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Think or Not? Exploring Thinking Efficiency in Large Reasoning Models via an Information-Theoretic Lens

Think or Not? Exploring Thinking Efficiency in Large Reasoning Models via an Information-Theoretic Lens

23 May 2025
Xixian Yong
Xiao Zhou
Yingying Zhang
Jinlin Li
Yefeng Zheng
X. Wu
    LRM
ArXiv (abs)PDFHTML

Papers citing "Think or Not? Exploring Thinking Efficiency in Large Reasoning Models via an Information-Theoretic Lens"

14 / 14 papers shown
Title
Between Underthinking and Overthinking: An Empirical Study of Reasoning Length and correctness in LLMs
Between Underthinking and Overthinking: An Empirical Study of Reasoning Length and correctness in LLMs
Jinyan Su
Jennifer Healey
Preslav Nakov
Claire Cardie
LRM
354
13
0
30 Apr 2025
Dynamic Early Exit in Reasoning Models
Dynamic Early Exit in Reasoning Models
Chenxu Yang
Qingyi Si
Yongjie Duan
Zheliang Zhu
Chenyu Zhu
Zheng Lin
Zheng Lin
Li Cao
Weiping Wang
ReLMLRM
172
22
0
22 Apr 2025
Reasoning Models Can Be Effective Without Thinking
Reasoning Models Can Be Effective Without Thinking
Wenjie Ma
Jingxuan He
Charlie Snell
Tyler Griggs
Sewon Min
Matei A. Zaharia
ReLMLRM
141
53
1
14 Apr 2025
Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models
Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models
Yang Sui
Yu-Neng Chuang
Guanchu Wang
Jiamu Zhang
Tianyi Zhang
...
Hongyi Liu
Andrew Wen
Shaochen
Zhong
Hanjie Chen
OffRLReLMLRM
204
101
0
20 Mar 2025
Optimizing Test-Time Compute via Meta Reinforcement Fine-Tuning
Yuxiao Qu
Matthew Y. R. Yang
Amrith Rajagopal Setlur
Lewis Tunstall
E. Beeching
Ruslan Salakhutdinov
Aviral Kumar
OffRL
159
49
0
10 Mar 2025
Towards Thinking-Optimal Scaling of Test-Time Compute for LLM Reasoning
Towards Thinking-Optimal Scaling of Test-Time Compute for LLM Reasoning
Wenkai Yang
Shuming Ma
Yankai Lin
Furu Wei
LRM
113
50
0
25 Feb 2025
The Relationship Between Reasoning and Performance in Large Language Models -- o3 (mini) Thinks Harder, Not Longer
The Relationship Between Reasoning and Performance in Large Language Models -- o3 (mini) Thinks Harder, Not Longer
Marthe Ballon
Andres Algaba
Vincent Ginis
LRMReLM
104
17
0
24 Feb 2025
Entropy-Lens: The Information Signature of Transformer Computations
Entropy-Lens: The Information Signature of Transformer Computations
Riccardo Ali
Francesco Caso
Christopher Irwin
Pietro Lio
98
3
0
23 Feb 2025
CoT-Valve: Length-Compressible Chain-of-Thought Tuning
CoT-Valve: Length-Compressible Chain-of-Thought Tuning
Xinyin Ma
Guangnian Wan
Runpeng Yu
Gongfan Fang
Xinchao Wang
LRM
164
55
0
13 Feb 2025
When More is Less: Understanding Chain-of-Thought Length in LLMs
When More is Less: Understanding Chain-of-Thought Length in LLMs
Yuyang Wu
Yifei Wang
Tianqi Du
Stefanie Jegelka
Yisen Wang
Yisen Wang
LRM
158
51
0
11 Feb 2025
BOLT: Bootstrap Long Chain-of-Thought in Language Models without Distillation
BOLT: Bootstrap Long Chain-of-Thought in Language Models without Distillation
Bo Pang
Hanze Dong
Jiacheng Xu
Siyang Song
Yingbo Zhou
Caiming Xiong
KELMLRM
162
10
0
06 Feb 2025
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
DeepSeek-AI
Daya Guo
Dejian Yang
Haowei Zhang
Junxiao Song
...
Shiyu Wang
S. Yu
Shunfeng Zhou
Shuting Pan
S.S. Li
ReLMVLMOffRLAI4TSLRM
390
2,024
0
22 Jan 2025
To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning
To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning
Zayne Sprague
Fangcong Yin
Juan Diego Rodriguez
Dongwei Jiang
Manya Wadhwa
Prasann Singhal
Xinyu Zhao
Xi Ye
Kyle Mahowald
Greg Durrett
ReLMLRM
243
132
0
18 Sep 2024
Make Every Penny Count: Difficulty-Adaptive Self-Consistency for Cost-Efficient Reasoning
Make Every Penny Count: Difficulty-Adaptive Self-Consistency for Cost-Efficient Reasoning
Xinglin Wang
Shaoxiong Feng
Yiwei Li
Peiwen Yuan
Y. Zhang
Boyuan Pan
Heda Wang
Yao Hu
Kan Li
LRM
150
25
0
24 Aug 2024
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