Cover Image

LLMs are Single-threaded Reasoners: Demystifying the Working Mechanism of Soft Thinking

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wu, Junhong, Lu, Jinliang, Ren, Zixuan, Hu, Gangqiang, Wu, Zhi, Dai, Dai, Wu, Hua
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Emergent Hierarchical Reasoning in LLMs through Reinforcement Learning
by: Wang, Haozhe, et al.
Published: (2025)

Demystifying Hybrid Thinking: Can LLMs Truly Switch Between Think and No-Think?
by: Wang, Shouren, et al.
Published: (2025)

Soft Thinking: Unlocking the Reasoning Potential of LLMs in Continuous Concept Space
by: Zhang, Zhen, et al.
Published: (2025)

Demystifying Reasoning Dynamics with Mutual Information: Thinking Tokens are Information Peaks in LLM Reasoning
by: Qian, Chen, et al.
Published: (2025)

Are LLMs Capable of Data-based Statistical and Causal Reasoning? Benchmarking Advanced Quantitative Reasoning with Data
by: Liu, Xiao, et al.
Published: (2024)

Think Before Recommend: Unleashing the Latent Reasoning Power for Sequential Recommendation
by: Tang, Jiakai, et al.
Published: (2025)

Don't Think Twice! Over-Reasoning Impairs Confidence Calibration
by: Lacombe, Romain, et al.
Published: (2025)

MR-Ben: A Meta-Reasoning Benchmark for Evaluating System-2 Thinking in LLMs
by: Zeng, Zhongshen, et al.
Published: (2024)

Parallel Scaling Law: Unveiling Reasoning Generalization through A Cross-Linguistic Perspective
by: Yang, Wen, et al.
Published: (2025)

Demystifying Domain-adaptive Post-training for Financial LLMs
by: Ke, Zixuan, et al.
Published: (2025)

MatryoshkaThinking: Recursive Test-Time Scaling Enables Efficient Reasoning
by: Chen, Hongwei, et al.
Published: (2025)

Thinking LLMs: General Instruction Following with Thought Generation
by: Wu, Tianhao, et al.
Published: (2024)

How Do Answer Tokens Read Reasoning Traces? Self-Reading Patterns in Thinking LLMs for Quantitative Reasoning
by: Chen, Haoyang, et al.
Published: (2026)

Think Parallax: Solving Multi-Hop Problems via Multi-View Knowledge-Graph-Based Retrieval-Augmented Generation
by: Liu, Jinliang, et al.
Published: (2025)

To Think or Not to Think: Exploring the Unthinking Vulnerability in Large Reasoning Models
by: Zhu, Zihao, et al.
Published: (2025)

SwiReasoning: Switch-Thinking in Latent and Explicit for Pareto-Superior Reasoning LLMs
by: Shi, Dachuan, et al.
Published: (2025)

Read Quietly, Think Aloud: Decoupling Comprehension and Reasoning in LLMs
by: Wang, Yuanxin, et al.
Published: (2025)

Do LLMs Really Think Step-by-step In Implicit Reasoning?
by: Yu, Yijiong
Published: (2024)

Beyond Imitation: Learning Key Reasoning Steps from Dual Chain-of-Thoughts in Reasoning Distillation
by: Dai, Chengwei, et al.
Published: (2024)

KAG-Thinker: Interactive Thinking and Deep Reasoning in LLMs via Knowledge-Augmented Generation
by: Zhang, Dalong, et al.
Published: (2025)

RuleArena: A Benchmark for Rule-Guided Reasoning with LLMs in Real-World Scenarios
by: Zhou, Ruiwen, et al.
Published: (2024)

MedAgentsBench: Benchmarking Thinking Models and Agent Frameworks for Complex Medical Reasoning
by: Tang, Xiangru, et al.
Published: (2025)

Mission Impossible: Feedback-Guided Dynamic Interactive Planning for Improving Reasoning on LLMs
by: Yan, Dong, et al.
Published: (2025)

Draft-Thinking: Learning Efficient Reasoning in Long Chain-of-Thought LLMs
by: Cao, Jie, et al.
Published: (2026)

MixReasoning: Switching Modes to Think
by: Lu, Haiquan, et al.
Published: (2025)

The Reasoning Error About Reasoning: Why Different Types of Reasoning Require Different Representational Structures
by: Wu, Yiling
Published: (2026)

Intermittent Semi-Working Mask: A New Masking Paradigm for LLMs
by: Hu, HaoYuan, et al.
Published: (2024)

Think or Not? Exploring Thinking Efficiency in Large Reasoning Models via an Information-Theoretic Lens
by: Yong, Xixian, et al.
Published: (2025)

Reverse Thinking Makes LLMs Stronger Reasoners
by: Chen, Justin Chih-Yao, et al.
Published: (2024)

Are LLMs Prescient? A Continuous Evaluation using Daily News as the Oracle
by: Dai, Hui, et al.
Published: (2024)

Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learning
by: Xie, Tian, et al.
Published: (2025)

QuestA: Expanding Reasoning Capacity in LLMs via Question Augmentation
by: Li, Jiazheng, et al.
Published: (2025)

Effectively Controlling Reasoning Models through Thinking Intervention
by: Wu, Tong, et al.
Published: (2025)

The Thinking Spectrum: An Empirical Study of Tunable Reasoning in LLMs through Model Merging
by: Lan, Xiaochong, et al.
Published: (2025)

Search and Refine During Think: Facilitating Knowledge Refinement for Improved Retrieval-Augmented Reasoning
by: Shi, Yaorui, et al.
Published: (2025)

Improve Student's Reasoning Generalizability through Cascading Decomposed CoTs Distillation
by: Dai, Chengwei, et al.
Published: (2024)

Explore the Reasoning Capability of LLMs in the Chess Testbed
by: Wang, Shu, et al.
Published: (2024)

Disagreements in Reasoning: How a Model's Thinking Process Dictates Persuasion in Multi-Agent Systems
by: Zhao, Haodong, et al.
Published: (2025)

AbstRaL: Augmenting LLMs' Reasoning by Reinforcing Abstract Thinking
by: Gao, Silin, et al.
Published: (2025)

Reasoning Court: Combining Reasoning, Action, and Judgment for Multi-Hop Reasoning
by: Wu, Jingtian, et al.
Published: (2025)