708 citations · 713 across the 7 of their papers we have counts for
6 papers · 1 filter
SO-Bench: A Structural Output Evaluation of Multimodal LLMs
Di Feng, Kaixin Ma, Feng Nan +9
Multimodal large language models (MLLMs) are increasingly deployed in real-world, agentic settings where outputs must not only be correct, but also conform to predefined data schem…
MANZANO: A Simple and Scalable Unified Multimodal Model with a Hybrid Vision Tokenizer
Yanghao Li, Rui Qian, Bowen Pan +24
Unified multimodal Large Language Models (LLMs) that can both understand and generate visual content hold immense potential. However, existing open-source models often suffer from…
Stylus: Automatic Adapter Selection for Diffusion Models
Michael Luo, Justin Wong, Brandon Trabucco +5
Beyond scaling base models with more data or parameters, fine-tuned adapters provide an alternative way to generate high fidelity, custom images at reduced costs. As such, adapters…
3D-MAN: 3D Multi-frame Attention Network for Object Detection
Zetong Yang, Yin Zhou, Zhifeng Chen +1
3D object detection is an important module in autonomous driving and robotics. However, many existing methods focus on using single frames to perform 3D detection, and do not fully…
Scalability in Perception for Autonomous Driving: Waymo Open Dataset
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla +22
The research community has increasing interest in autonomous driving research, despite the resource intensity of obtaining representative real world data. Existing self-driving dat…
GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism
Yanping Huang, Youlong Cheng, Ankur Bapna +8
Scaling up deep neural network capacity has been known as an effective approach to improving model quality for several different machine learning tasks. In many cases, increasing m…