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19942026
most citedGender bias and stereotypes in Large Language Models

361 citations

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5 papers · 1 filter

cs.IR2026

Unifying Ranking and Generation in Query Auto-Completion via Retrieval-Augmented Generation and Multi-Objective Alignment

Kai Yuan, Anthony Zheng, Jia Hu +9

Query Auto-Completion (QAC) suggests query completions as users type, helping them articulate intent and reach results more efficiently. Existing approaches face fundamental challe…

cs.IR2024★ 10 cited

Synthetic Query Generation using Large Language Models for Virtual Assistants

Sonal Sannigrahi, Thiago Fraga-Silva, Youssef Oualil +1

Virtual Assistants (VAs) are important Information Retrieval platforms that help users accomplish various tasks through spoken commands. The speech recognition system (speech-to-te…

cs.IR2023★ 2 cited

Graph-Based Model-Agnostic Data Subsampling for Recommendation Systems

Xiaohui Chen, Jiankai Sun, Taiqing Wang +3

Data subsampling is widely used to speed up the training of large-scale recommendation systems. Most subsampling methods are model-based and often require a pre-trained pilot model…

cs.IR2023★ 4 cited

Modeling Spoken Information Queries for Virtual Assistants: Open Problems, Challenges and Opportunities

Christophe Van Gysel

Virtual assistants are becoming increasingly important speech-driven Information Retrieval platforms that assist users with various tasks. We discuss open problems and challenges w…

cs.IR2020★ 7 cited

Predicting Entity Popularity to Improve Spoken Entity Recognition by Virtual Assistants

Christophe Van Gysel, Manos Tsagkias, Ernest Pusateri +1

We focus on improving the effectiveness of a Virtual Assistant (VA) in recognizing emerging entities in spoken queries. We introduce a method that uses historical user interactions…