Think or Not? Exploring Thinking Efficiency in Large Reasoning Models via an Information-Theoretic Lens
Fuente:
arXiv
Saved in:
| Main Authors: | Yong, Xixian, Zhou, Xiao, Zhang, Yingying, Li, Jinlin, Zheng, Yefeng, Wu, Xian |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
To Think or Not to Think: Exploring the Unthinking Vulnerability in Large Reasoning Models
by: Zhu, Zihao, et al.
Published: (2025)
by: Zhu, Zihao, et al.
Published: (2025)
MOTIF: Modular Thinking via Reinforcement Fine-tuning in LLMs
by: Mitra, Purbesh, et al.
Published: (2025)
by: Mitra, Purbesh, et al.
Published: (2025)
DeepRAG: Thinking to Retrieve Step by Step for Large Language Models
by: Guan, Xinyan, et al.
Published: (2025)
by: Guan, Xinyan, et al.
Published: (2025)
Think Before Recommend: Unleashing the Latent Reasoning Power for Sequential Recommendation
by: Tang, Jiakai, et al.
Published: (2025)
by: Tang, Jiakai, et al.
Published: (2025)
An Information-Theoretic Approach to Analyze NLP Classification Tasks
by: Wang, Luran, et al.
Published: (2024)
by: Wang, Luran, et al.
Published: (2024)
Think Less, Label Better: Multi-Stage Domain-Grounded Synthetic Data Generation for Fine-Tuning Large Language Models in Telecommunications
by: Shi, Chenhua, et al.
Published: (2025)
by: Shi, Chenhua, et al.
Published: (2025)
Exploring the System 1 Thinking Capability of Large Reasoning Models
by: Zhang, Wenyuan, et al.
Published: (2025)
by: Zhang, Wenyuan, et al.
Published: (2025)
RAG over Thinking Traces Can Improve Reasoning Tasks
by: Arabzadeh, Negar, et al.
Published: (2026)
by: Arabzadeh, Negar, et al.
Published: (2026)
TaoSR1: The Thinking Model for E-commerce Relevance Search
by: Dong, Chenhe, et al.
Published: (2025)
by: Dong, Chenhe, et al.
Published: (2025)
MotiveBench: How Far Are We From Human-Like Motivational Reasoning in Large Language Models?
by: Yong, Xixian, et al.
Published: (2025)
by: Yong, Xixian, et al.
Published: (2025)
To Think or Not To Think, That is The Question for Large Reasoning Models in Theory of Mind Tasks
by: Gong, Nanxu, et al.
Published: (2026)
by: Gong, Nanxu, et al.
Published: (2026)
ThinkRec: Thinking-based recommendation via LLM
by: Yu, Qihang, et al.
Published: (2025)
by: Yu, Qihang, et al.
Published: (2025)
Thinking Forward and Backward: Multi-Objective Reinforcement Learning for Retrieval-Augmented Reasoning
by: Wei, Wenda, et al.
Published: (2025)
by: Wei, Wenda, et al.
Published: (2025)
Modeling Hierarchical Thinking in Large Reasoning Models
by: Shahariar, G M, et al.
Published: (2025)
by: Shahariar, G M, et al.
Published: (2025)
Fast Think-on-Graph: Wider, Deeper and Faster Reasoning of Large Language Model on Knowledge Graph
by: Liang, Xujian, et al.
Published: (2025)
by: Liang, Xujian, et al.
Published: (2025)
An Information Theoretic Perspective on Agentic System Design
by: He, Shizhe, et al.
Published: (2025)
by: He, Shizhe, et al.
Published: (2025)
On the Reasoning Capacity of AI Models and How to Quantify It
by: Radha, Santosh Kumar, et al.
Published: (2025)
by: Radha, Santosh Kumar, et al.
Published: (2025)
ThinkPilot: Steering Reasoning Models via Automated Think-prefixes Optimization
by: Li, Sunzhu, et al.
Published: (2025)
by: Li, Sunzhu, et al.
Published: (2025)
The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity
by: Shojaee, Parshin, et al.
Published: (2025)
by: Shojaee, Parshin, et al.
Published: (2025)
On Theoretical Interpretations of Concept-Based In-Context Learning
by: Tang, Huaze, et al.
Published: (2025)
by: Tang, Huaze, et al.
Published: (2025)
Thinking Ahead: Prospection-Guided Retrieval of Memory with Language Models
by: Chopra, Harshita, et al.
Published: (2026)
by: Chopra, Harshita, et al.
