4 citations · 7 across the 11 of their papers we have counts for
12 papers
From Prompting to Behavioral Alignment: Personalized LLM Judges for Recommendation Evaluation
Alireza S. Ziabari, Kat Ellis, Colleen Chan +1
Traditional offline recommendation evaluation relies heavily on complex, manually maintained feature pipelines that are difficult to scale. While Large Language Models (LLMs) offer…
The Subjectivity of Respect in Police Traffic Stops: Modeling Community Perspectives in Body-Worn Camera Footage
Preni Golazizian, Elnaz Rahmati, Jackson Trager +17
Traffic stops are among the most frequent police-civilian interactions, and body-worn cameras (BWCs) provide a unique record of how these encounters unfold. Respect is a central di…
Flip-Flop Consistency: Unsupervised Training for Robustness to Prompt Perturbations in LLMs
Parsa Hejabi, Elnaz Rahmati, Alireza S. Ziabari +1
Large Language Models (LLMs) often produce inconsistent answers when faced with different phrasings of the same prompt. In this paper, we propose Flip-Flop Consistency (), an…
The Homogenizing Effect of Large Language Models on Human Expression and Thought
Zhivar Sourati, Alireza S. Ziabari, Morteza Dehghani
Cognitive diversity, reflected in variations of language, perspective, and reasoning, is essential to creativity and collective intelligence. This diversity is rich and grounded in…
CoCo-CoLa: Evaluating and Improving Language Adherence in Multilingual LLMs
Elnaz Rahmati, Alireza S. Ziabari, Morteza Dehghani
Multilingual Large Language Models (LLMs) develop cross-lingual abilities despite being trained on limited parallel data. However, they often struggle to generate responses in the…
Reasoning on a Spectrum: Aligning LLMs to System 1 and System 2 Thinking
Alireza S. Ziabari, Nona Ghazizadeh, Zhivar Sourati +3
Large Language Models (LLMs) exhibit impressive reasoning abilities, yet their reliance on structured step-by-step processing reveals a critical limitation. In contrast, human cogn…
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…
Evaluating Creativity and Deception in Large Language Models: A Simulation Framework for Multi-Agent Balderdash
Parsa Hejabi, Elnaz Rahmati, Alireza S. Ziabari +3
Large Language Models (LLMs) have shown impressive capabilities in complex tasks and interactive environments, yet their creativity remains underexplored. This paper introduces a s…
Secret Keepers: The Impact of LLMs on Linguistic Markers of Personal Traits
Zhivar Sourati, Meltem Ozcan, Colin McDaniel +5
Prior research has established associations between individuals' language usage and their personal traits; our linguistic patterns reveal information about our personalities, emoti…
Cost-Efficient Subjective Task Annotation and Modeling through Few-Shot Annotator Adaptation
Preni Golazizian, Alireza S. Ziabari, Ali Omrani +1
In subjective NLP tasks, where a single ground truth does not exist, the inclusion of diverse annotators becomes crucial as their unique perspectives significantly influence the an…
Towards a Unified Framework for Adaptable Problematic Content Detection via Continual Learning
Ali Omrani, Alireza S. Ziabari, Preni Golazizian +2
Detecting problematic content, such as hate speech, is a multifaceted and ever-changing task, influenced by social dynamics, user populations, diversity of sources, and evolving la…
The Moral Foundations Reddit Corpus
Jackson Trager, Alireza S. Ziabari, Elnaz Rahmati +15
Moral framing and sentiment can affect a variety of online and offline behaviors, including donation, environmental action, political engagement, and protest. Various computational…