Eshika Saxena

According to our database, Eshika Saxena authored at least 11 papers between 2022 and 2026.

Collaborative distances:

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

2026

Improving ML Attacks on LWE with Data Repetition and Stepwise Regression.

Alberto Alfarano, Eshika Saxena, Emily Wenger, François Charton, Kristin E. Lauter

CoRR, April, 2026

2025

Calibrating LLM Judges: Linear Probes for Fast and Reliable Uncertainty Estimation.

Bhaktipriya Radharapu, Eshika Saxena, Kenneth Li, Chenxi Whitehouse, Adina Williams, Nicola Cancedda

CoRR, December, 2025

Salsa Fresca: Angular Embeddings and Pre-Training for ML Attacks on Learning With Errors.

Samuel Stevens, Emily Wenger, Cathy Yuanchen Li, Niklas Nolte, Eshika Saxena, François Charton, Kristin E. Lauter

Trans. Mach. Learn. Res., 2025

Making Hard Problems Easier with Custom Data Distributions and Loss Regularization: A Case Study in Modular Arithmetic.

Eshika Saxena, Alberto Alfarano, François Charton, Zeyuan Allen-Zhu, Emily Wenger, Kristin E. Lauter

IACR Cryptol. ePrint Arch., 2025

Benchmarking Attacks on Learning with Errors.

Emily Wenger, Eshika Saxena, Mohamed Malhou, Ellie Thieu, Kristin E. Lauter

Proceedings of the IEEE Symposium on Security and Privacy, 2025

TAPAS: Datasets for Learning the Learning with Errors Problem.

Eshika Saxena, Alberto Alfarano, François Charton, Emily Wenger, Kristin E. Lauter

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

Making Hard Problems Easier with Custom Data Distributions and Loss Regularization: A Case Study in Modular Arithmetic.

Eshika Saxena, Alberto Alfarano, Emily Wenger, Kristin E. Lauter

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Teaching Transformers Modular Arithmetic at Scale.

Eshika Saxena, Alberto Alfarano, Emily Wenger, Kristin E. Lauter

CoRR, 2024

2022

Rethinking Stability for Attribution-based Explanations.

Chirag Agarwal, Nari Johnson, Martin Pawelczyk, Satyapriya Krishna, Eshika Saxena, Marinka Zitnik, Himabindu Lakkaraju

CoRR, 2022

OpenXAI: Towards a Transparent Evaluation of Model Explanations.

Chirag Agarwal, Satyapriya Krishna, Eshika Saxena, Martin Pawelczyk, Nari Johnson, Isha Puri, Marinka Zitnik, Himabindu Lakkaraju

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Deep Learning for Personalized Preoperative Planning of Microsurgical Free Tissue Transfers.

Eshika Saxena

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022