62a23dee-e4dd-4c7c-8039-48fe40462f59 · outbound

This paper cites STaR: Bootstrapping Reasoning With Reasoning.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning STaR: Bootstrapping Reasoning With Reasoning

Reference 39

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T03:26:28.783144Z

Source-reported events for the cited work

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Observation d9e616b2-281e-4a7c-bae7-49caaba5bf14 · outbound

This paper cites Intern-s1-pro: Scientific multimodal foundation model at trillion scale.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Intern-s1-pro: Scientific multimodal foundation model at trillion scale

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-07-02T03:26:28.770707Z

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Observation 33041e62-0011-49dc-bacd-603141ca1b7e · outbound

This paper cites Quantile radius analysis We characterize the resulting representation distributions using the Effective Radius.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Quantile radius analysis We characterize the resulting representation distributions using the Effective Radius

Reference 41

Resolution: unresolved; no resolver link, observed 2026-06-28T10:07:16.700499Z

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Observation c42a5d70-495e-4e28-b384-9015b1553330 · outbound

This paper cites Recent works further improve PRM data construction or stepwise correction for mathematical reasoning (Sun et al., 2025; Wu et al., 2025b).

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Recent works further improve PRM data construction or stepwise correction for mathematical reasoning (Sun et al., 2025; Wu et al., 2025b)

Reference 42

Resolution: unresolved; no resolver link, observed 2026-06-28T10:07:16.700499Z

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Observation 33e5e486-5ea0-4d3b-8911-aefbb7f4716e · outbound

This paper cites Beyond these applications, RL has been widely applied to practical optimization scenarios, such as chip design (Geng et al., 2024; 2025; Wang et al., 2026).

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Beyond these applications, RL has been widely applied to practical optimization scenarios, such as chip design (Geng et al., 2024; 2025; Wang et al., 2026)

Reference 43

Resolution: unresolved; no resolver link, observed 2026-06-28T10:07:16.700499Z

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Observation d192b59f-c233-435f-b6d1-5eb2de62510b · outbound

This paper cites These findings support the use of answer-to-reasoning attention as a practical proxy for identifying low-contribution reasoning steps.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning These findings support the use of answer-to-reasoning attention as a practical proxy for identifying low-contribution reasoning steps

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-07-02T03:26:28.723579Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Pith citing papers

Observation 2cb42830-614a-4c62-bcd0-5bb19caaf82c · inbound

AdvancedMathBench: A Benchmark Suite for Advanced Mathematical Proof Generation and Verification cites this paper.

AdvancedMathBench: A Benchmark Suite for Advanced Mathematical Proof Generation and Verification ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-14T02:43:21.225324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.