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cs.CL2026
Dual Hierarchical Dialogue Policy Learning for Legal Inquisitive Conversational Agents
Xubo Lin, Zezhi Deng, Shihao Wang +2
Most existing dialogue systems are user-driven, primarily designed to fulfill user requests. However, in many critical real-world scenarios, a conversational agent must proactively…
cs.CL2026
YIELD: A Large-Scale Dataset and Evaluation Framework for Information Elicitation Agents
Victor De Lima, Grace Hui Yang
Most conversational agents (CAs) are designed to satisfy user needs through user-driven interactions. However, many real-world settings, such as academic interviewing, judicial pro…