Search Results for author: Jianyu Chen

Found 48 papers, 22 papers with code

UP-VLA: A Unified Understanding and Prediction Model for Embodied Agent

no code implementations31 Jan 2025 Jianke Zhang, Yanjiang Guo, Yucheng Hu, Xiaoyu Chen, Xiang Zhu, Jianyu Chen

Recent advancements in Vision-Language-Action (VLA) models have leveraged pre-trained Vision-Language Models (VLMs) to improve the generalization capabilities.

Improving Vision-Language-Action Model with Online Reinforcement Learning

no code implementations28 Jan 2025 Yanjiang Guo, Jianke Zhang, Xiaoyu Chen, Xiang Ji, Yen-Jen Wang, Yucheng Hu, Jianyu Chen

Recent studies have successfully integrated large vision-language models (VLMs) into low-level robotic control by supervised fine-tuning (SFT) with expert robotic datasets, resulting in what we term vision-language-action (VLA) models.

reinforcement-learning Reinforcement Learning +1

AIF-SFDA: Autonomous Information Filter-driven Source-Free Domain Adaptation for Medical Image Segmentation

1 code implementation6 Jan 2025 Haojin Li, Heng Li, Jianyu Chen, Rihan Zhong, Ke Niu, Huazhu Fu, Jiang Liu

Decoupling domain-variant information (DVI) from domain-invariant information (DII) serves as a prominent strategy for mitigating domain shifts in the practical implementation of deep learning algorithms.

Image Segmentation Medical Image Segmentation +2

Prediction with Action: Visual Policy Learning via Joint Denoising Process

no code implementations27 Nov 2024 Yanjiang Guo, Yucheng Hu, Jianke Zhang, Yen-Jen Wang, Xiaoyu Chen, Chaochao Lu, Jianyu Chen

On the other line, diffusion models have also shown promise in robotic control tasks by denoising actions, known as diffusion policy.

Denoising Image Generation +2

HiRT: Enhancing Robotic Control with Hierarchical Robot Transformers

no code implementations12 Sep 2024 Jianke Zhang, Yanjiang Guo, Xiaoyu Chen, Yen-Jen Wang, Yucheng Hu, Chengming Shi, Jianyu Chen

Large Vision-Language-Action (VLA) models, leveraging powerful pre trained Vision-Language Models (VLMs) backends, have shown promise in robotic control due to their impressive generalization ability.

Advancing Humanoid Locomotion: Mastering Challenging Terrains with Denoising World Model Learning

1 code implementation26 Aug 2024 Xinyang Gu, Yen-Jen Wang, Xiang Zhu, Chengming Shi, Yanjiang Guo, Yichen Liu, Jianyu Chen

In this work, we introduce Denoising World Model Learning (DWL), an end-to-end reinforcement learning framework for humanoid locomotion control, which demonstrates the world's first humanoid robot to master real-world challenging terrains such as snowy and inclined land in the wild, up and down stairs, and extremely uneven terrains.

Denoising reinforcement-learning +1

RaffeSDG: Random Frequency Filtering enabled Single-source Domain Generalization for Medical Image Segmentation

1 code implementation2 May 2024 Heng Li, Haojin Li, Jianyu Chen, Zhongxi Qiu, Huazhu Fu, Lidai Wang, Yan Hu, Jiang Liu

To tackle domain shifts in data-scarce medical scenarios, we propose a Random frequency filtering enabled Single-source Domain Generalization algorithm (RaffeSDG), which promises robust out-of-domain inference with segmentation models trained on a single-source domain.

Data Augmentation Image Segmentation +4

Humanoid-Gym: Reinforcement Learning for Humanoid Robot with Zero-Shot Sim2Real Transfer

1 code implementation8 Apr 2024 Xinyang Gu, Yen-Jen Wang, Jianyu Chen

Humanoid-Gym is an easy-to-use reinforcement learning (RL) framework based on Nvidia Isaac Gym, designed to train locomotion skills for humanoid robots, emphasizing zero-shot transfer from simulation to the real-world environment.

