GPT Is an Unreliable Information Store
Understanding the limitations and dangers of large language models- 20557Murphy ≡ DeepGuide
Can We Stop LLMs from Hallucinating?
One of the greatest barriers to widespread LLM adoption may be inherently unsolvable.- 26123Murphy ≡ DeepGuide
How to Perform Hallucination Detection for LLMs
Hallucination metrics for open-domain and closed-domain question answering- 20620Murphy ≡ DeepGuide
Fact-checking vs claim verification
Why hallucination detection task is wrongly named- 27028Murphy ≡ DeepGuide
Language as a Universal Learning Machine
Saying is believing. Seeing is hallucinating.- 28071Murphy ≡ DeepGuide
How LLMs Work: Pre-Training to Post-Training, Neural Networks, Hallucinations, and Inference
With the recent explosion of interest in large language models (LLMs), they often seem almost magical. But let’s demystify them. I wanted to step back and unpack the fundamentals — breaking down how LLMs are built, trained, and fine-tuned to become the AI- 26977Murphy ≡ DeepGuide
LettuceDetect: A Hallucination Detection Framework for RAG Applications
How to capitalize on ModernBERT’s extended context window to build a token-level classifier for hallucination detection- 21276Murphy ≡ DeepGuide
We look at an implementation of the HyperLogLog cardinality estimati
Using clustering algorithms such as K-means is one of the most popul
Level up Your Data Game by Mastering These 4 Skills
Learn how to create an object-oriented approach to compare and evalu
When I was a beginner using Kubernetes, my main concern was getting
Tutorial and theory on how to carry out forecasts with moving averag