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At #ICRA24 we've a few papers on 𝗴𝗿𝗼𝘂𝗻𝗱𝗲𝗱 𝗿𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴 of LLMs/VLMs. • Grounded common-sense reasoning via active perception - Minae Kwon's 🧵👇 • Physically grounding VLMs - Jensen Gao's 🧵👇 • Learning from online language corrections - @lihanzha's 🧵👇

Excited to share our work DROC at #ICRA2024!🚀 DROC empowers robots to learn from online language corrections and effortlessly generalize to new tasks. Join my presentation in room AX-F201 from 13:30 - 15:00 on Thu 16 May,and swing by our poster at BT13-AX.6 between 16:30-18:00!

Update: - Oral: Tomorrow 14:20-14:30, AX - F201 - Poster: 16:30-18:00, #13.06 Drop by if you are interested in language for robotics, learning during deployment or HRI! More than happy to chat and connect :)

A capable hardware can unlock the potential of existing algorithms in many ways. Stay tuned for more exciting developments on this hardware! Congratulations to Yen-Jen Wang and my undergraduate advisor, Jianyu Chen!

Congrats Yuchen Cui!! Your mentorship during my Stanford internship was invaluable. Wishing you all the best in your future endeavors! 🎉

I received tenure at #Princeton! It’s been an incredible journey, and I am immensely grateful to my group, collaborators, mentors, and family. Looking forward to continuing our work on making 🤖 more trustworthy! I will be on sabbatical 2024-25, spending time at Google DeepMind.

👇Introducing DPPO, Diffusion Policy Policy Optimization DPPO optimizes pre-trained Diffusion Policy using policy gradient from RL, showing 𝘀𝘂𝗿𝗽𝗿𝗶𝘀𝗶𝗻𝗴 𝗶𝗺𝗽𝗿𝗼𝘃𝗲𝗺𝗲𝗻𝘁𝘀 over a variety of baselines across benchmarks and sim2real transfer diffusion-ppo.github.io