🔔 Join our MAGELLAN talk on July 2! We'll explore how LLM agents can monitor their own learning progress and choose what to learn next, like curious humans 🤔 1h presentation + 1h Q&A on autotelic agents & more! 📅 July 2, 4:30 PM CEST 🎟️ forms.gle/1PC2fxJx1PZYfqFr7

@cartathomas.bsky.social · last yr.

🚀 Introducing 🧭MAGELLAN—our new metacognitive framework for LLM agents! It predicts its own learning progress (LP) in vast natural language goal spaces, enabling efficient exploration of complex domains.🌍✨Learn more: 🔗 arxiv.org/abs/2502.07709 #OpenEndedLearning #LLM #RL

🚨New preprint🚨 When testing LLMs with questions, how can we know they did not see the answer in their training? In this new paper we propose a simple out of the box and fast method to spot contamination on short texts with @stepalminteri.bsky.social and Pierre-Yves Oudeyer !

🚀 Introducing 🧭MAGELLAN—our new metacognitive framework for LLM agents! It predicts its own learning progress (LP) in vast natural language goal spaces, enabling efficient exploration of complex domains.🌍✨Learn more: 🔗 arxiv.org/abs/2502.07709 #OpenEndedLearning #LLM #RL

MAGELLAN: Metacognitive predictions of learning progress guide...

Open-ended learning agents must efficiently prioritize goals in vast possibility spaces, focusing on those that maximize learning progress (LP). When such autotelic exploration is achieved by LLM...

arxiv.org