16 citations · 38 across the 13 of their papers we have counts for
14 papers
Generalized Agent Iteration: One Formal Framework for Iterative Policy Improvement and Recursive Self-Improvement
Hongyao Tang, Yi Ma, Pengyi Li +1
When we speak of recursive self-improvement (RSI), are we speaking of a phenomenon, a mechanism, or a prospect? Towards autonomous and evolving intelligence, RSI is being claimed a…
NoC-Out: A Formally-verified Network-on-Chip Library for Rule-based Hardware Designs
Max Kurze, František Farka, Sebastian Ertel
The Network-on-Chip (NoC) is the communication backbone of any multiprocessor chip. A failure of the NoC has severe consequences for the whole system. Yet, no approach exists that…
ForceFlow: Learning to Feel and Act via Contact-Driven Flow Matching
Shuoheng Zhang, Yifu Yuan, Hongyao Tang +7
Existing imitation learning methods enable robots to interact autonomously with the physical environment. However, contact-rich manipulation tasks remain a significant challenge du…
Opinion dynamics and mutual influence with LLM agents through dialog simulation
Yulong He, Dutao Zhang, Sergey Kovalchuk +2
A fundamental challenge in opinion dynamics research is the scarcity of real-world longitudinal opinion data, which complicates the validation of theoretical models. To address thi…
Embodied Arena: A Comprehensive, Unified, and Evolving Evaluation Platform for Embodied AI
Fei Ni, Min Zhang, Pengyi Li +34
Embodied AI development significantly lags behind large foundation models due to three critical challenges: (1) lack of systematic understanding of core capabilities needed for Emb…
Embodied-R1: Reinforced Embodied Reasoning for General Robotic Manipulation
Yifu Yuan, Haiqin Cui, Yaoting Huang +7
Generalization in embodied AI is hindered by the "seeing-to-doing gap," which stems from data scarcity and embodiment heterogeneity. To address this, we pioneer "pointing" as a uni…
From Seeing to Doing: Bridging Reasoning and Decision for Robotic Manipulation
Yifu Yuan, Haiqin Cui, Yibin Chen +7
Achieving generalization in robotic manipulation remains a critical challenge, particularly for unseen scenarios and novel tasks. Current Vision-Language-Action (VLA) models, while…
DKDL-Net: A Lightweight Bearing Fault Detection Model via Decoupled Knowledge Distillation and Low-Rank Adaptation Fine-tuning
Ovanes Petrosian, Li Pengyi, He Yulong +4
Rolling bearing fault detection has developed rapidly in the field of fault diagnosis technology, and it occupies a very important position in this field. Deep learning-based beari…
CleanDiffuser: An Easy-to-use Modularized Library for Diffusion Models in Decision Making
Zibin Dong, Yifu Yuan, Jianye Hao +4
Leveraging the powerful generative capability of diffusion models (DMs) to build decision-making agents has achieved extensive success. However, there is still a demand for an easy…
DiffuserLite: Towards Real-time Diffusion Planning
Zibin Dong, Jianye Hao, Yifu Yuan +4
Diffusion planning has been recognized as an effective decision-making paradigm in various domains. The capability of generating high-quality long-horizon trajectories makes it a p…
Bridging Evolutionary Algorithms and Reinforcement Learning: A Comprehensive Survey on Hybrid Algorithms
Pengyi Li, Jianye Hao, Hongyao Tang +3
Evolutionary Reinforcement Learning (ERL), which integrates Evolutionary Algorithms (EAs) and Reinforcement Learning (RL) for optimization, has demonstrated remarkable performance…
ERL-Re: Efficient Evolutionary Reinforcement Learning with Shared State Representation and Individual Policy Representation
Jianye Hao, Pengyi Li, Hongyao Tang +3
Deep Reinforcement Learning (Deep RL) and Evolutionary Algorithms (EA) are two major paradigms of policy optimization with distinct learning principles, i.e., gradient-based v.s. g…
PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration
Pengyi Li, Hongyao Tang, Tianpei Yang +8
Learning to collaborate is critical in Multi-Agent Reinforcement Learning (MARL). Previous works promote collaboration by maximizing the correlation of agents' behaviors, which is…
HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representation
Boyan Li, Hongyao Tang, Yan Zheng +5
Discrete-continuous hybrid action space is a natural setting in many practical problems, such as robot control and game AI. However, most previous Reinforcement Learning (RL) works…