2 citations · 3 across the 11 of their papers we have counts for
6 papers · 1 filter
Black-box Model Merging for Language-Model-as-a-Service with Massive Model Repositories
Shilian Chen, Jie Zhou, Tianyu Huai +9
Model merging refers to the process of integrating multiple distinct models into a unified model that preserves and combines the strengths and capabilities of the individual models…
LifeAlign: Lifelong Alignment for Large Language Models with Memory-Augmented Focalized Preference Optimization
Junsong Li, Jie Zhou, Bihao Zhan +7
Alignment plays a crucial role in Large Language Models (LLMs) in aligning with human preferences on a specific task/domain. Traditional alignment methods suffer from catastrophic…
Forget What's Sensitive, Remember What Matters: Token-Level Differential Privacy in Memory Sculpting for Continual Learning
Bihao Zhan, Jie Zhou, Junsong Li +9
Continual Learning (CL) models, while adept at sequential knowledge acquisition, face significant and often overlooked privacy challenges due to accumulating diverse information. T…
Building Self-Evolving Agents via Experience-Driven Lifelong Learning: A Framework and Benchmark
Yuxuan Cai, Yipeng Hao, Jie Zhou +14
As AI advances toward general intelligence, the focus is shifting from systems optimized for static tasks to creating open-ended agents that learn continuously. In this paper, we i…
Reinforced Interactive Continual Learning via Real-time Noisy Human Feedback
Yutao Yang, Jie Zhou, Junsong Li +5
This paper introduces an interactive continual learning paradigm where AI models dynamically learn new skills from real-time human feedback while retaining prior knowledge. This pa…
Teaching LLMs for Step-Level Automatic Math Correction via Reinforcement Learning
Junsong Li, Jie Zhou, Yutao Yang +7
Automatic math correction aims to check students' solutions to mathematical problems via artificial intelligence technologies. Most existing studies focus on judging the final answ…