Safety, security & interpretability for advanced learners
71 resources · page 3 of 3
Lost in the Middle
by Nelson F. Liu et al. (Stanford University)
arXiv paper (2023) "Lost in the Middle", showing LLM accuracy drops for information placed mid-context.
MCP docs: Security best practices
MCP security best practices: mitigations for confused deputy, token passthrough and session hijacking attacks.
Opacus
Opacus: PyTorch library and tutorials for training models with differential privacy.
Shortcut Learning in Deep Neural Networks
by Robert Geirhos et al. (University of Tübingen)
arXiv paper (2020) "Shortcut Learning in Deep Neural Networks", analysing how networks learn shortcut solutions that fail under distribution shift.
Strengthening our defenses against distillation attacks
by Anthropic
Anthropic research post on defending against illicit distillation of its models.
Tracing the thoughts of a large language model
by Anthropic
Anthropic interpretability research tracing internal mechanisms of Claude with attribution graphs.
UK education generative-AI product safety standards
by Department for Education (UK Government)
UK Department for Education generative AI product safety standards for AI tools used in education.