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Paper Citation Record · LEDGER

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping

As of 19 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2607.11089.

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

pith.paper-citation-record.v1
2607.11089 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-14T07:09:11.486851Z

measured 34 of 34 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 0 of 0 inbound itemization

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measured 0 of 1 external citation measurements

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Reference resolution

34 of 34 outbound references displayed

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  • verified fuzzy0
  • unresolved33
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

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Outbound references

Observation d502edfd-d6b6-4ef9-ab58-731057a46333 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models, 2023.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Chain-of-thought prompting elicits reasoning in large language models, 2023

Reference 1

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source=pdf_text observed=2026-07-14T07:09:11.486851Z digest=sha256:0d15de6a81be49b08399cab6567f7e6071f66067732e33440aabcc6bab9fb528

Observation 82b395ae-97aa-4ae3-b966-51c451053a43 · outbound

This paper cites Self-consistency improves chain of thought reasoning in language models, 2023.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Self-consistency improves chain of thought reasoning in language models, 2023

Reference 2

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source=pdf_text observed=2026-07-14T07:09:11.486851Z digest=sha256:2257f769a0c2084731f400a1decf05bb7eacdad9883da8f7e165048b51c2438a

Observation 9c9fa60a-b365-4705-9a65-96754c010f1a · outbound

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

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 3

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Observation c774fc75-4c1e-4fb1-9c13-7bc6be621f2f · outbound

This paper cites s1: Simple test-time scaling.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping s1: Simple test-time scaling

Reference 4

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source=pdf_text observed=2026-07-14T07:09:11.486851Z digest=sha256:18f6e68025af5b3e7047bfa70c2f1c20e045ac8b9d1f2e993820a1bb28341dee

Observation 042889fd-755d-475b-87ea-7df922a6101b · outbound

This paper cites Steering LLM Thinking with Budget Guidance.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Steering LLM Thinking with Budget Guidance

Reference 5

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source=pdf_text observed=2026-07-14T07:09:11.486851Z digest=sha256:8a3bfb3e13f244f29f3f6ef9c7ea5ad21106f720a6aa1e2edfef08351ee5a441

Observation de24d6c5-9489-42a2-9866-085dbf671fb1 · outbound

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

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping O1-Pruner: Length-Harmonizing Fine-Tuning for O1-Like Reasoning Pruning

Reference 6

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source=pdf_text observed=2026-07-14T07:09:11.486851Z digest=sha256:d8ba86c3555e4ec019df19e468d5cb09823698878506e067c8a3ad034a950b89

Observation 8191c467-aab2-4a78-a578-0a115e3bf2b5 · outbound

This paper cites TokenSkip: Control- lable Chain-of-Thought Compression in LLMs, September 2025.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping TokenSkip: Control- lable Chain-of-Thought Compression in LLMs, September 2025

Reference 7

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Observation ba08b205-c337-4aa5-929c-67de818be298 · outbound

This paper cites Making Slow Thinking Faster: Compressing LLM Chain-of-Thought via Step Entropy, February 2026.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Making Slow Thinking Faster: Compressing LLM Chain-of-Thought via Step Entropy, February 2026

Reference 8

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Observation e80696a1-3626-4ab2-9801-2340ddacfb9f · outbound

This paper cites DRPO: Efficient Reasoning via Decoupled Reward Policy Optimization, March 2026.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping DRPO: Efficient Reasoning via Decoupled Reward Policy Optimization, March 2026

Reference 9

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Observation cde9ea56-22ae-4e25-a597-70332969c2a7 · outbound

This paper cites HALT-CoT: Model-Agnostic Early Stopping for Chain-of-Thought Reasoning via Answer Entropy.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping HALT-CoT: Model-Agnostic Early Stopping for Chain-of-Thought Reasoning via Answer Entropy

Reference 10

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Observation fd6ee554-63e0-422f-9122-86723ad13bd7 · outbound

This paper cites Answer Convergence as a Signal for Early Stopping in Reasoning, September 2025.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Answer Convergence as a Signal for Early Stopping in Reasoning, September 2025

Reference 11

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source=pdf_text observed=2026-07-14T07:09:11.486851Z digest=sha256:7cf94181292177f4f776e1931a46b7bf8f2aafb0c66aa9c4c505596286ea2ffe

Observation 1a892f27-1215-4753-b7c3-693c9e512a43 · outbound

This paper cites Incentivizing llms to self-verify their answers, 2025.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Incentivizing llms to self-verify their answers, 2025

Reference 12

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Observation ac84fc34-3f0f-4421-b844-d9e111871f62 · outbound

This paper cites FlashThink: An Early Exit Method For Efficient Reasoning.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping FlashThink: An Early Exit Method For Efficient Reasoning

Reference 13

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Observation 95add1f7-315c-4f69-b96d-0c9b4ec3ef0d · outbound

