Aodong Li

According to our database, Aodong Li authored at least 13 papers between 2017 and 2026.

Collaborative distances:

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

2026

AgentSM: Semantic Memory for Agentic Text-to-SQL.

Asim Biswal, Chuan Lei, Xiao Qin, Aodong Li, Balakrishnan Narayanaswamy, Tim Kraska

CoRR, January, 2026

Probabilistic Hash Embeddings for Online Learning of Categorical Features.

Aodong Li, Abishek Sankararaman, Balakrishnan Narayanaswamy

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Model Selection of Anomaly Detectors in the Absence of Labeled Validation Data.

Clement Fung, Chen Qiu, Aodong Li, Maja Rudolph

IEEE Trans. Artif. Intell., December, 2025

Learning from Noisy Data Using Pretrained Vision-Language Representations.

Yuqi Liao, Aodong Li, Yisha Chen, Qianfang Xu, Jiarui Xie, Anxin Li, Bo Xiao

Proceedings of the IEEE International Conference on Multimedia and Expo, 2025

2024

Deep Anomaly Detection and Distribution Shifts

Aodong Li

PhD thesis, 2024

Anomaly Detection of Tabular Data Using LLMs.

Aodong Li, Yunhan Zhao, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt

CoRR, 2024

2023

Zero-Shot Anomaly Detection without Foundation Models.

Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt

CoRR, 2023

Zero-Shot Anomaly Detection via Batch Normalization.

Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Deep Anomaly Detection under Labeling Budget Constraints.

Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Stephan Mandt, Maja Rudolph

Proceedings of the International Conference on Machine Learning, 2023

2022

Latent Outlier Exposure for Anomaly Detection with Contaminated Data.

Chen Qiu, Aodong Li, Marius Kloft, Maja Rudolph, Stephan Mandt

Proceedings of the International Conference on Machine Learning, 2022

2021

Detecting and Adapting to Irregular Distribution Shifts in Bayesian Online Learning.

Aodong Li, Alex Boyd, Padhraic Smyth, Stephan Mandt

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

2020

Variational Beam Search for Online Learning with Distribution Shifts.

Aodong Li, Alex Boyd, Padhraic Smyth, Stephan Mandt

CoRR, 2020

2017

Enhanced neural machine translation by learning from draft.

Aodong Li, Shiyue Zhang, Dong Wang, Thomas Fang Zheng

Proceedings of the 2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 2017