Evaluating Transformer Models for Suicide Risk Detection on Social Media

arXiv:2410.08375 · cs.CL · Submitted 2024-10-10 · Read on arXiv

cs.CL

Submitted: 2024-10-10

Updated: 2024-10-10

Project page: https://competitionpolyu.github.io/report.html

Terminology

• Transformer — 22× in this paper · explained in 2 episodes
• Fine-Tuning — 10× in this paper · explained in 5 episodes
• Accuracy — 8× in this paper · explained in 1 episode
• Transformer Models — 5× in this paper · explained in 2 episodes
• Benchmark — 4× in this paper · explained in 2 episodes
• Natural Language Processing — 4× in this paper
• In-Context Learning — 3× in this paper · explained in 4 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Chain of Thought — 2× in this paper
• Core — 2× in this paper · explained in 2 episodes
• Few-Shot Learning — 2× in this paper · explained in 4 episodes
• Artificial Intelligence — 1× in this paper
• Artificial Intelligence (AI) — 1× in this paper · explained in 2 episodes
• Attention Mechanism — 1× in this paper · explained in 2 episodes
• Chain-of-Thought Prompting — 1× in this paper · explained in 2 episodes
• Contextual Understanding — 1× in this paper · explained in 2 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Ensemble Learning — 1× in this paper · explained in 2 episodes
• Explainability — 1× in this paper · explained in 3 episodes
• F1 Score — 1× in this paper · explained in 3 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Large Language Model — 1× in this paper
• Long Short-Term Memory — 1× in this paper
• Loss Function — 1× in this paper · explained in 2 episodes
• Prompt Engineering — 1× in this paper · explained in 4 episodes
• Pseudo-labeling — 1× in this paper · explained in 3 episodes
• Pseudo-labels — 1× in this paper · explained in 2 episodes
• Synthetic Data Generation — 1× in this paper · explained in 5 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• DeBERTa: Decoding-enhanced BERT with Disentangled Attention
• Language Models are Few-Shot Learners
• A Quantitative and Qualitative Analysis of Suicide Ideation Detection using Deep Learning
• RoBERTa: A Robustly Optimized BERT Pretraining Approach
• Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations

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