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Bryan Catanzaro

ICLR 2026×9ACL 2026推理多模态数据与预训练强化学习与后训练对齐与偏好
新星分资深
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核心/参与34
方向广度13
合作网络12
0 一作 · 10 篇 · ICLR 2026 / ACL 2026

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2026 顶会论文

10
作者位次 #27/32ICLR 2026Poster· Computer Vision / Vision Models & Multimodal

OmniVinci: Enhancing Architecture and Data for Omni-Modal Understanding LLM

Hanrong Ye · Chao-Han Huck Yang · Arushi Goel · Wei Huang · Zhen Wan · Jinchuan Tian · An-Chieh Cheng · Ligeng Zhu · Yuanhang Su · Yuming Lou · Yong-Xiang Lin · Dong Yang · Sreyan Ghosh · Zhijian Liu · Yukang Chen · Ehsan Jahangiri · Ambrish Dantrey · Daguang Xu · Ehsan Hosseini-Asl · Seyed Danial Mohseni Taheri · Vidya Nariyambut Murali · Sifei Liu · Yao Lu · Oluwatobi Olabiyi · Yu-Chiang Frank Wang · Rafael Valle · Bryan Catanzaro · Andrew Tao · Song Han · Jan Kautz · Hongxu (Danny) Yin · Pavlo Molchanov

多模态长上下文与架构OpenReview
作者位次 #8/8ACL 2026Findings· Findings of ACL

From 128 K to 4 M : Efficient Training of Ultra-Long Context Large Language Models

Chejian Xu · Wei Ping · Peng Xu · Zihan Liu · Boxin Wang · Mohammad Shoeybi · Bo Li · Bryan Catanzaro

摘要

Long-context capabilities are essential for a wide range of applications, including document and video understanding, in-context learning, and inference-time scaling, all of which require models to process and reason over long sequences of text and multimodal data. In this work, we introduce an e...

对齐与偏好多模态效率与系统OpenReview 项目页

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