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Learning How Hard to Think: Input-Adaptive Allocation of LM Computation

Learning How Hard to Think: Input-Adaptive Allocation of LM Computation

7 October 2024
Mehul Damani
Idan Shenfeld
Andi Peng
Andreea Bobu
Jacob Andreas
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Papers citing "Learning How Hard to Think: Input-Adaptive Allocation of LM Computation"

4 / 4 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
49
0
0
30 Apr 2025
Taming the Titans: A Survey of Efficient LLM Inference Serving
Taming the Titans: A Survey of Efficient LLM Inference Serving
Ranran Zhen
J. Li
Yixin Ji
Z. Yang
Tong Liu
Qingrong Xia
Xinyu Duan
Z. Wang
Baoxing Huai
M. Zhang
LLMAG
77
0
0
28 Apr 2025
Automatic Curriculum Expert Iteration for Reliable LLM Reasoning
Automatic Curriculum Expert Iteration for Reliable LLM Reasoning
Zirui Zhao
Hanze Dong
Amrita Saha
Caiming Xiong
Doyen Sahoo
LRM
27
3
0
10 Oct 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
37
16
0
24 Aug 2024
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