About Me
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.
Publications
-
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
ICML 2022.
-
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
KDD 2021.
[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
NAACL 2021.
[arXiv] [bibtex] -
Stochastic Package Queries in Probabilistic Databases
Matteo Brucato, Nishant Yadav, Azza Abouzied, Peter J. Haas, Alexandra Meliou
SIGMOD 2020.
[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]