Loris Gaven
@lorisgaven.bsky.social
Striving to make computers smarter.
PhD student @FlowersINRIA
PhD student @FlowersINRIA
Pinned
Loris Gaven
@lorisgaven.bsky.social
· Mar 24
🚀 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
Humans excel at estimating their own competence and progress on tasks. But can LLM agents do the same?
With 🧭MAGELLAN, our agent predicts its own learning progress across vast goal spaces, even generalizing to new tasks!
📄Paper: arxiv.org/abs/2502.07709
With 🧭MAGELLAN, our agent predicts its own learning progress across vast goal spaces, even generalizing to new tasks!
📄Paper: arxiv.org/abs/2502.07709
🔔 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
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
🚀 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
June 25, 2025 at 3:14 PM
🔔 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
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
Reposted by Loris Gaven
🔥Our paper PhyloLM got accepted at ICLR 2025 !🔥
In this work we show how easy it can be to infer relationship between LLMs by constructing trees and to predict their performances and behavior at a very low cost with @stepalminteri.bsky.social and @pyoudeyer.bsky.social ! Here is a brief recap ⬇️
In this work we show how easy it can be to infer relationship between LLMs by constructing trees and to predict their performances and behavior at a very low cost with @stepalminteri.bsky.social and @pyoudeyer.bsky.social ! Here is a brief recap ⬇️
April 24, 2025 at 1:15 PM
🔥Our paper PhyloLM got accepted at ICLR 2025 !🔥
In this work we show how easy it can be to infer relationship between LLMs by constructing trees and to predict their performances and behavior at a very low cost with @stepalminteri.bsky.social and @pyoudeyer.bsky.social ! Here is a brief recap ⬇️
In this work we show how easy it can be to infer relationship between LLMs by constructing trees and to predict their performances and behavior at a very low cost with @stepalminteri.bsky.social and @pyoudeyer.bsky.social ! Here is a brief recap ⬇️
Humans excel at estimating their own competence and progress on tasks. But can LLM agents do the same?
With 🧭MAGELLAN, our agent predicts its own learning progress across vast goal spaces, even generalizing to new tasks!
📄Paper: arxiv.org/abs/2502.07709
With 🧭MAGELLAN, our agent predicts its own learning progress across vast goal spaces, even generalizing to new tasks!
📄Paper: arxiv.org/abs/2502.07709
🚀 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
March 24, 2025 at 7:53 PM
Humans excel at estimating their own competence and progress on tasks. But can LLM agents do the same?
With 🧭MAGELLAN, our agent predicts its own learning progress across vast goal spaces, even generalizing to new tasks!
📄Paper: arxiv.org/abs/2502.07709
With 🧭MAGELLAN, our agent predicts its own learning progress across vast goal spaces, even generalizing to new tasks!
📄Paper: arxiv.org/abs/2502.07709
Reposted by Loris Gaven
we are recruiting interns for a few projects with @pyoudeyer
in bordeaux
> studying llm-mediated cultural evolution with @nisioti_eleni
@Jeremy__Perez
> balancing exploration and exploitation with autotelic rl with @ClementRomac
details and links in 🧵
please share!
in bordeaux
> studying llm-mediated cultural evolution with @nisioti_eleni
@Jeremy__Perez
> balancing exploration and exploitation with autotelic rl with @ClementRomac
details and links in 🧵
please share!
November 27, 2024 at 5:43 PM
we are recruiting interns for a few projects with @pyoudeyer
in bordeaux
> studying llm-mediated cultural evolution with @nisioti_eleni
@Jeremy__Perez
> balancing exploration and exploitation with autotelic rl with @ClementRomac
details and links in 🧵
please share!
in bordeaux
> studying llm-mediated cultural evolution with @nisioti_eleni
@Jeremy__Perez
> balancing exploration and exploitation with autotelic rl with @ClementRomac
details and links in 🧵
please share!