Papers by Yishuai Cai

1 papers
Conflict-Aware Memory for Embodied Agents: Enhancing Vector Data Quality via Detection Rules (2026.acl-long)

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Challenge: Embodied agents have successfully leveraged large language models (LLMs) to better transform human instructions and images into executable task plans.
Approach: They propose Conflict Detection Rules to identify and manage data quality issues in vector knowledge bases and correct the index structure.
Outcome: Experimental results show that planners with Conflict Detection Rules exceed the basic LLM planner by 15.25% and 14.25% in grammatical accuracy (GA) and interpretation accuracy (IA) on average.

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