most citedIn-context Exploration-Exploitation for Reinforcement Learning

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

collaborators

2 papers

cs.IR2024

Prompt-to-Slate: Diffusion Models for Prompt-Conditioned Slate Generation

Federico Tomasi, Francesco Fabbri, Justin Carter +3

Slate generation is a common task in streaming and e-commerce platforms, where multiple items are presented together as a list or ``slate''. Traditional systems focus mostly on ite…

cs.LG2024★ 1 cited

In-context Exploration-Exploitation for Reinforcement Learning

Zhenwen Dai, Federico Tomasi, Sina Ghiassian

In-context learning is a promising approach for online policy learning of offline reinforcement learning (RL) methods, which can be achieved at inference time without gradient opti…