Tag: guidance
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Inference-Time Alignment for Diffusion Models via Doob’s Matching
Inference-Time Alignment for Diffusion Models via Doob’s Matching arXiv:2601.06514v1 Announce Type: new Abstract: Inference-time alignment for diffusion models aims to adapt a pre-trained diffusion model toward a target distribution without retraining the base score network, thereby preserving the generative capacity of the base model while enforcing desired properties at the inference time. A central mechanism…
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Provable Efficiency of Guidance in Diffusion Models for General Data Distribution
Provable Efficiency of Guidance in Diffusion Models for General Data Distribution arXiv:2505.01382v1 Announce Type: new Abstract: Diffusion models have emerged as a powerful framework for generative modeling, with guidance techniques playing a crucial role in enhancing sample quality. Despite their empirical success, a comprehensive theoretical understanding of the guidance effect remains limited. Existing studies only…
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Classifier-free guidance for LLMs performance enhancing
Classifier-free guidance for LLMs performance enhancing Classifier-Free Guidance for LLMs Performance Enhancing Check and improve classifier-free guidance for text generation large language models. While participating in NeurIPS 2024 Competitions track I was awarded the second prize in the LLM Privacy challenge. The solution I had used classifier-free guidance (CFG). I noticed that with high CFG guidance…