YouTube2Text: Recognizing and Describing Arbitrary Activities Using Semantic Hierarchies and Zero-Shot Recognition. - Sergio Guadarrama; Niveda Krishnamoorthy; Girish Malkarnenkar; Subhashini Venugopalan; Raymond J. Mooney; Trevor Darrell; Kate Saenko (ICCV, 2013)

Integrating Language and Vision to Generate Natural Language Descriptions of Videos in the Wild. - Jesse Thomason; Subhashini Venugopalan; Sergio Guadarrama; Kate Saenko; Raymond J. Mooney (COLING, 2014)

Sequence to Sequence - Video to Text. - Subhashini Venugopalan; Marcus Rohrbach; Jeffrey Donahue; Raymond J. Mooney; Trevor Darrell; Kate Saenko (ICCV, 2015)

Translating Videos to Natural Language Using Deep Recurrent Neural Networks. - Subhashini Venugopalan; Huijuan Xu 001; Jeff Donahue; Marcus Rohrbach; Raymond J. Mooney; Kate Saenko (HLT-NAACL, 2015)

A Multi-scale Multiple Instance Video Description Network. - Huijuan Xu 001; Subhashini Venugopalan; Vasili Ramanishka; Marcus Rohrbach; Kate Saenko (CoRR, 2015)

Deep Compositional Captioning: Describing Novel Object Categories without Paired Training Data. - Lisa Anne Hendricks; Subhashini Venugopalan; Marcus Rohrbach; Raymond J. Mooney; Kate Saenko; Trevor Darrell (CVPR, 2016)

Improving LSTM-based Video Description with Linguistic Knowledge Mined from Text. - Subhashini Venugopalan; Lisa Anne Hendricks; Raymond J. Mooney; Kate Saenko (EMNLP, 2016)

Multimodal Video Description. - Vasili Ramanishka; Abir Das; Dong Huk Park; Subhashini Venugopalan; Lisa Anne Hendricks; Marcus Rohrbach; Kate Saenko (ACM Multimedia, 2016)

Utilizing Large Scale Vision and Text Datasets for Image Segmentation from Referring Expressions. - Ronghang Hu; Marcus Rohrbach; Subhashini Venugopalan; Trevor Darrell (CoRR, 2016)

Captioning Images with Diverse Objects. - Subhashini Venugopalan; Lisa Anne Hendricks; Marcus Rohrbach; Raymond J. Mooney; Trevor Darrell; Kate Saenko (CVPR, 2017)

Semantic Text Summarization of Long Videos. - Shagan Sah; Sourabh Kulhare; Allison Gray; Subhashini Venugopalan; Emily Prud'hommeaux; Raymond W. Ptucha (WACV, 2017)

Detecting Cancer Metastases on Gigapixel Pathology Images. - Yun Liu 013; Krishna Gadepalli; Mohammad Norouzi 002; George E. Dahl; Timo Kohlberger; Aleksey Boyko; Subhashini Venugopalan; Aleksei Timofeev; Philip Q. Nelson; Gregory S. Corrado; Jason D. Hipp; Lily Peng; et al. (CoRR, 2017)

Long-Term Recurrent Convolutional Networks for Visual Recognition and Description. - Jeff Donahue; Lisa Anne Hendricks; Marcus Rohrbach; Subhashini Venugopalan; Sergio Guadarrama; Kate Saenko; Trevor Darrell (IEEE Trans. Pattern Anal. Mach. Intell., 2017)

Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning. - Avinash V. Varadarajan; Pinal Bavishi; Paisan Raumviboonsuk; Peranut Chotcomwongse; Subhashini Venugopalan; Arunachalam Narayanaswamy; Jorge Cuadros; Kuniyoshi Kanai; George Bresnick; Mongkol Tadarati; Sukhum Silpa-Archa; Jirawut Limwattanayingyong; et al. (CoRR, 2018)

It's easy to fool yourself: Case studies on identifying bias and confounding in bio-medical datasets. - Subhashini Venugopalan; Arunachalam Narayanaswamy; Samuel J. Yang; Anton Gerashcenko; Scott Lipnick; Nina Makhortova; James Hawrot; Christine Marques; João Pereira; Michael P. Brenner; Lee Rubin; Brian Wainger; et al. (CoRR, 2019)

Attribution in Scale and Space. - Shawn Xu; Subhashini Venugopalan; Mukund Sundararajan (CVPR, 2020)

