most citedUni-RLHF: Universal Platform and Benchmark Suite for Reinforcement Learning with Diverse Human Feedback

3 citations · 6 across the 3 of their papers we have counts for

collaborators

6 papers

cs.RO2025

Embodied Arena: A Comprehensive, Unified, and Evolving Evaluation Platform for Embodied AI

Fei Ni, Min Zhang, Pengyi Li +34

Embodied AI development significantly lags behind large foundation models due to three critical challenges: (1) lack of systematic understanding of core capabilities needed for Emb…

cs.RO2025

EmbodiedMAE: A Unified 3D Multi-Modal Representation for Robot Manipulation

Zibin Dong, Fei Ni, Yifu Yuan +2

We present EmbodiedMAE, a unified 3D multi-modal representation for robot manipulation. Current approaches suffer from significant domain gaps between training datasets and robot m…

cs.CL2025

From Chaos to Order: The Atomic Reasoner Framework for Fine-grained Reasoning in Large Language Models

Jinyi Liu, Yan Zheng, Rong Cheng +8

Recent advances in large language models (LLMs) have shown remarkable progress, yet their capacity for logical ``slow-thinking'' reasoning persists as a critical research frontier.…

cs.LG20243 cited

Uni-RLHF: Universal Platform and Benchmark Suite for Reinforcement Learning with Diverse Human Feedback

Yifu Yuan, Jianye Hao, Yi Ma +6

Reinforcement Learning with Human Feedback (RLHF) has received significant attention for performing tasks without the need for costly manual reward design by aligning human prefere…

cs.RO20241 cited

Enhancing Robotic Manipulation with AI Feedback from Multimodal Large Language Models

Jinyi Liu, Yifu Yuan, Jianye Hao +4

Recently, there has been considerable attention towards leveraging large language models (LLMs) to enhance decision-making processes. However, aligning the natural language text in…

cs.LG20232 cited

MetaDiffuser: Diffusion Model as Conditional Planner for Offline Meta-RL

Fei Ni, Jianye Hao, Yao Mu +4

Recently, diffusion model shines as a promising backbone for the sequence modeling paradigm in offline reinforcement learning(RL). However, these works mostly lack the generalizati…