knowledge base

Hackathon knowledge base

Working notes for the Lexsi Labs AI Safety & Alignment Hackathon, with Cohere and Hugging Face, November 2026. Each page builds one method from its smallest parts, with fixed definitions and small worked numbers.

What this is for: reading machine-learning papers about large language models (LLMs) is easier when every term has one fixed meaning. Every underlined term links to the glossary. Abbreviations are spelled out at first use on each page.

Pages

The steering code we are using (SafeTune)

SafeTune is Lexsi Labs' library for auditing and repairing safety behaviour in fine-tuned models. Its steering methods live in one folder. The one we use is Conditional Activation Steering (CAST), which adds a behaviour vector only when a condition vector fires. Its behaviour vector comes from Contrastive Activation Addition (CAA). Explanation: steering §10.

CAST in SafeTune

Note: SafeTune's code and docs credit CAST to "Wu et al." The paper on arXiv (2409.05907) is by Bruce W. Lee, Inkit Padhi and colleagues at IBM Research. IBM's original library: IBM/activation-steering. Line numbers are for commit 3901a9f (3 November 2026); the main links follow later changes.

Lexsi Labs tools

Hackathon and models

Private project notes

Project notes (password protected): the journal, night reports, literature reviews, results and the definitions of every assistant behaviour.