Generative AI Weekly Research Highlights | Apr'24 Part 1

Research Paper Summaries and Links:

Green AI: Exploring Carbon Footprints, Mitigation Strategies, and Trade Offs in Large Language Model Training [https://arxiv.org/pdf/2404.01157.pdf]

Evalverse: Unified and Accessible Library for Large Language Model Evaluation [https://arxiv.org/pdf/2404.00943.pdf]

The Butterfly Effect of Altering Prompts: How Small Changes and Jailbreaks Affect Large Language Model Performance [https://arxiv.org/pdf/2401.03729.pdf]

Unleashing the Potential of Large Language Models for Predictive Tabular Tasks in Data Science [https://arxiv.org/pdf/2403.20208.pdf]

How Interpretable are Reasoning Explanations from Prompting Large Language Models? [https://arxiv.org/pdf/2402.11863.pdf]

Confronting LLMs with Traditional ML: Rethinking the Fairness of Large Language Models in Tabular Classifications [https://arxiv.org/pdf/2310.14607.pdf]

AI Act and Large Language Models (LLMs): When critical issues and privacy impact require human and ethical oversight. [https://arxiv.org/pdf/2404.00600.pdf]

Developing Safe and Responsible Large Language Models - A Comprehensive Framework [https://arxiv.org/pdf/2404.01399.pdf]

Disclaimer: The content in this video is AI-generated and adheres to YouTube's guidelines. Each video undergoes manual review and curation before publishing to ensure accuracy and quality.

00:00 Intro

00:19 How AI Impacts the Environment

00:45 How to Evaluate LLMs Easily

01:03 Small Changes, Big LLM Differences

01:27 LLMs Meet Table Data

01:52 Making AI Explanations Clearer

02:12 Fairness in AI: A Closer Look

02:33 LLMs and Privacy Concerns

02:55 Building Safer AI Models

03:14 End