23 citations · 61 across the 32 of their papers we have counts for
13 papers · 1 filter
UniCanvas: A Diffusion-base Unified Model for Text-in-Image Joint Generation
Zeyuan Yang, Hao-Wei Chen, Xueyang Yu +5
Recent years have seen remarkable progress in unified vision-language models handling both multimodal understanding and generation within a single architecture. While autoregressiv…
Fast Spatial Memory with Elastic Test-Time Training
Ziqiao Ma, Xueyang Yu, Haoyu Zhen +3
Large Chunk Test-Time Training (LaCT) has shown strong performance on long-context 3D reconstruction, but its fully plastic inference-time updates remain vulnerable to catastrophic…
A Very Big Video Reasoning Suite
Maijunxian Wang, Ruisi Wang, Juyi Lin +53
Rapid progress in video models has largely focused on visual quality, leaving their reasoning capabilities underexplored. Video reasoning grounds intelligence in spatiotemporally c…
Next-Embedding Prediction Makes Strong Vision Learners
Sihan Xu, Ziqiao Ma, Wenhao Chai +5
Inspired by the success of generative pretraining in natural language, we ask whether the same principles can yield strong self-supervised visual learners. Instead of training mode…
ROVER: Benchmarking Reciprocal Cross-Modal Reasoning for Omnimodal Generation
Yongyuan Liang, Wei Chow, Feng Li +7
Unified multimodal models (UMMs) have emerged as a powerful paradigm for seamlessly unifying text and image understanding and generation. However, prevailing evaluations treat thes…
4D-LRM: Large Space-Time Reconstruction Model From and To Any View at Any Time
Ziqiao Ma, Xuweiyi Chen, Shoubin Yu +10
Can we scale 4D pretraining to learn general space-time representations that reconstruct an object from a few views at some times to any view at any time? We provide an affirmative…
Vision-Language Models Mistake Head Orientation for Gaze Direction: Nonverbal Conversation Cues
Zory Zhang, Pinyuan Feng, Bingyang Wang +7
Where someone looks is a nonverbal communication cue that children and adults readily use. How well can Vision-Language Models (VLMs) infer gaze targets? To construct evaluation st…
VEGGIE: Instructional Editing and Reasoning Video Concepts with Grounded Generation
Shoubin Yu, Difan Liu, Ziqiao Ma +5
Recent video diffusion models have enhanced video editing, but it remains challenging to handle instructional editing and diverse tasks (e.g., adding, removing, changing) within a…
Multi-Object Hallucination in Vision-Language Models
Xuweiyi Chen, Ziqiao Ma, Xuejun Zhang +5
Large vision language models (LVLMs) often suffer from object hallucination, producing objects not present in the given images. While current benchmarks for object hallucination pr…
DriVLMe: Enhancing LLM-based Autonomous Driving Agents with Embodied and Social Experiences
Yidong Huang, Jacob Sansom, Ziqiao Ma +2
Recent advancements in foundation models (FMs) have unlocked new prospects in autonomous driving, yet the experimental settings of these studies are preliminary, over-simplified, a…
GROUNDHOG: Grounding Large Language Models to Holistic Segmentation
Yichi Zhang, Ziqiao Ma, Xiaofeng Gao +3
Most multimodal large language models (MLLMs) learn language-to-object grounding through causal language modeling where grounded objects are captured by bounding boxes as sequences…
Inversion-Free Image Editing with Natural Language
Sihan Xu, Yidong Huang, Jiayi Pan +2
Despite recent advances in inversion-based editing, text-guided image manipulation remains challenging for diffusion models. The primary bottlenecks include 1) the time-consuming n…
CycleNet: Rethinking Cycle Consistency in Text-Guided Diffusion for Image Manipulation
Sihan Xu, Ziqiao Ma, Yidong Huang +2
Diffusion models (DMs) have enabled breakthroughs in image synthesis tasks but lack an intuitive interface for consistent image-to-image (I2I) translation. Various methods have bee…