Blocking effect reduction in low bitrate video on a mobile platform. - Aleksandar Petrov; Tomislav Kartalov; Zoran A. Ivanovski (ICIP, 2009)

Learning Camera Miscalibration Detection. - Andrei Cramariuc; Aleksandar Petrov; Rohit Suri; Mayank Mittal; Roland Siegwart; Cesar Cadena 001 (ICRA, 2020)

Integrated Benchmarking and Design for Reproducible and Accessible Evaluation of Robotic Agents. - Jacopo Tani; Andrea F. Daniele; Gianmarco Bernasconi; Amaury Camus; Aleksandar Petrov; Anthony Courchesne; Bhairav Mehta; Rohit Suri; Tomasz Zaluska; Matthew R. Walter; Emilio Frazzoli; Liam Paull; et al. (IROS, 2020)

HiddenGems: Efficient safety boundary detection with active learning. - Aleksandar Petrov; Carter Fang; Khang Minh Pham; You Hong Eng; James Guo Ming Fu; Scott Drew Pendleton (IROS, 2022)

Robustness of Unsupervised Representation Learning without Labels. - Aleksandar Petrov; Marta Kwiatkowska (CoRR, 2022)

Certifying Ensembles: A General Certification Theory with S-Lipschitzness. - Aleksandar Petrov; Francisco Eiras; Amartya Sanyal; Philip H. S. Torr; Adel Bibi (ICML, 2023)

Language Model Tokenizers Introduce Unfairness Between Languages. - Aleksandar Petrov; Emanuele La Malfa; Philip H. S. Torr; Adel Bibi (NeurIPS, 2023)

The ARRT of Language-Models-as-a-Service: Overview of a New Paradigm and its Challenges. - Emanuele La Malfa; Aleksandar Petrov; Simon Frieder; Christoph Weinhuber; Ryan Burnell; Anthony G. Cohn 001; Nigel Shadbolt; Michael J. Wooldridge (CoRR, 2023)

Remote Sensing Data Preparation for Recognition and Classification of Building Roofs. - Emil Popov Hristov; Dessislava Petrova-Antonova; Aleksandar Petrov; Milena Borukova; Evgeny Shirinyan (Data, 2023)

When Do Prompting and Prefix-Tuning Work? A Theory of Capabilities and Limitations. - Aleksandar Petrov; Philip Torr 001; Adel Bibi (ICLR, 2024)

Position: Near to Mid-term Risks and Opportunities of Open-Source Generative AI. - Francisco Eiras; Aleksandar Petrov; Bertie Vidgen; Christian Schröder de Witt; Fabio Pizzati; Katherine Elkins; Supratik Mukhopadhyay; Adel Bibi; Botos Csaba; Fabro Steibel; Fazl Barez; Genevieve Smith; et al. (ICML, 2024)

Prompting a Pretrained Transformer Can Be a Universal Approximator. - Aleksandar Petrov; Philip Torr 001; Adel Bibi (ICML, 2024)

Universal In-Context Approximation By Prompting Fully Recurrent Models. - Aleksandar Petrov; Tom A. Lamb; Alasdair Paren; Philip Torr 001; Adel Bibi (NeurIPS, 2024)

Near to Mid-term Risks and Opportunities of Open Source Generative AI. - Francisco Eiras; Aleksandar Petrov; Bertie Vidgen; Christian Schröder de Witt; Fabio Pizzati; Katherine Elkins; Supratik Mukhopadhyay; Adel Bibi; Botos Csaba; Fabro Steibel; Fazl Barez; Genevieve Smith; et al. (CoRR, 2024)

Risks and Opportunities of Open-Source Generative AI. - Francisco Eiras; Aleksandar Petrov; Bertie Vidgen; Christian Schröder de Witt; Fabio Pizzati; Katherine Elkins; Supratik Mukhopadhyay; Adel Bibi; Aaron Purewal; Botos Csaba; Fabro Steibel; Fazel Keshtkar; et al. (CoRR, 2024)

Mimicking User Data: On Mitigating Fine-Tuning Risks in Closed Large Language Models. - Francisco Eiras; Aleksandar Petrov; Philip H. S. Torr; M. Pawan Kumar; Adel Bibi (CoRR, 2024)

Language-Models-as-a-Service: Overview of a New Paradigm and its Challenges. - Emanuele La Malfa; Aleksandar Petrov; Simon Frieder; Christoph Weinhuber; Ryan Burnell; Raza Nazar; Anthony G. Cohn 001; Nigel Shadbolt; Michael J. Wooldridge (J. Artif. Intell. Res., 2024)

Foundational Challenges in Assuring Alignment and Safety of Large Language Models. - Usman Anwar; Abulhair Saparov; Javier Rando; Daniel Paleka; Miles Turpin; Peter Hase; Ekdeep Singh Lubana; Erik Jenner; Stephen Casper; Oliver Sourbut; Benjamin L. Edelman; Zhaowei Zhang; et al. (Trans. Mach. Learn. Res., 2024)

Do as I do (Safely): Mitigating Task-Specific Fine-tuning Risks in Large Language Models. - Francisco Eiras; Aleksandar Petrov; Philip Torr 001; M. Pawan Kumar; Adel Bibi (ICLR, 2025)

On the Coexistence and Ensembling of Watermarks. - Aleksandar Petrov; Shruti Agarwal; Philip H. S. Torr; Adel Bibi; John P. Collomosse (CoRR, 2025)

Long Context In-Context Compression by Getting to the Gist of Gisting. - Aleksandar Petrov; Mark Sandler 002; Andrey Zhmoginov; Nolan Miller; Max Vladymyrov (CoRR, 2025)