9 citations · 25 across the 19 of their papers we have counts for
19 papers
TVGL-CFM:Generating and Forecasting Time-Varying Trajectories of Dynamic Networks with Conditional Flow Matching
Om Roy, Yashar Moshfeghi, Keith Malcolm Smith
Many complex systems, including brain networks, financial markets, and gene-regulatory circuits, are better described by interaction structures that evolve over time than by a sing…
POW: Political Overton Windows of Large Language Models
Leif Azzopardi, Yashar Moshfeghi
Political bias in Large Language Models (LLMs) presents a growing concern for the responsible deployment of AI systems. Traditional audits often attempt to locate a model's politic…
Covariance Density Neural Networks
Om Roy, Yashar Moshfeghi, Keith Smith
Graph neural networks have re-defined how we model and predict on network data but there lacks a consensus on choosing the correct underlying graph structure on which to model sign…
On Error Classification from Physiological Signals within Airborne Environment
Niall McGuire, Yashar Moshfeghi
Human error remains a critical concern in aviation safety, contributing to 70-80% of accidents despite technological advancements. While physiological measures show promise for err…
Brain-Machine Interfaces & Information Retrieval Challenges and Opportunities
Yashar Moshfeghi, Niall McGuire
The fundamental goal of Information Retrieval (IR) systems lies in their capacity to effectively satisfy human information needs - a challenge that encompasses not just the technic…
A Hodge-FAST Framework for High-Resolution Dynamic Functional Connectivity Analysis of Higher Order Interactions in EEG Signals
Om Roy, Yashar Moshfeghi, Jason Smith +3
We introduce a novel framework that integrates Hodge decomposition with Filtered Average Short-Term (FAST) functional connectivity to analyze dynamic functional connectivity (DFC)…
On Creating A Brain-To-Text Decoder
Zenon Lamprou, Yashar Moshfeghi
Brain decoding has emerged as a rapidly advancing and extensively utilized technique within neuroscience. This paper centers on the application of raw electroencephalogram (EEG) si…
Aligning Brain Activity with Advanced Transformer Models: Exploring the Role of Punctuation in Semantic Processing
Zenon Lamprou, Frank Polick, Yashar Moshfeghi
This research examines the congruence between neural activity and advanced transformer models, emphasizing the semantic significance of punctuation in text understanding. Utilizing…
Customizable LLM-Powered Chatbot for Behavioral Science Research
Zenon Lamprou, Yashar Moshfeghi
The rapid advancement of Artificial Intelligence has resulted in the advent of Large Language Models (LLMs) with the capacity to produce text that closely resembles human communica…
Towards Brain Passage Retrieval -- An Investigation of EEG Query Representations
Niall McGuire, Yashar Moshfeghi
Information Retrieval (IR) systems primarily rely on users' ability to translate their internal information needs into (text) queries. However, this translation process is often un…
PRISM: A Methodology for Auditing Biases in Large Language Models
Leif Azzopardi, Yashar Moshfeghi
Auditing Large Language Models (LLMs) to discover their biases and preferences is an emerging challenge in creating Responsible Artificial Intelligence (AI). While various methods…
On the Role of Activation Functions in EEG-To-Text Decoder
Zenon Lamprou, Iakovos Tenedios, Yashar Moshfeghi
In recent years, much interdisciplinary research has been conducted exploring potential use cases of neuroscience to advance the field of information retrieval. Initial research co…
Prediction of the Realisation of an Information Need: An EEG Study
Niall McGuire, Dr Yashar Moshfeghi
One of the foundational goals of Information Retrieval (IR) is to satisfy searchers' Information Needs (IN). Understanding how INs physically manifest has long been a complex and e…
GOLD: Geometry Problem Solver with Natural Language Description
Jiaxin Zhang, Yashar Moshfeghi
Addressing the challenge of automated geometry math problem-solving in artificial intelligence (AI) involves understanding multi-modal information and mathematics. Current methods…
FAST functional connectivity implicates P300 connectivity in working memory deficits in Alzheimer's disease
Om Roy, Yashar Moshfeghi, Agustin Ibanez +3
Measuring transient functional connectivity is an important challenge in Electroencephalogram (EEG) research. Here, the rich potential for insightful, discriminative information of…
GeoEval: Benchmark for Evaluating LLMs and Multi-Modal Models on Geometry Problem-Solving
Jiaxin Zhang, Zhongzhi Li, Mingliang Zhang +3
Recent advancements in large language models (LLMs) and multi-modal models (MMs) have demonstrated their remarkable capabilities in problem-solving. Yet, their proficiency in tackl…
GAPS: Geometry-Aware Problem Solver
Jiaxin Zhang, Yinghui Jiang, Yashar Moshfeghi
Geometry problem solving presents a formidable challenge within the NLP community. Existing approaches often rely on models designed for solving math word problems, neglecting the…
Why People Skip Music? On Predicting Music Skips using Deep Reinforcement Learning
Francesco Meggetto, Crawford Revie, John Levine +1
Music recommender systems are an integral part of our daily life. Recent research has seen a significant effort around black-box recommender based approaches such as Deep Reinforce…
ELASTIC: Numerical Reasoning with Adaptive Symbolic Compiler
Jiaxin Zhang, Yashar Moshfeghi
Numerical reasoning over text is a challenging task of Artificial Intelligence (AI), requiring reading comprehension and numerical reasoning abilities. Previous approaches use nume…