Sumformer: Universal Approximation for Efficient Transformers. - Silas Alberti; Niclas Dern; Laura Thesing; Gitta Kutyniok (TAG-ML, 2023)

Learning Generalized Zero-Shot Learners for Open-Domain Image Geolocalization. - Lukas Haas; Silas Alberti; Michal Skreta (CoRR, 2023)

PIGEON: Predicting Image Geolocations. - Lukas Haas; Michal Skreta; Silas Alberti (CoRR, 2023)

SuperHF: Supervised Iterative Learning from Human Feedback. - Gabriel Mukobi; Peter Chatain; Su Fong; Robert Windesheim; Gitta Kutyniok; Kush Bhatia; Silas Alberti (CoRR, 2023)

PIGEON: Predicting Image Geolocations. - Lukas Haas; Michal Skreta; Silas Alberti; Chelsea Finn (CVPR, 2024)

Black-Box Access is Insufficient for Rigorous AI Audits. - Stephen Casper; Carson Ezell; Charlotte Siegmann; Noam Kolt; Taylor Lynn Curtis; Benjamin Bucknall; Andreas A. Haupt; Kevin Wei; Jérémy Scheurer; Marius Hobbhahn; Lee Sharkey; Satyapriya Krishna; et al. (FAccT, 2024)

Simple linear attention language models balance the recall-throughput tradeoff. - Simran Arora; Sabri Eyuboglu; Michael Zhang; Aman Timalsina; Silas Alberti; James Zou 001; Atri Rudra; Christopher Ré (ICML, 2024)

Simple linear attention language models balance the recall-throughput tradeoff. - Simran Arora; Sabri Eyuboglu; Michael Zhang; Aman Timalsina; Silas Alberti; Dylan Zinsley; James Zou 001; Atri Rudra; Christopher Ré (CoRR, 2024)

Cannot or Should Not? Automatic Analysis of Refusal Composition in IFT/RLHF Datasets and Refusal Behavior of Black-Box LLMs. - Alexander von Recum; Christoph Schnabl; Gabor Hollbeck; Silas Alberti; Philip Blinde; Marvin Von Hagen (CoRR, 2024)

Data Unlearning in Diffusion Models. - Silas Alberti; Kenan Hasanaliyev; Manav Shah; Stefano Ermon (ICLR, 2025)

Kevin: Multi-Turn RL for Generating CUDA Kernels. - Carlo Baronio; Pietro Marsella; Ben Pan; Simon Guo; Silas Alberti (CoRR, 2025)