activity
20232026
most citedMachine Psychology

73 citations · 97 across the 7 of their papers we have counts for

collaborators

7 papers

cs.AI2026

Positive Alignment: Artificial Intelligence for Human Flourishing

Ruben Laukkonen, Seb Krier, Chloé Bakalar +13

Existing alignment research is dominated by concerns about safety and preventing harm: safeguards, controllability, and compliance. This paradigm of alignment parallels early psych…

cs.AI2026

Architecting Trust in Artificial Epistemic Agents

Nahema Marchal, Stephanie Chan, Matija Franklin +5

Large language models increasingly function as epistemic agents -- entities that can 1) autonomously pursue epistemic goals and 2) actively shape our shared knowledge environment.…

cs.CL2025

Uncovering Competency Gaps in Large Language Models and Their Benchmarks

Maty Bohacek, Nino Scherrer, Nicholas Dufour +3

The evaluation of large language models relies heavily on standardized benchmarks. These benchmarks provide useful aggregated metrics, but can obscure (i) particular sub-areas wher…

cs.LG2025

An evolutionary perspective on modes of learning in Transformers

Alexander Y. Ku, Thomas L. Griffiths, Stephanie C. Y. Chan

The success of Transformers lies in their ability to improve inference through two complementary strategies: the permanent refinement of model parameters via in-weight learning (IW…

cs.CY2024★ 4 cited

LearnLM: Improving Gemini for Learning

LearnLM Team, Abhinit Modi, Aditya Srikanth Veerubhotla +43

Today's generative AI systems are tuned to present information by default, rather than engage users in service of learning as a human tutor would. To address the wide range of pote…

cs.CY2024★ 20 cited

Towards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach

Irina Jurenka, Markus Kunesch, Kevin R. McKee +71

A major challenge facing the world is the provision of equitable and universal access to quality education. Recent advances in generative AI (gen AI) have created excitement about…

cs.CL2023★ 73 cited

Machine Psychology

Thilo Hagendorff, Ishita Dasgupta, Marcel Binz +5

Large language models (LLMs) show increasingly advanced emergent capabilities and are being incorporated across various societal domains. Understanding their behavior and reasoning…