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ORCIDNicholas Monath
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Journal Articles
- 2024
[j1]Somnath Basu Roy Chowdhury, Nicholas Monath, Kumar Avinava Dubey, Manzil Zaheer, Andrew McCallum, Amr Ahmed, Snigdha Chaturvedi:
Incremental Extractive Opinion Summarization Using Cover Trees. Trans. Mach. Learn. Res. 2024 (2024)
Conference and Workshop Papers
- 2024
- [c39]Raghuveer Thirukovalluru, Nicholas Monath, Bhuwan Dhingra, Sam Wiseman:
Sequence Reducible Holdout Loss for Language Model Pretraining. LREC/COLING 2024: 14705-14716 - [c38]Somnath Basu Roy Chowdhury, Nicholas Monath, Ahmad Beirami, Rahul Kidambi, Kumar Avinava Dubey, Amr Ahmed, Snigdha Chaturvedi:
Enhancing Group Fairness in Online Settings Using Oblique Decision Forests. ICLR 2024 - [c37]Nishant Yadav, Nicholas Monath, Manzil Zaheer, Rob Fergus, Andrew McCallum:
Adaptive Retrieval and Scalable Indexing for k-NN Search with Cross-Encoders. ICLR 2024 - [c36]Nicholas Monath, Will Sussman Grathwohl, Michael Boratko, Rob Fergus, Andrew McCallum, Manzil Zaheer:
A Fresh Take on Stale Embeddings: Improving Dense Retriever Training with Corrector Networks. ICML 2024 - 2023
- [c35]Nicholas Monath, Manzil Zaheer, Kelsey Allen, Andrew McCallum:
Improving Dual-Encoder Training through Dynamic Indexes for Negative Mining. AISTATS 2023: 9308-9330 - [c34]Kumar Shridhar, Nicholas Monath, Raghuveer Thirukovalluru, Alessandro Stolfo, Manzil Zaheer, Andrew McCallum, Mrinmaya Sachan:
Longtonotes: OntoNotes with Longer Coreference Chains. EACL (Findings) 2023: 1398-1412 - [c33]Somnath Basu Roy Chowdhury, Nicholas Monath, Kumar Dubey, Amr Ahmed, Snigdha Chaturvedi:
Unsupervised Opinion Summarization Using Approximate Geodesics. EMNLP (Findings) 2023: 97-112 - [c32]Nishant Yadav, Nicholas Monath, Manzil Zaheer, Andrew McCallum:
Efficient k-NN Search with Cross-Encoders using Adaptive Multi-Round CUR Decomposition. EMNLP (Findings) 2023: 8088-8103 - [c31]Nicholas Monath
, Manzil Zaheer, Andrew McCallum:
Online Level-wise Hierarchical Clustering. KDD 2023: 1733-1745 - [c30]Somnath Basu Roy Chowdhury, Nicholas Monath, Kumar Avinava Dubey, Amr Ahmed, Snigdha Chaturvedi:
Robust Concept Erasure via Kernelized Rate-Distortion Maximization. NeurIPS 2023 - 2022
- [c29]Siddhartha Mishra, Nicholas Monath, Michael Boratko, Ariel Kobren, Andrew McCallum:
An Evaluative Measure of Clustering Methods Incorporating Hyperparameter Sensitivity. AAAI 2022: 7788-7796 - [c28]Archan Ray, Nicholas Monath, Andrew McCallum, Cameron Musco:
Sublinear Time Approximation of Text Similarity Matrices. AAAI 2022: 8072-8080 - [c27]Tianyu Liu, Yuchen Eleanor Jiang, Nicholas Monath, Ryan Cotterell, Mrinmaya Sachan:
Autoregressive Structured Prediction with Language Models. EMNLP (Findings) 2022: 993-1005 - [c26]Nishant Yadav, Nicholas Monath, Rico Angell, Manzil Zaheer, Andrew McCallum:
Efficient Nearest Neighbor Search for Cross-Encoder Models using Matrix Factorization. EMNLP 2022: 2171-2194 - [c25]Rico Angell, Nicholas Monath, Nishant Yadav, Andrew McCallum:
Interactive Correlation Clustering with Existential Cluster Constraints. ICML 2022: 703-716 - [c24]Dhruv Agarwal, Rico Angell, Nicholas Monath, Andrew McCallum:
Entity Linking via Explicit Mention-Mention Coreference Modeling. NAACL-HLT 2022: 4644-4658 - 2021
