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20242026
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cs.CL2026

TinyR1-32B-Preview: Boosting Accuracy with Branch-Merge Distillation

Lin Sun, Guangxiang Zhao, Xiaoqi Jian +18

The challenge of reducing the size of Large Language Models (LLMs) while maintaining their performance has gained significant attention. However, existing methods, such as model di…

cs.CL2025

SUPERChem: A Multimodal Reasoning Benchmark in Chemistry

Zehua Zhao, Zhixian Huang, Junren Li +28

Current benchmarks for evaluating the chemical reasoning capabilities of Large Language Models (LLMs) are limited by oversimplified tasks, lack of process-level evaluation, and mis…

cs.CL2025

SciDA: Scientific Dynamic Assessor of LLMs

Junting Zhou, Tingjia Miao, Yiyan Liao +15

Advancement in Large Language Models (LLMs) reasoning capabilities enables them to solve scientific problems with enhanced efficacy. Thereby, a high-quality benchmark for comprehen…

cs.CL2025

HardTests: Synthesizing High-Quality Test Cases for LLM Coding

Zhongmou He, Yee Man Choi, Kexun Zhang +6

Verifiers play a crucial role in large language model (LLM) reasoning, needed by post-training techniques such as reinforcement learning. However, reliable verifiers are hard to ge…

cs.CL2025

KORGym: A Dynamic Game Platform for LLM Reasoning Evaluation

Jiajun Shi, Jian Yang, Jiaheng Liu +26

Recent advancements in large language models (LLMs) underscore the need for more comprehensive evaluation methods to accurately assess their reasoning capabilities. Existing benchm…

cs.CL2025

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…