6 papers
Structural Abstraction as an Inductive Bias for Non-Stationary Language Model Training
Elnaz Rahmati, Nona Ghazizadeh, Zhivar Sourati +2
A foundational principle in cognitive science holds that intelligent agents do not learn by storing experiences as isolated instances, but by forming abstract schemas that capture…
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…
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…
naab: A ready-to-use plug-and-play corpus for Farsi
Sadra Sabouri, Elnaz Rahmati, Soroush Gooran +1
The rise of large language models (LLMs) has transformed numerous natural language processing (NLP) tasks, yet their performance in low and mid-resource languages, such as Farsi, s…
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…