In Fall 2026, I will begin a tenure-track faculty position @JHUCompSci Announcing the SciPhy lab, where we will study the science of physical agents (robots) We are now recruiting our first cohort of PhD students. If this is you, see sci-fi-lab.github.io/

Attending @CVPRConf after a 2-year hiatus. For anyone looking to chat robotics / world models, or just to connect, drop me a message (DMs open)

Learn about the research our computer scientists will be presenting at @CVPR 2026 next week in Denver! ⛰️ (🧵 1/7) #CVPR2026

Start your #CVPR2026 with a coffee and some hard truths ☕ Tomorrow morning, we're talking 'Bitter Lessons' -- hard-won wisdom our field has accumulated but rarely discusses Come be part of a candid conversation👇 sites.google.com/view/Bitter… Wed, 8:45am, Four Seasons Ballroom 4

There have been a lot of fresh discussions lately around "bitter lessons". Continuing our tradition of community-building at CVPR, our workshop is back! This year's theme: Bitter Lessons in Computer Vision. Join us on Jun 3rd at 8:45 AM in Room 3A-3D at #CVPR2026 🔗 Website: sites.google.com/view/bitter… We have an incredible lineup to share their "bitter lessons": Bill Freeman, Alyosha Efros, @georgiagkioxari, @jon_barron, @vincesitzmann, @BharathHarihar3, @ShenlongWang, David Forsyth, @dimadamen @ev4n3sce, @CVPR

We are recruiting multiple Postdoctoral Fellows at the Johns Hopkins University Vision and Image Understanding (VIU) Lab. We are looking for candidates with strong expertise in multimodal AI, large language models (LLMs), diffusion/generative models, image & video synthesis, computer vision, and machine learning. Postdoctoral researchers will collaborate with a highly interdisciplinary team on cutting-edge problems spanning multimodal reasoning, generative AI, visual understanding, synthetic data generation, and foundation models for real-world applications. Interested candidates should send their CV, recent publications, and a brief description of their research interests to (vpatel36@jhu.edu). #AI #ComputerVision #MultimodalAI #LLM #DiffusionModels #GenerativeAI #Postdoc #JohnsHopkins

Extremely excited to share our recent work on diffusion world models. We ask a simple question - what space supports diffusion world modeling the most and how do we evaluate that?Turns out representation is the answer with JEPA space yielding the strongest diffusion world models!

Reproducing all of Schmidhuber’s papers (1990-2025) using an AI coding assistant. Cool project by @yaroslavvb! It even reproduced the “World Models” paper by me and @SchmidhuberAI with a toy env, with a full VAE RNN world model implementation. Project: github.com/cybertronai/schmi…

Launching my research group, MAGIC (Manipulation and General Intelligence Control) Lab @NUSComputing, Singapore! We focus on building the next generation of human-centric models for robotic manipulation — deployable safely, reliably, and easily in the real world. Our research spans MLLM reasoning, 3D vision, robot learning, simulation, dexterous manipulation, and cross-embodiment learning. Interested in joining? Sign up here and I'll send a reminder email: forms.gle/oJPLR2pLTt8kLCxZ7

VLAExplain — Interpreting Vision-Language-Action (VLA) Models VLAExplain is an interpretability toolkit designed to help users visually understand the inner workings of Vision-Language-Action (VLA) models. Currently, attention analysis is supported for both the pi05 and unifolm-vla models. For details, please check pi05 and UnifoLM-VLA readme files respectively. Demo of pi05 in action:

Releasing RecGen: a collaboration between @ToyotaResearch, @toyota_europe, and @UvA_Amsterdam tackling a core 3D vision challenge: reconstructing complete multi-object scenes (parts, poses, textures, even occluded geometry) from just 1 to a few RGB-D views. Trained purely on synthetic data, RecGen achieves SOTA on real-world robotics and 6D pose benchmarks, handling occlusions, symmetry, and complex interactions. A step toward scalable, high-fidelity digital twins for robotics, and better evaluation and training of generalist policies. reconstruction-by-generation…

RT @anand_bhattad: If you're at #ICLR2026, make sure to stop by and hear @VaibhavVavilala present our Generative Blocks World paper *now* i…

A few interesting rollouts from the Foundry-QwenVLA-2.5B multi-task model on seen tasks in sim –  a 🧵. I really like behaviors that involve non-prehensile manipulation, like the little nudges in StoreCerealBoxUnderShelf.

This is actually a pretty big deal — we rely on @imp_aa’s implementations to tell when policies are statistically different than each other. If someone presents some quick mean-only results internally without the CLD analysis, you can be sure someone will eventually ask for it.

VLA Foundry supports both from-scratch training and pretrained HF backbones. We trained two model types to show it off: • Fully from scratch via our LLM→VLM→VLA pipeline • Built on Qwen3-VL We share the weightshttps://huggingface.co/collections/TRI-ML/vla-foundry

Our white paper just came out on Arxiv arxiv.org/abs/2604.19728v1. We open-sourced it all github.com/TRI-ML/vla_foundr…. Our project website also has links to the white paper, the weights, and more videos tri-ml.github.io/vla_foundry

Releasing VLA Foundry: an open-source framework that unifies LLM, VLM, and VLA training in a single codebase. End-to-end control from language pretraining to action-expert fine-tuning — no more stitching together incompatible repos.

New release from TRI

CRAFT hand🫳 1. Achieves all 33/33 dexterous grasps > 2x-20x $$ hands! 2. < $600 3. Handles fragile objects 4. Durable under contact 5. Open-sourced craft-hand.github.io/ @leo_lin6 & @shivanshpatel35 (on market; hire him🚀) will happily share anything else that you may need. Details in 🧵 🌟 Big shout out to @kenny__shaw (Leap & v2), @irmakkguzey (RUKA), @orcahand (ORCA), and many others who helped build this open research community. Thank you!

Thrilled to announce I’m joining @JHUCompSci as a CS PhD student with @mangahomanga. Looking forward to collaborating with new faculty members @_krishna_murthy, @jmin__cho, @anand_bhattad, @HaiminHu & @zihyunchiu and being part of this rising community. Great things ahead!

Robot learning is growing at @JHUCompSci @HopkinsDSAI Thanks @DexmateAI for supporting us! @anand_bhattad @mangahomanga Greg Hager and I put this proposal together. I just happened to be the one to hit submit :)