Functional grasping with dexterous robotic hands is a key capability for enabling tool use and complex manipulation, yet progress has been constrained by two pe...
Referring Expression Segmentation (RES) and Comprehension (REC) respectively segment and detect the object described by an expression, while Referring Expressio...
As language models become increasingly capable, users expect them to provide not only accurate responses but also behaviors aligned with diverse human preferenc...
The diversity, quantity, and quality of manipulation data are critical for training effective robot policies. However, due to hardware and physical setup constr...
Large language models suffer from 'hallucinations'-logical inconsistencies induced by semantic noise. We propose that current architectures operate in a 'Metric...
Camera-controlled generative video re-rendering methods, such as ReCamMaster, have achieved remarkable progress. However, despite their success in single-view s...
Humans can effortlessly anticipate how objects might move or change through interaction--imagining a cup being lifted, a knife slicing, or a lid being closed. W...
We used machine learning and artificial intelligence: 1) to measure levels of peace in countries from news and social media and 2) to develop on-line tools that...
Agents capable of reasoning and planning in the real world require the ability of predicting the consequences of their actions. While world models possess this ...
I propose a novel framework that integrates stochastic differential equations (SDEs) with deep generative models to improve uncertainty quantification in machin...
One-shot prediction enables rapid adaptation of pretrained foundation models to new tasks using only one labeled example, but lacks principled uncertainty quant...
We present textsc{MineNPC-Task}, a user-authored benchmark and evaluation harness for testing memory-aware, mixed-initiative LLM agents in open-world Minecraft....
