Author

See-Kiong Ng

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#artificial intelligence Preprint Aug 2026

Clearing the Fog: Towards Installing and Refining Proactive Exploration Capabilities in LLM Agents

This work proposes \the authors', a novel method designed to instill and refine proactive exploration in LLM agents, which consists of two components: Exploratory Data Construction, which synthesizes exploration-rich trajectories to mitigate the hindsight bias of standard demonstrations; and RL Optimization with Contra...

Zhizhao Guan, Chen Huang, Zi-Ming Liu et al. · 1 citation

#artificial intelligence Preprint Sep 2026

Towards Effective Structured Context Modeling for Conversational Recommender Systems via Dual-node Monte Carlo Tree Search

DREAMS is proposed, a novel tree-structured context modeling framework that explicitly captures user preference evolution throughout multi-turn interactions and introduces two specialized node types to support the two fundamental objectives of CRSs: preference elicitation and preference exploitation.

Jin-Cheng Zhang, Chen Huang, Wen-Qiang Lei et al. · 0 citations

Preprint Aug 2026

ExpConCAD: Experience-Guided Text-to-CAD Generation from Shape Descriptions with Implicit Spatial Constraints

It is argued that missing spatial constraints should be inferred with respect to the underlying construction structure and informed by reusable design experience and informed by reusable design experience in ExpConCAD, an experience-enhanced framework for implicit spatial constraint completion.

Jingyao Liu, Jin Tang, Chen Huang et al. · 0 citations