| 2025 | ACL | LADDER: Language-Driven Slice Discovery and Error Rectification in Vision Classifiers. | Shantanu Ghosh, Rayan Syed, Chenyu Wang, Vaibhav Choudhary, Binxu Li, Clare B. Poynton, Shyam Visweswaran, Kayhan Batmanghelich |
| 2025 | AIES | A Human-Centered Approach to Identifying Promises, Risks, & Challenges of Text-to-Image Generative AI in Radiology. | Katelyn Morrison, Arpit Mathur, Aidan Bradshaw, Tom Wartmann, Steven Lundi, Afrooz Zandifar, Weichang Dai, Kayhan Batmanghelich, Motahhare Eslami, Adam Perer |
| 2025 | NAACL | Semantic Consistency-Based Uncertainty Quantification for Factuality in Radiology Report Generation. | Chenyu Wang, Weichao Zhou, Shantanu Ghosh, Kayhan Batmanghelich, Wenchao Li |
| 2025 | WACV | Multi-Modal Large Language Models are Effective Vision Learners. | Li Sun, Chaitanya Ahuja, Peng Chen, Matt D'Zmura, Kayhan Batmanghelich, Philip Bontrager |
| 2024 | MICCAI | Mammo-CLIP: A Vision Language Foundation Model to Enhance Data Efficiency and Robustness in Mammography. | Shantanu Ghosh, Clare B. Poynton, Shyam Visweswaran, Kayhan Batmanghelich |
| 2023 | ACL | From Characters to Words: Hierarchical Pre-trained Language Model for Open-vocabulary Language Understanding. | Li Sun, Florian Luisier, Kayhan Batmanghelich, Dinei A. F. Florncio, Cha Zhang |
| 2023 | ICML | Dividing and Conquering a BlackBox to a Mixture of Interpretable Models: Route, Interpret, Repeat. | Shantanu Ghosh, Ke Yu, Forough Arabshahi, Kayhan Batmanghelich |
| 2023 | MICCAI | Distilling BlackBox to Interpretable Models for Efficient Transfer Learning. | Shantanu Ghosh, Ke Yu, Kayhan Batmanghelich |
| 2023 | MICCAI | Physics-Informed Neural Networks for Tissue Elasticity Reconstruction in Magnetic Resonance Elastography. | Matthew Ragoza, Kayhan Batmanghelich |
| 2023 | WACV | Augmentation by Counterfactual Explanation -Fixing an Overconfident Classifier. | Sumedha Singla, Nihal Murali, Forough Arabshahi, Sofia Triantafyllou, Kayhan Batmanghelich |
| 2022 | AAAI | Knowledge Distillation via Constrained Variational Inference. | Ardavan Saeedi, Yuria Utsumi, Li Sun, Kayhan Batmanghelich, Li-Wei H. Lehman |
| 2022 | CVPR | Maximum Spatial Perturbation Consistency for Unpaired Image-to-Image Translation. | Yanwu Xu, Shaoan Xie, Wenhao Wu, Kun Zhang, Mingming Gong, Kayhan Batmanghelich |
| 2022 | MICCAI | Adversarial Consistency for Single Domain Generalization in Medical Image Segmentation. | Yanwu Xu, Shaoan Xie, Maxwell Reynolds, Matthew Ragoza, Mingming Gong, Kayhan Batmanghelich |
| 2022 | MICCAI | Anatomy-Guided Weakly-Supervised Abnormality Localization in Chest X-rays. | Ke Yu, Shantanu Ghosh, Zhexiong Liu, Christopher Deible, Kayhan Batmanghelich |
| 2021 | AAAI | Context Matters: Graph-based Self-supervised Representation Learning for Medical Images. | Li Sun, Ke Yu, Kayhan Batmanghelich |
| 2021 | MICCAI | Self-supervised Vessel Enhancement Using Flow-Based Consistencies. | Rohit Jena, Sumedha Singla, Kayhan Batmanghelich |
| 2021 | MICCAI | Using Causal Analysis for Conceptual Deep Learning Explanation. | Sumedha Singla, Stephen Wallace, Sofia Triantafillou, Kayhan Batmanghelich |
| 2020 | AAAI | Weakly Supervised Disentanglement by Pairwise Similarities. | Junxiang Chen, Kayhan Batmanghelich |
| 2020 | AAAI | Generative-Discriminative Complementary Learning. | Yanwu Xu, Mingming Gong, Junxiang Chen, Tongliang Liu, Kun Zhang, Kayhan Batmanghelich |
| 2020 | ICASSP | Human-Machine Collaboration for Medical Image Segmentation. | Mahdyar Ravanbakhsh, Vadim Tschernezki, Felix Last, Tassilo Klein, Kayhan Batmanghelich, Volker Tresp, Moin Nabi |
| 2020 | ICLR | Explanation by Progressive Exaggeration. | Sumedha Singla, Brian Pollack, Junxiang Chen, Kayhan Batmanghelich |
| 2020 | ICML | Label-Noise Robust Domain Adaptation. | Xiyu Yu, Tongliang Liu, Mingming Gong, Kun Zhang, Kayhan Batmanghelich, Dacheng Tao |
| 2019 | CVPR | Geometry-Consistent Generative Adversarial Networks for One-Sided Unsupervised Domain Mapping. | Huan Fu, Mingming Gong, Chaohui Wang, Kayhan Batmanghelich, Kun Zhang, Dacheng Tao |
| 2018 | ACCV | Robust Angular Local Descriptor Learning. | Yanwu Xu, Mingming Gong, Tongliang Liu, Kayhan Batmanghelich, Chaohui Wang |
| 2018 | CVPR | Deep Ordinal Regression Network for Monocular Depth Estimation. | Huan Fu, Mingming Gong, Chaohui Wang, Kayhan Batmanghelich, Dacheng Tao |
| 2018 | CVPR | An Efficient and Provable Approach for Mixture Proportion Estimation Using Linear Independence Assumption. | Xiyu Yu, Tongliang Liu, Mingming Gong, Kayhan Batmanghelich, Dacheng Tao |
| 2018 | MICCAI | Multi-scale Masked 3-D U-Net for Brain Tumor Segmentation. | Yanwu Xu, Mingming Gong, Huan Fu, Dacheng Tao, Kun Zhang, Kayhan Batmanghelich |
| 2018 | UAI | Causal Discovery with Linear Non-Gaussian Models under Measurement Error: Structural Identifiability Results. | Kun Zhang, Mingming Gong, Joseph D. Ramsey, Kayhan Batmanghelich, Peter Spirtes, Clark Glymour |