Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning | Paper Citation Record

Observation 80d9cd6b-36de-46fc-9d5f-4d915d320ab6 · inbound

Search, Verify and Feedback: Towards Next Generation Post-training Paradigm of Foundation Models via Verifier Engineering cites this paper.

Search, Verify and Feedback: Towards Next Generation Post-training Paradigm of Foundation Models via Verifier Engineering Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 135

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Observation 03f1aaf6-a946-4a12-8d6b-55ed8d4c73d0 · inbound

Towards Adaptive Mechanism Activation in Language Agent cites this paper.

Towards Adaptive Mechanism Activation in Language Agent Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 53

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Observation 492cfe2a-9964-483a-9eb5-c6b866a3df65 · inbound

From Multimodal LLMs to Generalist Embodied Agents: Methods and Lessons cites this paper.

From Multimodal LLMs to Generalist Embodied Agents: Methods and Lessons Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 92

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Observation 9e51b3f5-5634-463f-bc0e-2fa5f74376bd · inbound

A Systematic Examination of Preference Learning through the Lens of Instruction-Following cites this paper.

A Systematic Examination of Preference Learning through the Lens of Instruction-Following Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 23

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Observation 5d1afb34-b79c-41d5-a450-4c01cd1a1143 · inbound

Formal Mathematical Reasoning: A New Frontier in AI cites this paper.

Formal Mathematical Reasoning: A New Frontier in AI Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 204

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Observation f562407d-f349-4e75-ab5c-e7e219e36a82 · inbound

System-2 Mathematical Reasoning via Enriched Instruction Tuning cites this paper.

System-2 Mathematical Reasoning via Enriched Instruction Tuning Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 50

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Observation 8af40692-2384-4830-b52c-7e7b4d258317 · inbound

Towards Intrinsic Self-Correction Enhancement in Monte Carlo Tree Search Boosted Reasoning via Iterative Preference Learning cites this paper.

Towards Intrinsic Self-Correction Enhancement in Monte Carlo Tree Search Boosted Reasoning via Iterative Preference Learning Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 38

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Observation 88b8f79a-7ea5-42ed-aba9-38b42bd20d11 · inbound

Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search cites this paper.

Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 23

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Observation 454a3d22-e998-4677-8a83-aa9d8470165a · inbound

Enhancing Reasoning through Process Supervision with Monte Carlo Tree Search cites this paper.

Enhancing Reasoning through Process Supervision with Monte Carlo Tree Search Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 31

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Observation fc1a4bc7-b4e5-41a8-8d5c-28877f071ae2 · inbound

ReARTeR: Retrieval-Augmented Reasoning with Trustworthy Process Rewarding cites this paper.

ReARTeR: Retrieval-Augmented Reasoning with Trustworthy Process Rewarding Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 49

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Observation ce697286-0ca5-40b7-afc7-b01a640d9510 · inbound

Aligning Instruction Tuning with Pre-training cites this paper.

Aligning Instruction Tuning with Pre-training Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 59

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Observation 86487eec-c682-434f-a033-314558ab702d · inbound

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

Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 167

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Observation ae83e03f-ef37-4ed0-b88f-b93fdb94aeee · inbound

Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps cites this paper.

Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 91

Resolution: verified exact; arxiv_id, observed 2026-05-20T11:45:17.625495Z

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Observation 7f15cafc-3d7b-4b6b-ba01-2abf8ce793f2 · inbound

Efficient Multi-Agent System Training with Data Influence-Oriented Tree Search cites this paper.

Efficient Multi-Agent System Training with Data Influence-Oriented Tree Search Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-23T04:07:30.543382Z

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Observation ca48cf8c-0bac-4244-8be4-0fafc950c87c · inbound

Adversarial Reasoning at Jailbreaking Time cites this paper.

Adversarial Reasoning at Jailbreaking Time Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 50

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Observation 77bd2389-0d2d-41bf-8f95-2dc1e2df1484 · inbound

Metastable Dynamics of Chain-of-Thought Reasoning: Provable Benefits of Search, RL and Distillation cites this paper.

Metastable Dynamics of Chain-of-Thought Reasoning: Provable Benefits of Search, RL and Distillation Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 74

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Observation 7c5120fd-060a-47a6-a75e-7e2775365954 · inbound

LongDPO: Unlock Better Long-form Generation Abilities for LLMs via Critique-augmented Stepwise Information cites this paper.

