18 citations · 27 across the 18 of their papers we have counts for
21 papers
Generalized Odds for Ordinal Outcomes: A Causal Inference Framework Adjusting for Covariates
Runnian Huang, Dandan Shi, Lan Liu +1
Background: Generalized Odds (Gen Odds) provide summaries for ordinal outcomes without requiring the proportional odds assumption. However, conventional Gen Odds compares independe…
Encoded but Not in Control: Revealing the Grounding Gap in Vision-Language Robot Policies
Shaohan Jiang, Jiahang Cao, Qiduo He +9
Instruction following is central to language-conditioned robot policies: language should determine what to do when the same scene permits multiple valid actions. Yet successful exe…
EgoWild2Dex: Learning Dexterous Robotic Manipulation from In-the-Wild Human Experience
Kunyang Lin, Xutao Wen, Jingxi Lin +8
Egocentric human data provide a principled source of supervision for learning dexterous robot manipulation. Unlike prior approaches that often collect such data in constrained or s…
Data Pyramid for Embodied Manipulation: A Survey
Yifan Ye, Yankai Fu, Yaoxu Lv +26
Multimodal foundation models learned to see and to speak by consuming the whole internet. Embodied agents admit no such shortcut, since they require data that couple observations w…
UR-VC: Unsupervised Robotic Value Correction for Time-Derived Progress Proxies
Lirui Zhao, Modi Shi, Li Chen +3
Modern robot learning systems increasingly rely on dense progress or value signals to evaluate intermediate states, guide policy learning, and detect task completion, making the qu…
MM-Hand: A 21-DOF Multi-modal Modular Dexterous Robotic Hand with Remote Actuation
Zhuoheng Li, Qingquan Lin, Checheng Yu +5
High-DOF dexterous hands require compact actuation, rich sensing, and reliable thermal behavior, but conventional designs often occupy valuable in-hand space, increase end-effector…
SMASH: Mastering Scalable Whole-Body Skills for Humanoid Ping-Pong with Egocentric Vision
Junli Ren, Yinghui Li, Kai Zhang +12
Existing humanoid table tennis systems remain limited by their reliance on external sensing and their inability to achieve agile whole-body coordination for precise task execution.…
: Resource-Aware Robust Manipulation via Taming Distributional Inconsistencies
Checheng Yu, Chonghao Sima, Gangcheng Jiang +14
High-reliability long-horizon robotic manipulation has traditionally relied on large-scale data and compute to understand complex real-world dynamics. However, we identify that the…
RISE: Self-Improving Robot Policy with Compositional World Model
Jiazhi Yang, Kunyang Lin, Jinwei Li +10
Despite the sustained scaling on model capacity and data acquisition, Vision-Language-Action (VLA) models remain brittle in contact-rich and dynamic manipulation tasks, where minor…
EgoHumanoid: Unlocking In-the-Wild Loco-Manipulation with Robot-Free Egocentric Demonstration
Modi Shi, Shijia Peng, Jin Chen +6
Human demonstrations offer rich environmental diversity and scale naturally, making them an appealing alternative to robot teleoperation. While this paradigm has advanced robot-arm…
Agility Meets Stability: Versatile Humanoid Control with Heterogeneous Data
Yixuan Pan, Ruoyi Qiao, Li Chen +8
Humanoid robots are envisioned to perform a wide range of tasks in human-centered environments, requiring controllers that combine agility with robust balance. Recent advances in l…
Is Diversity All You Need for Scalable Robotic Manipulation?
Modi Shi, Li Chen, Jin Chen +7
Data scaling has driven remarkable success in foundation models for Natural Language Processing (NLP) and Computer Vision (CV), yet the principles of effective data scaling in robo…
UniVLA: Learning to Act Anywhere with Task-centric Latent Actions
Qingwen Bu, Yanting Yang, Jisong Cai +5
A generalist robot should perform effectively across various environments. However, most existing approaches heavily rely on scaling action-annotated data to enhance their capabili…
Centaur: Robust End-to-End Autonomous Driving with Test-Time Training
Chonghao Sima, Kashyap Chitta, Zhiding Yu +5
How can we rely on an end-to-end autonomous vehicle's complex decision-making system during deployment? One common solution is to have a ``fallback layer'' that checks the planned…
AgiBot World Colosseo: A Large-scale Manipulation Platform for Scalable and Intelligent Embodied Systems
AgiBot World Contributors, AgiBot-World-Contributors, Qingwen Bu +50
We explore how scalable robot data can address real-world challenges for generalized robotic manipulation. Introducing AgiBot World, a large-scale platform comprising over 1 millio…
Closed-Loop Visuomotor Control with Generative Expectation for Robotic Manipulation
Qingwen Bu, Jia Zeng, Li Chen +7
Despite significant progress in robotics and embodied AI in recent years, deploying robots for long-horizon tasks remains a great challenge. Majority of prior arts adhere to an ope…
Learning Manipulation by Predicting Interaction
Jia Zeng, Qingwen Bu, Bangjun Wang +12
Representation learning approaches for robotic manipulation have boomed in recent years. Due to the scarcity of in-domain robot data, prevailing methodologies tend to leverage larg…
GenAD: Generalized Predictive Model for Autonomous Driving
Jiazhi Yang, Shenyuan Gao, Yihang Qiu +11
In this paper, we introduce the first large-scale video prediction model in the autonomous driving discipline. To eliminate the restriction of high-cost data collection and empower…
A Survey of Reasoning with Foundation Models
Jiankai Sun, Chuanyang Zheng, Enze Xie +31
Reasoning, a crucial ability for complex problem-solving, plays a pivotal role in various real-world settings such as negotiation, medical diagnosis, and criminal investigation. It…
DriveLM: Driving with Graph Visual Question Answering
Chonghao Sima, Katrin Renz, Kashyap Chitta +7
We study how vision-language models (VLMs) trained on web-scale data can be integrated into end-to-end driving systems to boost generalization and enable interactivity with human u…
OpenLane-V2: A Topology Reasoning Benchmark for Unified 3D HD Mapping
Huijie Wang, Tianyu Li, Yang Li +13
Accurately depicting the complex traffic scene is a vital component for autonomous vehicles to execute correct judgments. However, existing benchmarks tend to oversimplify the scen…