7 citations · 12 across the 13 of their papers we have counts for
16 papers
Reputation, Strategy, and Emotion Effects on Generative AI Cooperation: A Comparison Across Reasoning and Non-Reasoning Models
Celso de Melo, Zishan Feng, James Hale +3
As generative AI (Gen AI) systems take on increasingly autonomous roles in economically and socially consequential interactions, understanding their propensity to cooperate -- and…
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…
Personality Expression Across Contexts: Linguistic and Behavioral Variation in LLM Agents
Bin Han, Deuksin Kwon, Jonathan Gratch
Large Language Models (LLMs) can be conditioned with explicit personality prompts, yet their behavioral realization often varies depending on context. This study examines how ident…
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…
Can LLMs Generate Behaviors for Embodied Virtual Agents Based on Personality Traits?
Bin Han, Deuksin Kwon, Spencer Lin +2
This study proposes a framework that employs personality prompting with Large Language Models to generate verbal and nonverbal behaviors for virtual agents based on personality tra…
Salience Adjustment for Context-Based Emotion Recognition
Bin Han, Jonathan Gratch
Emotion recognition in dynamic social contexts requires an understanding of the complex interaction between facial expressions and situational cues. This paper presents a salience-…
ASTRA: A Negotiation Agent with Adaptive and Strategic Reasoning via Tool-integrated Action for Dynamic Offer Optimization
Deuksin Kwon, Jiwon Hae, Emma Clift +3
Negotiation requires dynamically balancing self-interest and cooperation within the flow of conversation to maximize one's own utility. Yet, existing agents struggle due to bounded…
Exploring Emotion-Sensitive LLM-Based Conversational AI
Antonin Brun, Ruying Liu, Aryan Shukla +2
Conversational AI chatbots have become increasingly common within the customer service industry. Despite improvements in their emotional development, they often lack the authentici…
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…
Knowledge-based Emotion Recognition using Large Language Models
Bin Han, Cleo Yau, Su Lei +1
Emotion recognition in social situations is a complex task that requires integrating information from both facial expressions and the situational context. While traditional approac…
In-Depth Analysis of Emotion Recognition through Knowledge-Based Large Language Models
Bin Han, Cleo Yau, Su Lei +1
Emotion recognition in social situations is a complex task that requires integrating information from both facial expressions and the situational context. While traditional approac…
Are LLMs Effective Negotiators? Systematic Evaluation of the Multifaceted Capabilities of LLMs in Negotiation Dialogues
Deuksin Kwon, Emily Weiss, Tara Kulshrestha +3
A successful negotiation requires a range of capabilities, including comprehension of the conversation context, Theory-of-Mind (ToM) skills to infer the partner's motives, strategi…
Context Unlocks Emotions: Text-based Emotion Classification Dataset Auditing with Large Language Models
Daniel Yang, Aditya Kommineni, Mohammad Alshehri +4
The lack of contextual information in text data can make the annotation process of text-based emotion classification datasets challenging. As a result, such datasets often contain…
Can Language Model Moderators Improve the Health of Online Discourse?
Hyundong Cho, Shuai Liu, Taiwei Shi +8
Conversational moderation of online communities is crucial to maintaining civility for a constructive environment, but it is challenging to scale and harmful to moderators. The inc…