LongDPO: Unlock Better Long-form Generation Abilities for LLMs via Critique-augmented Stepwise Information Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-09T13:25:52.121741Z

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Observation 54b0c245-e256-405e-8ae9-67f8c9c35f16 · inbound

Policy Guided Tree Search for Enhanced LLM Reasoning cites this paper.

Policy Guided Tree Search for Enhanced LLM Reasoning Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 64

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Observation f123c1d2-b171-4acc-94cb-4186e2f1a67d · inbound

The Process of Categorical Clipping at the Core of the Genesis of Concepts in Synthetic Neural Cognition cites this paper.

The Process of Categorical Clipping at the Core of the Genesis of Concepts in Synthetic Neural Cognition Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 148

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Observation e7b5c070-3cd7-411a-8e25-612bae7b00b3 · inbound

From System 1 to System 2: A Survey of Reasoning Large Language Models cites this paper.

From System 1 to System 2: A Survey of Reasoning Large Language Models Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 150

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Observation f0e36665-2446-416b-a711-e2d2184c22d7 · inbound

LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL cites this paper.

LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 84

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Observation d344b008-9029-4da1-81dc-eeaff6a905f7 · inbound

A Survey of Scaling in Large Language Model Reasoning cites this paper.

A Survey of Scaling in Large Language Model Reasoning Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 231

Resolution: verified exact; arxiv_id, observed 2026-05-22T21:22:09.274394Z

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Observation 1c7c246d-3af2-4f84-bb1f-362cefc559c0 · inbound

ReTool: Reinforcement Learning for Strategic Tool Use in LLMs cites this paper.

ReTool: Reinforcement Learning for Strategic Tool Use in LLMs Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:42:39.110987Z

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Observation 805bb766-d5da-4d30-91a4-13e94bd898b0 · inbound

$\texttt{Complex-Edit}$: CoT-Like Instruction Generation for Complexity-Controllable Image Editing Benchmark cites this paper.

$\texttt{Complex-Edit}$: CoT-Like Instruction Generation for Complexity-Controllable Image Editing Benchmark Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 30

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Observation deaae569-f1a2-4a1f-9d4a-da39a1702705 · inbound

Not All Rollouts are Useful: Down-Sampling Rollouts in LLM Reinforcement Learning cites this paper.

Not All Rollouts are Useful: Down-Sampling Rollouts in LLM Reinforcement Learning Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 22

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Observation 804c29ac-bac8-4d13-83af-ec00d9c83727 · inbound

Reinforced MLLM: A Survey on RL-Based Reasoning in Multimodal Large Language Models cites this paper.

Reinforced MLLM: A Survey on RL-Based Reasoning in Multimodal Large Language Models Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 122

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Observation ae813dbc-8b2a-44ac-b6b5-de339479dfe9 · inbound

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control cites this paper.

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 17

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Observation 4f91cc1d-8841-40dd-9af8-9bcdc9cc5114 · inbound

CEC-Zero: Chinese Error Correction Solution Based on LLM cites this paper.

CEC-Zero: Chinese Error Correction Solution Based on LLM Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 66

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Observation 41751754-982f-4da2-806c-b400fd83650d · inbound

Guided Search Strategies in Non-Serializable Environments with Applications to Software Engineering Agents cites this paper.

Guided Search Strategies in Non-Serializable Environments with Applications to Software Engineering Agents Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 451

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Observation 3996829b-ccc4-498e-994f-8efd91710467 · inbound

EquivPruner: Boosting Efficiency and Quality in LLM-Based Search via Action Pruning cites this paper.

EquivPruner: Boosting Efficiency and Quality in LLM-Based Search via Action Pruning Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 23

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Observation b0e8a27f-7ab7-4583-9ee6-bbe4a596520d · inbound

Reward Model Generalization for Compute-Aware Test-Time Reasoning cites this paper.

Reward Model Generalization for Compute-Aware Test-Time Reasoning Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 44

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Observation aab6bc26-c491-4c70-a393-298260d74354 · inbound

First Finish Search: Efficient Test-Time Scaling in Large Language Models cites this paper.

First Finish Search: Efficient Test-Time Scaling in Large Language Models Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:42.491053Z

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Observation 6ec0619b-14a4-4f90-832b-942fe44fa2fa · inbound

ASPO: Adaptive Sentence-Level Preference Optimization for Fine-Grained Multimodal Reasoning cites this paper.

