2 citations · 4 across the 12 of their papers we have counts for
14 papers
Context-Matched Distillation: Teacher Causality for Autoregressive Video Distillation
Hmrishav Bandyopadhyay, Xuanchi Ren, Zijian Huang +7
Interactive autoregressive video generation demands both low-latency rollouts and precise online control. Few-step distillation accelerates generation by reducing denoising steps,…
Block Cascading: Training Free Acceleration of Block-Causal Video Models
Hmrishav Bandyopadhyay, Nikhil Pinnaparaju, Rahim Entezari +3
Block-causal video generation faces a stark speed-quality trade-off: small 1.3B models manage only 16 FPS while large 14B models crawl at 4.5 FPS, forcing users to choose between r…
SD3.5-Flash: Distribution-Guided Distillation of Generative Flows
Hmrishav Bandyopadhyay, Rahim Entezari, Jim Scott +3
We present SD3.5-Flash, an efficient few-step distillation framework that brings high-quality image generation to accessible consumer devices. Our approach distills computationally…
Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models
Dar-Yen Chen, Hmrishav Bandyopadhyay, Kai Zou +1
Negative guidance -- explicitly suppressing unwanted attributes -- remains a fundamental challenge in diffusion models, particularly in few-step sampling regimes. While Classifier-…
NitroFusion: High-Fidelity Single-Step Diffusion through Dynamic Adversarial Training
Dar-Yen Chen, Hmrishav Bandyopadhyay, Kai Zou +1
We introduce NitroFusion, a fundamentally different approach to single-step diffusion that achieves high-quality generation through a dynamic adversarial framework. While one-step…
FlipSketch: Flipping Static Drawings to Text-Guided Sketch Animations
Hmrishav Bandyopadhyay, Yi-Zhe Song
Sketch animations offer a powerful medium for visual storytelling, from simple flip-book doodles to professional studio productions. While traditional animation requires teams of s…