Francisco Girbal Eiras

According to our database, Francisco Girbal Eiras authored at least 23 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

The Singapore Consensus on Global AI Safety Research Priorities.

Yoshua Bengio, Tegan Maharaj, Luke Ong, Stuart Russell, Dawn Song, Max Tegmark, Lan Xue, Ya-Qin Zhang, Stephen Casper, Wan Sie Lee, Sören Mindermann, Vanessa Wilfred, Vidhisha Balachandran, Fazl Barez, Michael Belinsky, Imane Bello, Malo Bourgon, Mark Brakel, Siméon Campos, Duncan Cass-Beggs, Jiahao Chen, Rumman Chowdhury, Kuan Chua Seah, Jeff Clune, Juntao Dai, Agnès Delaborde, Nouha Dziri, Francisco Eiras, Joshua Engels, Jinyu Fan, Adam Gleave, Noah Goodman, Fynn Heide, Johannes Heidecke, Dan Hendrycks, Cyrus Hodes, Bryan Low Kian Hsiang, Minlie Huang, Sami Jawhar, Wang Jingyu, Adam Tauman Kalai, Meindert Kamphuis, Mohan S. Kankanhalli, Subhash Kantamneni, Mathias Bonde Kirk, Thomas Kwa, Jeffrey Ladish, Kwok-Yan Lam, Wan Lee Sie, Taewhi Lee, Xiaojian Li, Jiajun Liu, Chaochao Lu, Yifan Mai, Richard Mallah, Julian Michael, Nick Moës, Simon Möller, Kihyuk Nam, Kwan Yee Ng, Mark Nitzberg, Besmira Nushi, Seán Ó hÉigeartaigh, Alejandro Ortega, Pierre Peigné, James Petrie, Benjamin Prud'homme, Reihaneh Rabbany, Nayat Sanchez-Pi, Sarah Schwettmann, Buck Shlegeris, Saad Siddiqui, Aradhana Sinha, Martín Soto, Cheston Tan, Dong Ting, William-Chandra Tjhi, Robert Trager, Brian Tse, Anthony Tung K. H., John Willes, Denise Wong, Wei Xu, Rongwu Xu, Yi Zeng, HongJiang Zhang, Djordje Zikelic

CoRR, June, 2025

Know Thy Judge: On the Robustness Meta-Evaluation of LLM Safety Judges.

Francisco Eiras, Eliott Zemour, Eric Lin, Vaikkunth Mugunthan

CoRR, March, 2025

Do as I do (Safely): Mitigating Task-Specific Fine-tuning Risks in Large Language Models.

Francisco Eiras, Aleksandar Petrov, Philip Torr, M. Pawan Kumar, Adel Bibi

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

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

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, Fazl Barez, Genevieve Smith, Gianluca Guadagni, Jon Chun, Jordi Cabot, Joseph Marvin Imperial, Juan Arturo Nolazco, Lori Landay, Matthew Thomas Jackson, Philip H. S. Torr, Trevor Darrell, Yong Suk Lee, Jakob N. Foerster

CoRR, 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, Gianluca Guadagni, Jon Chun, Jordi Cabot, Joseph Marvin Imperial, Juan A. Nolazco-Flores, Lori Landay, Matthew Thomas Jackson, Paul Röttger, Philip H. S. Torr, Trevor Darrell, Yong Suk Lee, Jakob N. Foerster

CoRR, 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, Gianluca Guadagni, Jon Chun, Jordi Cabot, Joseph Marvin Imperial, Juan A. Nolazco-Flores, Lori Landay, Matthew Thomas Jackson, Paul Röttger, Philip H. S. Torr, Trevor Darrell, Yong Suk Lee, Jakob N. Foerster

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Efficient Error Certification for Physics-Informed Neural Networks.

Francisco Eiras, Adel Bibi, Rudy Bunel, Krishnamurthy Dj Dvijotham, Philip Torr, M. Pawan Kumar

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Segment, Select, Correct: A Framework for Weakly-Supervised Referring Segmentation.

Francisco Eiras, Kemal Oksuz, Adel Bibi, Philip H. S. Torr, Puneet K. Dokania

Proceedings of the Computer Vision - ECCV 2024 Workshops, 2024

2023

Faithful Knowledge Distillation.

Tom A. Lamb, Rudy Bunel, Krishnamurthy (Dj) Dvijotham, M. Pawan Kumar, Philip H. S. Torr, Francisco Eiras

CoRR, 2023

Provably Correct Physics-Informed Neural Networks.

Francisco Eiras, Adel Bibi, Rudy Bunel, Krishnamurthy (Dj) Dvijotham, Philip H. S. Torr, M. Pawan Kumar

CoRR, 2023

RANCER: Non-Axis Aligned Anisotropic Certification with Randomized Smoothing.

Taras Rumezhak, Francisco Girbal Eiras, Philip H. S. Torr, Adel Bibi

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Certifying Ensembles: A General Certification Theory with S-Lipschitzness.

Aleksandar Petrov, Francisco Eiras, Amartya Sanyal, Philip H. S. Torr, Adel Bibi

Proceedings of the International Conference on Machine Learning, 2023

2022

A Two-Stage Optimization-Based Motion Planner for Safe Urban Driving.

Francisco Eiras, Majd Hawasly, Stefano V. Albrecht, Subramanian Ramamoorthy

IEEE Trans. Robotics, 2022

ANCER: Anisotropic Certification via Sample-wise Volume Maximization.

Francisco Eiras, Motasem Alfarra, Philip H. S. Torr, M. Pawan Kumar, Puneet K. Dokania, Bernard Ghanem, Adel Bibi

Trans. Mach. Learn. Res., 2022

2021

PILOT: Efficient Planning by Imitation Learning and Optimisation for Safe Autonomous Driving.

Henry Pulver, Francisco Eiras, Ludovico Carozza, Majd Hawasly, Stefano V. Albrecht, Subramanian Ramamoorthy

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

Interpretable Goal Recognition in the Presence of Occluded Factors for Autonomous Vehicles.

Josiah P. Hanna, Arrasy Rahman, Elliot Fosong, Francisco Eiras, Mihai Dobre, John Redford, Subramanian Ramamoorthy, Stefano V. Albrecht

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

Interpretable Goal-based Prediction and Planning for Autonomous Driving.

Stefano V. Albrecht, Cillian Brewitt, John Wilhelm, Balint Gyevnar, Francisco Eiras, Mihai Dobre, Subramanian Ramamoorthy

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

2020

Integrating Planning and Interpretable Goal Recognition for Autonomous Driving.

Stefano V. Albrecht, Cillian Brewitt, John Wilhelm, Francisco Eiras, Mihai Dobre, Subramanian Ramamoorthy

CoRR, 2020

A Two-Stage Optimization Approach to Safe-by-Design Planning for Autonomous Driving.

Francisco Eiras, Majd Hawasly, Stefano V. Albrecht, Subramanian Ramamoorthy

CoRR, 2020

PaRoT: A Practical Framework for Robust Deep Neural Network Training.

Edward W. Ayers, Francisco Eiras, Majd Hawasly, Iain Whiteside

Proceedings of the NASA Formal Methods - 12th International Symposium, 2020

2019

Correct-by-Construction Advanced Driver Assistance Systems Based on a Cognitive Architecture.

Francisco Eiras, Morteza Lahijanian, Marta Kwiatkowska

Proceedings of the IEEE 2nd Connected and Automated Vehicles Symposium, 2019

2018

Analytical Modeling of Vanishing Points and Curves in Catadioptric Cameras.

Pedro Miraldo, Francisco Eiras, Srikumar Ramalingam

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018