It's #CVPR week! 🎉 If you're looking to dive deep into the future of intelligent reasoning systems, we've got your 𝗧𝗵𝘂𝗿𝘀𝗱𝗮𝘆 𝗺𝗼𝗿𝗻𝗶𝗻𝗴 plans sorted in #Denver. Join us for the 6th 𝗠𝘂𝗹𝘁𝗶𝗺𝗼𝗱𝗮𝗹 𝗔𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺𝗶𝗰 𝗥𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴 Workshop! We've put together an incredible lineup of keynotes, talks, and deep-dive discussions exploring the cutting edge of AI reasoning. You won't want to miss this. 📅 When: Thursday, June 4, 2026 | 8:55 AM - 12:30 PM MDT 📍 Where: 𝗥𝗼𝗼𝗺 𝟲𝟬𝟭, Colorado Convention Center, Denver, CO We are incredibly honored to welcome this stellar lineup of keynote speakers: ⏰ 𝟬𝟵:𝟬𝟬 𝗔𝗠 | 🎤 𝗝𝘂𝗮𝗻 𝗖𝗮𝗿𝗹𝗼𝘀 𝗡𝗶𝗲𝗯𝗹𝗲𝘀 @jcniebles 💡 — 𝗦𝗮𝗹𝗲𝘀𝗳𝗼𝗿𝗰𝗲 𝗔𝗜 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 @SFResearch ⏰ 𝟬𝟵:𝟯𝟬 𝗔𝗠 | 🎤 𝗝𝗶𝗮𝘆𝘂𝗮𝗻 𝗠𝗮𝗼 @maojiayuan 💡 — 𝗨𝗻𝗶𝘃𝗲𝗿𝘀𝗶𝘁𝘆 𝗼𝗳 𝗣𝗲𝗻𝗻𝘀𝘆𝗹𝘃𝗮𝗻𝗶𝗮 @Penn ⏰ 𝟭𝟬:𝟰𝟱 𝗔𝗠 | 🎤 𝗠𝗲𝗹𝗮𝗻𝗶𝗲 𝗠𝗶𝘁𝗰𝗵𝗲𝗹𝗹 @MelMitchell1 💡 — 𝗦𝗮𝗻𝘁𝗮 𝗙𝗲 𝗜𝗻𝘀𝘁𝗶𝘁𝘂𝘁𝗲 @sfiscience ⏰ 𝟭𝟭:𝟭𝟱 𝗔𝗠 | 🎤 𝗝𝗶𝗮𝗹𝗼𝗻𝗴 𝗪𝘂 💡 — 𝗧𝘀𝗶𝗻𝗴𝗵𝘂𝗮 𝗨𝗻𝗶𝘃𝗲𝗿𝘀𝗶𝘁𝘆 @Tsinghua_Uni A huge thank you to our generous sponsors for making this event a reality: 🤝 𝗠𝗶𝘁𝘀𝘂𝗯𝗶𝘀𝗵𝗶 𝗘𝗹𝗲𝗰𝘁𝗿𝗶𝗰 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗟𝗮𝗯𝗼𝗿𝗮𝘁𝗼𝗿𝗶𝗲𝘀 (𝗠𝗘𝗥𝗟) @merl_news : 🌐 merl.com/ 🤝 𝗘𝗹𝗼𝗿𝗶𝗮𝗻 𝗔𝗜 @ElorianAI : 🌐 elorian.ai/ Massive shoutout to our dedicated organizers: 🔹 𝗔𝗻𝗼𝗼𝗽 𝗖𝗵𝗲𝗿𝗶𝗮𝗻 @anoopcherian — 𝗠𝗘𝗥𝗟 🔹 𝗦𝘂𝗵𝗮𝘀 𝗟𝗼𝗵𝗶𝘁 @Suhas_Lohit — 𝗠𝗘𝗥𝗟 🔹 𝗞𝘂𝗮𝗻-𝗖𝗵𝘂𝗮𝗻 𝗣𝗲𝗻𝗴 @KuanChuanPeng — 𝗠𝗘𝗥𝗟 🔹 𝗛𝗼𝗻𝗴𝗹𝘂 𝗭𝗵𝗼𝘂 @zhou_honglu — 𝗦𝗮𝗹𝗲𝘀𝗳𝗼𝗿𝗰𝗲 𝗔𝗜 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 🔹 𝗞𝗲𝘃𝗶𝗻 𝗦𝗺𝗶𝘁𝗵 @realkevinsmith — 𝗠𝗜𝗧 @MIT 🔹 𝗝𝗼𝘀𝗵𝘂𝗮 𝗕. 𝗧𝗲𝗻𝗲𝗻𝗯𝗮𝘂𝗺 — 𝗠𝗜𝗧 As AI systems become increasingly capable across vision, language, action, and interaction, reasoning remains one of the field's most exciting open challenges. This workshop brings together researchers and practitioners across academia and industry to discuss the latest advances in multimodal reasoning, foundation models, physical & agentic reasoning, and human–AI comparisons. 👉 𝗚𝗲𝘁 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝘀𝗰𝗵𝗲𝗱𝘂𝗹𝗲 𝗮𝗻𝗱 𝘄𝗼𝗿𝗸𝘀𝗵𝗼𝗽 𝗱𝗲𝘁𝗮𝗶𝗹𝘀 𝗵𝗲𝗿𝗲: 🌐 marworkshop.github.io/cvpr26… Will you be joining us on Thursday? Drop a comment or tag a colleague you're attending with! 👇 #CVPR2026 #CVPRWorkshop #AI #MultimodalAI #Reasoning #FoundationModels #MachineLearning #MultimodalReasoning #IntelligentSystems

