39 citations · 56 across the 16 of their papers we have counts for
16 papers
DriveReferee: Geometric Safety Verdicts Need Not Be Learned for Driving World-Action Models
Fengcheng Yu, Dhruv Parikh, Junjie Ye +5
Generative world-action models (WAMs) jointly generate future video and vehicle actions, while their action branches remain primarily optimized by expert imitation. Yet imitation p…
Logic-VLA: A Temporal Logic Conditioned Vision-Language-Action Model
Celina Shiyu Wang, Yiqi Zhao, Junjie Ye +2
Vision-language-action (VLA) models can follow natural-language (NL) task instructions, but such instructions may not precisely specify safety-critical or spatiotemporal requiremen…
Distill What RGB Can Recover: Privileged 3D Evidence for RGB-Only Vision-Language Models
Yanbin Hu, Jin Cui, Jun Ye +4
3D scene understanding requires reasoning about entity existence, spatial layout, and object relations, yet RGB images alone often provide insufficient 3D cues. Existing 3D-VLMs co…
Duet: Dual-Robot Understanding via Efficient Teaching
Yiqi Zhao, Ruohai Ge, Celina Shiyu Wang +10
Dual-robot collaboration enables tasks that exceed the reach and payload of a single robot, such as collaboratively transporting objects across environments and executing coordinat…
SIMPLE: Simulation-Based Policy Learning and Evaluation for Humanoid Loco-manipulation
Songlin Wei, Zhenhao Ni, Jie Liu +9
Humanoid foundation models are advancing faster than we can evaluate them. While real-world testing is expensive and difficult to reproduce, existing simulation benchmarks focus pr…
RoboDream: Compositional World Models for Scalable Robot Data Synthesis
Junjie Ye, Rong Xue, Basile Van Hoorick +6
Scaling robot learning requires large-scale, diverse demonstrations, yet real-world data collection via teleoperation remains prohibitively expensive and time-consuming. While vide…
HyperLogic: A Hard, Forward-Authored Chinese Logical Reasoning Benchmark with Execution-Derived Answers
Ming Zhang, Qiyuan Peng, Yinxi Wei +16
Existing logic benchmarks primarily measure models' ability to answer reasoning questions directly. Scalable benchmarks often generate text from formal structures, which makes answ…
ECHO: Continuous Hierarchical Memory for Vision-Language-Action Models
Yanbin Hu, Jin Cui, Jiayi Lu +6
Memory capacity is a critical factor determining the performance of Vision-Language-Action (VLA) models in long-horizon manipulation tasks. Existing memory-augmented architectures…
FinToolSyn: A forward synthesis Framework for Financial Tool-Use Dialogue Data with Dynamic Tool Retrieval
Caishuang Huang, Yang Qiao, Rongyu Zhang +8
Tool-use capabilities are vital for Large Language Models (LLMs) in finance, a domain characterized by massive investment targets and data-intensive inquiries. However, existing da…
VideoGPA: Distilling Geometry Priors for 3D-Consistent Video Generation
Hongyang Du, Junjie Ye, Xiaoyan Cong +7
While recent video diffusion models (VDMs) produce visually impressive results, they fundamentally struggle to maintain 3D structural consistency, often resulting in object deforma…
AnchorDream: Repurposing Video Diffusion for Embodiment-Aware Robot Data Synthesis
Junjie Ye, Rong Xue, Basile Van Hoorick +4
The collection of large-scale and diverse robot demonstrations remains a major bottleneck for imitation learning, as real-world data acquisition is costly and simulators offer limi…
SMART: Advancing Scalable Map Priors for Driving Topology Reasoning
Junjie Ye, David Paz, Hengyuan Zhang +5
Topology reasoning is crucial for autonomous driving as it enables comprehensive understanding of connectivity and relationships between lanes and traffic elements. While recent ap…
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…
RAM: Retrieval-Based Affordance Transfer for Generalizable Zero-Shot Robotic Manipulation
Yuxuan Kuang, Junjie Ye, Haoran Geng +5
This work proposes a retrieve-and-transfer framework for zero-shot robotic manipulation, dubbed RAM, featuring generalizability across various objects, environments, and embodiment…
A Language Agent for Autonomous Driving
Jiageng Mao, Junjie Ye, Yuxi Qian +2
Human-level driving is an ultimate goal of autonomous driving. Conventional approaches formulate autonomous driving as a perception-prediction-planning framework, yet their systems…
GPT-Driver: Learning to Drive with GPT
Jiageng Mao, Yuxi Qian, Junjie Ye +2
We present a simple yet effective approach that can transform the OpenAI GPT-3.5 model into a reliable motion planner for autonomous vehicles. Motion planning is a core challenge i…