Why Do Language Models Hallucinate?
An analysis of why language models hallucinate — hallucinations arise from statistical pressures in training and evaluation procedures that reward guessing over acknowledging …
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5 min read
Why Entropy Matters in Machine Learning?
Understanding entropy and why it's a core concept in decision trees, neural networks, and loss functions like cross-entropy.
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3 min read
Understanding FlashAttention: Inner vs Outer Loop Optimization
FlashAttention is a groundbreaking optimization technique for computing attention in Transformer models, drastically improving GPU memory efficiency through inner vs outer loop …
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1 min read
Adversarial Attacks on Large Language Models (LLMs)
An overview of adversarial attacks on large language models (LLMs) — how manipulated inputs can deceive models into generating harmful or incorrect outputs, covering key attack …
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3 min read
GLiNER: A Generalist Model for Named Entity Recognition using Bidirectional Transformers
A detailed summary of the GLiNER paper, introducing a lightweight, scalable, and highly effective model for open-type named entity recognition using bidirectional transformers with …
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3 min read
Comparing batch vs layer normalization
The purpose of this post is just to understand the key difference between two types of well-known normalization techniques.
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