31 citations · 113 across the 23 of their papers we have counts for
4 papers · 1 filter
IGOR: Image-GOal Representations are the Atomic Control Units for Foundation Models in Embodied AI
Xiaoyu Chen, Junliang Guo, Tianyu He +5
We introduce Image-GOal Representations (IGOR), aiming to learn a unified, semantically consistent action space across human and various robots. Through this unified latent action…
Policy Filtration for RLHF to Mitigate Noise in Reward Models
Chuheng Zhang, Wei Shen, Li Zhao +4
While direct policy optimization methods exist, pioneering LLMs are fine-tuned with reinforcement learning from human feedback (RLHF) to generate better responses under the supervi…
Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL
Yunseon Choi, Sangmin Bae, Seonghyun Ban +6
With the advent of foundation models, prompt tuning has positioned itself as an important technique for directing model behaviors and eliciting desired responses. Prompt tuning reg…
Empowering Large Language Models on Robotic Manipulation with Affordance Prompting
Guangran Cheng, Chuheng Zhang, Wenzhe Cai +3
While large language models (LLMs) are successful in completing various language processing tasks, they easily fail to interact with the physical world by generating control sequen…