Yuting Guo

Check out our RAG-based study on medial queries in @jmirpub🎉jmir.org/2025/1/e66220 In Collab w/ @sarkerabeed @YutingGuo12 @jhairstonphd @jeannempowell @DrewWalkerr @SahithiLakamana @selenbzkt @RezaSameni @YunyuXiaoPhD @SangmiKimPhD @techsexed @JLoveMD @TSpadaro91 @JMPerroneMD

Compare 36+ Vector Databases on features, performance and price ⚖️

Exciting News! Presenting our latest work: "Aspect-level Sentiment Analysis Dataset for Therapies on Twitter" 🌐🔄 Unlock insights into public sentiment surrounding therapies. Download now: sciencedirect.com/science/articl… #Research #SentimentAnalysis 🚀

In addition to prompting LLMs, many developers are now also experimenting with fine-tuning. I describe in The Batch how to choose from the growing menu of options for building applications with LLMs: Prompting, few-shot, fine-tuning, pre-training. deeplearning.ai/the-batch/issu…

We just released "Large Language Models with Semantic Search”, built with @cohere, and taught by @JayAlammar and @SerranoAcademy. Search is a key part of many applications. Say, you need to retrieve documents or products in response to a user query; how can LLMs help? You’ll learn about (i) Embeddings, to retrieve a collection of documents loosely related to a query, and (ii) LLM assisted re-ranking, to rank them precisely according to relevance. You’ll also go through code showing how to tie all this together to build a complete search system for retrieving relevant Wikipedia articles. Please check it out! deeplearning.ai/short-courses/…

A very unique textbook "Information theory, inference and learning algorithms" by Sir MacKay combining Information Theory with Machine Learning. Nicely written! Book PDF freely available at: 👉inference.org.uk/itila/book.html

A cheat sheet explanation of how Large Language Models work:

How to Extract Text from Any PDF and Image for Large Language Model by @zoumana_keita_ buff.ly/3Y4H1XL

I needed this animation when I started learning PyTorch. If you are just starting your PyTorch journey, bookmark this:

If you are interested in reviewing research on alignment for LLMs, look no further. This new survey paper covers different aspects of alignment research such as data collection, training methodologies, and model evaluation. Aligning LLMs with human expectations is an active area of research but is already responsible for some of the most advanced LLMs we have today. This paper sheds light on this area of research, tactics, and insights, including challenges and future directions. It's an impressive resource for researchers and practitioners. There is also a nice GitHub repo along with the paper. paper: arxiv.org/abs/2307.12966 repo: github.com/GaryYufei/Alig…

Twitter's new API pricing (and related mess) is causing so much headache for us! If you are an academic researcher working with Twitter data, how are you dealing with the changes? #AcademicTwitter

Excited and grateful to have my recent publication acknowledged by my advisor @sarkerabeed! Thank you for your support and guidance throughout this research journey.

New paper alert (on @JAHA_AHA): "Text Classification System Detects Fontan Patients in Electronic Records With Higher Accuracy Than ICD Codes" | Journal of the American Heart Association ... (congrats @YutingGuo12) ahajournals.org/doi/10.1161/JA…

Great presentation by @jeannempowell at the #aime2023 session on NLP. @emorybmi

New paper out. My student @jeannempowell will be presenting this work at AIME "Classification of Fall Types in Parkinson's Disease from Self-report Data Using Natural Language Processing" link.springer.com/chapter/10.100…

I’m honored to have been selected as a Student Travel Award recipient to present my work on fall classification using NLP at the 21st International Conference on Artificial Intelligence in Medicine! Thank you to coauthors @YutingGuo12, @sarkerabeed, and @JLucasMcKay!!

Explore the world of social media NLP with #SocBERT - our pretrained model designed for analyzing social media text. Discover new insights and boost performance. Check out our latest paper to learn more! #NLP #LLM paper: aclanthology.org/2023.insights-… model: huggingface.co/sarkerlab/SocB…

Very nice course!

“Transformers from scratch” by Brandon Rohrer 🤖 This is one of the best write ups, that starts from 0 and explains every single detail of the model architecture. Even if you need a refresher or don’t, I would still highly recommend reading it: e2eml.school/transformers.h…