30 years of RL research and superhuman Gran Turismo: so excited to share Peter Stone's talk: (link below)

Please stop by our poster if you are at #IROS . We propose a simple yet effective method for representing learning in trajectory predictions. Since collecting trajectory data is more challenging than gathering vision data, we utilize synthetic techniques and vector

🚀Unsupervised RL can learn skills purely from reward-free interactions with an environment. But what form of skills can facilitate efficient downstream hierarchical learning? Introducing DUSDi: Disentangled Unsupervised Skill Discovery (NeurIPS24). jiahenghu.github.io/DUSDi-site 🧵

Mitigating racial bias from LLMs is a lot easier than removing it from humans! Can’t believe this happened at the best AI conference NeurIPS Conference We have ethical reviews for authors, but missed it for invited speakers? 😡

🙌 Meet the 2024 ACM Technical Awards Recipients! We’re proud to honor this year’s innovators in autonomous systems, cryptography, and software for parallel computers: 🏆 Peter Stone – ACM-AAAI Allen Newell Award For significant contributions to the theory and practice of

[1/n] Can LLM Agents learn to communicate and coordinate in natural language in driving scenarios 🚗 through self-play interactions? Our recent research shows the potential for such learning; interestingly, there is evidence that they develop concise protocols for collaboration!

💡Can we let an arm-mounted quadrupedal robot to perform task with both arms and legs? Introducing ReLIC: Reinforcement Learning for Interlimb Coordination for versatile loco-manipulation in unstructured environments. [1/6] relic-locoman.rai-inst.com

I’m hiring multiple PhD students and one postdoc at NTU Singapore, starting in Spring or Fall 2026, to push the frontiers of robot planning, learning, and embodied AI. Details are available here: yoonchangsung.com/opportunity Thank you for your support in sharing this opportunity!

📢 Excited to sharing a little late update (before it is no longer news): I’ll be joining UT Austin Computer Science at UT Austin as an Assistant Professor! I'm recruiting PhD students from Computer Science at UT Austin in the Fall 2025 cycle and also looking for RAs/interns! More info see chenfengx.com

Check out our new benchmark for testing whether VLMs can truly understand social navigation scenes and align with human reasoning. We hope the community finds it useful for advancing foundation models in social navigation. Catch Michael Munje at CoRL 2025 to learn more!

It’s crucial for robots to navigate in line with user preferences among crowds. Excited to share ComposableNav that allows composable instruction-following navigation in dynamic environments. If you’re at CoRL, check it out—Michael Munje will present it alongside SocialNav-SUB!

How can we align a policy with human preferences efficiently? MEReQ tackles this by inferring residual rewards that capture discrepancies from human experts and adapting via residual Q-learning (arxiv.org/pdf/2306.09526). Check it out at CoRL along with @Yuxin’s other work, ReLIC!