ASPO: Adaptive Sentence-Level Preference Optimization for Fine-Grained Multimodal Reasoning Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 47

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Observation d28e2eda-1c8d-4a34-b6ab-382e6809f35a · inbound

Large Language Models for Planning: A Comprehensive and Systematic Survey cites this paper.

Large Language Models for Planning: A Comprehensive and Systematic Survey Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 288

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Observation 9bf720c4-d531-484a-9cea-ec5a7b6a8677 · inbound

Guided by Gut: Efficient Test-Time Scaling with Reinforced Intrinsic Confidence cites this paper.

Guided by Gut: Efficient Test-Time Scaling with Reinforced Intrinsic Confidence Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 39

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Observation 53db4d41-a0ef-45ab-a84d-865bbc38514c · inbound

Control-R: Towards controllable test-time scaling cites this paper.

Control-R: Towards controllable test-time scaling Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 7

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Observation a09a2f29-2492-42e0-b9f1-000907bd094a · inbound

Revisiting Test-Time Scaling: A Survey and a Diversity-Aware Method for Efficient Reasoning cites this paper.

Revisiting Test-Time Scaling: A Survey and a Diversity-Aware Method for Efficient Reasoning Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 92

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Observation f65d5de8-86c7-4087-8689-c8d1d2d00d61 · inbound

Just Enough Thinking: Efficient Reasoning with Adaptive Length Penalties Reinforcement Learning cites this paper.

Just Enough Thinking: Efficient Reasoning with Adaptive Length Penalties Reinforcement Learning Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 16

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Observation 8f17ab33-77d9-4642-8147-261668aec8db · inbound

AI Agent Behavioral Science cites this paper.

AI Agent Behavioral Science Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 172

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Observation 3f1b2dee-12e0-4eea-ac87-090838360a58 · inbound

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation cites this paper.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 40

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Observation 52378c17-6432-4034-b1cb-652c1758abaf · inbound

ViCrit: A Verifiable Reinforcement Learning Proxy Task for Visual Perception in VLMs cites this paper.

ViCrit: A Verifiable Reinforcement Learning Proxy Task for Visual Perception in VLMs Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 67

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Observation 23e05b3c-5c67-4de9-af7d-a2f197b49a0f · inbound

TreeRL: LLM Reinforcement Learning with On-Policy Tree Search cites this paper.

TreeRL: LLM Reinforcement Learning with On-Policy Tree Search Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 44

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Observation 5dfb5fc4-6623-405c-9e18-0c96c5b66eea · inbound

Aligning Frozen LLMs by Reinforcement Learning: An Iterative Reweight-then-Optimize Approach cites this paper.

Aligning Frozen LLMs by Reinforcement Learning: An Iterative Reweight-then-Optimize Approach Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-15T19:08:14.502275Z

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Observation e070fe5c-7e87-41b8-8a10-5bf39df4fad6 · inbound

PLoP: Precise LoRA Placement for Efficient Finetuning of Large Models cites this paper.

PLoP: Precise LoRA Placement for Efficient Finetuning of Large Models Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T22:50:14.576341Z

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Observation adf48413-f128-401a-9f20-b1603e517bd6 · inbound

Enhancing User Engagement in Socially-Driven Dialogue through Interactive LLM Alignments cites this paper.

Enhancing User Engagement in Socially-Driven Dialogue through Interactive LLM Alignments Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T22:30:15.833229Z

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Observation 11e6cd9d-3b1c-4b70-ac25-4c9c5de4798b · inbound

Interactive Reasoning: Visualizing and Controlling Chain-of-Thought Reasoning in Large Language Models cites this paper.

Interactive Reasoning: Visualizing and Controlling Chain-of-Thought Reasoning in Large Language Models Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-06T21:37:56.996116Z

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Observation e5e80796-9eed-4796-bcae-9ef353d7f30d · inbound

CaughtCheating: Is Your MLLM a Good Cheating Detective? Exploring the Boundary of Visual Perception and Reasoning cites this paper.

CaughtCheating: Is Your MLLM a Good Cheating Detective? Exploring the Boundary of Visual Perception and Reasoning Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-15T18:39:18.997563Z

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Observation 1c03327a-0a26-410a-9f02-e0d0947c75a1 · inbound

ChipSeek: Optimizing Verilog Generation via EDA-Integrated Reinforcement Learning cites this paper.

ChipSeek: Optimizing Verilog Generation via EDA-Integrated Reinforcement Learning Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 33

Resolution: metadata mismatch; arxiv_id, observed 2026-05-19T06:52:08.359154Z

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Observation da8eb2be-757c-408d-9572-55982b3900b1 · inbound

Large Language Models Reasoning Abilities Under Non-Ideal Conditions After RL-Fine-Tuning cites this paper.

