Author

Silas Alberti

Observed name: Alberti, Silas

Institutions: Cambridge Cognition (United Kingdom), Stanford University

Observed institutions: Cambridge Cognition (United Kingdom), Ludwig-Maximilians-Universität München, Stanford University

ORCID: 0000-0003-1611-5737

Observed ORCID: 0000-0003-1611-5737

OpenAlex ID: A5033138872

Black-Box Access is Insufficient for Rigorous AI Audits

2024 · Stephen Casper, Carson Ezell, et al. · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · 80

PIGEON: Predicting Image Geolocations

2024 · Lukas Haas, Michal Skreta, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 30

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Learning Generalized Zero-Shot Learners for Open-Domain Image Geolocalization

2023 · Haas, Lukas, Alberti, Silas, et al. · arXiv (Cornell University) · 15

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Simple linear attention language models balance the recall-throughput tradeoff

2024 · Arora, Simran, Eyuboglu, Sabri, et al. · arXiv (Cornell University) · 5

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SuperHF: Supervised Iterative Learning from Human Feedback

2023 · Mukobi, Gabriel, Chatain, Peter, et al. · arXiv (Cornell University) · 2

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Kevin: Multi-Turn RL for Generating CUDA Kernels

2025 · Baronio, Carlo, Marsella, Pietro, et al. · arXiv (Cornell University) · 1

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Expected Reward Prediction, with Applications to Model Routing

2026 · Hasanaliyev, Kenan, Alberti, Silas, et al. · arXiv (Cornell University)

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APEX-SWE

2026 · Kottamasu, Abhi, Mahapatra, Chirag, et al. · arXiv (Cornell University)

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Data Unlearning in Diffusion Models

2025 · Alberti, Silas, Hasanaliyev, Kenan, et al. · arXiv (Cornell University)

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Cannot or Should Not? Automatic Analysis of Refusal Composition in IFT/RLHF Datasets and Refusal Behavior of Black-Box LLMs

2024 · von Recum, Alexander, Schnabl, Christoph, et al. · arXiv (Cornell University)

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Sumformer: Universal Approximation for Efficient Transformers

2023 · Alberti, Silas, Dern, Niclas, et al. · arXiv (Cornell University)

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Study on safety of non-embedded software; Service, data access, and legal issues of advanced robots, autonomous, connected and AI-based vehicles and systems

2019 · M.J. van Lieshout, T. Timan, et al.

Works count: 12

Citation count: 133

H-index: 4

I10-index: 3