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cs.LG2024
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…
cs.LG2024★ 1 cited
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…
cs.CL2024★ 1 cited
Your Finetuned Large Language Model is Already a Powerful Out-of-distribution Detector
Andi Zhang, Tim Z. Xiao, Weiyang Liu +2
We revisit the likelihood ratio between a pretrained large language model (LLM) and its finetuned variant as a criterion for out-of-distribution (OOD) detection. The intuition behi…