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cs.CL2026

Mitigating Provenance-Role Collapse in Long-Term Agents via Typed Memory Representation

Zhengda Jin, Bingbing Wang, Jing Li +2

Long-term memory is essential for persistent LLM agents, yet prevailing architectures store historical interactions as unstructured, flat text. This unconstrained storage induces p…

cs.CL2026

CRPO: Character-centric Group Relative Policy Optimization for Role-aware Reasoning in Role-playing Agents

Yihong Tang, Kehai Chen, Liang Yue +2

Recent advancements in Reinforcement Learning (RL), particularly Group Relative Policy Optimization (GRPO), have significantly enhanced the reasoning capabilities of Large Language…

cs.CL2026

When to Trust Tools? Adaptive Tool Trust Calibration For Tool-Integrated Math Reasoning

Ruotao Xu, Yixin Ji, Yu Luo +5

Large reasoning models (LRMs) have achieved strong performance enhancement through scaling test time computation, but due to the inherent limitations of the underlying language mod…

cs.CL2026

When Is Thinking Enough? Early Exit via Sufficiency Assessment for Efficient Reasoning

Yang Xiang, Yixin Ji, Ruotao Xu +4

Large reasoning models (LRMs) have achieved remarkable performance in complex reasoning tasks, driven by their powerful inference-time scaling capability. However, LRMs often suffe…

cs.CL2026

Echoes as Anchors: Probabilistic Costs and Attention Refocusing in LLM Reasoning

Zhuoyuan Hao, Zhuo Li, Wu Li +3

Test-time compute allocation in large reasoning models (LRMs) is widely used and has applications in mathematical problem solving, code synthesis, and planning. Recent work has add…

cs.CL2025

MIND Your Reasoning: A Meta-Cognitive Intuitive-Reflective Network for Dual-Reasoning in Multimodal Stance Detection

Bingbing Wang, Zhengda Jin, Bin Liang +4

Multimodal Stance Detection (MSD) is a crucial task for understanding public opinion on social media. Existing methods predominantly operate by learning to fuse modalities. They la…