MuJoCo Physical Simulations +1

Efficient and Generalized end-to-end Autonomous Driving System with Latent Deep Reinforcement Learning and Demonstrations

no code implementations22 Jan 2024 Zuojin Tang, Xiaoyu Chen, Yongqiang Li, Jianyu Chen

To address these challenges, this paper introduces an Efficient and Generalized end-to-end Autonomous Driving System (EGADS) for complex and varied scenarios.

Autonomous Driving Deep Reinforcement Learning +3

Prompt a Robot to Walk with Large Language Models

1 code implementation18 Sep 2023 Yen-Jen Wang, Bike Zhang, Jianyu Chen, Koushil Sreenath

Large language models (LLMs) pre-trained on vast internet-scale data have showcased remarkable capabilities across diverse domains.

From Artificially Real to Real: Leveraging Pseudo Data from Large Language Models for Low-Resource Molecule Discovery

1 code implementation11 Sep 2023 Yuhan Chen, Nuwa Xi, Yanrui Du, Haochun Wang, Jianyu Chen, Sendong Zhao, Bing Qin

Furthermore, our method shows a sustained improvement as the volume of pseudo data increases, revealing the great potential of pseudo data in advancing low-resource cross-modal molecule discovery.

Descriptive Domain Adaptation +2

DoReMi: Grounding Language Model by Detecting and Recovering from Plan-Execution Misalignment

no code implementations1 Jul 2023 Yanjiang Guo, Yen-Jen Wang, Lihan Zha, Jianyu Chen

Large language models (LLMs) encode a vast amount of semantic knowledge and possess remarkable understanding and reasoning capabilities.

Language Modeling Language Modelling +2

Decentralized Motor Skill Learning for Complex Robotic Systems

no code implementations30 Jun 2023 Yanjiang Guo, Zheyuan Jiang, Yen-Jen Wang, Jingyue Gao, Jianyu Chen

Experiments on quadruped and humanoid robots demonstrate that the learned policy is robust against local motor malfunctions and can be transferred to new tasks.

Reinforcement Learning (RL)

Asking Before Acting: Gather Information in Embodied Decision Making with Language Models

no code implementations25 May 2023 Xiaoyu Chen, Shenao Zhang, Pushi Zhang, Li Zhao, Jianyu Chen

With strong capabilities of reasoning and a broad understanding of the world, Large Language Models (LLMs) have demonstrated immense potential in building versatile embodied decision-making agents capable of executing a wide array of tasks.

Imitation Learning

Towards Generalizable Reinforcement Learning for Trade Execution

no code implementations12 May 2023 Chuheng Zhang, Yitong Duan, Xiaoyu Chen, Jianyu Chen, Jian Li, Li Zhao

To evaluate our algorithms, we also implement a carefully designed simulator based on historical limit order book (LOB) data to provide a high-fidelity benchmark for different algorithms.

Offline RL reinforcement-learning +2

Learning Robust, Agile, Natural Legged Locomotion Skills in the Wild

no code implementations21 Apr 2023 Yikai Wang, Zheyuan Jiang, Jianyu Chen

In this paper, we propose a new framework for learning robust, agile and natural legged locomotion skills over challenging terrain.

reinforcement-learning Reinforcement Learning

An Adaptive Deep RL Method for Non-Stationary Environments with Piecewise Stable Context

no code implementations24 Dec 2022 Xiaoyu Chen, Xiangming Zhu, Yufeng Zheng, Pushi Zhang, Li Zhao, Wenxue Cheng, Peng Cheng, Yongqiang Xiong, Tao Qin, Jianyu Chen, Tie-Yan Liu

One of the key challenges in deploying RL to real-world applications is to adapt to variations of unknown environment contexts, such as changing terrains in robotic tasks and fluctuated bandwidth in congestion control.

