2 citations · 2 across the 10 of their papers we have counts for
13 papers
T-Rex: Tactile-Reactive Dexterous Manipulation
Dantong Niu, Zhuoyang Liu, Zekai Wang +31
The ability to react dynamically to tactile signals has long been considered crucial to agile human-level dexterity. Yet contemporary learning-based Vision-Language-Action (VLA) mo…
Playful Agentic Robot Learning
Junyi Zhang, Jiaxin Ge, Hanjun Yoo +17
Current agentic robot systems can write executable Code-as-Policy programs, observe feedback, and revise behavior across multiple attempts, but they remain largely task-driven: reu…
VisGym: Diverse, Customizable, Scalable Environments for Multimodal Agents
Zirui Wang, Junyi Zhang, Jiaxin Ge +9
Modern Vision-Language Models (VLMs) remain poorly characterized in multi-step visual interactions, particularly in how they integrate perception, memory, and action over long hori…
Vision-as-Inverse-Graphics Agent via Interleaved Multimodal Reasoning
Shaofeng Yin, Jiaxin Ge, Zora Zhiruo Wang +6
Vision-as-inverse-graphics, the concept of reconstructing images into editable programs, remains challenging for Vision-Language Models (VLMs), which inherently lack fine-grained s…
Chain-of-Visual-Thought: Teaching VLMs to See and Think Better with Continuous Visual Tokens
Yiming Qin, Bomin Wei, Jiaxin Ge +4
Vision-Language Models (VLMs) excel at reasoning in linguistic space but struggle with perceptual understanding that requires dense visual perception, e.g., spatial reasoning and g…
Constantly Improving Image Models Need Constantly Improving Benchmarks
Jiaxin Ge, Grace Luo, Heekyung Lee +7
Recent advances in image generation, often driven by proprietary systems like GPT-4o Image Gen, regularly introduce new capabilities that reshape how users interact with these mode…
Puzzled by Puzzles: When Vision-Language Models Can't Take a Hint
Heekyung Lee, Jiaxin Ge, Tsung-Han Wu +3
Rebus puzzles, visual riddles that encode language through imagery, spatial arrangement, and symbolic substitution, pose a unique challenge to current vision-language models (VLMs)…
Generate, but Verify: Reducing Hallucination in Vision-Language Models with Retrospective Resampling
Tsung-Han Wu, Heekyung Lee, Jiaxin Ge +3
Vision-Language Models (VLMs) excel at visual understanding but often suffer from visual hallucinations, where they generate descriptions of nonexistent objects, actions, or concep…
Enough Coin Flips Can Make LLMs Act Bayesian
Ritwik Gupta, Rodolfo Corona, Jiaxin Ge +4
Large language models (LLMs) exhibit the ability to generalize given few-shot examples in their input prompt, an emergent capability known as in-context learning (ICL). We investig…
AutoPresent: Designing Structured Visuals from Scratch
Jiaxin Ge, Zora Zhiruo Wang, Xuhui Zhou +8
Designing structured visuals such as presentation slides is essential for communicative needs, necessitating both content creation and visual planning skills. In this work, we tack…
Recursive Visual Programming
Jiaxin Ge, Sanjay Subramanian, Baifeng Shi +2
Visual Programming (VP) has emerged as a powerful framework for Visual Question Answering (VQA). By generating and executing bespoke code for each question, these methods demonstra…
From Wrong To Right: A Recursive Approach Towards Vision-Language Explanation
Jiaxin Ge, Sanjay Subramanian, Trevor Darrell +1
Addressing the challenge of adapting pre-trained vision-language models for generating insightful explanations for visual reasoning tasks with limited annotations, we present ReVis…
Lyfe Agents: Generative agents for low-cost real-time social interactions
Zhao Kaiya, Michelangelo Naim, Jovana Kondic +5
Highly autonomous generative agents powered by large language models promise to simulate intricate social behaviors in virtual societies. However, achieving real-time interactions…