Julian Asilis

According to our database, Julian Asilis authored at least 15 papers between 2021 and 2026.

Collaborative distances:

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

2026

Semi-Random Graphs, Robust Asymmetry, and Reconstruction.

Julian Asilis, Xi Chen, Dutch Hansen, Shang-Hua Teng

Proceedings of the 17th Innovations in Theoretical Computer Science Conference, 2026

Textual Steering Vectors Can Improve Visual Understanding in Multimodal Large Language Models.

Woody Haosheng Gan, Deqing Fu, Julian Asilis, Ollie Liu, Vatsal Sharan, Robin Jia, Willie Neiswanger

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

2025

Resa: Transparent Reasoning Models via SAEs.

Shangshang Wang, Julian Asilis, Ömer Faruk Akgül, Enes Burak Bilgin, Ollie Liu, Deqing Fu, Willie Neiswanger

CoRR, June, 2025

Textual Steering Vectors Can Improve Visual Understanding in Multimodal Large Language Models.

Woody Haosheng Gan, Deqing Fu, Julian Asilis, Ollie Liu, Dani Yogatama, Vatsal Sharan, Robin Jia, Willie Neiswanger

CoRR, May, 2025

Tina: Tiny Reasoning Models via LoRA.

Shangshang Wang, Julian Asilis, Ömer Faruk Akgül, Enes Burak Bilgin, Ollie Liu, Willie Neiswanger

CoRR, April, 2025

On Agnostic PAC Learning in the Small Error Regime.

Julian Asilis, Mikael Møller Høgsgaard, Grigoris Velegkas

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Local Regularizers Are Not Transductive Learners.

Sky Jafar, Julian Asilis, Shaddin Dughmi

Proceedings of the Thirty Eighth Annual Conference on Learning Theory, 2025

Understanding Aggregations of Proper Learners in Multiclass Classification.

Julian Asilis, Mikael Møller Høgsgaard, Grigoris Velegkas

Proceedings of the International Conference on Algorithmic Learning Theory, 2025

Proper Learnability and the Role of Unlabeled Data.

Julian Asilis, Siddartha Devic, Shaddin Dughmi, Vatsal Sharan, Shang-Hua Teng

Proceedings of the International Conference on Algorithmic Learning Theory, 2025

2024

Learnability is a Compact Property.

Julian Asilis, Siddartha Devic, Shaddin Dughmi, Vatsal Sharan, Shang-Hua Teng

CoRR, 2024

Transductive Learning is Compact.

Julian Asilis, Siddartha Devic, Shaddin Dughmi, Vatsal Sharan, Shang-Hua Teng

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Open Problem: Can Local Regularization Learn All Multiclass Problems?

Julian Asilis, Siddartha Devic, Shaddin Dughmi, Vatsal Sharan, Shang-Hua Teng

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Regularization and Optimal Multiclass Learning.

Julian Asilis, Siddartha Devic, Shaddin Dughmi, Vatsal Sharan, Shang-Hua Teng

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2022

Computable PAC Learning of Continuous Features.

Nathanael L. Ackerman, Julian Asilis, Jieqi Di, Cameron E. Freer, Jean-Baptiste Tristan

Proceedings of the LICS '22: 37th Annual ACM/IEEE Symposium on Logic in Computer Science, Haifa, Israel, August 2, 2022

2021

On computable learning of continuous features.

Nathanael L. Ackerman, Julian Asilis, Jieqi Di, Cameron E. Freer, Jean-Baptiste Tristan

CoRR, 2021