Liu, Anji

ProAgent: Building Proactive Cooperative Agents with Large Language Models

Zhang, C., Yang, K., Hu, S., Wang, Z., Li, G., Sun, Y., Zhang, C., Zhang, Z., Liu, A., Zhu, S.-C., et al. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence

Reinforcement Learning in RoboticsMulti-Agent Systems and Negotiation

Cited by 88

Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task Agents

Wang, Z., Cai, S., Chen, G., Liu, A., Ma, X., & Liang, Y. (2023) · arXiv

AI-based Problem Solving and PlanningReinforcement Learning in Robotics

Cited by 55

JARVIS -1: Open-World Multi-Task Agents With Memory-Augmented Multimodal Language Models

Wang, Z., Cai, S., Liu, A., Jin, Y., Hou, J., Zhang, B., Lin, H., He, Z., Zheng, Z., Yang, Y., et al. (2025) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 36

Open-World Multi-Task Control Through Goal-Aware Representation Learning and Adaptive Horizon Prediction

Cai, S., Wang, Z., Ma, X., Liu, A., & Liang, Y. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 12

JARVIS-1: Open-World Multi-task Agents with Memory-Augmented Multimodal Language Models

Wang, Z., Cai, S., Liu, A., Jin, Y., Hou, J., Zhang, B., Lin, H., He, Z., Zheng, Z., Yang, Y., et al. (2023) · arXiv

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 6