most citedReaching Consensus in Cooperative Multi-Agent Reinforcement Learning with Goal Imagination

1 citations · 2 across the 6 of their papers we have counts for

collaborators

7 papers

cs.SD2025

DiTSinger: Scaling Singing Voice Synthesis with Diffusion Transformer and Implicit Alignment

Zongcai Du, Guilin Deng, Xiaofeng Guo +8

Recent progress in diffusion-based Singing Voice Synthesis (SVS) demonstrates strong expressiveness but remains limited by data scarcity and model scalability. We introduce a two-s…

cs.CV2025

Yan: Foundational Interactive Video Generation

Deheng Ye, Fangyun Zhou, Jiacheng Lv +15

We present Yan, a foundational framework for interactive video generation, covering the entire pipeline from simulation and generation to editing. Specifically, Yan comprises three…

cs.CV2025

PRJ: Perception-Retrieval-Judgement for Generated Images

Qiang Fu, Zonglei Jing, Zonghao Ying +1

The rapid progress of generative AI has enabled remarkable creative capabilities, yet it also raises urgent concerns regarding the safety of AI-generated visual content in real-wor…

cs.AI2024

Playable Game Generation

Mingyu Yang, Junyou Li, Zhongbin Fang +5

In recent years, Artificial Intelligence Generated Content (AIGC) has advanced from text-to-image generation to text-to-video and multimodal video synthesis. However, generating pl…

cs.AI2024★ 1 cited

Hokoff: Real Game Dataset from Honor of Kings and its Offline Reinforcement Learning Benchmarks

Yun Qu, Boyuan Wang, Jianzhun Shao +15

The advancement of Offline Reinforcement Learning (RL) and Offline Multi-Agent Reinforcement Learning (MARL) critically depends on the availability of high-quality, pre-collected o…

cs.AI2024★ 1 cited

Reaching Consensus in Cooperative Multi-Agent Reinforcement Learning with Goal Imagination

Liangzhou Wang, Kaiwen Zhu, Fengming Zhu +6

Reaching consensus is key to multi-agent coordination. To accomplish a cooperative task, agents need to coherently select optimal joint actions to maximize the team reward. However…

cs.HC2024

Enhancing Human Experience in Human-Agent Collaboration: A Human-Centered Modeling Approach Based on Positive Human Gain

Yiming Gao, Feiyu Liu, Liang Wang +12

Existing game AI research mainly focuses on enhancing agents' abilities to win games, but this does not inherently make humans have a better experience when collaborating with thes…