6 citations · 9 across the 8 of their papers we have counts for
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cs.LG2025
Efficient Regression-Based Training of Normalizing Flows for Boltzmann Generators
Danyal Rehman, Oscar Davis, Jiarui Lu +5
Simulation-free training frameworks have been at the forefront of the generative modelling revolution in continuous spaces, leading to large-scale diffusion and flow matching model…
cs.LG2024★ 3 cited
HRLAIF: Improvements in Helpfulness and Harmlessness in Open-domain Reinforcement Learning From AI Feedback
Ang Li, Qiugen Xiao, Peng Cao +12
Reinforcement Learning from AI Feedback (RLAIF) has the advantages of shorter annotation cycles and lower costs over Reinforcement Learning from Human Feedback (RLHF), making it hi…
cs.LG2024
In-Context Learning Can Re-learn Forbidden Tasks
Sophie Xhonneux, David Dobre, Jian Tang +2
Despite significant investment into safety training, large language models (LLMs) deployed in the real world still suffer from numerous vulnerabilities. One perspective on LLM safe…