most citedData Scaling Laws in Imitation Learning for Robotic Manipulation

2 citations · 2 across the 2 of their papers we have counts for

collaborators

7 papers

cs.RO2026

Critical Interval MSE: Toward Reliable Offline Validation for Robot Manipulation Policies

Haoxu Huang, Tongsam Zheng, Yifan Chen +2

Real-world evaluation is the gold standard for robot policies because it tests them against the physical conditions and deployment challenges they are ultimately designed to handle…

cs.RO20262 cited

Data Scaling Laws in Imitation Learning for Robotic Manipulation

Fanqi Lin, Yingdong Hu, Pingyue Sheng +3

Data scaling has revolutionized fields like natural language processing and computer vision, providing models with remarkable generalization capabilities. In this paper, we investi…

cs.RO2026

OneTwoVLA: A Unified Vision-Language-Action Model with Adaptive Reasoning

Fanqi Lin, Ruiqian Nai, Yingdong Hu +3

General-purpose robots capable of performing diverse tasks require synergistic reasoning and acting capabilities. However, recent dual-system approaches, which separate high-level…

cs.CL2025

Kimi Linear: An Expressive, Efficient Attention Architecture

Kimi Team, Yu Zhang, Zongyu Lin +57

We introduce Kimi Linear, a hybrid linear attention architecture that, for the first time, outperforms full attention under fair comparisons across various scenarios -- including s…

cs.LG2025

LoRI: Reducing Cross-Task Interference in Multi-Task Low-Rank Adaptation

Juzheng Zhang, Jiacheng You, Ashwinee Panda +1

Low-Rank Adaptation (LoRA) has emerged as a popular parameter-efficient fine-tuning (PEFT) method for Large Language Models (LLMs), yet it still incurs notable overhead and suffers…

cs.RO2025

SKIL: Semantic Keypoint Imitation Learning for Generalizable Data-efficient Manipulation

Shengjie Wang, Jiacheng You, Yihang Hu +2

Real-world tasks such as garment manipulation and table rearrangement demand robots to perform generalizable, highly precise, and long-horizon actions. Although imitation learning…