Subhashini Venugopalan

According to our database, Subhashini Venugopalan authored at least 41 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

SPIQA: A Dataset for Multimodal Question Answering on Scientific Papers.

Shraman Pramanick, Rama Chellappa, Subhashini Venugopalan

CoRR, 2024

A Design Space for Intelligent and Interactive Writing Assistants.

Mina Lee, Katy Ilonka Gero, John Joon Young Chung, Simon Buckingham Shum, Vipul Raheja, Hua Shen, Subhashini Venugopalan, Thiemo Wambsganss, David Zhou, Emad A. Alghamdi, Tal August, Avinash Bhat, Madiha Zahrah Choksi, Senjuti Dutta, Jin L. C. Guo, Md. Naimul Hoque, Yewon Kim, Simon Knight, Seyed Parsa Neshaei, Agnia Sergeyuk, Antonette Shibani, Disha Shrivastava, Lila Shroff, Jessi Stark, Sarah Sterman, Sitong Wang, Antoine Bosselut, Daniel Buschek, Joseph Chee Chang, Sherol Chen, Max Kreminski, Joonsuk Park, Roy Pea, Eugenia H. Rho, Shannon Zejiang Shen, Pao Siangliulue

CoRR, 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

SkipWriter: LLM-Powered Abbreviated Writing on Tablets.

Zheer Xu, Shanqing Cai, Mukund Varma T., Subhashini Venugopalan, Shumin Zhai

Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology, 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

Proceedings of the IEEE International Conference on Acoustics, 2024

A Design Space for Intelligent and Interactive Writing Assistants.

Mina Lee, Katy Ilonka Gero, John Joon Young Chung, Simon Buckingham Shum, Vipul Raheja, Hua Shen, Subhashini Venugopalan, Thiemo Wambsganss, David Zhou, Emad A. Alghamdi, Tal August, Avinash Bhat, Madiha Zahrah Choksi, Senjuti Dutta, Jin L. C. Guo, Md. Naimul Hoque, Yewon Kim, Simon Knight, Seyed Parsa Neshaei, Antonette Shibani, Disha Shrivastava, Lila Shroff, Agnia Sergeyuk, Jessi Stark, Sarah Sterman, Sitong Wang, Antoine Bosselut, Daniel Buschek, Joseph Chee Chang, Sherol Chen, Max Kreminski, Joonsuk Park, Roy Pea, Eugenia Ha Rim Rho, Zejiang Shen, Pao Siangliulue

Proceedings of the CHI Conference on Human Factors in Computing Systems, 2024

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

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, Blair Casey, Steve M. Gleason, Philip Q. Nelson, Michael P. Brenner

CoRR, 2023

Is Attention All That NeRF Needs?

Mukund Varma T., Peihao Wang, Xuxi Chen, Tianlong Chen, Subhashini Venugopalan, Zhangyang Wang

Proceedings of the Eleventh International Conference on Learning Representations, 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

Proceedings of the IEEE International Conference on Acoustics, 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

Proceedings of the Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, 2023

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

Proceedings of the 5th Clinical Natural Language Processing Workshop, 2023

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

Assessing ASR Model Quality on Disordered Speech using BERTScore.

Jimmy Tobin, Qisheng Li, Subhashini Venugopalan, Katie Seaver, Richard Cave, Katrin Tomanek

CoRR, 2022

Is Attention All NeRF Needs?

Mukund Varma T., Peihao Wang, Xuxi Chen, Tianlong Chen, Subhashini Venugopalan, Zhangyang Wang

CoRR, 2022

Sparse Winning Tickets are Data-Efficient Image Recognizers.

Mukund Varma T., Xuxi Chen, Zhenyu Zhang, Tianlong Chen, Subhashini Venugopalan, Zhangyang Wang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Context-Aware Abbreviation Expansion Using Large Language Models.

Shanqing Cai, Subhashini Venugopalan, Katrin Tomanek, Ajit Narayanan, Meredith Ringel Morris, Michael P. Brenner

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

TRILLsson: Distilled Universal Paralinguistic Speech Representations.

