Papers by Zijian Shao

2 papers
Graph Neural Network Enhanced Retrieval for Question Answering of Large Language Models (2025.naacl-long)

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Challenge: Existing retrieval methods divide reference documents into passages, treating them in isolation. Existing methods only use contiguous passages or keywords.
Approach: They propose a retrieval method that leverages graph neural networks to exploit relatedness between passages to enhance retrieval.
Outcome: The proposed method improves retrieval by exploiting the relatedness between passages.
Personal Travel Solver: A Preference-Driven LLM-Solver System for Travel Planning (2025.acl-long)

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Challenge: Recent advances in Large Language Models (LLMs) have demonstrated remarkable capabilities in understanding complex instructions and reasoning across diverse domains.
Approach: They propose to integrate user’s implicit preference into the progress of travel planning by integrating real user reviews and point-of-interest metadata from Google Local into RealTravel.
Outcome: The proposed system achieves better performance than baseline methods and improves the level of personalization.

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