2 papers
cs.CL2026
Attn-GS: Attention-Guided Context Compression for Efficient Personalized LLMs
Shenglai Zeng, Tianqi Zheng, Chuan Tian +10
Personalizing large language models (LLMs) to individual users requires incorporating extensive interaction histories and profiles, but input token constraints make this impractica…
cs.IR2024
Towards Scalability and Extensibility of Query Reformulation Modeling in E-commerce Search
Ziqi Zhang, Yupin Huang, Quan Deng +3
Customer behavioral data significantly impacts e-commerce search systems. However, in the case of less common queries, the associated behavioral data tends to be sparse and noisy,…