| 2024 | CVPR | Robust Disaster Assessment from Aerial Imagery Using Text-to-Image Synthetic Data. | Tarun Kalluri, Jihyeon Lee, Kihyuk Sohn, Sahil Singla, Manmohan Chandraker, Joseph Xu, Jeremiah Z. Liu |
| 2023 | ACL | Using Domain Knowledge to Guide Dialog Structure Induction via Neural Probabilistic Soft Logic. | Connor Pryor, Quan Yuan, Jeremiah Z. Liu, Mehran Kazemi, Deepak Ramachandran, Tania Bedrax-Weiss, Lise Getoor |
| 2023 | EMNLP | Retrieval-Augmented Parsing for Complex Graphs by Exploiting Structure and Uncertainty. | Zi Lin, Quan Yuan, Panupong Pasupat, Jeremiah Z. Liu, Jingbo Shang |
| 2023 | EMNLP | On Uncertainty Calibration and Selective Generation in Probabilistic Neural Summarization: A Benchmark Study. | Polina Zablotskaia, Du Phan, Joshua Maynez, Shashi Narayan, Jie Ren, Jeremiah Z. Liu |
| 2022 | EMNLP | Neural-Symbolic Inference for Robust Autoregressive Graph Parsing via Compositional Uncertainty Quantification. | Zi Lin, Jeremiah Z. Liu, Jingbo Shang |
| 2021 | AISTATS | Variable Selection with Rigorous Uncertainty Quantification using Deep Bayesian Neural Networks: Posterior Concentration and Bernstein-von Mises Phenomenon. | Jeremiah Z. Liu |
| 2020 | EMNLP | Pruning Redundant Mappings in Transformer Models via Spectral-Normalized Identity Prior. | Zi Lin, Jeremiah Z. Liu, Zi Yang, Nan Hua, Dan Roth |