Large Language Models Reasoning Abilities Under Non-Ideal Conditions After RL-Fine-Tuning Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T23:49:05.025670Z

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Observation 06bec0d1-228a-4eb2-8616-7e5318d67b2e · inbound

Building Task Bots with Self-learning for Enhanced Adaptability, Extensibility, and Factuality cites this paper.

Building Task Bots with Self-learning for Enhanced Adaptability, Extensibility, and Factuality Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 198

Resolution: unresolved; no resolver link, observed 2026-08-05T15:38:55.207976Z

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Observation 3ed8bf8c-fce5-4454-a622-c5bef9720374 · inbound

LLaVA-Critic-R1: Your Critic Model is Secretly a Strong Policy Model cites this paper.

LLaVA-Critic-R1: Your Critic Model is Secretly a Strong Policy Model Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-05T13:24:39.898650Z

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Observation aa814ac9-bc2e-474d-9163-cfea9b35fa5e · inbound

Retrieval-of-Thought: Efficient Reasoning via Reusing Thoughts cites this paper.

Retrieval-of-Thought: Efficient Reasoning via Reusing Thoughts Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T13:42:38.694348Z

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Observation 576f190c-e985-4613-8133-602f0e0edbac · inbound

Explore-Execute Chain: Towards an Efficient Structured Reasoning Paradigm cites this paper.

Explore-Execute Chain: Towards an Efficient Structured Reasoning Paradigm Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-04T14:44:39.878932Z

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Observation fbf825b4-52e4-4b83-8952-4c4bae846dfd · inbound

Less Diverse, Less Safe: The Indirect But Pervasive Risk of Test-Time Scaling in Large Language Models cites this paper.

Less Diverse, Less Safe: The Indirect But Pervasive Risk of Test-Time Scaling in Large Language Models Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T09:56:13.094934Z

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Observation 0f043711-7720-401a-a758-a72b39b21b18 · inbound

The Art of Scaling Reinforcement Learning Compute for LLMs cites this paper.

The Art of Scaling Reinforcement Learning Compute for LLMs Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 21

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T16:29:14.038199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b56b40c4-68a7-4348-99d7-7eb4484f2f73 · inbound

When Fewer Layers Break More Chains: Layer Pruning Harms Test-Time Scaling in LLMs cites this paper.

When Fewer Layers Break More Chains: Layer Pruning Harms Test-Time Scaling in LLMs Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-04T08:11:52.628741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1336d905-1baf-45fd-9289-70be4433e537 · inbound

Native Parallel Reasoner: Reasoning in Parallelism via Self-Distilled Reinforcement Learning cites this paper.

Native Parallel Reasoner: Reasoning in Parallelism via Self-Distilled Reinforcement Learning Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-17T01:13:47.957447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f41c982a-01ce-450e-8365-cea84e37ddb8 · inbound

Boosting RL-Based Visual Reasoning with Selective Adversarial Entropy Intervention cites this paper.

Boosting RL-Based Visual Reasoning with Selective Adversarial Entropy Intervention Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-03T17:15:17.701284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1427f7f5-f06b-4302-885a-0aeb295ecd74 · inbound

Can I Have Your Order? Monte-Carlo Tree Search for Slot Filling Ordering in Diffusion Language Models cites this paper.

Can I Have Your Order? Monte-Carlo Tree Search for Slot Filling Ordering in Diffusion Language Models Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-02T23:50:37.479610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b0a4382-6d8c-49de-bae7-f6361f8e2a36 · inbound

Online Self-Calibration Against Hallucination in Vision-Language Models cites this paper.

Online Self-Calibration Against Hallucination in Vision-Language Models Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 36

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T15:16:10.758067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 68714fb5-68aa-476d-9c59-4a3b6fff7f38 · inbound

StoryAlign: Evaluating and Training Reward Models for Story Generation cites this paper.

StoryAlign: Evaluating and Training Reward Models for Story Generation Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 30

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T17:31:07.625809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c8ef7e11-e612-4411-85d7-be0817289dcd · inbound

A$^2$TGPO: Agentic Turn-Group Policy Optimization with Adaptive Turn-level Clipping cites this paper.

