activity
20232026
most citedText2Reward: Reward Shaping with Language Models for Reinforcement Learning

9 citations · 31 across the 15 of their papers we have counts for

collaborators

15 papers

cs.RO2026

HOTICE: Whole-Body Humanoid Object Transportation in Cluttered Environments

Toan Nguyen, Weiduo Yuan, Siheng Zhao +2

Object transportation is a fundamental capability for humanoid robots operating in real-world, human-centric environments, yet existing methods struggle when clutter constrains fre…

cs.RO2026

LadderMan: Learning Humanoid Perceptive Ladder Climbing

Siheng Zhao, Yuanhang Zhang, Ziqi Lu +6

Humanoid robots hold great promise for operating in human-centered environments, yet ladder climbing remains one of the most challenging tasks due to sparse footholds and handholds…

cs.RO2026

D-REX: Differentiable Real-to-Sim-to-Real Engine for Learning Dexterous Grasping

Haozhe Lou, Mingtong Zhang, Haoran Geng +9

Simulation provides a cost-effective and flexible platform for data generation and policy learning to develop robotic systems. However, bridging the gap between simulation and real…

cs.RO2025

TWIST2: Scalable, Portable, and Holistic Humanoid Data Collection System

Yanjie Ze, Siheng Zhao, Weizhuo Wang +6

Large-scale data has driven breakthroughs in robotics, from language models to vision-language-action models in bimanual manipulation. However, humanoid robotics lacks equally effe…

cs.RO2025

ResMimic: From General Motion Tracking to Humanoid Whole-body Loco-Manipulation via Residual Learning

Siheng Zhao, Yanjie Ze, Yue Wang +4

Humanoid whole-body loco-manipulation promises transformative capabilities for daily service and warehouse tasks. While recent advances in general motion tracking (GMT) have enable…

cs.RO2025

Robot Learning from Any Images

Siheng Zhao, Jiageng Mao, Wei Chow +11

We introduce RoLA, a framework that transforms any in-the-wild image into an interactive, physics-enabled robotic environment. Unlike previous methods, RoLA operates directly on a…

cs.RO2025★ 1 cited

RoboVerse: Towards a Unified Platform, Dataset and Benchmark for Scalable and Generalizable Robot Learning

Haoran Geng, Feishi Wang, Songlin Wei +34

Data scaling and standardized evaluation benchmarks have driven significant advances in natural language processing and computer vision. However, robotics faces unique challenges i…

cs.RO2024

Learning from Massive Human Videos for Universal Humanoid Pose Control

Jiageng Mao, Siheng Zhao, Siqi Song +7

Scalable learning of humanoid robots is crucial for their deployment in real-world applications. While traditional approaches primarily rely on reinforcement learning or teleoperat…

cs.RO2024

GRUtopia: Dream General Robots in a City at Scale

Hanqing Wang, Jiahe Chen, Wensi Huang +19

Recent works have been exploring the scaling laws in the field of Embodied AI. Given the prohibitive costs of collecting real-world data, we believe the Simulation-to-Real (Sim2Rea…

cs.RO2024

TieBot: Learning to Knot a Tie from Visual Demonstration through a Real-to-Sim-to-Real Approach

Weikun Peng, Jun Lv, Yuwei Zeng +5

The tie-knotting task is highly challenging due to the tie's high deformation and long-horizon manipulation actions. This work presents TieBot, a Real-to-Sim-to-Real learning from…

cs.AI2024★ 8 cited

OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments

Tianbao Xie, Danyang Zhang, Jixuan Chen +14

Autonomous agents that accomplish complex computer tasks with minimal human interventions have the potential to transform human-computer interaction, significantly enhancing access…

cs.CL2023★ 6 cited

Lemur: Harmonizing Natural Language and Code for Language Agents

Yiheng Xu, Hongjin Su, Chen Xing +13

We introduce Lemur and Lemur-Chat, openly accessible language models optimized for both natural language and coding capabilities to serve as the backbone of versatile language agen…

cs.LG2023★ 9 cited

Text2Reward: Reward Shaping with Language Models for Reinforcement Learning

Tianbao Xie, Siheng Zhao, Chen Henry Wu +5

Designing reward functions is a longstanding challenge in reinforcement learning (RL); it requires specialized knowledge or domain data, leading to high costs for development. To a…

cs.RO2023★ 2 cited

ClothesNet: An Information-Rich 3D Garment Model Repository with Simulated Clothes Environment

Bingyang Zhou, Haoyu Zhou, Tianhai Liang +10

We present ClothesNet: a large-scale dataset of 3D clothes objects with information-rich annotations. Our dataset consists of around 4400 models covering 11 categories annotated wi…

cs.CL2023★ 5 cited

kNN-BOX: A Unified Framework for Nearest Neighbor Generation

Wenhao Zhu, Qianfeng Zhao, Yunzhe Lv +4

Augmenting the base neural model with a token-level symbolic datastore is a novel generation paradigm and has achieved promising results in machine translation (MT). In this paper,…