4 citations · 12 across the 28 of their papers we have counts for
9 papers · 1 filter
HeteroVDiff: Pipelining Video Diffusion across Mobile NPU and GPU with Shared Weights
Zheyu Shen, Ziyao Wang, Yexiao He +5
Video generation is moving from the cloud to phones for privacy and offline use, and applications often ask for several clips at a time, so on-device video generation is a throughp…
Frozen Models, Evolving Expertise: Model-Agnostic Learning from Deployment Experience for Multimodal Medical AI
Yexiao He, Yucheng Tang, Pengfei Guo +6
Large language models (LLMs) and vision-language models (VLMs) are usually frozen after deployment, so they do not learn from the cases they solve. This is especially concerning in…
DIVA: Dual-Space Intent-Aware Visual Attenuation for Vision-Language-Action Policies
Kaixi Feng, Guoheng Sun, Ziyao Wang +3
Vision-language-action (VLA) policies typically feed dense visual patch tokens into a language-action backbone, preserving scene context but offering no explicit mechanism to regul…
TacGen: Touch Is a Necessary Dimension of Physical-World Representation -- Addressing Tactile Data Scarcity with Scalable Vision-to-Touch Alignment and Generation
Wanghao Ye, Aarosh Das, Sihan Chen +19
Touch resolves the physical-property ambiguity left by vision: exploratory contact recovers shape, texture, compliance, and material, and visuo-haptic object representations conver…
Drop-Then-Recovery: How Redundant Are Vision-Language-Action Models?
Guoheng Sun, Kaixi Feng, Shwai He +8
Vision-Language-Action (VLA) models enable instruction-driven robotic manipulation, but they inherit oversized language backbones from pretrained VLMs whose capacity far exceeds wh…
Mirage: a Clean-Label Backdoor against LiDAR 3D Object Detection
Ziba Parsons, Ang Li
Deep neural network-based LiDAR 3D object detection serves as a critical perception component in safety-critical autonomous systems. However, recent studies have revealed its vulne…
Vision-Language-Action in Robotics: A Survey of Datasets, Benchmarks, and Data Engines
Ziyao Wang, Bingying Wang, Hanrong Zhang +7
Despite remarkable progress in Vision--Language--Action (VLA) models, a central bottleneck remains underexamined: the data infrastructure that underlies embodied learning. In this…
Cognibit: From Digital Exhaustion to Real-World Connection Through Gamified Territory Control and LLM-Powered Twin Networking
Wanghao Ye, Sihan Chen, Yiting Wang +20
We present an LLM-powered social discovery platform that uses digital twins to autonomously evaluate interpersonal compatibility through behavioral simulation. The platform unifies…
UniCompress: Token Compression for Unified Vision-Language Understanding and Generation
Ziyao Wang, Chen Chen, Jingtao Li +4
Unified models aim to support both understanding and generation by encoding images into discrete tokens and processing them alongside text within a single autoregressive framework.…