- [c23]Raghuveer Thirukovalluru, Nicholas Monath, Kumar Shridhar, Manzil Zaheer, Mrinmaya Sachan, Andrew McCallum:
Scaling Within Document Coreference to Long Texts. ACL/IJCNLP (Findings) 2021: 3921-3931 - [c22]Sebastian Macaluso, Craig S. Greenberg, Nicholas Monath, Ji Ah Lee, Patrick Flaherty, Kyle Cranmer, Andrew McGregor, Andrew McCallum:
Cluster Trellis: Data Structures & Algorithms for Exact Inference in Hierarchical Clustering. AISTATS 2021: 2467-2475 - [c21]Nicholas Monath, Manzil Zaheer, Kumar Avinava Dubey, Amr Ahmed, Andrew McCallum:
DAG-Structured Clustering by Nearest Neighbors. AISTATS 2021: 2854-2862 - [c20]Sunil Mohan, Rico Angell, Nicholas Monath, Andrew McCallum:
Low resource recognition and linking of biomedical concepts from a large ontology. BCB 2021: 54:1-54:10 - [c19]Nicholas Monath, Kumar Avinava Dubey, Guru Guruganesh, Manzil Zaheer, Amr Ahmed, Andrew McCallum, Gökhan Mergen, Marc Najork, Mert Terzihan, Bryon Tjanaka, Yuan Wang, Yuchen Wu:
Scalable Hierarchical Agglomerative Clustering. KDD 2021: 1245-1255 - [c18]Rico Angell, Nicholas Monath, Sunil Mohan, Nishant Yadav, Andrew McCallum:
Clustering-based Inference for Biomedical Entity Linking. NAACL-HLT 2021: 2598-2608 - [c17]Michael Boratko, Dongxu Zhang, Nicholas Monath, Luke Vilnis, Kenneth L. Clarkson, Andrew McCallum:
Capacity and Bias of Learned Geometric Embeddings for Directed Graphs. NeurIPS 2021: 16423-16436 - [c16]Raghuveer Thirukovalluru, Mukund Sridhar, Dung Thai, Shruti Chanumolu, Nicholas Monath, Sankaranarayanan Ananthakrishnan, Andrew McCallum:
Knowledge Informed Semantic Parsing for Conversational Question Answering. RepL4NLP@ACL-IJCNLP 2021: 231-240 - [c15]Craig S. Greenberg, Sebastian Macaluso, Nicholas Monath, Avinava Dubey, Patrick Flaherty, Manzil Zaheer, Amr Ahmed, Kyle Cranmer, Andrew McCallum:
Exact and approximate hierarchical clustering using A. UAI 2021: 2061-2071 - 2020
- [c14]Derek Tam, Nicholas Monath, Ari Kobren, Andrew McCallum:
Predicting Institution Hierarchies with Set-based Models. AKBC 2020 - [c13]Dung Thai, Zhiyang Xu, Nicholas Monath, Boris Veytsman, Andrew McCallum:
Using BibTeX to Automatically Generate Labeled Data for Citation Field Extraction. AKBC 2020 - [c12]Rajarshi Das, Ameya Godbole, Nicholas Monath, Manzil Zaheer, Andrew McCallum:
Probabilistic Case-based Reasoning in Knowledge Bases. EMNLP (Findings) 2020: 4752-4765 - 2019
- [c11]Derek Tam, Nicholas Monath, Ari Kobren, Aaron Traylor, Rajarshi Das, Andrew McCallum:
Optimal Transport-based Alignment of Learned Character Representations for String Similarity. ACL (1) 2019: 5907-5917 - [c10]Ari Kobren, Nicholas Monath, Andrew McCallum:
Integrating User Feedback under Identity Uncertainty in Knowledge Base Construction. AKBC 2019 - [c9]Nishant Yadav, Ari Kobren, Nicholas Monath, Andrew McCallum:
Supervised Hierarchical Clustering with Exponential Linkage. ICML 2019: 6973-6983 - [c8]Nicholas Monath, Manzil Zaheer, Daniel Silva, Andrew McCallum, Amr Ahmed:
Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space. KDD 2019: 714-722 - [c7]Nicholas Monath, Ari Kobren, Akshay Krishnamurthy, Michael R. Glass, Andrew McCallum:
Scalable Hierarchical Clustering with Tree Grafting. KDD 2019: 1438-1448 - 2018
- [c6]Bo Xiao, Nicholas Monath, Shankar Ananthakrishnan, Abishek Ravi:
