Tag: AI interpretability
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Aligning Human Concepts with Machine Learning Representations
Explore a geometric framework to align human concepts with machine learning models, enhancing interpretable AI and concept representation accuracy.
Optimizing Prompts to Decode LLMs’ Scientific Reasoning
Explore how prompt optimization reveals Large Language Models' scientific reasoning behavior for better AI interpretability and AGI interaction.
Complexity-Aware Deep Symbolic Regression with Robust Policy Gradients
Discover a novel deep symbolic regression method using robust risk-seeking policy gradients to improve model robustness and interpretability.
Gemma Scope 2: Advanced AI Safety for Language Models
Discover how Gemma Scope 2 enhances AI safety by providing tools to analyze and understand complex language model behavior effectively.
Steering Vision-Language Models to Explain Visual Features
Discover how steering techniques in vision-language models enable automated, scalable explanations of visual features in AI vision systems.