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cs.CL2026

Ask, Relax, or Act? Evaluating Actionable Indeterminacy in LLM Preference Reasoning

Ang Li, Yue Lin, Feifei Kou +6

An LLM agent can recognize uncertainty yet still choose the wrong next step: asking when action is already justified, or seeking clarification when the constraints must change. We…

cs.CL2026

HiMed: Incentivizing Hindi Reasoning in Medical LLMs

Dingfeng Jiang, Han Yan, Chenze Ma +12

Medical large language models hold promise for reducing healthcare disparities, yet Hindi remains severely underrepresented. While medical LLMs excel in high-resource languages, th…

cs.CL2026

AriadneMem: Threading the Maze of Lifelong Memory for LLM Agents

Wenhui Zhu, Xiwen Chen, Zhipeng Wang +11

Long-horizon LLM agents require memory systems that remain accurate under fixed context budgets. However, existing systems struggle with two persistent challenges in long-term dial…

cs.CL2026

All That Glisters Is Not Gold: A Benchmark for Reference-Free Counterfactual Financial Misinformation Detection

Yuechen Jiang, Zhiwei Liu, Yupeng Cao +10

We introduce RFC Bench, a benchmark for evaluating large language models on financial misinformation under realistic news. RFC Bench operates at the paragraph level and captures th…

cs.CL2026

Same Claim, Different Judgment: Benchmarking Scenario-Induced Bias in Multilingual Financial Misinformation Detection

Zhiwei Liu, Yupen Cao, Yuechen Jiang +22

Large language models (LLMs) have been widely applied across various domains of finance. Since their training data are largely derived from human-authored corpora, LLMs may inherit…