Decomposed Mutual Information Optimization for Generalized Context in Meta-Reinforcement Learning

1 code implementation9 Oct 2022 Yao Mu, Yuzheng Zhuang, Fei Ni, Bin Wang, Jianyu Chen, Jianye Hao, Ping Luo

This paper addresses such a challenge by Decomposed Mutual INformation Optimization (DOMINO) for context learning, which explicitly learns a disentangled context to maximize the mutual information between the context and historical trajectories, while minimizing the state transition prediction error.

Decision Making Meta Reinforcement Learning +3

Performance-Driven Controller Tuning via Derivative-Free Reinforcement Learning

no code implementations11 Sep 2022 YuHeng Lei, Jianyu Chen, Shengbo Eben Li, Sifa Zheng

Choosing an appropriate parameter set for the designed controller is critical for the final performance but usually requires a tedious and careful tuning process, which implies a strong need for automatic tuning methods.

Autonomous Driving reinforcement-learning +2

A Contact-Safe Reinforcement Learning Framework for Contact-Rich Robot Manipulation

no code implementations27 Jul 2022 Xiang Zhu, Shucheng Kang, Jianyu Chen

In this paper, we propose a contact-safe reinforcement learning framework for contact-rich robot manipulation, which maintains safety in both the task space and joint space.

reinforcement-learning Reinforcement Learning +3

CtrlFormer: Learning Transferable State Representation for Visual Control via Transformer

1 code implementation17 Jun 2022 Yao Mu, Shoufa Chen, Mingyu Ding, Jianyu Chen, Runjian Chen, Ping Luo

In visual control, learning transferable state representation that can transfer between different control tasks is important to reduce the training sample size.

Transfer Learning

Flow-based Recurrent Belief State Learning for POMDPs

no code implementations23 May 2022 Xiaoyu Chen, Yao Mu, Ping Luo, Shengbo Li, Jianyu Chen

Furthermore, we show that the learned belief states can be plugged into downstream RL algorithms to improve performance.

Decision Making Sequential Decision Making +1

Reachability Constrained Reinforcement Learning

2 code implementations16 May 2022 Dongjie Yu, Haitong Ma, Shengbo Eben Li, Jianyu Chen

Recent studies incorporate feasible sets into CRL with energy-based methods such as control barrier function (CBF), safety index (SI), and leverage prior conservative estimations of feasible sets, which harms the performance of the learned policy.

reinforcement-learning Reinforcement Learning +2

Scale-Equivalent Distillation for Semi-Supervised Object Detection

no code implementations CVPR 2022 Qiushan Guo, Yao Mu, Jianyu Chen, Tianqi Wang, Yizhou Yu, Ping Luo

Further, we overcome these challenges by introducing a novel approach, Scale-Equivalent Distillation (SED), which is a simple yet effective end-to-end knowledge distillation framework robust to large object size variance and class imbalance.

Knowledge Distillation Object +3

Learn Zero-Constraint-Violation Policy in Model-Free Constrained Reinforcement Learning

1 code implementation25 Nov 2021 Haitong Ma, Changliu Liu, Shengbo Eben Li, Sifa Zheng, Wenchao Sun, Jianyu Chen

Existing methods mostly use the posterior penalty for dangerous actions, which means that the agent is not penalized until experiencing danger.

reinforcement-learning Reinforcement Learning (RL)

Joint Synthesis of Safety Certificate and Safe Control Policy using Constrained Reinforcement Learning

1 code implementation15 Nov 2021 Haitong Ma, Changliu Liu, Shengbo Eben Li, Sifa Zheng, Jianyu Chen

This paper proposes a novel approach that simultaneously synthesizes the energy-function-based safety certificate and learns the safe control policy with CRL.

reinforcement-learning Reinforcement Learning (RL) +1

Feasible Actor-Critic: Constrained Reinforcement Learning for Ensuring Statewise Safety

3 code implementations22 May 2021 Haitong Ma, Yang Guan, Shegnbo Eben Li, Xiangteng Zhang, Sifa Zheng, Jianyu Chen

The safety constraints commonly used by existing safe reinforcement learning (RL) methods are defined only on expectation of initial states, but allow each certain state to be unsafe, which is unsatisfying for real-world safety-critical tasks.

reinforcement-learning Reinforcement Learning +3

Model-based Constrained Reinforcement Learning using Generalized Control Barrier Function

1 code implementation2 Mar 2021 Haitong Ma, Jianyu Chen, Shengbo Eben Li, Ziyu Lin, Yang Guan, Yangang Ren, Sifa Zheng

Model information can be used to predict future trajectories, so it has huge potential to avoid dangerous region when implementing reinforcement learning (RL) on real-world tasks, like autonomous driving.

