Julian Coda-Forno @juliancodaforno
PhD Student in Machine Learning @cpilab @ELLISforEurope exploring Cognitive Models of Meta-RL supervised by Eric Schulz & @janexwang. juliancodaforno.github.io Joined January 2022-
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Excited to announce our full-day workshop on “In-context learning in natural and artificial intelligence” at CogSci (@cogsci_soc) 2024 in Rotterdam (with @JacquesPesnot @akjagadish @summerfieldlab and Ishita Dasgupta). jacquespesnot.github.io/2024_CogSci_Wo…
🚨Announcing the next Harvard #efficientml seminar on Learning to learn, featuring @janexwang and Rising Star @juliancodaforno ! 🧠 ➡️ April 22, 2:30 ET 📅Registration: tinyurl.com/yyzt9c96 🔗 Website: efficientml.org @harvard_data @HarvardDBMI @KempnerInst
Passionate about cogsci, ML, and/or computational psychiatry? Ready for a change in 2024? Come join us at the new Institute for Human-Centered AI at @HelmholtzMunich. We have an open call for 2 open-topic postdoc positions. Deadline: Jan 12th cpilab.org/img/Postdoc_Jo…
For more than two years now, a part of our lab has been focusing on using the behavioral sciences to better understand Large Language Models. Time for a small recap of what we have found. As these agents will interact with us increasingly more often, how do they actually behave?
LLMs are impressive but often show unhuman-like characteristics. How can we fix this? We propose to finetune an LLM (LLaMA) on data from psychological experiments. Link: arxiv.org/abs/2306.03917
In new work led by @elifakata and with @Lion_Schulz @juliancodaforno @coallaoh and @MatthiasBethge, we let #LLMs play repeated games with each other and with human-like strategies. We find that #GPT4 is best but plays very unforgivingly and fails to coordinate with simple agents.
It’s time for some game theory! What happens if we ask AI to play common economic games? They do very well at games where being selfish is optimal (Prisoner’s Dilemma) but worse at those that require coordination. GPT-4 did best, especially with prompting arxiv.org/pdf/2305.16867…
New preprint: We present a reinforcement learning algorithm that learns to solve tasks with compressible action sequences! Joint work with @EltetoNoemi, Peter Dayan, Marcel Binz and Eric Schulz (@cpilab). arxiv.org/pdf/2305.17109…
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check out Julian's heroic effort to benchmark LLMs using psychology experiments😎
1/ 🎉 Excited to share our new paper "CogBench: a large language model walks into a psychology lab" accepted at #ICML2024! 🧠🤖 📄 Read the full paper here: [arxiv.org/pdf/2402.18225] Co-authored with @marcel_binz, @janexwang and @cpilab
In the 3rd paper, led by Johannes Schubert and @akjagadish, co-supervised by @marcel_binz, we show that LLMs are --like people-- asymmetric belief updaters. This turns out to be an adaptive behavior. arxiv.org/abs/2402.03969
In the 2nd paper, led by @akjagadish and @marcel_binz, we introduce ecological rational meta-learned inference (ERMI): we train meta-learning agents on data generated by LLMs. ERMI explains human category learning and reaches SOTA in tabular regression. arxiv.org/html/2402.0182…
1/ Really excited to share: Language in Brains, Minds, and Machines w @Nancy_Kanwisher @ev_fedorenko @AnnualReviews We survey the insights that language models (LMs) provide on the question of how language is represented and processed in the human brain. rb.gy/8afztv
Happy that our lab got 3 papers accepted @icmlconf this year. 🥳
In the 1st paper, led by @juliancodaforno and @marcel_binz, and co-supervised by @janexwang, we developed a cognitive benchmark that includes 10 behavioral metrics (model-basedness, meta-cognition, reasoning, etc.) and applied it to 35 LLMs: arxiv.org/pdf/2402.18225
Woke up to 3/3 papers accepted at ICML (with @juliancodaforno @janexwang @akjagadish @cpilab and twitterless Johannes Schubert and Mirko Thalmann) and celebrated already with a lab hike 🏔️🚶 More detailed tweets to follow! #cogsci #ML
Happy that our lab got 3 papers accepted @icmlconf this year. 🥳
Excited to announce our full-day workshop on “In-context learning in natural and artificial intelligence” at CogSci (@cogsci_soc) 2024 in Rotterdam (with @JacquesPesnot @akjagadish @summerfieldlab and Ishita Dasgupta). jacquespesnot.github.io/2024_CogSci_Wo…
Happy tweet. I'll be in London for 6 months working on ML for cogsci at Deepmind. Let me know what else I should do in London!
🚨Announcing the next Harvard #efficientml seminar on Learning to learn, featuring @janexwang and Rising Star @juliancodaforno ! 🧠 ➡️ April 22, 2:30 ET 📅Registration: tinyurl.com/yyzt9c96 🔗 Website: efficientml.org @harvard_data @HarvardDBMI @KempnerInst
Anxiety and depression might be related to increased, not decreased, exploration behaviour. What could be possible mechanisms underlying this? Beyond thrilled to share my very first first-author preprint with @toby_wise @docqhuys and @cpilab. osf.io/preprints/psya… 🧵⬇️ [1/n]
I never thought I'd say this with a straight face but: Thank you for coming to my ted talk. youtu.be/_hmB-dcl7Ao?si…
I am really excited to reveal what @GoogleDeepMind's Open Endedness Team has been up to 🚀. We introduce Genie 🧞, a foundation world model trained exclusively from Internet videos that can generate an endless variety of action-controllable 2D worlds given image prompts.
Happy to announce that this was accepted to ICLR. Looking forward to meeting people in Vienna, and keep your eyes open for extensions of this project coming soon!
LLMs are impressive but often show unhuman-like characteristics. How can we fix this? We propose to finetune an LLM (LLaMA) on data from psychological experiments. Link: arxiv.org/abs/2306.03917
Politics seems home to the most calculating - and yet least rational - elements of humanity. How can we systematically understand this? Really excited to share a computational take on political cognition with @RaBhui in @TrendsCognSci! 🧵👇[1/n] rb.gy/55atfg
🌟Exciting news alert! 🌟 I am beyond thrilled to share that in January I am joining @HelmholtzMunich as a director & @TU_Muenchen as a Liesel Beckman distinguished professor! This opportunity marks an incredible leap in my career journey, one I'm deeply grateful for.
Passionate about cogsci, ML, and/or computational psychiatry? Ready for a change in 2024? Come join us at the new Institute for Human-Centered AI at @HelmholtzMunich. We have an open call for 2 open-topic postdoc positions. Deadline: Jan 12th cpilab.org/img/Postdoc_Jo…
How do we learn whom to trust and how to tease apart information from misinformation? Excited to share our new preprint on this with Eric Schulz (@cpilab), @RaBhui and Peter Dayan (@MPICybernetics). 🧵👇 [1/n]
Sadly I am not going to #NeurIPS2023, but if you are, you should definitely check out @juliancodaforno's paper on Meta-in-context Learning in LLMs! neurips.cc/virtual/2023/p… on Thursday at 5:15 pm x.com/cpilab/status/…
🚨New work led by @juliancodaforno and together with Marcel Binz @zeynepakata Matt Botvinick and @janexwang. 🚨 We show that large language models can meta-learn in context. This means that in-context learning of LLMs can be recursively improved via in-context learning itself 🤯
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