Decoding LLM States: New Framework for Interpretability
Published:Dec 22, 2025 13:51
•1 min read
•ArXiv
Analysis
This ArXiv paper proposes a novel approach to understanding and controlling the internal states of Large Language Models. The methodology, likely involving grounding LLM activations, promises to significantly improve interpretability and potentially allow for more targeted control of LLM behavior.
Key Takeaways
- •Focuses on improving LLM interpretability.
- •Aims to allow for more precise control of LLM outputs.
- •Based on a brain-grounded axes approach, suggesting links to neuroscience.
Reference
“The paper is available on ArXiv.”