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20162026
most citedPruning Convolutional Neural Networks for Resource Efficient Inference

1.3k citations · 1.8k across the 82 of their papers we have counts for

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10 papers · 1 filter

cs.CV2026

Nemotron-Labs-Diffusion-Image: Advancing Masked Discrete Diffusion for High-Resolution Image Synthesis

Shufan Li, Greg Heinrich, Hanrong Ye +4

We propose Nemotron-Labs-Diffusion-Image, a state-of-the-art masked discrete diffusion model (MDM) for high-resolution text-to-image synthesis. Compared with prior work on masked i…

cs.CL2026

Nemotron-Labs-Diffusion: A Tri-Mode Language Model Unifying Autoregressive, Diffusion, and Self-Speculation Decoding

Yonggan Fu, Lexington Whalen, Abhinav Garg +23

We introduce Nemotron-Labs-Diffusion, a tri-mode language model (LM) that unifies AR, diffusion, and self-speculation decoding within a single architecture. Trained with a joint AR…

cs.CV2026

RADIO1D: Elastic Representations for Condensed Vision Modeling

Greg Heinrich, Mike Ranzinger, Collin McCarthy +6

This paper challenges the assumption that vision-language models (VLMs) require fixed patch-based 2D vision features. Analyzing fine-tuned vision encoders, we find that representat…

cs.AI2026

PRESTO: Prefix-Aligned Tree Drafting for Diffusion Speculative Decoding

Zheng Wang, Zhifan Ye, Qi Cheng +8

Diffusion Large Language Models (dLLMs) have emerged as a promising alternative to autoregressive (AR) LLMs, generating tokens in parallel. This makes them effective draft models f…

cs.CV2026

Reinforcing Dual-Path Reasoning in Spatial Vision Language Models

Yatai Ji, An-Chieh Cheng, Yang Fu +13

Spatial VLMs have made substantial progress in geometric perception, yet complex spatial reasoning requiring multi-step inference over depth, distance, and scene relations remains…

cs.CV2026

Grounded 3D-Aware Spatial Vision-Language Modeling

An-Chieh Cheng, Yang Fu, Yatai Ji +12

We present GR3D, a spatial vision language model equipped with three complementary grounding capabilities--explicit 2D grounding, implicit 2D grounding, and monocular 3D grounding-…

cs.CV2026

Attend Before Attention: Efficient and Scalable Video Understanding via Autoregressive Gazing

Baifeng Shi, Stephanie Fu, Long Lian +10

Multi-modal large language models (MLLMs) have advanced general-purpose video understanding but struggle with long, high-resolution videos -- they process every pixel equally in th…

cs.CV2026

C-RADIOv4 (Tech Report)

Mike Ranzinger, Greg Heinrich, Collin McCarthy +4

By leveraging multi-teacher distillation, agglomerative vision backbones provide a unified student model that retains and improves the distinct capabilities of multiple teachers. I…

cs.CL2026

GDPO: Group reward-Decoupled Normalization Policy Optimization for Multi-reward RL Optimization

Shih-Yang Liu, Xin Dong, Ximing Lu +10

As language models become increasingly capable, users expect them to provide not only accurate responses but also behaviors aligned with diverse human preferences across a variety…

cs.CV2026

NitroGen: An Open Foundation Model for Generalist Gaming Agents

Loïc Magne, Anas Awadalla, Guanzhi Wang +11

We introduce NitroGen, a vision-action foundation model for generalist gaming agents that is trained on 40,000 hours of gameplay videos across more than 1,000 games. We incorporate…