A complete end-to-end pipeline for LLM interpretability with sparse autoencoders (SAEs) using Llama 3.2, written in pure PyTorch and fully reproducible.

Real-time 3D visualisation of SAE feature activations inside GPT-2, token by token

Fast XAI with interactions at large scale. SPEX can help you understand the output of your LLM, even if you have a long context!

Automates attribution-graph analysis via probe prompting: circuit-trace a prompt, auto-generate concept probes, profile feature activations, cluster supernodes.

Spectral Attention Divergence — dynamical systems probe for LLM inference via dual-path attention comparison and delay-coordinate attractor reconstruction

A minimal mech-interp project for steering LLMs

Replication of 'From Reasoning to Answer' (EMNLP 2025) — Reasoning-Focus Heads + Activation Patching on DeepSeek-R1-Distill-Qwen-7B

This project explores methods to detect and mitigate jailbreak behaviors in Large Language Models (LLMs). By analyzing activation patterns—particularly in deeper layers—we identify distinct differences between compliant and non-compliant responses to uncover a jailbreak "direction." Using this insight, we develop intervention strategies that modify

Normative, machine-first definition of Interpretive SEO (SEO interprétatif), aligned with the Interpretive Governance standard.

Fine-tuned DistilBERT for binary sentiment analysis on IMDB movie reviews with token-level interpretability using LayerIntegratedGradients

Multi-scale Haar wavelet probes of LLM hidden states for FX direction prediction. Walk-forward Sharpe=1.22 net OOS on GBP/USD 2020-2026.

Studying LLM latent space topology using persistent homology and Hodge decomposition. Discovers that Hodge gradient potential recovers the animacy hierarchy — a linguistic universal — without supervision.

Layerwise diagnostic showing instruction-tuned LLMs settle on next-token predictions later.

Real-time 3D visualization of LLM cognitive states — explore transformer geometry during inference

Cross-patching diagnostic showing instruction-tuned late effects depend on upstream state.

Mechanistic interpretability toolkit for comparing transformer activations, token shifts, and activation patching behaviour.