Decomposing LLM Judge Scores Into Yes/No Questions
An LLM-judge approach that brings interpretability and actionability to your scores.
Notes tagged LargeLanguageModels
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LLM Training Pipeline
The two steps to training modern LLMs.
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LLM Reasoning
How LLMs use intermediate reasoning tokens, from chain-of-thought prompting to trained reasoning models, and how this relates to other forms of reasoning.
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Optimising Computation At The Token-Level
Optimising computation at the token-level
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Learning to Reason without External Rewards
aka Self-Confidence is All You Need
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Vibe-Coding Mathematical Discoveries
Using evolutionary algorithms with LLM-coding agents
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Absolute Zero: Reinforced Self-play Reasoning with Zero Data
learn to reason without any human-annotated data.
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Temperature Scaling
a parameter that controls how confident Softmax predictions are
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Few-Shot Knowledge-Distillation
Routes LLM tasks to cheaper or more powerful models based on task novelty.
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Large Language Models are Zero-Shot Reasoners (May 2022)
improve zero-shot prompt performance of LLMs by adding “Let’s think step by step” before each answer