A$^2$TGPO: Agentic Turn-Group Policy Optimization with Adaptive Turn-level Clipping Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T19:56:08.803918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a3040011-7ea3-44ec-a821-3ec480e3f0aa · inbound

CA-SQL: Complexity-Aware Inference Time Reasoning for Text-to-SQL via Exploration and Compute Budget Allocation cites this paper.

CA-SQL: Complexity-Aware Inference Time Reasoning for Text-to-SQL via Exploration and Compute Budget Allocation Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 28

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T03:25:58.162248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 68c07757-b090-4bc8-8122-a6503e8fca4c · inbound

APCD: Adaptive Path-Contrastive Decoding for Reliable Large Language Model Generation cites this paper.

APCD: Adaptive Path-Contrastive Decoding for Reliable Large Language Model Generation Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 81

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:26:25.114868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c55c9fe3-ad48-4d46-99ac-8f5548f67e17 · inbound

Breaking the Reward Barrier: Accelerating Tree-of-Thought Reasoning via Speculative Exploration cites this paper.

Breaking the Reward Barrier: Accelerating Tree-of-Thought Reasoning via Speculative Exploration Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 61

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T06:51:30.308824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 57f9ef26-61e7-4a7b-9c54-95760f60ccb7 · inbound

Breaking the Reward Barrier: Accelerating Tree-of-Thought Reasoning via Speculative Exploration cites this paper.

Breaking the Reward Barrier: Accelerating Tree-of-Thought Reasoning via Speculative Exploration Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 61

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T05:15:03.377542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 15b827cc-a7dd-4a11-9f5c-b797760a1816 · inbound

Shepherd: Enabling Programmable Meta-Agents via Reversible Agentic Execution Traces cites this paper.

Shepherd: Enabling Programmable Meta-Agents via Reversible Agentic Execution Traces Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:16:30.885704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 48f329f6-4104-4082-8909-01fa1b90e315 · inbound

Shepherd: Enabling Programmable Meta-Agents via Reversible Agentic Execution Traces cites this paper.

Shepherd: Enabling Programmable Meta-Agents via Reversible Agentic Execution Traces Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-06-30T22:25:06.761279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 64f8b47c-59d7-4d39-a4ba-3ba70e8c492b · inbound

Scalable Token-Level Hallucination Detection in Large Language Models cites this paper.

Scalable Token-Level Hallucination Detection in Large Language Models Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T05:52:22.455333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6e1d9e44-cb39-4d6f-94dd-d1797095a35d · inbound

ScaleAcross Explorer: Exploring Communication Optimization for Scale-Across AI Model Training cites this paper.

ScaleAcross Explorer: Exploring Communication Optimization for Scale-Across AI Model Training Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 24

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T13:04:40.483302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation bae10265-a6c0-4d2c-bc44-db096746d7aa · inbound

ATLAS: Agentic Test-time Learning-to-Allocate Scaling cites this paper.

ATLAS: Agentic Test-time Learning-to-Allocate Scaling Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-07-01T22:26:17.086263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6e49eddc-22ef-4fce-a20d-44cbeb608b66 · inbound

Step-by-Step Optimization-like Reasoning in LLMs over Expanding Search Spaces cites this paper.

Step-by-Step Optimization-like Reasoning in LLMs over Expanding Search Spaces Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 37

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T08:46:48.943212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f6beadf6-5ee6-45d4-b3d0-40f50864e89c · inbound

Test-Time Scaling in Multimodal Foundation Models: A Comprehensive Survey of Generation and Reasoning cites this paper.

Test-Time Scaling in Multimodal Foundation Models: A Comprehensive Survey of Generation and Reasoning Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 97

Resolution: verified exact; arxiv_id, observed 2026-07-02T21:37:25.354455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2bc63d21-22b7-432f-b193-237cc353379a · inbound

TRACE: A Unified Rollout Budget Allocation Framework for Efficient Agentic Reinforcement Learning cites this paper.

TRACE: A Unified Rollout Budget Allocation Framework for Efficient Agentic Reinforcement Learning Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 54

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T04:27:36.752547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 28117a7f-5f6a-4c38-b65b-444a7c346444 · inbound

APPO: Agentic Procedural Policy Optimization cites this paper.

APPO: Agentic Procedural Policy Optimization Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 86

Resolution: verified exact; arxiv_id, observed 2026-07-03T09:37:49.336402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e9977467-00f8-4151-8f7b-7bd97cb7a3cf · inbound

APPO: Agentic Procedural Policy Optimization cites this paper.

