48 citations · 88 across the 27 of their papers we have counts for
29 papers
SUN: Agentic Robot Policy Learning with Persistent Task Programs
Weiqi Wang, Zhi Li, Yudong Lei +7
Model-based control can directly execute specified objectives, while learning can amortize such behaviors into reactive policies, making their combination a natural solution to mul…
RoboEdit: Turning Human Manipulation Videos into Scalable Robot Experience
Yaowei Guo, Zeng Tao, Yuxin Jiang +7
Collecting robot hand-object interaction data is costly and embodiment-specific, yet abundant human-object videos remain unusable for robot training. We present RoboEdit, a human-t…
WebRider: Persona-Conditioned Intent Controllers for Live-Web Assistance
Zhi Li, Tao Zhou, Yeqing Li +2
Delegating a web task involves more than asking a question; it requires transferring a policy: what to verify, how to handle uncertainty, which preferences matter, and when to stop…
Can Current Agents Close the Discovery-to-Application Gap? A Case Study in Minecraft
Zhou Ziheng, Huacong Tang, Jinyuan Zhang +9
Discovering causal regularities and applying them to build functional systems--the discovery-to-application loop--is a hallmark of general intelligence, yet evaluating this capacit…
MPM Lite: Linear Kernels and Integration without Particles
Xiang Feng, Yunuo Chen, Chang Yu +6
In this paper, we introduce MPM Lite, a new hybrid Lagrangian/Eulerian method that eliminates the need for particle-based quadrature at solve time. Standard MPM practices suffer fr…
Simple Role Assignment is Extraordinarily Effective for Safety Alignment
Zhou Ziheng, Jiakun Ding, Zhaowei Zhang +6
Principle-based alignment often lacks context sensitivity and completeness. Grounded in Theory of Mind, we propose role conditioning as a compact alternative: social roles (e.g., m…
AnimaMimic: Imitating 3D Animation from Video Priors
Tianyi Xie, Yunuo Chen, Yaowei Guo +5
Creating realistic 3D animation remains a time-consuming and expertise-dependent process, requiring manual rigging, keyframing, and fine-tuning of complex motions. Meanwhile, video…
A Human-centric Framework for Debating the Ethics of AI Consciousness Under Uncertainty
Zhou Ziheng, Haiqiang Dai, Bin Ling +2
As AI systems become increasingly sophisticated, questions about machine consciousness and its ethical implications have moved from fringe speculation to mainstream academic debate…
Why Are We Moral? An LLM-based Agent Simulation Approach to Study Moral Evolution
Zhou Ziheng, Huacong Tang, Mingjie Bi +7
The evolution of morality presents a puzzle: natural selection should favor self-interest, yet humans developed moral systems promoting altruism. Traditional approaches must abstra…
Review of Deep Learning Applications to Structural Proteomics Enabled by Cryogenic Electron Microscopy and Tomography
Brady K. Zhou, Jason J. Hu, Jane K. J. Lee +2
The past decade's "cryoEM revolution" has produced exponential growth in high-resolution structural data through advances in cryogenic electron microscopy (cryoEM) and tomography (…
CFSum: A Transformer-Based Multi-Modal Video Summarization Framework With Coarse-Fine Fusion
Yaowei Guo, Jiazheng Xing, Xiaojun Hou +5
Video summarization, by selecting the most informative and/or user-relevant parts of original videos to create concise summary videos, has high research value and consumer demand i…
TeamCraft: A Benchmark for Multi-Modal Multi-Agent Systems in Minecraft
Qian Long, Zhi Li, Ran Gong +3
Collaboration is a cornerstone of society. In the real world, human teammates make use of multi-sensory data to tackle challenging tasks in ever-changing environments. It is essent…
Wonderland: Navigating 3D Scenes from a Single Image
Hanwen Liang, Junli Cao, Vidit Goel +6
How can one efficiently generate high-quality, wide-scope 3D scenes from arbitrary single images? Existing methods suffer several drawbacks, such as requiring multi-view data, time…
Inverse Attention Agents for Multi-Agent Systems
Qian Long, Ruoyan Li, Minglu Zhao +2
A major challenge for Multi-Agent Systems is enabling agents to adapt dynamically to diverse environments in which opponents and teammates may continually change. Agents trained us…
Prompting Medical Large Vision-Language Models to Diagnose Pathologies by Visual Question Answering
Danfeng Guo, Demetri Terzopoulos
Large Vision-Language Models (LVLMs) have achieved significant success in recent years, and they have been extended to the medical domain. Although demonstrating satisfactory perfo…
Cross-Slice Attention and Evidential Critical Loss for Uncertainty-Aware Prostate Cancer Detection
Alex Ling Yu Hung, Haoxin Zheng, Kai Zhao +3
Current deep learning-based models typically analyze medical images in either 2D or 3D albeit disregarding volumetric information or suffering sub-optimal performance due to the an…
An Interactive Agent Foundation Model
Zane Durante, Bidipta Sarkar, Ran Gong +17
The development of artificial intelligence systems is transitioning from creating static, task-specific models to dynamic, agent-based systems capable of performing well in a wide…
Agent AI: Surveying the Horizons of Multimodal Interaction
Zane Durante, Qiuyuan Huang, Naoki Wake +11
Multi-modal AI systems will likely become a ubiquitous presence in our everyday lives. A promising approach to making these systems more interactive is to embody them as agents wit…
Aligner: One Global Token is Worth Millions of Parameters When Aligning Large Language Models
Zhou Ziheng, Yingnian Wu, Song-Chun Zhu +1
We introduce Aligner, a novel Parameter-Efficient Fine-Tuning (PEFT) method for aligning multi-billion-parameter-sized Large Language Models (LLMs). Aligner employs a unique design…
Unstructured Moving Least Squares Material Point Methods: A Stable Kernel Approach With Continuous Gradient Reconstruction on General Unstructured Tessellations
Yadi Cao, Yidong Zhao, Minchen Li +4
The Material Point Method (MPM) is a hybrid Eulerian Lagrangian simulation technique for solid mechanics with significant deformation. Structured background grids are commonly empl…
CSAM: A 2.5D Cross-Slice Attention Module for Anisotropic Volumetric Medical Image Segmentation
Alex Ling Yu Hung, Haoxin Zheng, Kai Zhao +6
A large portion of volumetric medical data, especially magnetic resonance imaging (MRI) data, is anisotropic, as the through-plane resolution is typically much lower than the in-pl…
Semi-Supervised Relational Contrastive Learning
Attiano Purpura-Pontoniere, Demetri Terzopoulos, Adam Wang +1
Disease diagnosis from medical images via supervised learning is usually dependent on tedious, error-prone, and costly image labeling by medical experts. Alternatively, semi-superv…
ARNOLD: A Benchmark for Language-Grounded Task Learning With Continuous States in Realistic 3D Scenes
Ran Gong, Jiangyong Huang, Yizhou Zhao +9
Understanding the continuous states of objects is essential for task learning and planning in the real world. However, most existing task learning benchmarks assume discrete (e.g.,…
A Mobility-Aware Deep Learning Model for Long-Term COVID-19 Pandemic Prediction and Policy Impact Analysis
Danfeng Guo, Zijie Huang, Junheng Hao +3
Pandemic(epidemic) modeling, aiming at disease spreading analysis, has always been a popular research topic especially following the outbreak of COVID-19 in 2019. Some representati…