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ORCIDAri Kobren
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- affiliation: Oracle Labs, Burlington, MA, USA
- affiliation: University of Massachusetts, Amherst, School of Computer Science, USA
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2020 – today
- 2024
[c19]Sagi Shaier, Ari Kobren, Philip V. Ogren:
Adaptive Question Answering: Enhancing Language Model Proficiency for Addressing Knowledge Conflicts with Source Citations. EMNLP 2024: 17226-17239- [i10]Muhammad Ali, Swetasudha Panda, Qinlan Shen, Michael L. Wick, Ari Kobren:
Understanding the Interplay of Scale, Data, and Bias in Language Models: A Case Study with BERT. CoRR abs/2407.21058 (2024) - [i9]Sagi Shaier, Ari Kobren, Philip V. Ogren:
Adaptive Question Answering: Enhancing Language Model Proficiency for Addressing Knowledge Conflicts with Source Citations. CoRR abs/2410.04241 (2024) - 2022
- [c18]Siddhartha Mishra, Nicholas Monath, Michael Boratko, Ariel Kobren, Andrew McCallum:
An Evaluative Measure of Clustering Methods Incorporating Hyperparameter Sensitivity. AAAI 2022: 7788-7796 - [c17]Ryan Steed
, Swetasudha Panda, Ari Kobren, Michael L. Wick:
Upstream Mitigation Is Not All You Need: Testing the Bias Transfer Hypothesis in Pre-Trained Language Models. ACL (1) 2022: 3524-3542 - [c16]Swetasudha Panda, Ari Kobren, Michael L. Wick, Qinlan Shen:
Don't Just Clean It, Proxy Clean It: Mitigating Bias by Proxy in Pre-Trained Models. EMNLP (Findings) 2022: 5073-5085 - 2021
- [c15]Ananya Gupta, Eric Johnson, Justin Payan, Aditya Kumar Roy, Ari Kobren, Swetasudha Panda, Jean-Baptiste Tristan, Michael L. Wick:
Online Post-Processing in Rankings for Fair Utility Maximization. WSDM 2021: 454-462 - 2020
- [c14]Derek Tam, Nicholas Monath, Ari Kobren, Andrew McCallum:
Predicting Institution Hierarchies with Set-based Models. AKBC 2020 - [c13]Naveen Jafer Nizar, Ari Kobren:
Leveraging Extracted Model Adversaries for Improved Black Box Attacks. BlackboxNLP@EMNLP 2020: 57-67 - [i8]Nicholas Monath, Ari Kobren, Akshay Krishnamurthy, Michael R. Glass, Andrew McCallum:
Scalable Hierarchical Clustering with Tree Grafting. CoRR abs/2001.00076 (2020) - [i7]Naveen Jafer Nizar, Ari Kobren:
Leveraging Extracted Model Adversaries for Improved Black Box Attacks. CoRR abs/2010.16336 (2020)
2010 – 2019
- 2019
- [c12]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 - [c11]Ari Kobren, Nicholas Monath, Andrew McCallum:
Integrating User Feedback under Identity Uncertainty in Knowledge Base Construction. AKBC 2019 - [c10]Nishant Yadav, Ari Kobren, Nicholas Monath, Andrew McCallum:
Supervised Hierarchical Clustering with Exponential Linkage. ICML 2019: 6973-6983 - [c9]Ari Kobren, Barna Saha, Andrew McCallum:
Paper Matching with Local Fairness Constraints. KDD 2019: 1247-1257 - [c8]Nicholas Monath, Ari Kobren, Akshay Krishnamurthy, Michael R. Glass, Andrew McCallum:
Scalable Hierarchical Clustering with Tree Grafting. KDD 2019: 1438-1448 - [c7]Ari Kobren, Pablo Barrio, Oksana Yakhnenko, Johann Hibschman, Ian Langmore:
Constructing High Precision Knowledge Bases with Subjective and Factual Attributes. KDD 2019: 2050-2058 - [c6]Blossom Metevier, Stephen Giguere, Sarah Brockman, Ari Kobren, Yuriy Brun, Emma Brunskill, Philip S. Thomas:
Offline Contextual Bandits with High Probability Fairness Guarantees. NeurIPS 2019: 14893-14904 - [i6]Ari Kobren, Barna Saha, Andrew McCallum:
Paper Matching with Local Fairness Constraints. CoRR abs/1905.11924 (2019) - [i5]Ari Kobren, Pablo Barrio, Oksana Yakhnenko, Johann Hibschman, Ian Langmore:
Constructing High Precision Knowledge Bases with Subjective and Factual Attributes. CoRR abs/1905.12807 (2019) - [i4]Nishant Yadav, Ari Kobren, Nicholas Monath, Andrew McCallum:
Supervised Hierarchical Clustering with Exponential Linkage. CoRR abs/1906.07859 (2019) - [i3]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
- [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]Ari Kobren, Nicholas Monath, Akshay Krishnamurthy, Andrew McCallum:
A Hierarchical Algorithm for Extreme Clustering. KDD 2017: 255-264 - [i2]Ari Kobren, Nicholas Monath, Akshay Krishnamurthy, Andrew McCallum:
An Online Hierarchical Algorithm for Extreme Clustering. CoRR abs/1704.01858 (2017) - 2015
- [c2]Ari Kobren, Chun How Tan, Panagiotis G. Ipeirotis, Evgeniy Gabrilovich:
Getting More for Less: Optimized Crowdsourcing with Dynamic Tasks and Goals. WWW 2015: 592-602 - 2013
- [c1]Michael L. Wick, Sameer Singh, Ari Kobren, Andrew McCallum:
Assessing confidence of knowledge base content with an experimental study in entity resolution. AKBC@CIKM 2013: 13-18 - [i1]Sameer Singh, Limin Yao, David Belanger, Ari Kobren, Sam Anzaroot, Mike Wick, Alexandre Passos, Harshal Pandya, Jinho D. Choi, Brian Martin, Andrew McCallum:
Universal Schema for Slot Filling and Cold Start: UMass IESL at TACKBP 2013. TAC 2013
Coauthor Index
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