Mixture-of-Parents Maximum Entropy Markov Models. - David S. Rosenberg; Dan Klein 001; Ben Taskar (UAI, 2007)

The Rademacher Complexity of Co-Regularized Kernel Classes. - David S. Rosenberg; Peter L. Bartlett (AISTATS, 2007)

An RKHS for multi-view learning and manifold co-regularization. - Vikas Sindhwani; David S. Rosenberg (ICML, 2008)

Multiview point cloud kernels for semisupervised learning [Lecture Notes]. - David S. Rosenberg; Vikas Sindhwani; Peter L. Bartlett; Partha Niyogi (IEEE Signal Process. Mag., 2009)

Collaborative Ranking for Local Preferences. - Berk Kapicioglu; David S. Rosenberg; Robert E. Schapire; Tony Jebara (AISTATS, 2014)

Collaborative Place Models. - Berk Kapicioglu; David S. Rosenberg; Robert E. Schapire; Tony Jebara (IJCAI, 2015)

Scatteract: Automated Extraction of Data from Scatter Plots. - Mathieu Cliche; David S. Rosenberg; Dhruv Madeka; Connie Yee (ECML/PKDD (1), 2017)

Adaptive Grey-Box Fuzz-Testing with Thompson Sampling. - Siddharth Karamcheti; Gideon Mann; David S. Rosenberg (AISec@CCS, 2018)

Improving Grey-Box Fuzzing by Modeling Program Behavior. - Siddharth Karamcheti; Gideon Mann; David S. Rosenberg (CoRR, 2018)

Visual Attention Model for Cross-Sectional Stock Return Prediction and End-to-End Multimodal Market Representation Learning. - Ran Zhao; Yuntian Deng; Mark Dredze; Arun Verma; David S. Rosenberg; Amanda Stent (FLAIRS, 2019)

Challenges in End-to-End Neural Scientific Table Recognition. - Yuntian Deng; David S. Rosenberg; Gideon Mann (ICDAR, 2019)

Dual Reinforcement-Based Specification Generation for Image De-Rendering. - Ramakanth Pasunuru; David S. Rosenberg; Gideon Mann; Mohit Bansal (SDU@AAAI, 2021)

MixCE: Training Autoregressive Language Models by Mixing Forward and Reverse Cross-Entropies. - Shiyue Zhang 001; Shijie Wu; Ozan Irsoy; Steven Lu 003; Mohit Bansal; Mark Dredze; David S. Rosenberg (ACL (1), 2023)

BloombergGPT: A Large Language Model for Finance. - Shijie Wu; Ozan Irsoy; Steven Lu 003; Vadim Dabravolski; Mark Dredze; Sebastian Gehrmann; Prabhanjan Kambadur; David S. Rosenberg; Gideon Mann (CoRR, 2023)

Academics Can Contribute to Domain-Specialized Language Models. - Mark Dredze; Genta Indra Winata; Prabhanjan Kambadur; Shijie Wu; Ozan Irsoy; Steven Lu 003; Vadim Dabravolski; David S. Rosenberg; Sebastian Gehrmann (EMNLP, 2024)

Understanding and Mitigating Risks of Generative AI in Financial Services. - Sebastian Gehrmann; Claire Huang; Xian Teng; Sergei Yurovski; Arjun Bhorkar; Naveen Thomas; John A. Doucette; David S. Rosenberg; Mark Dredze; David Rabinowitz (FAccT, 2025)

Understanding and Mitigating Risks of Generative AI in Financial Services. - Sebastian Gehrmann; Claire Huang; Xian Teng; Sergei Yurovski; Iyanuoluwa Shode; Chirag S. Patel; Arjun Bhorkar; Naveen Thomas; John A. Doucette; David S. Rosenberg; Mark Dredze; David Rabinowitz (CoRR, 2025)

Evaluating the Retrieval Robustness of Large Language Models. - Shuyang Cao; Karthik Radhakrishnan; David S. Rosenberg; Steven Lu 003; Pengxiang Cheng 001; Lu Wang 008; Shiyue Zhang 001 (CoRR, 2025)