Reminder: our submission deadline is approaching fast — 22 May (AOE)!
Submit your work on making RL truly out-of-the-box. We are particularly interested in research at the intersection of RL and LLMs to improve robustness and adaptability.
https://t.co/cXhEHTamYI
If that's something you're passionate about as well, consider submitting to the workshop!
The submission deadline is the 22nd of May, the workshop takes place on the 15th of August.
You can find our submission instructions here: https://t.co/jPwUBXZLb1
What even is AutoRL and what kind of submissions are we looking for? 🤔
In theory, it should be easy to use a successful algorithm like PPO that can solve many RL tasks on a new problem, but this is rarely the case. Instead, a lot of effort and expertise is needed each time.
AutoRL methods try to close that gap in various ways: meta-learning, stabilization techniques, optimizing hyperparameters, or gathering new insights about how reproducibility works in RL.
What's important is not the method, but the goal: making RL an out-of-the-box technology!
🔥 AutoRL Workshop returns to RLC 2026 in Montréal 🇨🇦
Join us to tackle RL brittleness and advance methods that work “out of the box”.
More info: https://t.co/cXhEHTamYI
This year's organisers are: Theresa Eimer, @DierkesJul67648, @johanobandoc, @pcastr, @HolgerHoos
We have a speaker change: instead of @jparkerholder we'll hear from @MichaelD1729 - the focus of the talk is the same, though, so join if you're interested in generating any environments you can imagine!
After a day of presentations, posters and a breakout session, we'll close with a panel discussion. @pcastr@AlexDGoldie@jakeABeck and Doina Precup will tell us their views on the present and future of AutoRL - join us for an exciting finale to @icmlconf 2024! 👑
Last but not least: Pablo Samuel Castro @pcastr is a senior researcher at @GoogleDeepMind known for his musical endeavors and pushing the limits of the ALE with algorithmic innovations and design decisions. He’ll talk about why the ALE is a great benchmark for AutoRL 👾����️
Up next: Jack Parker-Holder @jparkerholder works on open-endedness as a research scientist at @GoogleDeepMind and honorary lecturer with @UCL_DARK . His focus is on unlimited training data for open-ended RL - being able to generate interactive tasks controllably and at will 🔮
Our third speaker is Pierluca D'Oro @proceduralia, researcher at @AIatMeta and PhD student at @Mila_Quebec. You likely know his work combining RL with LLMs to create capable AI assistants. We’re excited to hear how he envisions the future of LLMs in RL and vice versa! 🗣️🧠
Speaker number two! 🔥 Roberta Raileanu @robertarail, research scientist at @AIatMeta, has worked on different aspects of RL, most recently teaching LLMs to make better decisions. She’ll discuss generalization for robust and capable agents in practice 💪
Chelsea Finn @chelseabfinn barely needs an introduction: If you’re interested in robotics or meta-learning, you almost certainly know her work. She’s an assistant professor at @Stanford, co-founder of @physical_int and expert in making RL work for real-world robotics tasks 🤖💫
Please send us your CV and a short statement as to why you should receive the complimentary registration to [email protected] by 8 July AOE in case you want one.
If you are attending the AutoRL workshop, we are offering two complimentary registrations to persons looking for financial support (you will be reimbursed in case you have already registered).
"Self-Exploring Language Models: Active Preference Elicitation for Online Alignment" adds optimism to the RLHF objective for better out-of-distribution sampling.
By @ShenaoZhang@Yudh9662, Hiteshi Sharma, @yzy_ai@shuohangw@hany_hassan & @zhaoran_wang
https://t.co/iYvQZCEpMj