6 citations · 8 across the 17 of their papers we have counts for
6 papers · 1 filter
ContextFlow: In-Context Flow Matching for Robot Manipulation
Jian Ding, Xianjie Dai, Roei Herzig +5
Although highly effective in vision and language domains, applying in-context learning to robotics remains challenging. Existing autoregressive in-context imitation methods discret…
Discriminative World Models for Web Agents
Kelvin Li, Dhruv Pendharkar, Anish Pahilajani +6
Recent web agents use world models for test-time action selection by sampling candidate actions, predicting the resulting web states, and ranking them with a ranker model or a Proc…
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…
Contrastive Action-Image Pre-training for Visuomotor Control
Yuvan Sharma, Dantong Niu, Anirudh Pai +16
Existing vision encoders for robotics face a fundamental bottleneck: robotic datasets lack the scale necessary for large-scale pre-training. Prior work circumvents this data scarci…
ChartNet: A Million-Scale, High-Quality Multimodal Dataset for Robust Chart Understanding
Jovana Kondic, Pengyuan Li, Dhiraj Joshi +24
Understanding charts requires models to jointly reason over geometric visual patterns, structured numerical data, and natural language -- a capability where current vision-language…