3 citations · 3 across the 4 of their papers we have counts for
8 papers
NExT-Search: Rebuilding User Feedback Ecosystem for Generative AI Search
Sunhao Dai, Wenjie Wang, Liang Pang +4
Generative AI search is reshaping information retrieval by offering end-to-end answers to complex queries, reducing users' reliance on manually browsing and summarizing multiple we…
Exploring the Impact of Personality Traits on Conversational Recommender Systems: A Simulation with Large Language Models
Xiaoyan Zhao, Yang Deng, Wenjie Wang +5
Conversational Recommender Systems (CRSs) engage users in multi-turn interactions to deliver personalized recommendations. The emergence of large language models (LLMs) further enh…
Personalized Text Generation with Contrastive Activation Steering
Jinghao Zhang, Yuting Liu, Wenjie Wang +4
Personalized text generation aims to infer users' writing style preferences from their historical texts and generate outputs that faithfully reflect these stylistic characteristics…
Exploring Training and Inference Scaling Laws in Generative Retrieval
Hongru Cai, Yongqi Li, Ruifeng Yuan +4
Generative retrieval reformulates retrieval as an autoregressive generation task, where large language models (LLMs) generate target documents directly from a query. As a novel par…
Bridging Jensen Gap for Max-Min Group Fairness Optimization in Recommendation
Chen Xu, Yuxin Li, Wenjie Wang +3
Group max-min fairness (MMF) is commonly used in fairness-aware recommender systems (RS) as an optimization objective, as it aims to protect marginalized item groups and ensures a…
TokenSkip: Controllable Chain-of-Thought Compression in LLMs
Heming Xia, Chak Tou Leong, Wenjie Wang +2
Chain-of-Thought (CoT) has been proven effective in enhancing the reasoning capabilities of large language models (LLMs). Recent advancements, such as OpenAI's o1 and DeepSeek-R1,…