1 citations · 2 across the 5 of their papers we have counts for
5 papers
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…
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…
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…
Fleet of Agents: Coordinated Problem Solving with Large Language Models
Lars Klein, Nearchos Potamitis, Roland Aydin +3
While numerous frameworks have been developed to enhance the reasoning abilities of large language models (LLMs), there is a scarcity of methods that effectively balance the trade-…
Emojinize: Enriching Any Text with Emoji Translations
Lars Henning Klein, Roland Aydin, Robert West
Emoji have become ubiquitous in written communication, on the Web and beyond. They can emphasize or clarify emotions, add details to conversations, or simply serve decorative purpo…