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Automatic Prompt Optimization

Practical techniques for improving prompt quality without manual effort...
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Decoder-Only Transformers: The Workhorse of Generative LLMs
 • Cameron R. Wolfe, Ph.D.
14
Easily Train a Specialized LLM: PEFT, LoRA, QLoRA, LLaMA-Adapter, and More
14
Understanding and Using Supervised Fine-Tuning (SFT) for Language Models
 • Cameron R. Wolfe, Ph.D.
4
Modern Advances in Prompt Engineering
 • Cameron R. Wolfe, Ph.D.
7
Model Merging: A Survey
From modern LLM applications to the early days of machine learning research...
 • 
Cameron R. Wolfe, Ph.D.
8
Using LLMs for Evaluation
LLM-as-a-Judge and other scalable additions to human quality ratings...
 • 
Cameron R. Wolfe, Ph.D.
14
Summarization and the Evolution of LLMs
How research on abstractive summarization changed language models forever...
 • 
Cameron R. Wolfe, Ph.D.
3
Modern Advances in Prompt Engineering
Distilling and understanding the most rapidly-evolving research topic in AI...
 • 
Cameron R. Wolfe, Ph.D.
7
DBRX, Continual Pretraining, RewardBench, Faster Inference, and More
A deep dive into recent and impactful advancements in LLM research...
 • 
Cameron R. Wolfe, Ph.D.
6
Mixture-of-Experts (MoE): The Birth and Rise of Conditional Computation
What two decades of research taught us about sparse language models...
 • 
Cameron R. Wolfe, Ph.D.
16
Decoder-Only Transformers: The Workhorse of Generative LLMs
Building the world's most influential neural network architecture from scratch...
 • 
Cameron R. Wolfe, Ph.D.
14
Deep (Learning) Focus
Deep (Learning) Focus
I contextualize and explain important topics in AI research.
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