activity
20192026
most citedToward Ergonomic Risk Prediction via Segmentation of Indoor Object Manipulation Actions Using Spatiotemporal Convolutional Networks

32 citations · 42 across the 15 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.RO2024

The One RING: a Robotic Indoor Navigation Generalist

Ainaz Eftekhar, Rose Hendrix, Luca Weihs +11

Modern robots vary significantly in shape, size, and sensor configurations used to perceive and interact with their environments. However, most navigation policies are embodiment-s…

cs.CV2024

SAT: Dynamic Spatial Aptitude Training for Multimodal Language Models

Arijit Ray, Jiafei Duan, Ellis Brown +9

Reasoning about motion and space is a fundamental cognitive capability that is required by multiple real-world applications. While many studies highlight that large multimodal lang…

cs.RO2024

FLaRe: Achieving Masterful and Adaptive Robot Policies with Large-Scale Reinforcement Learning Fine-Tuning

Jiaheng Hu, Rose Hendrix, Ali Farhadi +5

In recent years, the Robotics field has initiated several efforts toward building generalist robot policies through large-scale multi-task Behavior Cloning. However, direct deploym…

cs.CV2024★ 8 cited

Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models

Matt Deitke, Christopher Clark, Sangho Lee +47

Today's most advanced vision-language models (VLMs) remain proprietary. The strongest open-weight models rely heavily on synthetic data from proprietary VLMs to achieve good perfor…

cs.RO2024

PoliFormer: Scaling On-Policy RL with Transformers Results in Masterful Navigators

Kuo-Hao Zeng, Zichen Zhang, Kiana Ehsani +6

We present PoliFormer (Policy Transformer), an RGB-only indoor navigation agent trained end-to-end with reinforcement learning at scale that generalizes to the real-world without a…