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20202026
most citedA Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need?

109 citations · 288 across the 16 of their papers we have counts for

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6 papers · 1 filter

cs.AI2026

Experience Transfer for Multimodal LLM Agents in Minecraft Game

Chenghao Li, Jun Liu, Songbo Zhang +7

Multimodal LLM agents operating in complex game environments must continually reuse past experience to solve new tasks efficiently. In this work, we propose Echo, a transfer-orient…

cs.AI2026

Efficient and Interpretable Multi-Agent LLM Routing via Ant Colony Optimization

Xudong Wang, Chaoning Zhang, Jiaquan Zhang +8

Large Language Model (LLM)-driven Multi-Agent Systems (MAS) have demonstrated strong capability in complex reasoning and tool use, and heterogeneous agent pools further broaden the…

cs.AI2025

Continual Knowledge Adaptation for Reinforcement Learning

Jinwu Hu, Zihao Lian, Zhiquan Wen +5

Reinforcement Learning enables agents to learn optimal behaviors through interactions with environments. However, real-world environments are typically non-stationary, requiring ag…

cs.AI2023★ 109 cited

A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need?

Chaoning Zhang, Chenshuang Zhang, Sheng Zheng +14

As ChatGPT goes viral, generative AI (AIGC, a.k.a AI-generated content) has made headlines everywhere because of its ability to analyze and create text, images, and beyond. With su…

cs.AI2021★ 18 cited

Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning

Yiqin Yang, Xiaoteng Ma, Chenghao Li +5

Learning from datasets without interaction with environments (Offline Learning) is an essential step to apply Reinforcement Learning (RL) algorithms in real-world scenarios. Howeve…

cs.AI2020★ 7 cited

SOAC: The Soft Option Actor-Critic Architecture

Chenghao Li, Xiaoteng Ma, Chongjie Zhang +3

The option framework has shown great promise by automatically extracting temporally-extended sub-tasks from a long-horizon task. Methods have been proposed for concurrently learnin…