Xi Wang
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This paper proposes SelfCompact, a scaffold that allows models to decide when and how to compact long agent traces, improving summarization at a lower token cost.
The paper introduces SCENT, a multimodal framework that uses language guidance to align olfactory representations with visual and textual data, achieving state-of-the-art performance on crossmodal retrieval tasks.
This paper investigates the effectiveness of stage-dependent preference elicitation strategies in conversational recommendation systems and introduces COPE, a novel architecture for strategy modeling.
Aligning audio features with metadata improves profile retrieval and sex decoding