6 citations · 6 across the 3 of their papers we have counts for
5 papers
Bridge the Gap between Past and Future: Siamese Model Optimization for Context-Aware Document Ranking
Songhao Wu, Quan Tu, Mingjie Zhong +4
In the realm of information retrieval, users often engage in multi-turn interactions with search engines to acquire information, leading to the formation of sequences of user feedb…
Unify Graph Learning with Text: Unleashing LLM Potentials for Session Search
Songhao Wu, Quan Tu, Hong Liu +6
Session search involves a series of interactive queries and actions to fulfill user's complex information need. Current strategies typically prioritize sequential modeling for deep…
From 1,000,000 Users to Every User: Scaling Up Personalized Preference for User-level Alignment
Jia-Nan Li, Jian Guan, Songhao Wu +2
Large language models (LLMs) have traditionally been aligned through one-size-fits-all approaches that assume uniform human preferences, fundamentally overlooking the diversity in…
Autonomy-of-Experts Models
Ang Lv, Ruobing Xie, Yining Qian +5
Mixture-of-Experts (MoE) models mostly use a router to assign tokens to specific expert modules, activating only partial parameters and often outperforming dense models. We argue t…
PEAR: Position-Embedding-Agnostic Attention Re-weighting Enhances Retrieval-Augmented Generation with Zero Inference Overhead
Tao Tan, Yining Qian, Ang Lv +7
Large language models (LLMs) enhanced with retrieval-augmented generation (RAG) have introduced a new paradigm for web search. However, the limited context awareness of LLMs degrad…