5 papers
MTA: A Merge-then-Adapt Framework for Personalized Large Language Model
Xiaopeng Li, Yuanjin Zheng, Wanyu Wang +6
Personalized Large Language Models (PLLMs) aim to align model outputs with individual user preferences, a crucial capability for user-centric applications. However, the prevalent a…
Emotion and Intention Guided Multi-Modal Learning for Sticker Response Selection
Yuxuan Hu, Jian Chen, Yuhao Wang +6
Stickers are widely used in online communication to convey emotions and implicit intentions. The Sticker Response Selection (SRS) task aims to select the most contextually appropri…
Bridge the Domains: Large Language Models Enhanced Cross-domain Sequential Recommendation
Qidong Liu, Xiangyu Zhao, Yejing Wang +6
Cross-domain Sequential Recommendation (CDSR) aims to extract the preference from the user's historical interactions across various domains. Despite some progress in CDSR, two prob…
Behavior Modeling Space Reconstruction for E-Commerce Search
Yejing Wang, Chi Zhang, Xiangyu Zhao +8
Delivering superior search services is crucial for enhancing customer experience and driving revenue growth. Conventionally, search systems model user behaviors by combining user p…
Large Language Model Enhanced Recommender Systems: A Survey
Qidong Liu, Xiangyu Zhao, Yuhao Wang +9
Large Language Model (LLM) has transformative potential in various domains, including recommender systems (RS). There have been a handful of research that focuses on empowering the…