12 citations · 13 across the 4 of their papers we have counts for
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stat.ML2024
Training-Free Bayesianization for Low-Rank Adapters of Large Language Models
Haizhou Shi, Yibin Wang, Ligong Han +2
Estimating the uncertainty of responses from Large Language Models (LLMs) remains a critical challenge. While recent Bayesian methods have demonstrated effectiveness in quantifying…
cs.LG2024★ 1 cited
BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models
Yibin Wang, Haizhou Shi, Ligong Han +2
Large Language Models (LLMs) often suffer from overconfidence during inference, particularly when adapted to downstream domain-specific tasks with limited data. Previous work addre…
cs.LG2024★ 12 cited
Continual Learning of Large Language Models: A Comprehensive Survey
Haizhou Shi, Zihao Xu, Hengyi Wang +6
The recent success of large language models (LLMs) trained on static, pre-collected, general datasets has sparked numerous research directions and applications. One such direction…