most citedTowards Practical Multi-Object Manipulation using Relational Reinforcement Learning

21 citations · 21 across the 4 of their papers we have counts for

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cs.LG2026

Prompt-Driven Exploration

Sunshine Jiang, John Marangola, David Zhang +6

Exploration is essential to RL since a policy cannot improve by repeatedly sampling the behaviors it already prefers. Standard methods inject stochasticity in the action space, but…

cs.LG2026

Learning More from Less: Reinforcement Learning from Hindsight

Iris Xu, Sunshine Jiang, John Marangola +8

Reinforcement learning (RL) is increasingly used to post-train vision-language-action (VLA) models, but every update consumes robot rollouts that are slow and costly to collect, ma…