5 citations · 9 across the 6 of their papers we have counts for
8 papers
From Process Loss to Assembly Bonus: Human-Grounded Diagnosis of Multi-Agent LLM Collaboration
Ala N. Tak, Teruhisa Misu, Kumar Akash +3
LLM agents are increasingly used for collaborative problem solving and human-group simulation. This makes outcome-only evaluation insufficient: if LLM groups are used as models of…
Sparks of Rationality: Do Reasoning LLMs Align with Human Judgment and Choice?
Ala N. Tak, Amin Banayeeanzade, Anahita Bolourani +5
Large Language Models (LLMs) are increasingly positioned as decision engines for hiring, healthcare, and economic judgment, yet real-world human judgment reflects a balance between…
Psychological Steering in LLMs: An Evaluation of Effectiveness and Trustworthiness
Amin Banayeeanzade, Ala N. Tak, Fatemeh Bahrani +5
The ability to control LLMs' emulated emotional states and personality traits is an essential step in enabling rich, human-centered interactions in socially interactive settings. W…
The Shrinking Landscape of Linguistic Diversity in the Age of Large Language Models
Zhivar Sourati, Farzan Karimi-Malekabadi, Meltem Ozcan +7
Language is far more than a communication tool; it encodes a wealth of information about a person's identity, psychological state, and social context, providing valuable insights f…
Mechanistic Interpretability of Emotion Inference in Large Language Models
Ala N. Tak, Amin Banayeeanzade, Anahita Bolourani +3
Large language models (LLMs) show promising capabilities in predicting human emotions from text. However, the mechanisms through which these models process emotional stimuli remain…
GPT-4 Emulates Average-Human Emotional Cognition from a Third-Person Perspective
Ala N. Tak, Jonathan Gratch
This paper extends recent investigations on the emotional reasoning abilities of Large Language Models (LLMs). Current research on LLMs has not directly evaluated the distinction b…