6 citations · 12 across the 15 of their papers we have counts for
6 papers · 1 filter
Aligning Query Representation with Rewritten Query and Relevance Judgments in Conversational Search
Fengran Mo, Chen Qu, Kelong Mao +4
Conversational search supports multi-turn user-system interactions to solve complex information needs. Different from the traditional single-turn ad-hoc search, conversational sear…
How to Leverage Personal Textual Knowledge for Personalized Conversational Information Retrieval
Fengran Mo, Longxiang Zhao, Kaiyu Huang +3
Personalized conversational information retrieval (CIR) combines conversational and personalizable elements to satisfy various users' complex information needs through multi-turn i…
DoRA: Enhancing Parameter-Efficient Fine-Tuning with Dynamic Rank Distribution
Yulong Mao, Kaiyu Huang, Changhao Guan +3
Fine-tuning large-scale pre-trained models is inherently a resource-intensive task. While it can enhance the capabilities of the model, it also incurs substantial computational cos…
A Survey on Large Language Models with Multilingualism: Recent Advances and New Frontiers
Kaiyu Huang, Fengran Mo, Xinyu Zhang +10
The rapid development of Large Language Models (LLMs) demonstrates remarkable multilingual capabilities in natural language processing, attracting global attention in both academia…
ConvSDG: Session Data Generation for Conversational Search
Fengran Mo, Bole Yi, Kelong Mao +3
Conversational search provides a more convenient interface for users to search by allowing multi-turn interaction with the search engine. However, the effectiveness of the conversa…
History-Aware Conversational Dense Retrieval
Fengran Mo, Chen Qu, Kelong Mao +4
Conversational search facilitates complex information retrieval by enabling multi-turn interactions between users and the system. Supporting such interactions requires a comprehens…