1 citations · 1 across the 3 of their papers we have counts for
6 papers
Replay What Matters: Off-Policy Replay for Efficient LLM Reinforcement Unlearning
Zirui Pang, Chenlong Zhang, Haosheng Tan +3
LLM unlearning has emerged as a cost-effective alternative to full retraining for removing hazardous knowledge from pretrained models while preserving general utility. Recent RL-ba…
Consensus on Dynamic Stochastic Block Models: Fast Convergence and Phase Transitions
Haoyu Wang, Jiaheng Wei, Zhenyuan Zhang
We introduce two models of consensus following a majority rule on time-evolving stochastic block models (SBM), in which the network evolution is Markovian or non-Markovian. Under t…
Automatic Dataset Construction (ADC): Sample Collection, Data Curation, and Beyond
Minghao Liu, Zonglin Di, Jiaheng Wei +15
Large-scale data collection is essential for developing personalized training data, mitigating the shortage of training data, and fine-tuning specialized models. However, creating…
Incentivizing High-quality Participation From Federated Learning Agents
Jinlong Pang, Jiaheng Wei, Yifan Hua +2
Federated learning (FL) provides a promising paradigm for facilitating collaboration between multiple clients that jointly learn a global model without directly sharing their local…
Human and AI Perceptual Differences in Image Classification Errors
Minghao Liu, Jiaheng Wei, Yang Liu +1
Artificial intelligence (AI) models for computer vision trained with supervised machine learning are assumed to solve classification tasks by imitating human behavior learned from…
Measuring and Reducing LLM Hallucination without Gold-Standard Answers
Jiaheng Wei, Yuanshun Yao, Jean-Francois Ton +3
LLM hallucination, i.e. generating factually incorrect yet seemingly convincing answers, is currently a major threat to the trustworthiness and reliability of LLMs. The first step…