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cs.AI2026

ScienceArena: Benchmarking LLMs on Latest Scientific Olympiad Competitions

Guangxiang Zhao, Qilong Shi, Xusen Xiao +13

Benchmark saturation and data contamination increasingly obscure genuine scientific reasoning in frontier LLMs. We introduce \textsc{ScienceArena}, an olympiad-style benchmark from…

cs.AI2026

Harness-Bench: Evaluating Agent Harnesses across Models and Realistic Workflows

Yilun Yao, Xinyu Tan, Chao-Hsuan Liu +10

LLM agents are increasingly deployed as executable systems that use tools, modify workspaces, and produce concrete artifacts. In such workflows, performance depends not only on the…

cs.AI2026

Thinking with Reasoning Skills: Fewer Tokens, More Accuracy

Guangxiang Zhao, Qilong Shi, Xusen Xiao +3

Reasoning LLMs often spend substantial tokens on long intermediate reasoning traces (e.g., chain-of-thought) when solving new problems. We propose to summarize and store reusable r…

cs.AI2026

Beyond Parameter Arithmetic: Sparse Complementary Fusion for Distribution-Aware Model Merging

Weihong Lin, Lin Sun, Qilong Shi +6

Model merging has emerged as a promising paradigm for composing the capabilities of large language models by directly operating in weight space, enabling the integration of special…

cs.AI2025

Uncertainty Under the Curve: A Sequence-Level Entropy Area Metric for Reasoning LLM

Yongfu Zhu, Lin Sun, Guangxiang Zhao +2

In this work, we introduce Entropy Area Score (EAS), a simple yet effective metric to quantify uncertainty in the answer generation process of reasoning large language models (LLMs…

cs.AI2025

Evaluation is All You Need: Strategic Overclaiming of LLM Reasoning Capabilities Through Evaluation Design

Lin Sun, Weihong Lin, Jinzhu Wu +8

Reasoning models represented by the Deepseek-R1-Distill series have been widely adopted by the open-source community due to their strong performance in mathematics, science, progra…