Generative AI Weekly Research Highlights | Nov'23 Part 1

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To summarize, here are the research papers and their respective links:

"A Comprehensive Overview of Large Language Models" [https://arxiv.org/pdf/2307.06435.pdf]

"Evaluating Large Language Models: A Comprehensive Survey" [https://arxiv.org/pdf/2310.19736.pdf]

"YaRN: Efficient Context Window Extension of Large Language Models" [https://arxiv.org/pdf/2309.00071.pdf]

"A Survey of Large Language Models for Autonomous Driving" [https://arxiv.org/pdf/2311.01043.pdf]

"SheetCopilot: Bringing Software Productivity to the Next Level through Large Language Models" [https://arxiv.org/pdf/2305.19308.pdf]

"OpenAssistant Conversations - Democratizing Large Language Model Alignment" [https://arxiv.org/pdf/2304.07327.pdf]

"VisPercep: A Vision-Language Approach to Enhance Visual Perception for People with Blindness and Low Vision" [https://arxiv.org/pdf/2310.20225.pdf]

"iTutor: A Generative Tutorial System for Teaching the Elders to Use Smartphone Applications" [https://dl.acm.org/doi/pdf/10.1145/35...]

00:00 Intro

00:19 Advancements in LLMs

00:43 Evaluating LLMs

01:05 YARN: Extending Context in LLMs

01:26 LLMs in Autonomous Driving

01:48 Sheet Co-Pilot: Natural Language for Spreadsheets

02:10 Democratizing LLMs with Open Assistant Conversations

02:28 VisPercept: Vision Language Models for the Visually Impaired

02:47 iTutor: Generative AI for Elderly Learning

03:15 End

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