2 citations · 2 across the 6 of their papers we have counts for
7 papers
Cognitive Expert Language Models Better Align with the Corresponding Brain Systems
Zhivar Sourati, Mengxuan Helen Wu, Nona Ghazizadeh +3
Large language models (LLMs) can predict human brain activity across a variety of brain regions during natural language comprehension. Typically, however, LLM-brain alignment is me…
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…
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…
AIMA at SemEval-2024 Task 3: Simple Yet Powerful Emotion Cause Pair Analysis
Alireza Ghahramani Kure, Mahshid Dehghani, Mohammad Mahdi Abootorabi +3
The SemEval-2024 Task 3 presents two subtasks focusing on emotion-cause pair extraction within conversational contexts. Subtask 1 revolves around the extraction of textual emotion-…
AIMA at SemEval-2024 Task 10: History-Based Emotion Recognition in Hindi-English Code-Mixed Conversations
Mohammad Mahdi Abootorabi, Nona Ghazizadeh, Seyed Arshan Dalili +3
In this study, we introduce a solution to the SemEval 2024 Task 10 on subtask 1, dedicated to Emotion Recognition in Conversation (ERC) in code-mixed Hindi-English conversations. E…
HDNA: A graph-based change detection in HTML pages(Deface Attack Detection)
Mahdi Akhi, Nona Ghazizadeh
In this paper, a new approach called HDNA (HTML DNA) is introduced for analyzing and comparing Document Object Model (DOM) trees in order to detect differences in HTML pages. This…