Published: (2026)
OmniThink: Expanding Knowledge Boundaries in Machine Writing through Thinking
by: Xi, Zekun, et al.
Published: (2025)
by: Xi, Zekun, et al.
Published: (2025)
The Information of Large Language Model Geometry
by: Tan, Zhiquan, et al.
Published: (2024)
by: Tan, Zhiquan, et al.
Published: (2024)
The Thinking Spectrum: An Empirical Study of Tunable Reasoning in LLMs through Model Merging
by: Lan, Xiaochong, et al.
Published: (2025)
by: Lan, Xiaochong, et al.
Published: (2025)
Controlling Thinking Speed in Reasoning Models
by: Lin, Zhengkai, et al.
Published: (2025)
by: Lin, Zhengkai, 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)
by: Qian, Chen, et al.
Published: (2025)
Large Language Models as Evaluators for Scientific Synthesis
by: Evans, Julia, et al.
Published: (2024)
by: Evans, Julia, et al.
Published: (2024)
Conversational Complexity for Assessing Risk in Large Language Models
by: Burden, John, et al.
Published: (2024)
by: Burden, John, et al.
Published: (2024)
CoT-Space: A Theoretical Framework for Internal Slow-Thinking via Reinforcement Learning
by: Gan, Zeyu, et al.
Published: (2025)
by: Gan, Zeyu, et al.
Published: (2025)
Thinking About Thinking: Evaluating Reasoning in Post-Trained Language Models
by: Singla, Pratham, et al.
Published: (2025)
by: Singla, Pratham, et al.
Published: (2025)
Think Before you Write: QA-Guided Reasoning for Character Descriptions in Books
by: Papoudakis, Argyrios, et al.
Published: (2026)
by: Papoudakis, Argyrios, et al.
Published: (2026)
SAT: Balancing Reasoning Accuracy and Efficiency with Stepwise Adaptive Thinking
by: Huang, Weiyang, et al.
Published: (2026)
by: Huang, Weiyang, et al.
Published: (2026)
Large Model Strategic Thinking, Small Model Efficiency: Transferring Theory of Mind in Large Language Models
by: Lore, Nunzio, et al.
Published: (2024)
by: Lore, Nunzio, et al.
Published: (2024)
Large Language Models for Scientific Information Extraction: An Empirical Study for Virology
by: Shamsabadi, Mahsa, et al.
Published: (2024)
by: Shamsabadi, Mahsa, et al.
Published: (2024)
Think$^{2}$: Grounded Metacognitive Reasoning in Large Language Models
by: Elenjical, Abraham Paul, et al.
Published: (2026)
by: Elenjical, Abraham Paul, et al.
Published: (2026)
MeTHanol: Modularized Thinking Language Models with Intermediate Layer Thinking, Decoding and Bootstrapping Reasoning
by: Xi, Ningyuan, et al.
Published: (2024)
by: Xi, Ningyuan, et al.
Published: (2024)
Think before Recommendation: Autonomous Reasoning-enhanced Recommender
by: Kong, Xiaoyu, et al.
Published: (2025)
by: Kong, Xiaoyu, et al.
Published: (2025)
Evaluating Large Language Models for Structured Science Summarization in the Open Research Knowledge Graph
by: Nechakhin, Vladyslav, et al.
Published: (2024)
by: Nechakhin, Vladyslav, et al.
Published: (2024)
Slaves to the Law of Large Numbers: An Asymptotic Equipartition Property for Perplexity in Generative Language Models
by: Bell, Tyler, et al.
Published: (2024)
by: Bell, Tyler, et al.
Published: (2024)
Uncertainty Quantification and Data Efficiency in AI: An Information-Theoretic Perspective
by: Simeone, Osvaldo, et al.
Published: (2025)
by: Simeone, Osvaldo, et al.
Published: (2025)
Similar Items
-
To Think or Not to Think: Exploring the Unthinking Vulnerability in Large Reasoning Models
by: Zhu, Zihao, et al.
Published: (2025) -
MOTIF: Modular Thinking via Reinforcement Fine-tuning in LLMs
by: Mitra, Purbesh, et al.
Published: (2025) -
DeepRAG: Thinking to Retrieve Step by Step for Large Language Models
by: Guan, Xinyan, et al.
Published: (2025) -
Think Before Recommend: Unleashing the Latent Reasoning Power for Sequential Recommendation
by: Tang, Jiakai, et al.
Published: (2025) -
An Information-Theoretic Approach to Analyze NLP Classification Tasks
by: Wang, Luran, et al.
Published: (2024)