This paper cites Early stopping chain-of-thoughts in large language models, 2025.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Early stopping chain-of-thoughts in large language models, 2025

Reference 14

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Observation 4a27be70-4b20-4e0f-9817-5a5a9f036749 · outbound

This paper cites an unresolved cited work.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Unresolved cited work

Reference 15

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Observation 53f89ed2-b511-481c-ae26-e990d94e3766 · outbound

This paper cites Compressed Chain of Thought: Efficient Reasoning Through Dense Representations.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Compressed Chain of Thought: Efficient Reasoning Through Dense Representations

Reference 16

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Observation cba8c4fe-f21f-44d7-9a6a-86be93b1d866 · outbound

This paper cites Training Large Language Models to Reason in a Continuous Latent Space, November.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Training Large Language Models to Reason in a Continuous Latent Space, November

Reference 17

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Observation 404239de-8450-4aaa-8082-ad0c1633701d · outbound

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

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Training Large Language Models to Reason in a Continuous Latent Space

Reference 18

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Observation 6c924ed9-c3a3-4c0a-a404-0f4e98bc2e87 · outbound

This paper cites Chain of Draft: Thinking Faster by Writing Less.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Chain of Draft: Thinking Faster by Writing Less

Reference 19

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Observation 75d36c36-051a-4411-ba67-da0210fea0f4 · outbound

This paper cites Think just enough: Sequence-level entropy as a confidence signal for llm reasoning, 2025.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Think just enough: Sequence-level entropy as a confidence signal for llm reasoning, 2025

Reference 20

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Observation b86529b8-7c9d-46d1-af26-e4397be40328 · outbound

This paper cites Dynamic early exit in reasoning models, 2025.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Dynamic early exit in reasoning models, 2025

Reference 21

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Observation 33ba503c-91a0-4007-be51-dda8abfb246d · outbound

This paper cites Stop when enough: Adaptive early-stopping for chain-of-thought reasoning, 2025.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Stop when enough: Adaptive early-stopping for chain-of-thought reasoning, 2025

Reference 22

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Observation c394bb84-fd5e-4b9d-874d-8b14a6e8e104 · outbound

This paper cites Reasoning models know when they’re right: Probing hidden states for self-verification, 2025.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Reasoning models know when they’re right: Probing hidden states for self-verification, 2025

Reference 23

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Observation 59bb95da-03ca-48ba-9767-d96281844284 · outbound

This paper cites Efficient Memory Management for Large Language Model Serving with PagedAttention.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Efficient Memory Management for Large Language Model Serving with PagedAttention

Reference 24

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Observation 8f3b2d51-b066-417b-b03b-9934dd5d82f7 · outbound

This paper cites Making Small Language Models Efficient Reasoners: Intervention, Supervision, Reinforcement.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Making Small Language Models Efficient Reasoners: Intervention, Supervision, Reinforcement

Reference 25

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Observation 4e71ce58-624a-436f-b1d8-9cb65a938658 · outbound

This paper cites Math-Verify: Math Verification Library, April 2026.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Math-Verify: Math Verification Library, April 2026

Reference 26

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Observation be607687-6488-4f27-908c-fa7156c9f832 · outbound

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OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Unresolved cited work

Reference 27

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Observation e63ba075-05ec-4261-9101-08ce6a4cba4b · outbound

This paper cites gpt-oss-120b & gpt-oss-20b Model Card.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping gpt-oss-120b & gpt-oss-20b Model Card

Reference 28

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Observation 23292f2b-08c0-44c6-bad5-175e48ac9ec9 · outbound

This paper cites Deepscaler: Surpassing o1-preview with a 1.5b model by scaling rl.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Deepscaler: Surpassing o1-preview with a 1.5b model by scaling rl

Reference 29

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Observation 54ae2a75-170f-4185-8607-c99e59f0dca6 · outbound

This paper cites Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models

Reference 30

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Observation 5cee0f84-8327-4472-91b3-f2f6f8d37402 · outbound

This paper cites Imitate, Explore, and Self-Improve: A Reproduction Report on Slow-thinking Reasoning Systems.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Imitate, Explore, and Self-Improve: A Reproduction Report on Slow-thinking Reasoning Systems

Reference 31

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Observation 78b0cac9-bfec-4d47-aa69-b1b4c9bfd22d · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Training Verifiers to Solve Math Word Problems

Reference 32

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Observation 53b6f6b8-48ad-461f-86b1-08bcd1b08f7d · outbound

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

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Measuring Mathematical Problem Solving With the MATH Dataset

Reference 33

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Observation aad71eb9-d891-49e1-a230-ec9834b12c36 · outbound

This paper cites Not all thoughts are generated equal: Efficient llm reasoning via multi-turn reinforcement learning, 2025.

OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping Not all thoughts are generated equal: Efficient llm reasoning via multi-turn reinforcement learning, 2025

Reference 34

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