Dong Carlo An @andongverse

Research Scientist at Institute of Foundation Models, MBZUAI marsaki.github.io Beijing Joined September 2021

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🎉Excited to share that 𝗣𝗮𝗻𝗼𝗚𝗲𝗻 has been accepted to #NeurIPS2023! We create diverse panorama environments for VLN via recursive image outpainting, improving SotA agents on R2R, R4R, CVDN unseen envs. Looking fwd to meeting you all in New Orleans! cc @mohitban47 @uncnlp

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Jialu Li @JialuLi96

3 years ago

Jialu Li @JialuLi96

3 years ago

🚨Excited to share: “𝗣𝗮𝗻𝗼𝗚𝗲𝗻: Text-Conditioned Panoramic Environment Generation for Vision-and-Language Navigation”!🚨 PanoGen creates diverse 360-degree panorama via recursive outpainting, achieving SotA on R2R, R4R, CVDN. pano-gen.github.io @mohitban47 @uncnlp 🧵

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Zun Wang @ZunWang919

3 years ago

Excited to share our new #ICCV2023 paper: “Scaling Data Generation in Vision-and-Language Navigation”! We reduce the long-lasting generalization gap between navigating in seen & unseen scenes to < 1%, & approaching human performance for 1st time! 🥳 arxiv.org/abs/2307.15644 🧵

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Devendra Chaplot @dchaplot

4 years ago

Robot visual navigation in unseen homes is hard: end-to-end RL works well in sim but gets only 23% real-world success. Today, in the first real-world empirical study of visual navigation, we show Modular Learning achieves 90% success in unseen homes! theophilegervet.github.io/projects/real-… 1/N

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Tengyu Ma @tengyuma

4 years ago

When and how can models extrapolate to unseen domains? Previous understanding is mostly limited to linear models or well-covered new domains. We make some first baby steps beyond these by considering *structured* domain shift and nonlinear models. arxiv.org/abs/2211.11719 1/n

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Ted Xiao @xiao_ted

4 years ago

Our project SayCan (say-can.github.io) wins Best Paper Award at the RSS Workshop on Scaling Robot Learning! Thanks to all who came to the poster session with great questions and feedback 😁 The future of "LLMs for Robotics and Robotics for LLMs" is brighter than ever!

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Jacob Krantz @jacob__krantz

4 years ago

Language-guided navigators shouldn’t be carted off to a new environment with each new instruction. Instead, they should persist & improve over time. We present Iterative Vision-and-Language Navigation to evaluate exactly this! arxiv.org/abs/2210.03087 jacobkrantz.github.io/ivln

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Fei-Fei Li @drfeifei

4 years ago

Do you want to learn to train and evaluate embodied AI solutions for 1000 household tasks in a realistic simulator? Join our BEHAVIOR Tutorial at #ECCV2022: Benchmarking Embodied AI Solutions in Natural Tasks! Time: Monday, Oct 24th 14:00 local time (4:00 Pacific Time)

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AK @_akhaliq

4 years ago

Imagic: Text-Based Real Image Editing with Diffusion Models abs: arxiv.org/abs/2210.09276

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Carlos E. Perez @IntuitMachine

4 years ago

This is interesting, but do people run simulations when they reason? arxiv.org/abs/2210.05359

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AK @_akhaliq

4 years ago

Interactive Language: Talking to Robots in Real Time abs: arxiv.org/abs/2210.06407 project page: interactive-language.github.io

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Devendra Chaplot @dchaplot

4 years ago

We are announcing Habitat-Matterport 3D Semantics Dataset! 216 real-world 3D spaces with dense semantic annotations available to download now: aihabitat.org/datasets/hm3d-…

AI at Meta @AIatMeta

4 years ago

(1/3) Today we’re releasing the Habitat-Matterport 3D Semantics dataset, the largest public dataset of real-world 3D spaces with dense semantic annotations. HM3D-Sem is free and available to use with FAIR's Habitat simulator: bit.ly/3EymX8x