Play Duration Based User-Entity Affinity Modeling in Spoken Dialog System. INTERSPEECH 2018: 2057-2061 - [c5]Craig S. Greenberg, Nicholas Monath, Ari Kobren, Patrick Flaherty, Andrew McGregor, Andrew McCallum:
Compact Representation of Uncertainty in Clustering. NeurIPS 2018: 8639-8649 - 2017
- [c4]Ari Kobren, Nicholas Monath, Andrew McCallum:
Entity-centric Attribute Feedback for Interactive Knowledge Bases. AKBC@NIPS 2017 - [c3]Aaron Traylor, Nicholas Monath, Rajarshi Das, Andrew McCallum:
Learning String Alignments for Entity Aliases. AKBC@NIPS 2017 - [c2]Ari Kobren, Nicholas Monath, Akshay Krishnamurthy, Andrew McCallum:
A Hierarchical Algorithm for Extreme Clustering. KDD 2017: 255-264 - 2013
- [c1]Mykel J. Kochenderfer, Nicholas Monath:
Compression of Optimal Value Functions for Markov Decision Processes. DCC 2013: 501
Informal and Other Publications
- 2024
- [i29]Somnath Basu Roy Chowdhury, Nicholas Monath, Avinava Dubey, Manzil Zaheer, Andrew McCallum, Amr Ahmed, Snigdha Chaturvedi:
Incremental Extractive Opinion Summarization Using Cover Trees. CoRR abs/2401.08047 (2024) - [i28]Nishant Yadav, Nicholas Monath, Manzil Zaheer, Rob Fergus, Andrew McCallum:
Adaptive Retrieval and Scalable Indexing for k-NN Search with Cross-Encoders. CoRR abs/2405.03651 (2024) - [i27]Ameya Godbole, Nicholas Monath, Seungyeon Kim, Ankit Singh Rawat, Andrew McCallum, Manzil Zaheer:
Analysis of Plan-based Retrieval for Grounded Text Generation. CoRR abs/2408.10490 (2024) - [i26]Nicholas Monath, Will Grathwohl, Michael Boratko, Rob Fergus, Andrew McCallum, Manzil Zaheer:
A Fresh Take on Stale Embeddings: Improving Dense Retriever Training with Corrector Networks. CoRR abs/2409.01890 (2024) - 2023
- [i25]Nicholas Monath, Manzil Zaheer, Kelsey Allen, Andrew McCallum:
Improving Dual-Encoder Training through Dynamic Indexes for Negative Mining. CoRR abs/2303.15311 (2023) - [i24]Nishant Yadav, Nicholas Monath, Manzil Zaheer, Andrew McCallum:
Adaptive Selection of Anchor Items for CUR-based k-NN search with Cross-Encoders. CoRR abs/2305.02996 (2023) - [i23]Somnath Basu Roy Chowdhury, Nicholas Monath, Ahmad Beirami, Rahul Kidambi, Avinava Dubey, Amr Ahmed, Snigdha Chaturvedi:
Enhancing Group Fairness in Online Settings Using Oblique Decision Forests. CoRR abs/2310.11401 (2023) - [i22]Somnath Basu Roy Chowdhury, Nicholas Monath, Avinava Dubey, Amr Ahmed, Snigdha Chaturvedi:
Robust Concept Erasure via Kernelized Rate-Distortion Maximization. CoRR abs/2312.00194 (2023) - 2022
- [i21]Somnath Basu Roy Chowdhury, Nicholas Monath, Avinava Dubey, Amr Ahmed, Snigdha Chaturvedi:
Unsupervised Opinion Summarization Using Approximate Geodesics. CoRR abs/2209.07496 (2022) - [i20]Kumar Shridhar, Nicholas Monath, Raghuveer Thirukovalluru, Alessandro Stolfo, Manzil Zaheer, Andrew McCallum, Mrinmaya Sachan:
Longtonotes: OntoNotes with Longer Coreference Chains. CoRR abs/2210.03650 (2022) - [i19]Nishant Yadav, Nicholas Monath, Rico Angell, Manzil Zaheer, Andrew McCallum:
Efficient Nearest Neighbor Search for Cross-Encoder Models using Matrix Factorization. CoRR abs/2210.12579 (2022) - [i18]Tianyu Liu, Yuchen Jiang, Nicholas Monath, Ryan Cotterell, Mrinmaya Sachan:
Autoregressive Structured Prediction with Language Models. CoRR abs/2210.14698 (2022) - 2021
- [i17]Sunil Mohan, Rico Angell, Nicholas Monath, Andrew McCallum:
