Business Process Automation and XML Standards: Is there a Semantic Gap? - Adam Trachtenberg; Chester Karwatowski; Ajay Patel; Rob Barrett; Wendell Baker; Savitha Srinivasan (CEC/EEE, 2006)

Automatic cerebrospinal fluid segmentation in non-contrast CT images using a 3D convolutional network. - Ajay Patel; Sil C. van de Leemput; Mathias Prokop; Bram van Ginneken; Rashindra Manniesing (Computer-Aided Diagnosis, 2017)

Robust cranial cavity segmentation in CT and CT perfusion images of trauma and suspected stroke patients. - Ajay Patel; Bram van Ginneken; Frederick J. A. Meijer; Ewoud J. van Dijk; Mathias Prokop; Rashindra Manniesing (Medical Image Anal., 2017)

Magnitude: A Fast, Efficient Universal Vector Embedding Utility Package. - Ajay Patel; Alexander Sands; Chris Callison-Burch; Marianna Apidianaki (EMNLP (Demonstration), 2018)

A convolutional neural network for intracranial hemorrhage detection in non-contrast CT. - Ajay Patel; Rashindra Manniesing (Computer-Aided Diagnosis, 2018)

Multiclass Brain Tissue Segmentation in 4D CT Using Convolutional Neural Networks. - Sil C. van de Leemput; Midas Meijs; Ajay Patel; Frederick J. A. Meijer; Bram van Ginneken; Rashindra Manniesing (IEEE Access, 2019)

Image Level Training and Prediction: Intracranial Hemorrhage Identification in 3D Non-Contrast CT. - Ajay Patel; Sil C. van de Leemput; Mathias Prokop; Bram van Ginneken; Rashindra Manniesing (IEEE Access, 2019)

Multilingual Bidirectional Unsupervised Translation Through Multilingual Finetuning and Back-Translation. - Bryan Li; Mohammad Sadegh Rasooli; Ajay Patel; Chris Callison-Burch (CoRR, 2022)

Low-Resource Authorship Style Transfer with In-Context Learning. - Ajay Patel; Nicholas Andrews; Chris Callison-Burch (CoRR, 2022)

Learning Interpretable Style Embeddings via Prompting LLMs. - Ajay Patel; Delip Rao; Ansh Kothary; Kathleen R. McKeown; Chris Callison-Burch (EMNLP (Findings), 2023)

Bidirectional Language Models Are Also Few-shot Learners. - Ajay Patel; Bryan Li; Mohammad Sadegh Rasooli; Noah Constant; Colin Raffel; Chris Callison-Burch (ICLR, 2023)

Leveraging Large Language Models in Conversational Recommender Systems. - Luke Friedman; Sameer Ahuja; David Allen; Zhenning Tan; Hakim Sidahmed; Changbo Long; Jun Xie; Gabriel Schubiner; Ajay Patel; Harsh Lara; Brian Chu; Zexi Chen; et al. (CoRR, 2023)

Learning Interpretable Style Embeddings via Prompting LLMs. - Ajay Patel; Delip Rao; Chris Callison-Burch (CoRR, 2023)

Hand Gesture Data. - Ajay Patel; Charan KS; Prasansa Bhagat; Kshitij Sharma; C. Gururaj (IEEE DataPort, 2023)

ParaGuide: Guided Diffusion Paraphrasers for Plug-and-Play Textual Style Transfer. - Zachary Horvitz; Ajay Patel; Chris Callison-Burch; Zhou Yu; Kathleen R. McKeown (AAAI, 2024)

DataDreamer: A Tool for Synthetic Data Generation and Reproducible LLM Workflows. - Ajay Patel; Colin Raffel; Chris Callison-Burch (ACL (1), 2024)

TinyStyler: Efficient Few-Shot Text Style Transfer with Authorship Embeddings. - Zachary Horvitz; Ajay Patel; Kanishk Singh; Chris Callison-Burch; Kathleen R. McKeown; Zhou Yu (EMNLP (Findings), 2024)

Large Language Models Can Self-Improve At Web Agent Tasks. - Ajay Patel; Markus Hofmarcher; Claudiu Leoveanu-Condrei; Marius-Constantin Dinu; Chris Callison-Burch; Sepp Hochreiter (CoRR, 2024)

Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models. - Matt Deitke; Christopher Clark; Sangho Lee 008; Rohun Tripathi; Yue Yang 006; Jae Sung Park; Mohammadreza Salehi; Niklas Muennighoff; Kyle Lo; Luca Soldaini; Jiasen Lu; Taira Anderson; et al. (CoRR, 2024)

Scaling Text-Rich Image Understanding via Code-Guided Synthetic Multimodal Data Generation. - Yue Yang 006; Ajay Patel; Matt Deitke; Tanmay Gupta; Luca Weihs; Andrew Head; Mark Yatskar; Chris Callison-Burch; Ranjay Krishna; Aniruddha Kembhavi; Christopher Clark (ACL (1), 2025)

mStyleDistance: Multilingual Style Embeddings and their Evaluation. - Justin Qiu; Jiacheng Zhu; Ajay Patel; Marianna Apidianaki; Chris Callison-Burch (ACL (Findings), 2025)

Latent Space Interpretation for Stylistic Analysis and Explainable Authorship Attribution. - Milad Alshomary; Narutatsu Ri; Marianna Apidianaki; Ajay Patel; Smaranda Muresan; Kathleen R. McKeown (COLING, 2025)

Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models. - Matt Deitke; Christopher Clark; Sangho Lee 001; Rohun Tripathi; Yue Yang 006; Jae Sung Park; Mohammadreza Salehi; Niklas Muennighoff; Kyle Lo; Luca Soldaini; Jiasen Lu; Taira Anderson; et al. (CVPR, 2025)

StyleDistance: Stronger Content-Independent Style Embeddings with Synthetic Parallel Examples. - Ajay Patel; Jiacheng Zhu; Justin Qiu; Zachary Horvitz; Marianna Apidianaki; Kathleen McKeown; Chris Callison-Burch (NAACL (Long Papers), 2025)

Quantifying Misattribution Unfairness in Authorship Attribution. - Pegah Alipoormolabashi; Ajay Patel; Niranjan Balasubramanian (CoRR, 2025)