HERO: Human-Feedback Efficient Reinforcement Learning for Online Diffusion Model Finetuning

no code implementations • 7 Oct 2024 • Ayano Hiranaka, Shang-Fu Chen, Chieh-Hsin Lai, Dongjun Kim, Naoki Murata, Takashi Shibuya, Wei-Hsiang Liao, Shao-Hua Sun, Yuki Mitsufuji

Controllable generation through Stable Diffusion (SD) fine-tuning aims to improve fidelity, safety, and alignment with human guidance.

Image Generation reinforcement-learning +2

BEHAVIOR-1K: A Human-Centered, Embodied AI Benchmark with 1,000 Everyday Activities and Realistic Simulation

no code implementations • 14 Mar 2024 • Chengshu Li, Ruohan Zhang, Josiah Wong, Cem Gokmen, Sanjana Srivastava, Roberto Martín-Martín, Chen Wang, Gabrael Levine, Wensi Ai, Benjamin Martinez, Hang Yin, Michael Lingelbach, Minjune Hwang, Ayano Hiranaka, Sujay Garlanka, Arman Aydin, Sharon Lee, Jiankai Sun, Mona Anvari, Manasi Sharma, Dhruva Bansal, Samuel Hunter, Kyu-Young Kim, Alan Lou, Caleb R Matthews, Ivan Villa-Renteria, Jerry Huayang Tang, Claire Tang, Fei Xia, Yunzhu Li, Silvio Savarese, Hyowon Gweon, C. Karen Liu, Jiajun Wu, Li Fei-Fei

We present BEHAVIOR-1K, a comprehensive simulation benchmark for human-centered robotics.

Diversity

NOIR: Neural Signal Operated Intelligent Robots for Everyday Activities

no code implementations • 2 Nov 2023 • Ruohan Zhang, Sharon Lee, Minjune Hwang, Ayano Hiranaka, Chen Wang, Wensi Ai, Jin Jie Ryan Tan, Shreya Gupta, Yilun Hao, Gabrael Levine, Ruohan Gao, Anthony Norcia, Li Fei-Fei, Jiajun Wu

We present Neural Signal Operated Intelligent Robots (NOIR), a general-purpose, intelligent brain-robot interface system that enables humans to command robots to perform everyday activities through brain signals.

EEG

Primitive Skill-based Robot Learning from Human Evaluative Feedback

no code implementations • 28 Jul 2023 • Ayano Hiranaka, Minjune Hwang, Sharon Lee, Chen Wang, Li Fei-Fei, Jiajun Wu, Ruohan Zhang

By combining them, SEED reduces the human effort required in RLHF and increases safety in training robot manipulation with RL in real-world settings.

reinforcement-learning Reinforcement Learning +2