Yifei Cao

Apparent learning biases emerge from optimal inference: Insights from master equation analysis | PNAS Recent studies [S. Palminteri, G. Lefebvre, E. J. Kilford, S. J. Blakemore, PLoS Comput. Biol. 13, e1005684 (2017); G. Lefebvre, M. Lebreton, F. Me...

Very cool study showing that "apparent" asymmetric update in reinforcement learning can emerge from Bayes optimal principles by Prakhar Godara in @pnas.org

www.pnas.org/doi/abs/10.1...

Congrats Randolph!

A brain-inspired agentic architecture to improve planning with LLMs - Nature Communications Multi-step planning is a challenge for LLMs. Here, the authors introduce a brain-inspired Modular Agentic Planner that decomposes planning into specialized LLM modules, improving performance across tasks and highlighting the value of cognitive neuroscience for LLM design.

Very excited to share that our work (together with co-first author Shanka Subhra Mondal and @neuroai.bsky.social ) on a brain-inspired architecture for planning with LLMs is now out in Nature Communications! www.nature.com/articles/s41... (thread below)

Crazy cool work, Ji-An! your arXiv paper was like a tutorial for me on modeling behavior with cognitive and neural network models, I really read it a lot of times and feel so happy to see it on Nature now. Huge congrats! Looking forward to your future works!

Discovering cognitive strategies with tiny recurrent neural networks - Nature Modelling biological decision-making with tiny recurrent neural networks enables more accurate predictions of animal choices than classical cognitive models and offers insights into the underlying cog...

Thrilled to see our TinyRNN paper in @nature! We show how tiny RNNs predict choices of individual subjects accurately while staying fully interpretable. This approach can transform how we model cognitive processes in both healthy and disordered decisions. doi.org/10.1038/s415...

This is so crazy Marcel, really love this paper when I also modeling reversal learning with hybrid cog-RNN model. Big congrats!!!!!!

Congrats, Phillip!

Epic recordings of model-based and model-free learning signals from Kennerley lab (Bruno Miranda). Now at @elife.bsky.social

doi.org/10.7554/eLif...

Deep reinforcement learning can promote sustainable human behaviour in a common-pool resource problem - Nature Communications Koster et al introduce a deep reinforcement learning (RL) mechanism designed to manage common-pool resources successfully encourages sustainable cooperation among human participants by dynamically adj...

getting this paper published was a bit painful but I am proud of it: www.nature.com/articles/s41.... We use deep RL to find mechanisms that help (real) people sustain the commons. Well done to Raphael Koster and Miruna Pislar (not on BlueSky). non-paywalled version on arxiv.

Google PhD fellowship program The Google PhD Fellowship Program recognizes outstanding graduate students doing exceptional work in computer science, related disciplines, or promising research areas.

Applications for the global Google PhD Fellowship Program are open! Fellowships directly support graduate students doing exceptional and innovative research in computer science and related fields as they pursue their PhD. Learn more and apply by May 15 at goo.gle/phdfellowship.

Thank you for your reply Marcel, and it’s a bit pitty🥹 really enjoyed reading your work on meta-leaning and LLM cognition, hope we have opportunity to collaborate in the future😁

Hi Marcel, do you have any position for interns? Thanks!

We are looking for two PhD students at our institute in Munich.

Both postions are open-topic, so anything between cognitive science and machine learning is possible.

More information: hcai-munich.com/PhDHCAI.pdf

Feel free to share broadly!

Intrinsically-Motivated Humans and Agents in Open-World Exploration What drives exploration? Understanding intrinsic motivation is a long-standing challenge in both cognitive science and artificial intelligence; numerous objectives have been proposed and used to train...

New preprint with Aly Dayan Eliza Kosoy Yuqing Du.I really love this study, play and exploration, comparing free exploration of children adults and agents w entropy, empowerment and info gain as rewards. Plus kids private speech increases exploration.

arxiv.org/abs/2503.23631

Can LLMs be used to discover interpretable models of human and animal behavior?🤔

Turns out: yes!

Thrilled to share our latest preprint where we used FunSearch to automatically discover symbolic cognitive models of behavior.
1/12