Scientific Discovery by Generating Counterfactuals Using Image Translation. - Arunachalam Narayanaswamy; Subhashini Venugopalan; Dale R. Webster; Lily Peng; Gregory S. Corrado; Paisan Ruamviboonsuk; Pinal Bavishi; Michael P. Brenner; Philip C. Nelson; Avinash V. Varadarajan (MICCAI (1), 2020)

Batch equalization with a generative adversarial network. - Wesley Wei Qian; Cassandra Xia; Subhashini Venugopalan; Arunachalam Narayanaswamy; Michelle Dimon; George W. Ashdown; Jake Baum; Jian Peng 001; D. Michael Ando (Bioinform., 2020)

Scientific Discovery by Generating Counterfactuals using Image Translation. - Arunachalam Narayanaswamy; Subhashini Venugopalan; Dale R. Webster; Lily Peng; Greg Corrado; Paisan Ruamviboonsuk; Pinal Bavishi; Rory Sayres; Abigail E. Huang; Siva Balasubramanian; Michael P. Brenner; Philip Q. Nelson; et al. (CoRR, 2020)

Predicting Risk of Developing Diabetic Retinopathy using Deep Learning. - Ashish Bora; Siva Balasubramanian; Boris Babenko; Sunny Virmani; Subhashini Venugopalan; Akinori Mitani; Guilherme de Oliveira Marinho; Jorge Cuadros; Paisan Ruamviboonsuk; Gregory S. Corrado; Lily Peng; Dale R. Webster; et al. (CoRR, 2020)

Guided Integrated Gradients: An Adaptive Path Method for Removing Noise. - Andrei Kapishnikov; Subhashini Venugopalan; Besim Avci; Ben Wedin; Michael Terry; Tolga Bolukbasi (CVPR, 2021)

Scaling Symbolic Methods using Gradients for Neural Model Explanation. - Subham Sekhar Sahoo; Subhashini Venugopalan; Li Li 060; Rishabh Singh; Patrick Riley 001 (ICLR, 2021)

Comparing Supervised Models and Learned Speech Representations for Classifying Intelligibility of Disordered Speech on Selected Phrases. - Subhashini Venugopalan; Joel Shor; Manoj Plakal; Jimmy Tobin; Katrin Tomanek; Jordan R. Green; Michael P. Brenner (Interspeech, 2021)

Using a Cross-Task Grid of Linear Probes to Interpret CNN Model Predictions On Retinal Images. - Katy Blumer; Subhashini Venugopalan; Michael P. Brenner; Jon M. Kleinberg (CoRR, 2021)

TRILLsson: Distilled Universal Paralinguistic Speech Representations. - Joel Shor; Subhashini Venugopalan (INTERSPEECH, 2022)

Context-Aware Abbreviation Expansion Using Large Language Models. - Shanqing Cai; Subhashini Venugopalan; Katrin Tomanek; Ajit Narayanan; Meredith Ringel Morris; Michael P. Brenner (NAACL-HLT, 2022)

Sparse Winning Tickets are Data-Efficient Image Recognizers. - Mukund Varma T.; Xuxi Chen; Zhenyu Zhang 015; Tianlong Chen 001; Subhashini Venugopalan; Zhangyang Wang (NeurIPS, 2022)

Is Attention All NeRF Needs? - Mukund Varma T.; Peihao Wang; Xuxi Chen; Tianlong Chen 001; Subhashini Venugopalan; Zhangyang Wang (CoRR, 2022)

Assessing ASR Model Quality on Disordered Speech using BERTScore. - Jimmy Tobin; Qisheng Li; Subhashini Venugopalan; Katie Seaver; Richard Cave; Katrin Tomanek (CoRR, 2022)

A machine-learning based objective measure for ALS disease severity. - Fernando Vieira; Subhashini Venugopalan; Alan S. Premasiri; Maeve McNally; Aren Jansen; Kevin McCloskey; Michael P. Brenner; Steven Perrin (npj Digit. Medicine, 2022)

Clinical BERTScore: An Improved Measure of Automatic Speech Recognition Performance in Clinical Settings. - Joel Shor; Ruyue Agnes Bi; Subhashini Venugopalan; Steven Ibara; Roman Goldenberg; Ehud Rivlin (ClinicalNLP@ACL, 2023)

