Generative AI Weekly Research Highlights | Oct'23 Part 4

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To summarize, here are the links and names of the research papers discussed:

H2O Open Ecosystem for State-of-the-art Large Language Models [https://arxiv.org/pdf/2310.13012.pdf]

DETECTING PRETRAINING DATA FROM LARGE LANGUAGE MODELS [https://arxiv.org/pdf/2310.16789.pdf]

MindLLM: Pre-training Lightweight Large Language Model from Scratch, Evaluations and Domain Applications [https://arxiv.org/pdf/2310.15777.pdf]

Towards Possibilities & Impossibilities of AI-generated Text Detection: A Survey [https://arxiv.org/pdf/2310.15264.pdf]

MusicAgent: An AI Agent for Music Understanding and Generation with Large Language Models [https://arxiv.org/pdf/2310.11954.pdf]

INVESTIGATING THE FAIRNESS OF LARGE LANGUAGE MODELS FOR PREDICTIONS ON TABULAR DATA [https://arxiv.org/pdf/2310.14607.pdf]

CLINFO.AI: AN OPEN-SOURCE RETRIEVAL-AUGMENTED LARGE LANGUAGE MODEL SYSTEM FOR ANSWERING MEDICAL QUESTIONS USING SCIENTIFIC LITERATURE [https://arxiv.org/pdf/2310.16146.pdf]

Counter Turing Test (CT2): AI-Generated Text Detection is Not as Easy as You May Think – Introducing AI Detectability Index [https://arxiv.org/pdf/2310.05030.pdf]

00:00 Intro

00:19 H2O: Open AI Ecosystem

00:40 Pre-training Data Detection Method

00:58 Bilingual Lightweight LLMs

01:14 AI-Generated Text Detection Survey

01:29 AI-Powered Music Processing System

01:44 Fairness in LLM Predictions

01:58 Open-Source Clinical QA Web App

02:13 AI Detectability Index

02:35 End

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