5 papers
The Capability Frontier: Benchmarks Miss 82% of Model Performance
Bradley Fowler, Ryan Smith, Daniel Thi Graviet +8
Existing benchmarks typically report accuracy for a single model on a single run. This systematically understates real-world LLM capabilities, particularly under heterogeneous data…
Riemannian-Manifold Steering: Geometry-Aware Generative Autoencoders for Label-Free Steering
Narmeen Oozeer, Shivam Raval, Philip Quirke +4
Steering a language model - intervening on its internal activations to change downstream behaviour - has recently expanded beyond linear interpolation to nonlinear methods such as…
Spectral Superposition: A Theory of Feature Geometry
Georgi Ivanov, Narmeen Oozeer, Shivam Raval +3
Neural networks represent more features than they have dimensions via superposition, forcing features to share representational space. Current methods decompose activations into sp…
Position: Require Frontier AI Labs To Release Small "Analog" Models
Shriyash Upadhyay, Chaithanya Bandi, Narmeen Oozeer +1
Recent proposals for regulating frontier AI models have sparked concerns about the cost of safety regulation, and most such regulations have been shelved due to the safety-innovati…
Beyond Monoliths: Expert Orchestration for More Capable, Democratic, and Safe Language Models
Philip Quirke, Narmeen Oozeer, Chaithanya Bandi +8
This position paper argues that the prevailing trajectory toward ever larger, more expensive generalist foundation models controlled by a handful of companies limits innovation and…