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cs.CL2026

Notes2Skills: From Lab Notebooks to Certainty-Aware Scientific Agent Skills

Shi Liu, Jiayao Chen, Chengwei Qin +3

Scientific discovery workflows usually contain and rely heavily on lab notes, where researchers record observations, interpret uncertain results, and plan follow-up experiments. Su…

cs.CL2026

SafeReview: Defending LLM-based Review Systems Against Adversarial Hidden Prompts

Yuan Xin, Yixuan Weng, Minjun Zhu +5

As Large Language Models (LLMs) are increasingly integrated into academic peer review, their vulnerability to adversarial hidden prompts, i.e., adversarial instructions embedded in…

cs.CL2026

CoMMET: To What Extent Can LLMs Perform Theory of Mind Tasks?

Ruirui Chen, Weifeng Jiang, Chengwei Qin +1

Theory of Mind (ToM)-the ability to reason about the mental states of oneself and others-is a cornerstone of human social intelligence. As Large Language Models (LLMs) become ubiqu…

cs.CL2025

DRQA: Dynamic Reasoning Quota Allocation for Controlling Overthinking in Reasoning Large Language Models

Kaiwen Yan, Xuanqing Shi, Hongcheng Guo +3

Reasoning large language models (RLLMs), such as OpenAI-O3 and DeepSeek-R1, have recently demonstrated remarkable capabilities by performing structured and multi-step reasoning. Ho…

cs.CL2025

Agent-ScanKit: Unraveling Memory and Reasoning of Multimodal Agents via Sensitivity Perturbations

Pengzhou Cheng, Lingzhong Dong, Zeng Wu +5

Although numerous strategies have recently been proposed to enhance the autonomous interaction capabilities of multimodal agents in graphical user interface (GUI), their reliabilit…