Papers by Yanchao Tan

2 papers
How Much Do Robots Understand Rudeness? Challenges in Human-Robot Interaction (2024.lrec-main)

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Challenge: This paper examines the pressing need to understand and manage inappropriate language within the evolving human-robot interaction landscape.
Approach: They propose to use data cleaning methods to identify inappropriate language in real-time interactions and evaluate natural language models for their proficiency in discerning rudeness.
Outcome: The proposed methods identify and mitigate inappropriate language in real-time interactions and evaluate natural language models for their proficiency in discerning rudeness.
MoLoRAG: Bootstrapping Document Understanding via Multi-modal Logic-aware Retrieval (2025.emnlp-main)

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Challenge: Document Understanding is a foundational AI capability with broad applications . Large Vision-Language Models (LLMs) can't handle multi-page document comprehension . a logic-aware retrieval framework for multi-modal, multi- page document understanding is proposed .
Approach: They propose a logic-aware retrieval framework for multi-modal, multi-page document understanding . MoLoRAG uses semantic and logical relevance to deliver more accurate retrieval .
Outcome: The proposed framework improves on four DocQA datasets and demonstrates 9.68% accuracy improvement over existing methods.

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