most citedLIMO: Less is More for Reasoning

3 citations · 8 across the 7 of their papers we have counts for

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cs.CL2025

Interaction as Intelligence: Deep Research With Human-AI Partnership

Lyumanshan Ye, Xiaojie Cai, Xinkai Wang +23

This paper introduces "Interaction as Intelligence" research series, presenting a reconceptualization of human-AI relationships in deep research tasks. Traditional approaches treat…

cs.CL2025

CoLD: Counterfactually-Guided Length Debiasing for Process Reward Models in Mathematical Reasoning

Congmin Zheng, Jiachen Zhu, Jianghao Lin +6

Process Reward Models (PRMs) play a central role in evaluating and guiding multi-step reasoning in large language models (LLMs), especially for mathematical problem solving. Howeve…

cs.CL2025

Generative AI Act II: Test Time Scaling Drives Cognition Engineering

Shijie Xia, Yiwei Qin, Xuefeng Li +11

The first generation of Large Language Models - what might be called "Act I" of generative AI (2020-2023) - achieved remarkable success through massive parameter and data scaling,…

cs.CL2025★ 3 cited

LIMO: Less is More for Reasoning

Yixin Ye, Zhen Huang, Yang Xiao +3

We challenge the prevailing assumption that complex reasoning in large language models (LLMs) necessitates massive training data. We demonstrate that sophisticated mathematical rea…

cs.CL2024★ 2 cited

OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI

Zhen Huang, Zengzhi Wang, Shijie Xia +25

The evolution of Artificial Intelligence (AI) has been significantly accelerated by advancements in Large Language Models (LLMs) and Large Multimodal Models (LMMs), gradually showc…