CFDA & CLIP at TREC iKAT 2025: Enhancing Personalized Conversational Search via Query Reformulation and Rank Fusion
Authors: Yu-Cheng Chang, Guan-Wei Yeo, Quah Eugene, Fan-Jie Shih, Yuan-Ching Kuo, Tsung-En Yu, Hung-Chun Hsu, Ming-Feng Tsai, Chuan-Ju Wang
NIST Text REtrieval Conference (TREC), 2025
TL;DR
This paper presents our approach for the TREC iKAT 2025 track, focusing on personalized conversational search. We propose a pipeline that combines query reformulation techniques with rank fusion strategies to enhance retrieval performance in conversational settings.
For further details, please refer to our paper!