Low Resource Recognition and Linking of Biomedical Concepts from a Large Ontology. CoRR abs/2101.10587 (2021) - [i16]Ethan Shen, Maria Brbic, Nicholas Monath, Jiaqi Zhai, Manzil Zaheer, Jure Leskovec:
Model-Agnostic Graph Regularization for Few-Shot Learning. CoRR abs/2102.07077 (2021) - [i15]Craig S. Greenberg, Sebastian Macaluso, Nicholas Monath, Avinava Dubey, Patrick Flaherty, Manzil Zaheer, Amr Ahmed, Kyle Cranmer, Andrew McCallum:
Exact and Approximate Hierarchical Clustering Using A. CoRR abs/2104.07061 (2021) - [i14]Dhruv Agarwal, Rico Angell, Nicholas Monath, Andrew McCallum:
Entity Linking and Discovery via Arborescence-based Supervised Clustering. CoRR abs/2109.01242 (2021) - [i13]Archan Ray, Nicholas Monath, Andrew McCallum, Cameron Musco:
Sublinear Time Approximation of Text Similarity Matrices. CoRR abs/2112.09631 (2021) - 2020
- [i12]Nicholas Monath, Ari Kobren, Akshay Krishnamurthy, Michael R. Glass, Andrew McCallum:
Scalable Hierarchical Clustering with Tree Grafting. CoRR abs/2001.00076 (2020) - [i11]Craig S. Greenberg, Sebastian Macaluso, Nicholas Monath, Ji Ah Lee, Patrick Flaherty, Kyle Cranmer, Andrew McGregor, Andrew McCallum:
Compact Representation of Uncertainty in Hierarchical Clustering. CoRR abs/2002.11661 (2020) - [i10]Dung Thai, Zhiyang Xu, Nicholas Monath, Boris Veytsman, Andrew McCallum:
Using BibTeX to Automatically Generate Labeled Data for Citation Field Extraction. CoRR abs/2006.05563 (2020) - [i9]Rajarshi Das, Ameya Godbole, Nicholas Monath, Manzil Zaheer, Andrew McCallum:
Probabilistic Case-based Reasoning for Open-World Knowledge Graph Completion. CoRR abs/2010.03548 (2020) - [i8]Rico Angell, Nicholas Monath, Sunil Mohan, Nishant Yadav, Andrew McCallum:
Clustering-based Inference for Zero-Shot Biomedical Entity Linking. CoRR abs/2010.11253 (2020) - [i7]Nicholas Monath, Avinava Dubey, Guru Guruganesh, Manzil Zaheer, Amr Ahmed, Andrew McCallum, Gökhan Mergen, Marc Najork, Mert Terzihan, Bryon Tjanaka, Yuan Wang, Yuchen Wu:
Scalable Bottom-Up Hierarchical Clustering. CoRR abs/2010.11821 (2020) - 2019
- [i6]Nishant Yadav, Ari Kobren, Nicholas Monath, Andrew McCallum:
Supervised Hierarchical Clustering with Exponential Linkage. CoRR abs/1906.07859 (2019) - [i5]Derek Tam, Nicholas Monath, Ari Kobren, Aaron Traylor, Rajarshi Das, Andrew McCallum:
Optimal Transport-based Alignment of Learned Character Representations for String Similarity. CoRR abs/1907.10165 (2019) - 2018
- [i4]Bo Xiao, Nicholas Monath, Shankar Ananthakrishnan, Abishek Ravi:
Play Duration based User-Entity Affinity Modeling in Spoken Dialog System. CoRR abs/1806.11479 (2018) - 2017
- [i3]Ari Kobren, Nicholas Monath, Akshay Krishnamurthy, Andrew McCallum:
An Online Hierarchical Algorithm for Extreme Clustering. CoRR abs/1704.01858 (2017) - 2016
- [i2]Haw-Shiuan Chang, Abdurrahman Munir, Ao Liu, Johnny Tian-Zheng Wei, Aaron Traylor, Ajay Nagesh, Nicholas Monath, Patrick Verga, Emma Strubell, Andrew McCallum:
Extracting Multilingual Relations under Limited Resources: TAC 2016 Cold-Start KB construction and Slot-Filling using Compositional Universal Schema. TAC 2016 - 2015
- [i1]Benjamin Roth, Nicholas Monath, David Belanger, Emma Strubell, Patrick Verga, Andrew McCallum:
Building Knowledge Bases with Universal Schema: Cold Start and Slot-Filling Approaches. TAC 2015
Coauthor Index
aka: Kumar Avinava Dubey
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