3 citations · 12 across the 14 of their papers we have counts for
14 papers
Contrastive Similarity Learning for Market Forecasting: The ContraSim Framework
Nicholas Vinden, Raeid Saqur, Zining Zhu +1
We introduce the Contrastive Similarity Space Embedding Algorithm (ContraSim), a novel framework for uncovering the global semantic relationships between daily financial headlines…
What Teaches Robots to Walk, Teaches Them to Trade too -- Regime Adaptive Execution using Informed Data and LLMs
Raeid Saqur
Machine learning techniques applied to the problem of financial market forecasting struggle with dynamic regime switching, or underlying correlation and covariance shifts in true (…
Filtered not Mixed: Stochastic Filtering-Based Online Gating for Mixture of Large Language Models
Raeid Saqur, Anastasis Kratsios, Florian Krach +5
We propose MoE-F - a formalized mechanism for combining pre-trained Large Language Models (LLMs) for online time-series prediction by adaptively forecasting the best weighting…
NIFTY Financial News Headlines Dataset
Raeid Saqur, Ken Kato, Nicholas Vinden +1
We introduce and make publicly available the NIFTY Financial News Headlines dataset, designed to facilitate and advance research in financial market forecasting using large languag…
L(u)PIN: LLM-based Political Ideology Nowcasting
Ken Kato, Annabelle Purnomo, Christopher Cochrane +1
The quantitative analysis of political ideological positions is a difficult task. In the past, various literature focused on parliamentary voting data of politicians, party manifes…
Higher-Order Transformer Derivative Estimates for Explicit Pathwise Learning Guarantees
Yannick Limmer, Anastasis Kratsios, Xuwei Yang +2
An inherent challenge in computing fully-explicit generalization bounds for transformers involves obtaining covering number estimates for the given transformer class . Crude est…
Large Language Models are Fixated by Red Herrings: Exploring Creative Problem Solving and Einstellung Effect using the Only Connect Wall Dataset
Saeid Naeini, Raeid Saqur, Mozhgan Saeidi +2
The quest for human imitative AI has been an enduring topic in AI research since its inception. The technical evolution and emerging capabilities of the latest cohort of large lang…
Reward Learning using Structural Motifs in Inverse Reinforcement Learning
Raeid Saqur
The Inverse Reinforcement Learning (\textit{IRL}) problem has seen rapid evolution in the past few years, with important applications in domains like robotics, cognition, and healt…
CLEVR Parser: A Graph Parser Library for Geometric Learning on Language Grounded Image Scenes
Raeid Saqur, Ameet Deshpande
The CLEVR dataset has been used extensively in language grounded visual reasoning in Machine Learning (ML) and Natural Language Processing (NLP) domains. We present a graph parser…
Ethics of Artificial Intelligence in Surgery
Frank Rudzicz, Raeid Saqur
Here we discuss the four key principles of bio-medical ethics from surgical context. We elaborate on the definition of 'fairness' and its implications in AI system design, with tax…
CapsGAN: Using Dynamic Routing for Generative Adversarial Networks
Raeid Saqur, Sal Vivona
In this paper, we propose a novel technique for generating images in the 3D domain from images with high degree of geometrical transformations. By coalescing two popular concurrent…
ReGAN: RE[LAX|BAR|INFORCE] based Sequence Generation using GANs
Aparna Balagopalan, Satya Gorti, Mathieu Ravaut +1
Generative Adversarial Networks (GANs) have seen steep ascension to the peak of ML research zeitgeist in recent years. Mostly catalyzed by its success in the domain of image genera…
PrivySense: ce olatilit based timent stimation from Financial News using Machine Learning
Raeid Saqur, Nicole Langballe
As machine learning ascends the peak of computer science zeitgeist, the usage and experimentation with sentiment analysis using various forms of textual data seems pervasive. The e…
H4-Writer: A Text Entry Method Designed For Gaze Controlled Environment with Low KSPC and Spatial Footprint
Raeid Saqur
This paper presents a new text entry technique, namely H4-Writer, designed for gaze controlled environments and aimed at reducing average KSPC . and spatial footprint. It also pres…