Joel Shor, Subhashini Venugopalan

Proceedings of the 23rd Annual Conference of the International Speech Communication Association, 2022

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

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

Proceedings of the 22nd Annual Conference of the International Speech Communication Association, Interspeech 2021, Brno, Czechia, August 30, 2021

Scaling Symbolic Methods using Gradients for Neural Model Explanation.

Subham Sekhar Sahoo, Subhashini Venugopalan, Li Li, Rishabh Singh, Patrick Riley

Proceedings of the 9th International Conference on Learning Representations, 2021

Guided Integrated Gradients: An Adaptive Path Method for Removing Noise.

Andrei Kapishnikov, Subhashini Venugopalan, Besim Avci, Ben Wedin, Michael Terry, Tolga Bolukbasi

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

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, Avinash V. Varadarajan, Naama Hammel, Yun Liu, Pinal Bavishi

CoRR, 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, Avinash V. Varadarajan

CoRR, 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

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Attribution in Scale and Space.

Shawn Xu, Subhashini Venugopalan, Mukund Sundararajan

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

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, Joao Pereira, Michael P. Brenner, Lee Rubin, Brian Wainger, Marc Berndl

CoRR, 2019

2018

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, Variya Nganthavee, Joe Ledsam, Pearse A. Keane, Gregory S. Corrado, Lily Peng, Dale R. Webster

CoRR, 2018

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

Detecting Cancer Metastases on Gigapixel Pathology Images.

Yun Liu, Krishna Gadepalli, Mohammad Norouzi, George E. Dahl, Timo Kohlberger, Aleksey Boyko, Subhashini Venugopalan, Aleksei Timofeev, Philip Q. Nelson, Gregory S. Corrado, Jason D. Hipp, Lily Peng, Martin C. Stumpe

CoRR, 2017

Semantic Text Summarization of Long Videos.

Shagan Sah, Sourabh Kulhare, Allison Gray, Subhashini Venugopalan, Emily Prud'hommeaux, Raymond W. Ptucha

Proceedings of the 2017 IEEE Winter Conference on Applications of Computer Vision, 2017

Captioning Images with Diverse Objects.

Subhashini Venugopalan, Lisa Anne Hendricks, Marcus Rohrbach, Raymond J. Mooney, Trevor Darrell, Kate Saenko

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Utilizing Large Scale Vision and Text Datasets for Image Segmentation from Referring Expressions.

Ronghang Hu, Marcus Rohrbach, Subhashini Venugopalan, Trevor Darrell

CoRR, 2016

Multimodal Video Description.

Vasili Ramanishka, Abir Das, Dong Huk Park, Subhashini Venugopalan, Lisa Anne Hendricks, Marcus Rohrbach, Kate Saenko

Proceedings of the 2016 ACM Conference on Multimedia Conference, 2016

Improving LSTM-based Video Description with Linguistic Knowledge Mined from Text.

Subhashini Venugopalan, Lisa Anne Hendricks, Raymond J. Mooney, Kate Saenko

Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016

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

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015

A Multi-scale Multiple Instance Video Description Network.

Huijuan Xu, Subhashini Venugopalan, Vasili Ramanishka, Marcus Rohrbach, Kate Saenko

CoRR, 2015

Translating Videos to Natural Language Using Deep Recurrent Neural Networks.

Subhashini Venugopalan, Huijuan Xu, Jeff Donahue, Marcus Rohrbach, Raymond J. Mooney, Kate Saenko

Proceedings of the NAACL HLT 2015, The 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Denver, Colorado, USA, May 31, 2015

Sequence to Sequence - Video to Text.

Subhashini Venugopalan, Marcus Rohrbach, Jeffrey Donahue, Raymond J. Mooney, Trevor Darrell, Kate Saenko

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

2014

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

Proceedings of the COLING 2014, 2014

2013

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

Proceedings of the IEEE International Conference on Computer Vision, 2013