Autonomous Driving Collision Avoidance +4

Mixed Policy Gradient: off-policy reinforcement learning driven jointly by data and model

2 code implementations23 Feb 2021 Yang Guan, Jingliang Duan, Shengbo Eben Li, Jie Li, Jianyu Chen, Bo Cheng

Formally, MPG is constructed as a weighted average of the data-driven and model-driven PGs, where the former is the derivative of the learned Q-value function, and the latter is that of the model-predictive return.

Decision Making Reinforcement Learning (RL) +1

Separated Proportional-Integral Lagrangian for Chance Constrained Reinforcement Learning

no code implementations17 Feb 2021 Baiyu Peng, Yao Mu, Jingliang Duan, Yang Guan, Shengbo Eben Li, Jianyu Chen

Taking a control perspective, we first interpret the penalty method and the Lagrangian method as proportional feedback and integral feedback control, respectively.

Autonomous Driving reinforcement-learning +2

Steadily Learn to Drive with Virtual Memory

no code implementations16 Feb 2021 Yuhang Zhang, Yao Mu, Yujie Yang, Yang Guan, Shengbo Eben Li, Qi Sun, Jianyu Chen

Reinforcement learning has shown great potential in developing high-level autonomous driving.

Autonomous Driving

A Safe Hierarchical Planning Framework for Complex Driving Scenarios based on Reinforcement Learning

no code implementations17 Jan 2021 Jinning Li, Liting Sun, Jianyu Chen, Masayoshi Tomizuka, Wei Zhan

To address this challenge, we propose a hierarchical behavior planning framework with a set of low-level safe controllers and a high-level reinforcement learning algorithm (H-CtRL) as a coordinator for the low-level controllers.

Autonomous Vehicles reinforcement-learning +2

Efficient Deep Learning of Non-local Features for Hyperspectral Image Classification

1 code implementation2 Aug 2020 Yu Shen, Sijie Zhu, Chen Chen, Qian Du, Liang Xiao, Jianyu Chen, Delu Pan

Therefore, to incorporate the long-range contextual information, a deep fully convolutional network (FCN) with an efficient non-local module, named ENL-FCN, is proposed for HSI classification.

Deep Learning General Classification +1

The Design and Implementation of a Real Time Visual Search System on JD E-commerce Platform

1 code implementation19 Aug 2019 Jie Li, Haifeng Liu, Chuanghua Gui, Jianyu Chen, Zhenyun Ni, Ning Wang

We present the design and implementation of a visual search system for real time image retrieval on JD. com, the world's third largest and China's largest e-commerce site.

Image Retrieval Retrieval

Intention-aware Long Horizon Trajectory Prediction of Surrounding Vehicles using Dual LSTM Networks

no code implementations6 Jun 2019 Long Xin, Pin Wang, Ching-Yao Chan, Jianyu Chen, Shengbo Eben Li, Bo Cheng

As autonomous vehicles (AVs) need to interact with other road users, it is of importance to comprehensively understand the dynamic traffic environment, especially the future possible trajectories of surrounding vehicles.

Autonomous Vehicles feature selection +3

Model-free Deep Reinforcement Learning for Urban Autonomous Driving

2 code implementations20 Apr 2019 Jianyu Chen, Bodi Yuan, Masayoshi Tomizuka

Urban autonomous driving decision making is challenging due to complex road geometry and multi-agent interactions.

Autonomous Driving Decision Making +3

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