Latent-Explorer
What it is
Latent-Explorer is a Python library that decodes factual knowledge from the latent representations of Large Language Models (LLMs). It uses activation patching to map these representations into dynamic knowledge graphs, allowing researchers to observe how information evolves during model inference.
The problem it solves
The difficulty of interpretability in large language models, specifically understanding how and what facts are encoded within latent vector spaces.
What you could use it for
- Analyzing which specific facts an LLM relies on for claim verification.
- Visualizing the step-by-step evolution of knowledge throughout a model's inference process.
- Studying the internal semantic representations and information flow of instruction-tuned LLMs.
Read the source ↗Back to the library →
Summary written by an AI model from the source; check the source before you rely on it.