Generative AI Weekly Research Highlights | Feb'24 Part 3

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Summary of Research Papers:

1. LARGE LANGUAGE MODELS FOR FORECASTING AND ANOMALY DETECTION: A SYSTEMATIC LITERATURE REVIEW [https://arxiv.org/pdf/2402.10350.pdf]

2. A Survey of Table Reasoning with Large Language Models [https://arxiv.org/pdf/2402.08259.pdf]

3. LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models [https://arxiv.org/pdf/2402.10524.pdf]

4. AbuseGPT: Abuse of Generative AI ChatBots to Create Smishing Campaigns [https://arxiv.org/pdf/2402.09728.pdf]

5. Rationality Report Cards: Assessing the Economic Rationality of Large Language Models [https://arxiv.org/pdf/2402.09552.pdf]

6. Developing a Framework for Auditing Large Language Models Using Human-in-the-Loop [https://arxiv.org/pdf/2402.09346.pdf]

7. (Ir)rationality and Cognitive Biases in Large Language Models [https://arxiv.org/pdf/2402.09193.pdf]

8. SKIP \N: A SIMPLE METHOD TO REDUCE HALLUCINATION IN LARGE VISION-LANGUAGE MODELS [https://arxiv.org/pdf/2402.01345.pdf]

00:00 Intro

00:19 Forecasting Future with LLMs

00:53 LLMs Simplifying Table Data

01:18 Comparing LLMs: A Visual Guide

01:43 Preventing AI Misuse in Cybersecurity

02:05 LLMs Making Economic Decisions

02:25 Auditing LLMs: Bias and Beyond

02:45 Understanding LLMs' Rationality

03:06 Tackling Hallucinations in AI Models

03:32 End

#generativeai,#promptengineering,#largelanguagemodels,#openai,#chatgpt,#gpt4,#ai,#abcp,#prompt,#responsibleai