6 papers
LeanMem: Simple and Efficient Long-Term Memory for LLM Agents
Yuxin Liao, Le Wu, Min Hou +3
Long-term memory is essential for LLM-based agents to sustain interactions and reliably leverage distant history. However, existing memory systems typically process heterogeneous d…
An Efficient LLM-based Evolutional Recommendation with Locate-Forget-Update Paradigm
Hao Liu, Le Wu, Min Hou +4
Nowadays, Large Language Models (LLMs) have shown exceptional performance in sequential recommendations, and the adoption of LLM-based recommender systems (LLMRec) is becoming incr…
Multi-Value Alignment for LLMs via Value Decorrelation and Extrapolation
Hefei Xu, Le Wu, Chen Cheng +1
With the rapid advancement of large language models (LLMs), aligning them with human values for safety and ethics has become a critical challenge. This problem is especially challe…
WeaveRec: An LLM-Based Cross-Domain Sequential Recommendation Framework with Model Merging
Min Hou, Xin Liu, Le Wu +5
Cross-Domain Sequential Recommendation (CDSR) seeks to improve user preference modeling by transferring knowledge from multiple domains. Despite the progress made in CDSR, most exi…
RecCocktail: A Generalizable and Efficient Framework for LLM-Based Recommendation
Min Hou, Chenxi Bai, Le Wu +6
Large Language Models (LLMs) have achieved remarkable success in recent years, owing to their impressive generalization capabilities and rich world knowledge. To capitalize on the…
RecGPT Technical Report
Chao Yi, Dian Chen, Gaoyang Guo +51
Recommender systems are among the most impactful applications of artificial intelligence, serving as critical infrastructure connecting users, merchants, and platforms. However, mo…