Predicting future optical flow turns out to be surprisingly powerful; it boosts both robot control 🤖 and video generation 🎥. 🚀 New Research Alert! 📰 Paper: arxiv.org/abs/2601.10781 I'm thrilled to share the release of 𝗙𝗼𝗙𝗣𝗿𝗲𝗱 (paper/code/checkpoint/interactive demo) - our model forecasts optical flow conditioned on language instructions. 👉 𝗧𝗿𝘆 𝗶𝘁 𝘆𝗼𝘂𝗿𝘀𝗲𝗹𝗳 𝘃𝗶𝗮 𝘁𝗵𝗲 𝗱𝗲𝗺𝗼 link on our project website! • Website: fofpred.github.io/ • HuggingFace checkpoint: huggingface.co/Salesforce/FO… • Demo: fofpred.salesforceresearch.a… • GitHub: github.com/SalesforceAIResea… In this work, we argue that what has to be provided to the models for many (robot) control and (video) generation tasks is how things should move in the future. This inherently is a challenging task, as it requires: 1⃣ - a clear formulation of what type of ‘future motion’ we will be computing 2⃣ - curating large enough training data with strong supervisory signals 3⃣ - an elegant model capable of fully digesting such (potentially cross-domain) training data while generalizing across domains. We focus on 𝗙𝘂𝘁𝘂𝗿𝗲 𝗢𝗽𝘁𝗶𝗰𝗮𝗹 𝗙𝗹𝗼𝘄 𝗣𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝗼𝗻 - a language-conditioned, spatially dense motion prediction task. We discuss a 𝘀𝘂𝗶𝘁𝗮𝗯𝗹𝗲 𝗺𝗼𝗱𝗲𝗹 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 (a unified VLM-diffusion model) and show 𝗵𝗼𝘄 𝘄𝗲 𝗰𝗮𝗻 𝗵𝗶𝗴𝗵𝗹𝘆-𝘀𝗰𝗮𝗹𝗮𝗯𝗹𝗲 𝘁𝗿𝗮𝗶𝗻 our model with videos from various sources (web-scale human activity videos with noisy camera motion + robot action videos in controlled environments). FoFPred adapts to both 𝗹𝗮𝗻𝗴𝘂𝗮𝗴𝗲-𝗱𝗿𝗶𝘃𝗲𝗻 𝗿𝗼𝗯𝗼𝘁𝗶𝗰 𝗺𝗮𝗻𝗶𝗽𝘂𝗹𝗮𝘁𝗶𝗼𝗻 and 𝗹𝗮𝗻𝗴𝘂𝗮𝗴𝗲-𝗴𝘂𝗶𝗱𝗲𝗱 𝗺𝗼𝘁𝗶𝗼𝗻 𝘃𝗶𝗱𝗲𝗼 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 - to the best of our knowledge, the first to support such cross-domain versatility. We hope this work paves the way toward generalizable, 𝗺𝗼𝘁𝗶𝗼𝗻-𝗮𝘄𝗮𝗿𝗲 𝘄𝗼𝗿𝗹𝗱 𝗺𝗼𝗱𝗲𝗹𝘀 that understand and act through dynamic visual grounding. Be sure to check out the project website and read our paper, which covers lots of useful information, including qualitative results, ablations (on human web videos, architecture choices, camera motion separation / motion target disentanglement), and our insights on open challenges and future directions. 👏 Huge shoutout to Kanchana Ranasinghe @kahnchana, our intern at Salesforce AI Research @SFResearch, for the outstanding work on this project and for making an excellent open source! 🫶👍😁 #WorldModels #DiffusionModels #VideoGeneration #Robotics #EmbodiedAI #GenerativeAI