Hilaf Hasson

According to our database, Hilaf Hasson authored at least 16 papers between 2016 and 2026.

Collaborative distances:

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

2026

Decomposing Epistemic Uncertainty for Causal Decision Making.

Md. Musfiqur Rahman, Ziwei Jiang, Hilaf Hasson, Murat Kocaoglu

CoRR, January, 2026

RIMRULE: Improving Tool-Using Language Agents via MDL-Guided Rule Learning.

Xiang Gao, Yuguang Yao, Qi Zhang, Kaiwen Dong, Avinash Baidya, Ruocheng Guo, Hilaf Hasson, Kamalika Das

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

2025

Node-Level Uncertainty Estimation in LLM-Generated SQL.

Hilaf Hasson, Ruocheng Guo

CoRR, November, 2025

OMAC: A Broad Optimization Framework for LLM-Based Multi-Agent Collaboration.

Shijun Li, Hilaf Hasson, Joydeep Ghosh

CoRR, May, 2025

2024

Goal-Conditioned Supervised Learning for Multi-Objective Recommendation.

Shijun Li, Hilaf Hasson, Jing Hu, Joydeep Ghosh

CoRR, 2024

HyQE: Ranking Contexts with Hypothetical Query Embeddings.

Weichao Zhou, Jiaxin Zhang, Hilaf Hasson, Anu Singh, Wenchao Li

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

2023

Testing Causality for High Dimensional Data.

Arun Jambulapati, Hilaf Hasson, Youngsuk Park, Yuyang Wang

CoRR, 2023

Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting.

Hilaf Hasson, Danielle C. Maddix, Bernie Wang, Gaurav Gupta, Youngsuk Park

Proceedings of the International Conference on Machine Learning, 2023

Robust Multivariate Time-Series Forecasting: Adversarial Attacks and Defense Mechanisms.

Linbo Liu, Youngsuk Park, Trong Nghia Hoang, Hilaf Hasson, Luke Huan

Proceedings of the Eleventh International Conference on Learning Representations, 2023

But Are You Sure? An Uncertainty-Aware Perspective on Explainable AI.

Charles Marx, Youngsuk Park, Hilaf Hasson, Yuyang Wang, Stefano Ermon, Luke Huan

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Towards Robust Multivariate Time-Series Forecasting: Adversarial Attacks and Defense Mechanisms.

Linbo Liu, Youngsuk Park, Trong Nghia Hoang, Hilaf Hasson, Jun Huan

CoRR, 2022

8th SIGKDD International Workshop on Mining and Learning from Time Series - Deep Forecasting: Models, Interpretability, and Applications.

Sanjay Purushotham, Jun Huan, Cong Shen, Dongjin Song, Yuyang Wang, Jan Gasthaus, Hilaf Hasson, Youngsuk Park, Sungyong Seo, Yuriy Nevmyvaka

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021

Dynamic Regret for Strongly Adaptive Methods and Optimality of Online KRR.

Dheeraj Baby, Hilaf Hasson, Yuyang Wang

CoRR, 2021

Probabilistic Forecasting: A Level-Set Approach.

Hilaf Hasson, Bernie Wang, Tim Januschowski, Jan Gasthaus

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Normalizing Kalman Filters for Multivariate Time Series Analysis.

Emmanuel de Bézenac, Syama Sundar Rangapuram, Konstantinos Benidis, Michael Bohlke-Schneider, Richard Kurle, Lorenzo Stella, Hilaf Hasson, Patrick Gallinari, Tim Januschowski

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2016

Suzuki-invariant codes from the Suzuki curve.

Abdulla Eid, Hilaf Hasson, Amy Ksir, Justin D. Peachey

Des. Codes Cryptogr., 2016