most citedSuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines

4 citations · 4 across the 5 of their papers we have counts for

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cs.CL2025

KAT-V1: Kwai-AutoThink Technical Report

Zizheng Zhan, Ken Deng, Huaixi Tang +27

We present Kwaipilot-AutoThink (KAT), an open-source 40B large language model developed to address the overthinking problem in reasoning-intensive tasks, where an automatic thinkin…

cs.CL2025

CriticLean: Critic-Guided Reinforcement Learning for Mathematical Formalization

Zhongyuan Peng, Yifan Yao, Kaijing Ma +16

Translating natural language mathematical statements into formal, executable code is a fundamental challenge in automated theorem proving. While prior work has focused on generatio…

cs.CL2025

Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning?

Yancheng He, Shilong Li, Jiaheng Liu +8

Recently, o1-like models have drawn significant attention, where these models produce the long Chain-of-Thought (CoT) reasoning steps to improve the reasoning abilities of existing…

cs.CL20254 cited

SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines

P Team, Xinrun Du, Yifan Yao +94

Large language models (LLMs) have demonstrated remarkable proficiency in mainstream academic disciplines such as mathematics, physics, and computer science. However, human knowledg…

cs.CL2025

Mitigating Hallucinations in Large Vision-Language Models by Adaptively Constraining Information Flow

Jiaqi Bai, Hongcheng Guo, Zhongyuan Peng +4

Large vision-language models show tremendous potential in understanding visual information through human languages. However, they are prone to suffer from object hallucination, i.e…

cs.CL2025

CodeCriticBench: A Holistic Code Critique Benchmark for Large Language Models

Alexander Zhang, Marcus Dong, Jiaheng Liu +15

The critique capacity of Large Language Models (LLMs) is essential for reasoning abilities, which can provide necessary suggestions (e.g., detailed analysis and constructive feedba…