IEEE

Improving Arabic Multi-Label Emotion Classification using Stacked Embeddings and Hybrid Loss Function

Abstract: Multi-label emotion classification (MLEC) for low-resource languages like Arabic faces significant challenges due to class imbalance and label correlations, particularly in accurately ...
GitHub

GitHub - anthropics/claude-code-action

A general-purpose Claude Code action for GitHub PRs and issues that can answer questions and implement code changes. This action intelligently detects when to activate based on your workflow ...
IEEE

Framework for Emotion Recognition Using Cross-Modal Transformers With Non-Contact Multimodal Signals Aiming Clinical Service Support

In clinical communication, it is believed that accurately understanding and appropriately responding to patients’ emotions contributes to treatment effectiveness and patient satisfaction. Recently, ...
marktechpost

A Coding Implementation to Establish Rigorous Prompt Versioning and Regression Testing Workflows for Large Language Models using MLflow

In this tutorial, we show how we treat prompts as first-class, versioned artifacts and apply rigorous regression testing to large language model behavior using MLflow. We design an evaluation pipeline ...