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cs.AI2026
Clearing the Fog: Towards Installing and Refining Proactive Exploration Capabilities in LLM Agents
Zhizhao Guan, Chen Huang, Ziming Liu +5
We study proactive exploration in LLM agents, i.e., the ability to explore an environment to acquire information that improves future decision-making. In this regard, we first iden…
cs.CL2026
When Cognitive Graphs Meet LLMs: BDEI Cognitive Pathways for Panic Emotional Arousal Prediction
Mengzhu Liu, Long Qin, Chuan Ai +7
Predicting the timing of individual and collective panic emotional arousal before manifestation is essential for timely emergency intervention. Existing methods incorporate cogniti…
cs.LG2026
Advancing Edge Classification through High-Dimensional Causal Modeling of Node-Edge Interplay
Duanyu Feng, Li Ding, Hongru Liang +1
Edge classification, a crucial task for graph applications, remains relatively under-explored compared to link prediction. Current methods often overlook the potential causal influ…