14 citations · 33 across the 8 of their papers we have counts for
7 papers · 1 filter
FARA: Future-aware Ranking Algorithm for Fairness Optimization
Tao Yang, Zhichao Xu, Zhenduo Wang +1
Ranking systems are the key components of modern Information Retrieval (IR) applications, such as search engines and recommender systems. Besides the ranking relevance to users, th…
Reward-free Policy Imitation Learning for Conversational Search
Zhenduo Wang, Zhichao Xu, Qingyao Ai
Existing conversational search studies mainly focused on asking better clarifying questions and/or improving search result quality. These works aim at retrieving better responses a…
An In-depth Investigation of User Response Simulation for Conversational Search
Zhenduo Wang, Zhichao Xu, Qingyao Ai +1
Conversational search has seen increased recent attention in both the IR and NLP communities. It seeks to clarify and solve users' search needs through multi-turn natural language…
Zero-shot Clarifying Question Generation for Conversational Search
Zhenduo Wang, Yuancheng Tu, Corby Rosset +3
A long-standing challenge for search and conversational assistants is query intention detection in ambiguous queries. Asking clarifying questions in conversational search has been…
Marginal-Certainty-aware Fair Ranking Algorithm
Tao Yang, Zhichao Xu, Zhenduo Wang +2
Ranking systems are ubiquitous in modern Internet services, including online marketplaces, social media, and search engines. Traditionally, ranking systems only focus on how to get…
Simulating and Modeling the Risk of Conversational Search
Zhenduo Wang, Qingyao Ai
In conversational search, agents can interact with users by asking clarifying questions to increase their chance to find better results. Many recent works and shared tasks in both…
Controlling the Risk of Conversational Search via Reinforcement Learning
Zhenduo Wang, Qingyao Ai
Users often formulate their search queries with immature language without well-developed keywords and complete structures. Such queries fail to express their true information needs…