Nicholas Monath
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
33
Venues
13
Active years
2013–2025
Best venue rank
A*
Where they publish
Papers
33 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ACL | SIKeD: Self-guided Iterative Knowledge Distillation for Mathematical Reasoning. | Shivam Adarsh, Kumar Shridhar, Caglar Gulcehre, Nicholas Monath, Mrinmaya Sachan |
| 2025 | AISTATS | Fundamental Limits of Perfect Concept Erasure. | Somnath Basu Roy Chowdhury, Kumar Avinava Dubey, Ahmad Beirami, Rahul Kidambi, Nicholas Monath, Amr Ahmed, Snigdha Chaturvedi |
| 2025 | EMNLP | PRISM: Efficient Long-Range Reasoning With Short-Context LLMs. | Dulhan Jayalath, James Bradley Wendt, Nicholas Monath, Sandeep Tata, Beliz Gunel |
| 2024 | COLING | Sequence Reducible Holdout Loss for Language Model Pretraining. | Raghuveer Thirukovalluru, Nicholas Monath, Bhuwan Dhingra, Sam Wiseman |
| 2024 | EMNLP | Analysis of Plan-based Retrieval for Grounded Text Generation. | Ameya Godbole, Nicholas Monath, Seungyeon Kim, Ankit Singh Rawat, Andrew McCallum, Manzil Zaheer |
| 2024 | ICLR | Enhancing Group Fairness in Online Settings Using Oblique Decision Forests. | Somnath Basu Roy Chowdhury, Nicholas Monath, Ahmad Beirami, Rahul Kidambi, Kumar Avinava Dubey, Amr Ahmed, Snigdha Chaturvedi |
| 2024 | ICLR | Adaptive Retrieval and Scalable Indexing for k-NN Search with Cross-Encoders. | Nishant Yadav, Nicholas Monath, Manzil Zaheer, Rob Fergus, Andrew McCallum |
| 2024 | ICML | A Fresh Take on Stale Embeddings: Improving Dense Retriever Training with Corrector Networks. | Nicholas Monath, Will Sussman Grathwohl, Michael Boratko, Rob Fergus, Andrew McCallum, Manzil Zaheer |
| 2023 | AISTATS | Improving Dual-Encoder Training through Dynamic Indexes for Negative Mining. | Nicholas Monath, Manzil Zaheer, Kelsey Allen, Andrew McCallum |
| 2023 | EACL | Longtonotes: OntoNotes with Longer Coreference Chains. | Kumar Shridhar, Nicholas Monath, Raghuveer Thirukovalluru, Alessandro Stolfo, Manzil Zaheer, Andrew McCallum, Mrinmaya Sachan |
| 2023 | EMNLP | Unsupervised Opinion Summarization Using Approximate Geodesics. | Somnath Basu Roy Chowdhury, Nicholas Monath, Avinava Dubey, Amr Ahmed, Snigdha Chaturvedi |
| 2023 | EMNLP | Efficient k-NN Search with Cross-Encoders using Adaptive Multi-Round CUR Decomposition. | Nishant Yadav, Nicholas Monath, Manzil Zaheer, Andrew McCallum |
| 2023 | KDD | Online Level-wise Hierarchical Clustering. | Nicholas Monath, Manzil Zaheer, Andrew McCallum |
| 2022 | AAAI | An Evaluative Measure of Clustering Methods Incorporating Hyperparameter Sensitivity. | Siddhartha Mishra, Nicholas Monath, Michael Boratko, Ariel Kobren, Andrew McCallum |
| 2022 | AAAI | Sublinear Time Approximation of Text Similarity Matrices. | Archan Ray, Nicholas Monath, Andrew McCallum, Cameron Musco |
| 2022 | EMNLP | Autoregressive Structured Prediction with Language Models. | Tianyu Liu, Yuchen Eleanor Jiang, Nicholas Monath, Ryan Cotterell, Mrinmaya Sachan |
| 2022 | EMNLP | Efficient Nearest Neighbor Search for Cross-Encoder Models using Matrix Factorization. | Nishant Yadav, Nicholas Monath, Rico Angell, Manzil Zaheer, Andrew McCallum |
| 2022 | ICML | Interactive Correlation Clustering with Existential Cluster Constraints. | Rico Angell, Nicholas Monath, Nishant Yadav, Andrew McCallum |
| 2022 | NAACL | Entity Linking via Explicit Mention-Mention Coreference Modeling. | Dhruv Agarwal, Rico Angell, Nicholas Monath, Andrew McCallum |
| 2021 | ACL | Scaling Within Document Coreference to Long Texts. | Raghuveer Thirukovalluru, Nicholas Monath, Kumar Shridhar, Manzil Zaheer, Mrinmaya Sachan, Andrew McCallum |
| 2021 | AISTATS | Cluster Trellis: Data Structures & Algorithms for Exact Inference in Hierarchical Clustering. | Sebastian Macaluso, Craig S. Greenberg, Nicholas Monath, Ji Ah Lee, Patrick Flaherty, Kyle Cranmer, Andrew McGregor, Andrew McCallum |
| 2021 | AISTATS | DAG-Structured Clustering by Nearest Neighbors. | Nicholas Monath, Manzil Zaheer, Kumar Avinava Dubey, Amr Ahmed, Andrew McCallum |
| 2021 | KDD | Scalable Hierarchical Agglomerative Clustering. | Nicholas Monath, Kumar Avinava Dubey, Guru Guruganesh, Manzil Zaheer, Amr Ahmed, Andrew McCallum, Gkhan Mergen, Marc Najork, Mert Terzihan, Bryon Tjanaka, Yuan Wang, Yuchen Wu |
| 2021 | NAACL | Clustering-based Inference for Biomedical Entity Linking. | Rico Angell, Nicholas Monath, Sunil Mohan, Nishant Yadav, Andrew McCallum |
| 2021 | UAI | Exact and approximate hierarchical clustering using A. | Craig S. Greenberg, Sebastian Macaluso, Nicholas Monath, Avinava Dubey, Patrick Flaherty, Manzil Zaheer, Amr Ahmed, Kyle Cranmer, Andrew McCallum |
| 2020 | EMNLP | Probabilistic Case-based Reasoning in Knowledge Bases. | Rajarshi Das, Ameya Godbole, Nicholas Monath, Manzil Zaheer, Andrew McCallum |
| 2019 | ACL | Optimal Transport-based Alignment of Learned Character Representations for String Similarity. | Derek Tam, Nicholas Monath, Ari Kobren, Aaron Traylor, Rajarshi Das, Andrew McCallum |
| 2019 | ICML | Supervised Hierarchical Clustering with Exponential Linkage. | Nishant Yadav, Ari Kobren, Nicholas Monath, Andrew McCallum |
| 2019 | KDD | Scalable Hierarchical Clustering with Tree Grafting. | Nicholas Monath, Ari Kobren, Akshay Krishnamurthy, Michael R. Glass, Andrew McCallum |
| 2019 | KDD | Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space. | Nicholas Monath, Manzil Zaheer, Daniel Silva, Andrew McCallum, Amr Ahmed |
| 2018 | Interspeech | Play Duration Based User-Entity Affinity Modeling in Spoken Dialog System. | Bo Xiao, Nicholas Monath, Shankar Ananthakrishnan, Abishek Ravi |
| 2017 | KDD | A Hierarchical Algorithm for Extreme Clustering. | Ari Kobren, Nicholas Monath, Akshay Krishnamurthy, Andrew McCallum |
| 2013 | DCC | Compression of Optimal Value Functions for Markov Decision Processes. | Mykel J. Kochenderfer, Nicholas Monath |