SpeakFaster Observer: Long-Term Instrumentation of Eye-Gaze Typing for Measuring AAC Communication. - Shanqing Cai; Subhashini Venugopalan; Katrin Tomanek; Shaun K. Kane; Meredith Ringel Morris; Richard Cave; Robert L. MacDonald; Jon Campbell; Blair Casey; Emily Kornman; Daniel E. Vance; Jay C. Beavers (CHI Extended Abstracts, 2023)

Speech Intelligibility Classifiers from 550k Disordered Speech Samples. - Subhashini Venugopalan; Jimmy Tobin; Samuel J. Yang; Katie Seaver; Richard J. N. Cave; Pan-Pan Jiang; Neil Zeghidour; Rus Heywood; Jordan R. Green; Michael P. Brenner (ICASSP, 2023)

Is Attention All That NeRF Needs? - Mukund Varma T.; Peihao Wang; Xuxi Chen; Tianlong Chen 001; Subhashini Venugopalan; Zhangyang Wang (ICLR, 2023)

Using Large Language Models to Accelerate Communication for Users with Severe Motor Impairments. - Shanqing Cai; Subhashini Venugopalan; Katie Seaver; Xiang Xiao; Katrin Tomanek; Sri Jalasutram; Meredith Ringel Morris; Shaun K. Kane; Ajit Narayanan; Robert L. MacDonald; Emily Kornman; Daniel E. Vance; et al. (CoRR, 2023)

Parameter Efficient Tuning Allows Scalable Personalization of LLMs for Text Entry: A Case Study on Abbreviation Expansion. - Katrin Tomanek; Shanqing Cai; Subhashini Venugopalan (CoRR, 2023)

A Design Space for Intelligent and Interactive Writing Assistants. - Mina Lee 002; Katy Ilonka Gero; John Joon Young Chung; Simon Buckingham Shum; Vipul Raheja; Hua Shen 005; Subhashini Venugopalan; Thiemo Wambsganss; David Zhou; Emad A. Alghamdi; Tal August; Avinash Bhat; et al. (CHI, 2024)

Large Language Models As A Proxy For Human Evaluation In Assessing The Comprehensibility Of Disordered Speech Transcription. - Katrin Tomanek; Jimmy Tobin; Subhashini Venugopalan; Richard Cave; Katie Seaver; Jordan R. Green; Rus Heywood (ICASSP, 2024)

SPIQA: A Dataset for Multimodal Question Answering on Scientific Papers. - Shraman Pramanick; Rama Chellappa; Subhashini Venugopalan (NeurIPS, 2024)

SkipWriter: LLM-Powered Abbreviated Writing on Tablets. - Zheer Xu; Shanqing Cai; Mukund Varma T.; Subhashini Venugopalan; Shumin Zhai (UIST, 2024)

Quantum Many-Body Physics Calculations with Large Language Models. - Haining Pan; Nayantara Mudur; Will Taranto; Maria Tikhanovskaya; Subhashini Venugopalan; Yasaman Bahri; Michael P. Brenner; Eun-Ah Kim (CoRR, 2024)

Speech Recognition with LLMs Adapted to Disordered Speech Using Reinforcement Learning. - Chirag Nagpal; Subhashini Venugopalan; Jimmy Tobin; Marilyn A. Ladewig; Katherine A. Heller; Katrin Tomanek (ICASSP, 2025)

Towards a Single ASR Model That Generalizes to Disordered Speech. - Jimmy Tobin; Katrin Tomanek; Subhashini Venugopalan (ICASSP, 2025)

CURIE: Evaluating LLMs On Multitask Scientific Long Context Understanding and Reasoning. - Hao Cui; Zahra Shamsi; Gowoon Cheon; Xuejian Ma; Shutong Li; Maria Tikhanovskaya; Peter C. Norgaard; Nayantara Mudur; Martyna Plomecka; Paul Raccuglia; Yasaman Bahri; Victor V. Albert; et al. (CoRR, 2025)

Towards AI-assisted Academic Writing. - Daniel J. Liebling; Malcolm Kane; Madeleine Grunde-McLaughlin; Ian J. Lang; Subhashini Venugopalan; Michael P. Brenner (CoRR, 2025)

FEABench: Evaluating Language Models on Multiphysics Reasoning Ability. - Nayantara Mudur; Hao Cui; Subhashini Venugopalan; Paul Raccuglia; Michael P. Brenner; Peter C. Norgaard (CoRR, 2025)