lookahead

Lookahead Decoding breaks sequential dependency in autoregressive decoding using Jacobi iteration, achieving 1.5-2.3× speedup without draft models or training.

Skills
AI research
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What it does and how to use it

A skill that teaches Claude Code to do ai research tasks well. It is packaged knowledge the model uses whenever it is relevant.

Install the skill (command above).
In Claude Code, describe what you need - the skill turns on by itself when the context fits.
No commands to memorize: you talk in plain language and the skill does the rest.

Install (Claude Code)

mkdir -p .claude/skills/lookahead && curl -fsSL https://doutorai.pt/data/lib/skills__lookahead.md -o .claude/skills/lookahead/SKILL.md

Paste this command into the terminal, in your project folder, and the component installs automatically.

Content

# Lookahead Decoding: Jacobi Iteration

Based on ICML 2024 paper and LMSYS blog post

## Overview

**Source**: https://lmsys.org/blog/2023-11-21-lookahead-decoding/
**Paper**: ICML 2024
**GitHub**: https://github.com/hao-ai-lab/LookaheadDecoding

Lookahead Decoding breaks sequential dependency in autoregressive decoding using Jacobi iteration, achieving 1.5-2.3× speedup without draft models or training.

## Core Concept

### Reformulation as Equation Solving

**Traditional autoregressive**:
```
y_t = f(x, y_1, y_2, ..., y_{t-1})  # Sequential
```

**Jacobi iteration**:
```
y_t^{(k+1)} = f(x, y

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