I’m Yadnyesh, a student researcher. My research interests include reinforcement learning, reasoning and planning in robotics, flow and diffusion models, discovery-driven AI systems and foundational large language models. I am particularly focused on building interpretable, efficient, and scalable AI systems that drive scientific discovery and create real-world impact.
Flow-based generative models are starting to turn heads as a cool alternative to traditional diffusion methods for things like image and audio generation. What makes them stand out is how they learn smooth, efficient paths to transform one distribution into another—basically a neat and mathematically solid way to generate data. They’ve been getting a lot more buzz lately, especially after Black Forest Labs dropped their FLUX models and SD3.5 model by Stability AI. That success has brought fresh attention to the earlier ideas behind Rectified Flows, which first popped up at ICLR 2023.
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