APPO: Agentic Procedural Policy Optimization Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-03T02:12:34.483141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be34a2a5-a3d3-41c9-9d02-0bf58118a20d · inbound

ReSum: Synergizing LLM Reasoning and Summarization with Reinforcement Learning cites this paper.

ReSum: Synergizing LLM Reasoning and Summarization with Reinforcement Learning Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-07-03T15:08:33.369931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b85efc86-f7b5-42fb-a897-3b8873fc3b52 · inbound

ReSum: Synergizing LLM Reasoning and Summarization with Reinforcement Learning cites this paper.

ReSum: Synergizing LLM Reasoning and Summarization with Reinforcement Learning Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-03T02:12:23.860218Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 824af795-821b-434e-bc1f-1cdba21dd220 · inbound

Beyond Fixed Budgets: Characterizing the Inelasticity and Limitations of Tree-of-Thought Reasoning Strategies cites this paper.

Beyond Fixed Budgets: Characterizing the Inelasticity and Limitations of Tree-of-Thought Reasoning Strategies Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-06-30T18:44:59.791395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1410f6a1-38bf-4ab8-90ae-624ba2f850b4 · inbound

Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning cites this paper.

Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 236

Resolution: verified exact; arxiv_id, observed 2026-07-04T08:09:40.727786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation bd4cebbd-1f7e-4e37-97ef-503b2241cf42 · inbound

Efficient and Trainable Language Model Test-Time Scaling via Local Branch Routing cites this paper.

Efficient and Trainable Language Model Test-Time Scaling via Local Branch Routing Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 31

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T19:20:06.708349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0d3dd942-0e67-4127-8a6d-21c116e33c71 · inbound

Efficient and Trainable Language Model Test-Time Scaling via Local Branch Routing cites this paper.

Efficient and Trainable Language Model Test-Time Scaling via Local Branch Routing Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 31

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T06:35:29.541290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f526cda6-e761-4871-83c3-6b5e4f3a5928 · inbound

Addressing Over-Refusal in LLMs with Competing Rewards cites this paper.

Addressing Over-Refusal in LLMs with Competing Rewards Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 53

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T08:55:35.605736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f5348cad-0dee-43c0-8c6e-a9a67b0c39fe · inbound

Multi-Turn On-Policy Distillation with Prefix Replay cites this paper.

Multi-Turn On-Policy Distillation with Prefix Replay Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 73

Resolution: unresolved; no resolver link, observed 2026-07-11T13:53:36.775836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 611ae85f-0e67-41c6-b984-776c7bf72877 · inbound

Multi-Turn On-Policy Distillation with Prefix Replay cites this paper.

Multi-Turn On-Policy Distillation with Prefix Replay Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-02T08:40:39.787640Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ab0484c-befc-4fdd-877f-07d23aa35314 · inbound

Masked Diffusion Language Models are Strong and Steerable Text-Based World Models for Agentic RL cites this paper.

Masked Diffusion Language Models are Strong and Steerable Text-Based World Models for Agentic RL Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 111

Resolution: unresolved; no resolver link, observed 2026-08-02T14:50:17.718586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aaaaf2ff-7240-4b6f-b5d1-0bd167f1baa2 · inbound

Theoretical Foundations of $\max$@$k$ Reinforcement Learning cites this paper.

Theoretical Foundations of $\max$@$k$ Reinforcement Learning Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-15T15:43:00.157724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab2469e5-4b98-4ee1-8904-3346aacf9b3e · inbound

Thought-Level Beam Search for Reasoning cites this paper.

Thought-Level Beam Search for Reasoning Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-12T00:38:25.264770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42eeda29-89e7-4ce3-853e-7adcccbc75ce · inbound

Thought-Level Beam Search for Reasoning cites this paper.

Thought-Level Beam Search for Reasoning Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-15T14:30:50.755233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac3caf52-92a7-4a2a-a78f-cce02a3d2cf7 · inbound

ThinkRetrieve: Retrieval-Augmented Reasoning Traces for Test-Time Scaling cites this paper.

ThinkRetrieve: Retrieval-Augmented Reasoning Traces for Test-Time Scaling Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 166

Resolution: unresolved; no resolver link, observed 2026-08-12T14:10:45.699834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42632a1c-3669-4b61-9f89-470f2fcefc82 · inbound

Preference Tree Optimization: Enhancing Goal-Oriented Dialogue with Look-Ahead Simulations cites this paper.

Preference Tree Optimization: Enhancing Goal-Oriented Dialogue with Look-Ahead Simulations Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-16T00:21:59.252295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers