Generative AI Weekly Research Highlights | Feb'24 Part 1

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Research Paper Summaries and Links:

1. Efficient Large Language Models: A Survey [https://browse.arxiv.org/pdf/2312.038...]

2. TIME-LLM: Time Series Forecasting by Reprogramming Large Language Models [https://browse.arxiv.org/pdf/2310.017...]

3. A Survey on Hallucination in Large Vision-Language Models [https://browse.arxiv.org/pdf/2402.002...]

4. Safety of Multimodal Large Language Models on Images and Text [https://browse.arxiv.org/pdf/2402.003...]

5. Enhancing Ethical Explanations of Large Language Models through Iterative Symbolic Refinement [https://browse.arxiv.org/pdf/2402.007...]

6. Red-Teaming for Generative AI: Silver Bullet or Security Theater? [https://browse.arxiv.org/pdf/2401.158...]

7. What Does the Bot Say? Opportunities and Risks of Large Language Models in Social Media Bot Detection [https://browse.arxiv.org/pdf/2402.003...]

8. Foregrounding Artist Opinions: A Survey Study on Transparency, Ownership, and Fairness in AI Generative Art [https://browse.arxiv.org/pdf/2401.154...]

00:00 Intro

00:20 Making LLMs More Efficient

00:46 Time Series with LLMs

01:14 Overcoming Hallucinations in LVMS

01:40 Safeguarding Multimodal AI

02:03 Ethical AI: Beyond Logic

02:29 AI Security: Red Teaming Revisited

02:52 LLMs and Social Media Bots

03:12 Generative AI Meets Art

03:43 End

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