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Romane Cecchi

@romanececchi.bsky.social
151 followers 71 following 11 posts

Postdoc in the Human Reinforcement Learning team led by @stepalminteri.bsky.social at École Normale Supérieure (ENS) in Paris ✨

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Reposted by Romane Cecchi
Stefano Palminteri @stepalminteri.bsky.social · 23/06/2026
New paper in Nature Communications 🎉 Led by @romanececchi.bsky.social, with @sgluth.bsky.social, we show that attention shapes value normalization in human reinforcement learning. Eye-tracking models explain nonlinear reward scaling better than an ad hoc parameter. www.nature.com/articles/s41...
nature.com
Attention modulates value normalization in human reinforcement learning by shaping reward encoding - Nature Communications
People’s reward learning is shaped by context, but the cognitive origins of this bias remain poorly understood. Here, the authors provide evidence that attention may underlie these distortions by shap...
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Reposted by Romane Cecchi
Stefano Palminteri @stepalminteri.bsky.social · 27/05/2026
My lab will be present en masse at #sbdm2026 Paris. Here is a first sample of the posters, presented by @romanececchi.bsky.social "Dynamic range adaptation in vast decision spaces" and @fabiencerrotti.bsky.social "Correcting mis-conceptions and shaping preferences about energy sources with RL"
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Reposted by Romane Cecchi
Stefano Palminteri @stepalminteri.bsky.social · 03/02/2026
Very happy that @PNASNews agreed to publish our (w/ @romanececchi.bsky.social) response to Prakhar's thought-provoking study! You can find the final version at the link below. See the following tweet for Prakhar's response to our response. Happy to hear your thoughts! www.pnas.org/doi/10.1073/...
pnas.org
Genuine learning biases persist after accounting for temporally decreasing learning rates: Insight from fitting six datasets | PNAS
Genuine learning biases persist after accounting for temporally decreasing learning rates: Insight from fitting six datasets
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Romane Cecchi @romanececchi.bsky.social · 22/04/2025
🧵 New preprint out! 📄 "Elucidating attentional mechanisms underlying value normalization in human reinforcement learning" 👁️ We show that visual attention during learning causally shapes how values are encoded w/ @sgluth.bsky.social & @stepalminteri.bsky.social 🔗 doi.org/10.31234/osf...
doi.org
OSF
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Reposted by Romane Cecchi
Stefano Palminteri @stepalminteri.bsky.social · 23/01/2025
Epistemic biases in human reinforcement learning: behavioral evidence, computational characterization, normative status and possible applications. A quite self-centered review, but with a broad introduction and conclusions and very cool figures. Few main takes will follow osf.io/preprints/ps...
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Reposted by Romane Cecchi
Maëva L'Hôtellier @maevalhotellier.bsky.social · 10/12/2024
New preprint! 🚨 Performance of standard reinforcement learning (RL) algorithms depends on the scale of the rewards they aim to maximize. Inspired by human cognitive processes, we leverage a cognitive bias to develop scale-invariant RL algorithms: reward range normalization. Curious? Have a read!👇
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Reposted by Romane Cecchi
Stefano Palminteri @stepalminteri.bsky.social · 05/12/2024
🚨New preprint alert!🚨 Achieving Scale-Invariant Reinforcement Learning Performance with Reward Range Normalization. Where we show that things we discover in psychology can be useful for machine learning. By the amazing @maevalhotellier.bsky.social and Jeremy Perez. doi.org/10.31234/osf...
osf.io
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