5 citations · 8 across the 12 of their papers we have counts for
15 papers
EdgeWise: Bringing Long-Horizon Agents to the Edge via Selective Cloud Delegation
Zeru Shi, Jindong Jiang, Ryo Hachiuma +10
Complex and long-horizon agent tasks often rely on frontier models deployed in the cloud to achieve strong performance. However, using these models for every step of a long-horizon…
Mid-Harness: Scaling Actions Between Model and Harness for Terminal Agents
Minki Kang, Ryo Hachiuma, Shaokun Zhang +8
Terminal agents act through stochastic model generations, yet the ability to generate a useful action does not ensure its reliable execution. A poor command (e.g., wrong package in…
SpatialClaw: Rethinking Action Interface for Agentic Spatial Reasoning
Seokju Cho, Ryo Hachiuma, Abhishek Badki +8
Spatial reasoning, the ability to determine where objects are, how they relate, and how they move in 3D, remains a fundamental challenge for vision-language models (VLMs). Tool-aug…
3D-Layout-R1: Structured Reasoning for Language-Instructed Spatial Editing
Haoyu Zhen, Xiaolong Li, Yilin Zhao +5
Large Language Models (LLMs) and Vision Language Models (VLMs) have shown impressive reasoning abilities, yet they struggle with spatial understanding and layout consistency when p…
4D-RGPT: Toward Region-level 4D Understanding via Perceptual Distillation
Chiao-An Yang, Ryo Hachiuma, Sifei Liu +4
Despite advances in Multimodal LLMs (MLLMs), their ability to reason over 3D structures and temporal dynamics remains limited, constrained by weak 4D perception and temporal unders…
NVIDIA Nemotron Nano V2 VL
NVIDIA, :, Amala Sanjay Deshmukh +121
We introduce Nemotron Nano V2 VL, the latest model of the Nemotron vision-language series designed for strong real-world document understanding, long video comprehension, and reaso…
3D Aware Region Prompted Vision Language Model
An-Chieh Cheng, Yang Fu, Yukang Chen +10
We present Spatial Region 3D (SR-3D) aware vision-language model that connects single-view 2D images and multi-view 3D data through a shared visual token space. SR-3D supports flex…
The 9th AI City Challenge
Zheng Tang, Shuo Wang, David C. Anastasiu +25
The ninth AI City Challenge continues to advance real-world applications of computer vision and AI in transportation, industrial automation, and public safety. The 2025 edition fea…
FRAG: Frame Selection Augmented Generation for Long Video and Long Document Understanding
De-An Huang, Subhashree Radhakrishnan, Zhiding Yu +1
There has been impressive progress in Large Multimodal Models (LMMs). Recent works extend these models to long inputs, including multi-page documents and long videos. However, the…
Eagle 2: Building Post-Training Data Strategies from Scratch for Frontier Vision-Language Models
Zhiqi Li, Guo Chen, Shilong Liu +24
Recently, promising progress has been made by open-source vision-language models (VLMs) in bringing their capabilities closer to those of proprietary frontier models. However, most…
Omni-RGPT: Unifying Image and Video Region-level Understanding via Token Marks
Miran Heo, Min-Hung Chen, De-An Huang +5
We present Omni-RGPT, a multimodal large language model designed to facilitate region-level comprehension for both images and videos. To achieve consistent region representation ac…
Eagle: Exploring The Design Space for Multimodal LLMs with Mixture of Encoders
Min Shi, Fuxiao Liu, Shihao Wang +13
The ability to accurately interpret complex visual information is a crucial topic of multimodal large language models (MLLMs). Recent work indicates that enhanced visual perception…
What is Point Supervision Worth in Video Instance Segmentation?
Shuaiyi Huang, De-An Huang, Zhiding Yu +5
Video instance segmentation (VIS) is a challenging vision task that aims to detect, segment, and track objects in videos. Conventional VIS methods rely on densely-annotated object…
LITA: Language Instructed Temporal-Localization Assistant
De-An Huang, Shijia Liao, Subhashree Radhakrishnan +4
There has been tremendous progress in multimodal Large Language Models (LLMs). Recent works have extended these models to video input with promising instruction following capabilit…
DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision
Shiyi Lan, Zhiding Yu, Christopher Choy +5
We introduce DiscoBox, a novel framework that jointly learns instance segmentation and semantic correspondence using bounding box supervision. Specifically, we propose a self-ensem…