llm-activations

This paper proposes measuring concept content in text using LLM internal activations via linear probes and RFM concept vectors, applied to ESG classification. The best linear probe approaches fine-tuned classifier accuracy without task-specific fine-tuning and outperforms the model's own output, showing activations carry concept content beyond responses.