πIntroducing πππππ-πππ: A reporting checklist for using LLMs in behavioral & social science
β
GUIDE-LLM is a reporting checklist designed by 80+ experts to improve transparency, reproducibility & ethical accountability of LLM-based research
π llm-checklist.com
including historical querelles π§πmedium.com/@stefano.palminteri/do-l...
π¨ Updated preprint π¨
Excited to share this updated preprint, in which @ruimata.bsky.social and I discuss five ways LLMs can help address longstanding challenges in cognitive science and psychology, examining both opportunities and pitfalls.
π arxiv.org/abs/2511.00206
π¨ New publication π¨
Excited to share this new forum piece led by @kevinetiede.bsky.social
We propose broadening risk communication to cover neglected dimensions outlined in our risk-information taxonomy, requiring greater reliance on simulated experiences.
Open access: doi.org/10.1016/j.ti...
The workshop focuses on machines trained to replicate human behavior, as scientific models of human cognition and action, as tools for large-scale behavioral simulation, and as objects of study in their own right. We invite talks, lightning talks, and posters.
π¨ Deadline extension π¨
BEHAVIORAL CLONES WORKSHOP
Imitating humans is a powerful route to machine behavior and an emerging lens on human cognition and social simulation.
π Fri, 20 May 2026
π Following Machine+Behavior @ Max Planck Berlin
π£οΈ Invited talks: Danica Dillion, Raja Marjieh, Marcel Binz
π¨ 7 days left to submit your work!
We further demonstrate an important moderating role of embedding extraction method and confirm results suggesting that final-layer embeddings underrepresent psycholinguistic information.
We show that accessibility cascades from lexical to semantic information similarly across all transformer language models, but is still realized differently in encoder and decoder models.
π¨ New preprint π¨
Excited to share new work led by @tikhomirova.bsky.social, presenting a large-scale evaluation of the accessibility of psycholinguistic information in transformer language models.
Preprint: arxiv.org/abs/2601.03798
WORKSHOP ON BEHAVIORAL CLONES
Imitating humans is a powerful route to machine behavior, an emerging lens on human cognition, and a prerequisite for social simulation.
π Fri 20 May 26
Following Machine+Behavior @ Max Planck Berlin
Invited talks by @danicajdillion.bsky.social @marcelbinz.bsky.social
The workshop focuses on machines trained to replicate human behavior, as scientific models of human cognition and action, as tools for large-scale behavioral simulation, and as objects of study in their own right. We invite submissions for talks, lightning talks, and posters.
WORKSHOP ON BEHAVIORAL CLONES
Imitating humans is a powerful route to machine behavior and an emerging lens on human cognition and social simulation.
π Fri, 20 May 2026
Following Machine+Behavior @ Max Planck Berlin
Invited talks: Danica Dillon, @marcelbinz.bsky.social
π¨ New preprint π¨
We present the decisions-from-experience database (DfE-DB), including data from 168 studies.
The data are currently shared with the original authors and made public upon publication.
π Database: github.com/dwulff/dfe-db
π Preprint: www.biorxiv.org/content/10.6...
I am hiring a postdoc for a DFF-funded project on social influence, and the decision processes that fuel rich-get-richer dynamics in the online/offline world. The position is for up to a year, competitive Danish salary, remote work possible. Interested or know somebody? DM me or share!
I am sorry to hear. If you are interested, there is research showing the usefulness of LLMs for psychological research, which in part derives from the models' ingestion of academic literature during training. I see no reason why LLM capabilities wouldn't generalize to this context to some extent.
I think I grasped your point. But all good, no problem if we disagree.
Logically correct---not quite what I said. I genuinely think that LLMs can provide useful signals on such questions. But we need to do our best to assess error and bias, like we should do with every other approach used to address such questions.
The ratings should be validated, of course. But there are good reasons LLMs might "know" this up to some reasonable error and bias.
π¬ How has psychology contributed to achieving the πΊπ³ SDGs?
Our new preprint maps 230,000 psychology articles to the SDGs using our text2sdg R package (www.text2sdg.io) and analyzes historical trends in topics, national and gendered contributions, and citation patterns.
π arxiv.org/abs/2512.08628
@cos.io, I noticed that, since the relaunch, PsyArXiv preprints are no longer being indexed by Google Scholar. Do you know if this will be fixed? Thank you for your work!
@cos.io, I noticed that, since the relaunch, PsyArXiv preprints are no longer being indexed by Google Scholar. Do you know if this will be fixed? Thank you for your work!
With @tikhomirova.bsky.social, Valentin Kriegmair, Fritz GΓΌnther, Aliona Petrenco, Louis Schiekiera, @ercbravenewword.bsky.social, and @marcelbinz.bsky.social
π¨ Inviting collaborators! π¨
Weβre launching PsychLing-101 β an open, community-driven initiative to gather psycholinguistic datasets for cross-dataset analyses and the development of psycholinguistic foundation models.
π To contribute or propose a dataset, go to:
π github.com/Data-X01/Psy...
How can LLMs advance the cognitive sciences?
@ruimata.bsky.social and I put together a review on how LLMs can help us address five long-standing problems in cognitive science (e.g., disciplinary silos or lack of generalizability).
π arxiv.org/2511.00206
π¨ New preprint - Advancing Cognitive Science with LLMs
Excited to share this new preprint together with Rui Mata. We review how π€ LLMs can help address long-standing problems in cognitive science, highlighting opportunities and pitfalls.
π Preprint: arxiv.org/abs/2511.00206
π¨ New preprint - Advancing Cognitive Science with LLMs
Excited to share this new preprint together with Rui Mata. We review how π€ LLMs can help address long-standing problems in cognitive science, highlighting opportunities and pitfalls.
π Preprint: arxiv.org/abs/2511.00206
We have a new preprint: osf.io/preprints/so...
What have we learned about social media - the constantly moving target of empirical research - over the past decade?
