1 citations · 2 across the 7 of their papers we have counts for
4 papers · 1 filter
Value Gradient Guidance for Flow Matching Alignment
Zhen Liu, Tim Z. Xiao, Carles Domingo-Enrich +2
While methods exist for aligning flow matching models--a popular and effective class of generative models--with human preferences, existing approaches fail to achieve both adaptati…
Flipping Against All Odds: Reducing LLM Coin Flip Bias via Verbalized Rejection Sampling
Tim Z. Xiao, Johannes Zenn, Zhen Liu +3
Large language models (LLMs) can often accurately describe probability distributions using natural language, yet they still struggle to generate faithful samples from them. This mi…
Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets
Zhen Liu, Tim Z. Xiao, Weiyang Liu +2
While one commonly trains large diffusion models by collecting datasets on target downstream tasks, it is often desired to align and finetune pretrained diffusion models with some…
Verbalized Machine Learning: Revisiting Machine Learning with Language Models
Tim Z. Xiao, Robert Bamler, Bernhard Schölkopf +1
Motivated by the progress made by large language models (LLMs), we introduce the framework of verbalized machine learning (VML). In contrast to conventional machine learning (ML) m…