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cs.GT2025

Policy-Conditioned Policies for Multi-Agent Task Solving

Yue Lin, Shuhui Zhu, Wenhao Li +5

In multi-agent tasks, the central challenge lies in the dynamic adaptation of strategies. However, directly conditioning on opponents' strategies is intractable in the prevalent de…

cs.CV2025

Image-POSER: Reflective RL for Multi-Expert Image Generation and Editing

Hossein Mohebbi, Mohammed Abdulrahman, Yanting Miao +2

Recent advances in text-to-image generation have produced strong single-shot models, yet no individual system reliably executes the long, compositional prompts typical of creative…

cs.GT2025

Information Bargaining: Bilateral Commitment in Bayesian Persuasion

Yue Lin, Shuhui Zhu, William A Cunningham +4

Bayesian persuasion, an extension of cheap-talk communication, involves an informed sender committing to a signaling scheme to influence a receiver's actions. Compared to cheap tal…

cs.LG2025

Measures of Variability for Risk-averse Policy Gradient

Yudong Luo, Yangchen Pan, Jiaqi Tan +1

Risk-averse reinforcement learning (RARL) is critical for decision-making under uncertainty, which is especially valuable in high-stake applications. However, most existing works f…

math.AC2025

Cohen--Macaulay ideals of codimension two and the geometry of plane points

Dayane Lira, Geisa Oliveira, Zaqueu Ramos +1

We consider classes of codimension two Cohen--Macaulay ideals over a standard graded polynomial ring over a field. We revisit Vasconcelos' problem on matrices with homo…

cs.LG2025

A Comprehensive Survey on Inverse Constrained Reinforcement Learning: Definitions, Progress and Challenges

Guiliang Liu, Sheng Xu, Shicheng Liu +3

Inverse Constrained Reinforcement Learning (ICRL) is the task of inferring the implicit constraints that expert agents adhere to, based on their demonstration data. As an emerging…