6 papers
Frame-Conditioned Moral Computation in LLaMA 3.1-8B-Instruct: A Mechanistic Interpretability Audit of Ethical Reasoning
Ali Dasdan, Manan Shah, W. Russell Neuman +3
Behavioral audits of Large Language Models on moral prompts measure what the model says, not the internal computation producing it. We use Transluce, an AI-driven mechanistic-inter…
MAATS: A Multi-Agent Automated Translation System Based on MQM Evaluation
George Wang, Jiaqian Hu, Safinah Ali
We present MAATS, a Multi Agent Automated Translation System that leverages the Multidimensional Quality Metrics (MQM) framework as a fine-grained signal for error detection and re…
"Amazing, They All Lean Left" -- Analyzing the Political Temperaments of Current LLMs
W. Russell Neuman, Chad Coleman, Ali Dasdan +3
Recent studies have revealed a consistent liberal orientation in the ethical and political responses generated by most commercial large language models (LLMs), yet the underlying c…
Evaluating the Impact of AI-Powered Audiovisual Personalization on Learner Emotion, Focus, and Learning Outcomes
George Xi Wang, Jingying Deng, Safinah Ali
Independent learners often struggle with sustaining focus and emotional regulation in unstructured or distracting settings. Although some rely on ambient aids such as music, ASMR,…
The Convergent Ethics of AI? Analyzing Moral Foundation Priorities in Large Language Models with a Multi-Framework Approach
Chad Coleman, W. Russell Neuman, Ali Dasdan +2
As large language models (LLMs) are increasingly deployed in consequential decision-making contexts, systematically assessing their ethical reasoning capabilities becomes a critica…
Auditing the Ethical Logic of Generative AI Models
W. Russell Neuman, Chad Coleman, Ali Dasdan +2
As generative AI models become increasingly integrated into high-stakes domains, the need for robust methods to evaluate their ethical reasoning becomes increasingly important. Thi…