I am a PhD candidate in the Computer Science Department at Cornell University, where I am advised by Kilian Q Weinberger. I work on applied machine learning broadly. Currently, I’m interested in developing end-to-end document retrieval methods and improving text diffusion models. In the past I’ve also worked on text evaluation metrics and steganography.
During my PhD, I’ve interned at Google with Ni Lao and John Blitzer, at Microsoft Research with Tristan Nauman and at ASAPP with David Sontag.
Before joining Cornell, I completed my undergraduate degree in Math and Computer Science at Harvey Mudd College. There, I conducted research in algorithms for computational biology with Prof. Yi-Chieh (Jessica) Wu.
Outside of research, I enjoy climbing, playing basketball and exploring the outdoors!
Publications and Preprints
Latent Diffusion for Language Generation
Justin Lovelace, Varsha Kishore, Chao Wan, Eliot Shaktman, and Kilian Q Weinberger
In Advances in Neural Information Processing Systems (NeurIPS ), 2023.
@inproceedings { lovelace2022latent ,
title = {Latent Diffusion for Language Generation} ,
author = {Lovelace, Justin and Kishore, Varsha and Wan, Chao and Shaktman, Eliot and Weinberger, Kilian Q} ,
booktitle = {Advances in Neural Information Processing Systems} ,
acronym = {NeurIPS} ,
year = {2023} ,
}
IncDSI: Incrementally Updatable Document Retrieval
Varsha Kishore, Chao Wan, Justin Lovelace, Yoav Artzi, and Kilian Q Weinberger
In International Conference on Machine Learning (ICML ), 2023.
@inproceedings { kishore2023incdsi ,
title = {IncDSI: Incrementally Updatable Document Retrieval} ,
author = {Kishore, Varsha and Wan, Chao and Lovelace, Justin and Artzi, Yoav and Weinberger, Kilian Q} ,
booktitle = {International Conference on Machine Learning} ,
acronym = {ICML} ,
year = {2023} ,
}
Correction with Backtracking Reduces Hallucination in Summarization
Zhenzhen Liu, Chao Wan, Varsha Kishore, Jin Zhou, Minmin Chen, and
1 more author
In arXiv preprint arXiv:2310.16176 , 2023.
@inproceedings { liu2023correction ,
title = {Correction with Backtracking Reduces Hallucination in Summarization} ,
author = {Liu, Zhenzhen and Wan, Chao and Kishore, Varsha and Zhou, Jin and Chen, Minmin and Weinberger, Kilian Q} ,
booktitle = {arXiv preprint arXiv:2310.16176} ,
year = {2023} ,
}
Learning Iterative Neural Optimizers for Image Steganography
Varsha Kishore, Xiangyu Chen, and Kilian Q Weinberger
In International Conference on Learning Representations (ICLR ), 2022.
@inproceedings { chen2023learning ,
title = {Learning Iterative Neural Optimizers for Image Steganography} ,
author = {Kishore, Varsha and Chen, Xiangyu and Weinberger, Kilian Q} ,
booktitle = {International Conference on Learning Representations} ,
acronym = {ICLR} ,
year = {2022} ,
}
Harnessing interpretable and unsupervised machine learning to address big data from modern X-ray diffraction
Jordan Venderley, Krishnanand Mallayya, Michael Matty, Matthew Krogstad, Jacob Ruff, and
6 more authors
Proceedings of the National Academy of Sciences , 2022.
Fixed Neural Network Steganography: Train the images, not the network
Varsha Kishore, Xiangyu Chen, Yan Wang, Boyi Li, and Kilian Q Weinberger
In International Conference on Learning Representations (ICLR ), 2021.
@inproceedings { kishore2021fixed ,
title = {Fixed Neural Network Steganography: Train the images, not the network} ,
author = {Kishore, Varsha and Chen, Xiangyu and Wang, Yan and Li, Boyi and Weinberger, Kilian Q} ,
booktitle = {International Conference on Learning Representations} ,
acronym = {ICLR} ,
year = {2021} ,
}
Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi
In International Conference on Learning Representations (ICLR ), 2019.
@inproceedings { zhang2019bertscore ,
title = {Bertscore: Evaluating text generation with bert} ,
author = {Zhang, Tianyi and Kishore, Varsha and Wu, Felix and Weinberger, Kilian Q and Artzi, Yoav} ,
booktitle = {International Conference on Learning Representations} ,
acronym = {ICLR} ,
year = {2019} ,
}
Teaching
Cornell University
Harvey Mudd College
Head TA for CS140: Algorithms
TA for CS42: Principles and Practice of Computer Science
TA for CS70: Data Structures and Program Development
TA for CS158: Machine Learning
Contact