1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.IR2026
Can We Steer the Black-Box? Towards Controllability-Centric Evaluation of Recommender Systems with Collaborative Agents
Jiwen Zhou, Xiang Liu, Mingming Li +5
Recommender systems operate as Black-Boxes, leaving users and regulators unable to steer their outputs toward specific intentions or audit their behavior. This lack of controllabil…
cs.CR2024★ 1 cited
A Framework for Cost-Effective and Self-Adaptive LLM Shaking and Recovery Mechanism
Zhiyu Chen, Yu Li, Suochao Zhang +4
As Large Language Models (LLMs) gain great success in real-world applications, an increasing number of users are seeking to develop and deploy their customized LLMs through cloud s…
cs.LG2023
Federated Learning of Large Language Models with Parameter-Efficient Prompt Tuning and Adaptive Optimization
Tianshi Che, Ji Liu, Yang Zhou +5
Federated learning (FL) is a promising paradigm to enable collaborative model training with decentralized data. However, the training process of Large Language Models (LLMs) genera…