PhD in Computer Science at UMass Amherst.
I am a PhD student in Computer Science advised by Prof. Andrew McCallum. I am a member of Information Extraction and Synthesis Laboratory. I am broadly interested in natural language processing and machine learning. A bit more specifically, I am interested in representation learning methods, structured prediction models, clustering, nearest neighbor search and information retrieval.
I received my bachelors in Computer Science from IIT Delhi in 2017 where I worked with Prof. Amitabha Bagchi and Prof. Subodh Vishnu Sharma. I was a research intern at Big Data Experience Labs, Adobe, Bangalore in Summer 2016 where I worked with Sumit Shekhar.
Efficient Nearest Neighbor Search for Cross-Encoder Models using Matrix Factorization
Nishant Yadav, Nicholas Monath, Rico Angell, Manzil Zaheer, Andrew McCallum
To appear at EMNLP 2022.
[arXiv] [code] [pre-trained models]
Interactive Correlation Clustering with Existential Cluster Constraints
Rico Angell, Nicholas Monath, Nishant Yadav, Andrew McCallum
Robustness of Explanation Methods for NLP Models
Shriya Atmakuri, Tejas Chheda, Dinesh Kandula, Nishant Yadav, Taesung Lee, Hessel Tuinhof
Workshop on Trustworthy Artificial Intelligence at ECML/PKDD 2022.
Session-Aware Query Auto-completion using Extreme Multi-Label Ranking
Nishant Yadav, Rajat Sen, Daniel N. Hill, Arya Mazumdar, Inderjit S. Dhillon
[arXiv] [code] [talk] [blog] [bibtex]
Event & Entity Coreference using Trees to Encode Uncertainty in Joint Decisions
Nishant Yadav, Nicholas Monath, Rico Angell, Andrew McCallum
CRAC Workshop at EMNLP 2021. 🏆 Best Paper Award.
[talk] [slides] [bibtex]
SubSumE : A Dataset for Subjective Summary Extraction from Wikipedia Documents
Nishant Yadav*, Matteo Brucato*, Anna Fariha*, Oscar Youngquist, Julian Killingback, Alexandra Meliou, Peter J. Haas
NewSum Workshop at EMNLP 2021.
[data] [talk] [bibtex]
Clustering-based Inference for Zero-Shot Biomedical Entity Linking
Rico Angell, Nicholas Monath, Sunil Mohan, Nishant Yadav, Andrew McCallum
Stochastic Package Queries in Probabilistic Databases
Matteo Brucato, Nishant Yadav, Azza Abouzied, Peter J. Haas, Alexandra Meliou
[arXiv] [talk] [bibtex]
Supervised Hierarchical Clustering using Exponential Linkage
Nishant Yadav, Ari Kobren, Nicholas Monath, Andrew McCallum
International Conference of Machine Learning (ICML) 2019
[supplementary] [arXiv] [code] [bibtex]
Dynamic Partition Bloom Filters: A Bounded False Positive Solution For Dynamic Set Membership (Extended Abstract)
Sidharth Negi, Ameya Dubey, Amitabha Bagchi, Manish Yadav, Nishant Yadav, Jeetu Raj
arXiv preprint 2019 [Link]
VoCoG: An Intelligent, Non-Intrusive Assistant for Voice-based Collaborative Group-Viewing
Sumit Shekhar, Nishant Yadav, Anindya Shankar Bhandari, Aditya Siddhant
arXiv preprint 2018 [Link]