most citedInterpreting LLMs as Credit Risk Classifiers: Do Their Feature Explanations Align with Classical ML?

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cs.LG2025

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…

cs.LG2025

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…