6 papers
Measuring What LLMs Think They Do: SHAP Faithfulness and Deployability on Financial Tabular Classification
Saeed AlMarri, Mathieu Ravaut, Kristof Juhasz +3
Large Language Models (LLMs) have attracted significant attention for classification tasks, offering a flexible alternative to trusted classical machine learning models like LightG…
Interpreting LLMs as Credit Risk Classifiers: Do Their Feature Explanations Align with Classical ML?
Saeed AlMarri, Kristof Juhasz, Mathieu Ravaut +3
Large Language Models (LLMs) are increasingly explored as flexible alternatives to classical machine learning models for classification tasks through zero-shot prompting. However,…
Network Contagion in Financial Labor Markets: Predicting Turnover in Hong Kong
Abdulla AlKetbi, Patrick Yam, Gautier Marti +1
Employee turnover is a critical challenge in financial markets, yet little is known about the role of professional networks in shaping career moves. Using the Hong Kong Securities…
Residual Speech Embeddings for Tone Classification: Removing Linguistic Content to Enhance Paralinguistic Analysis
Hamdan Al Ahbabi, Gautier Marti, Saeed AlMarri +1
Self-supervised learning models for speech processing, such as wav2vec2, HuBERT, WavLM, and Whisper, generate embeddings that capture both linguistic and paralinguistic information…
Mapping Hong Kong's Financial Ecosystem: A Network Analysis of the SFC's Licensed Professionals and Institutions
Abdulla AlKetbi, Gautier Marti, Khaled AlNuaimi +2
We present the first study of the Public Register of Licensed Persons and Registered Institutions maintained by the Hong Kong Securities and Futures Commission (SFC) through the le…
Enriching Datasets with Demographics through Large Language Models: What's in a Name?
Khaled AlNuaimi, Gautier Marti, Mathieu Ravaut +3
Enriching datasets with demographic information, such as gender, race, and age from names, is a critical task in fields like healthcare, public policy, and social sciences. Such de…