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Notes on diffusion models
4 notes
Mask-Aware Policy Gradients for Diffusion Language Models
The paper presents a method for improving the performance of large language models in tasks like mathematical reasoning and coding by using reinforcement learning. This method addresses the challenge of extending…
Selective Timestep Weighting and Advantage-Based Replay for Sample-Efficient Diffusion RLHF
The paper proposes two methods for improving the efficiency of Reinforcement Learning from Human Feedback (RLHF) when applied to diffusion models, which are often inefficient due to high feedback requirements. The…
Distribution-Aware Diffusion-LLM for Robust Ultra-Long-Term Time Series Forecasting
The authors propose a new method called Diffusion-LLM for time series forecasting using Large Language Models (LLMs). The proposed framework integrates a conditional diffusion model into an LLM-based forecasting…
HyperQuant: A Rate-Distortion-Optimal Quantization Pipeline for Large Language and Diffusion Models
Researchers present HyperQuant, a quantization pipeline for large language and diffusion models, which outperforms other methods in terms of compression rate and quality across various experiments. The method combines…
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