25 citations · 67 across the 9 of their papers we have counts for
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cs.LG2026
LACRM: LLM-Guided Mining of Directed Advertiser Competition Relationships in E-Commerce Advertising
Xiang Shi, Yitian Kou, Bing Li +6
In e-commerce advertising, ad platforms typically fail to model the externalities among advertisers when making optimization decisions: an advertiser's actual performance is largel…
cs.LG2021★ 11 cited
Offline Pre-trained Multi-Agent Decision Transformer: One Big Sequence Model Tackles All SMAC Tasks
Linghui Meng, Muning Wen, Yaodong Yang +7
Offline reinforcement learning leverages previously-collected offline datasets to learn optimal policies with no necessity to access the real environment. Such a paradigm is also d…
cs.LG2021★ 24 cited
Settling the Variance of Multi-Agent Policy Gradients
Jakub Grudzien Kuba, Muning Wen, Yaodong Yang +5
Policy gradient (PG) methods are popular reinforcement learning (RL) methods where a baseline is often applied to reduce the variance of gradient estimates. In multi-agent RL (MARL…