3 papers
cs.AI2025
From Model Training to Model Raising
Roland Aydin, Christian Cyron, Steve Bachelor +2
Current AI training methods align models with human values only after their core capabilities have been established, resulting in models that are easily misaligned and lack deep-ro…
cs.LG2024
One-Step is Enough: Sparse Autoencoders for Text-to-Image Diffusion Models
Viacheslav Surkov, Chris Wendler, Antonio Mari +5
For large language models (LLMs), sparse autoencoders (SAEs) have been shown to decompose intermediate representations that often are not interpretable directly into sparse sums of…
cs.CL2024
Self-Recognition in Language Models
Tim R. Davidson, Viacheslav Surkov, Veniamin Veselovsky +3
A rapidly growing number of applications rely on a small set of closed-source language models (LMs). This dependency might introduce novel security risks if LMs develop self-recogn…