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Arjun Subramonian
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2020 – today
- 2024
- [c8]Arjun Subramonian, Levent Sagun, Yizhou Sun:
Networked Inequality: Preferential Attachment Bias in Graph Neural Network Link Prediction. ICML 2024 - [i12]Yixin Wan, Arjun Subramonian, Anaelia Ovalle, Zongyu Lin, Ashima Suvarna, Christina Chance, Hritik Bansal, Rebecca Pattichis, Kai-Wei Chang:
Survey of Bias In Text-to-Image Generation: Definition, Evaluation, and Mitigation. CoRR abs/2404.01030 (2024) - [i11]Arjun Subramonian, Jian Kang, Yizhou Sun:
Theoretical and Empirical Insights into the Origins of Degree Bias in Graph Neural Networks. CoRR abs/2404.03139 (2024) - [i10]Vagrant Gautam, Arjun Subramonian, Anne Lauscher, Os Keyes:
Stop! In the Name of Flaws: Disentangling Personal Names and Sociodemographic Attributes in NLP. CoRR abs/2405.17159 (2024) - [i9]Arjun Subramonian, Vagrant Gautam, Dietrich Klakow, Zeerak Talat:
Understanding "Democratization" in NLP and ML Research. CoRR abs/2406.11598 (2024) - 2023
- [c7]Arjun Subramonian, Xingdi Yuan, Hal Daumé III, Su Lin Blodgett:
It Takes Two to Tango: Navigating Conceptualizations of NLP Tasks and Measurements of Performance. ACL (Findings) 2023: 3234-3279 - [c6]Nathan Dennler, Anaelia Ovalle, Ashwin Singh, Luca Soldaini, Arjun Subramonian, Huy Tu, William Agnew, Avijit Ghosh, Kyra Yee, Irene Font Peradejordi, Zeerak Talat, Mayra Russo, Jessica de Jesus de Pinho Pinhal:
Bound by the Bounty: Collaboratively Shaping Evaluation Processes for Queer AI Harms. AIES 2023: 375-386 - [c5]Anaelia Ovalle, Arjun Subramonian, Vagrant Gautam, Gilbert Gee, Kai-Wei Chang:
Factoring the Matrix of Domination: A Critical Review and Reimagination of Intersectionality in AI Fairness. AIES 2023: 496-511 - [c4]Organizers Of QueerInAI, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J. Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi Jethwani, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx McLean, Pan Xu, Pranav A, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J. Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y. Bilenko, Andrew McNamara, Raphael Gontijo Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, Luke Stark:
Queer In AI: A Case Study in Community-Led Participatory AI. FAccT 2023: 1882-1895 - [i8]Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J. Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi Jethwani, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx McLean, Pan Xu, Pranav A, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J. Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y. Bilenko, Andrew McNamara, Raphael Gontijo Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, Luke Stark:
Queer In AI: A Case Study in Community-Led Participatory AI. CoRR abs/2303.16972 (2023) - [i7]Anaelia Ovalle, Arjun Subramonian, Vagrant Gautam, Gilbert Gee, Kai-Wei Chang:
Factoring the Matrix of Domination: A Critical Review and Reimagination of Intersectionality in AI Fairness. CoRR abs/2303.17555 (2023) - [i6]Arjun Subramonian, Xingdi Yuan, Hal Daumé III, Su Lin Blodgett:
It Takes Two to Tango: Navigating Conceptualizations of NLP Tasks and Measurements of Performance. CoRR abs/2305.09022 (2023) - [i5]Arjun Subramonian, Adina Williams, Maximilian Nickel, Yizhou Sun, Levent Sagun:
Weisfeiler and Lehman Go Measurement Modeling: Probing the Validity of the WL Test. CoRR abs/2307.05775 (2023) - [i4]Organizers Of QueerInAI, Nathaniel Dennler, Anaelia Ovalle, Ashwin Singh, Luca Soldaini, Arjun Subramonian, Huy Tu, William Agnew, Avijit Ghosh, Kyra Yee, Irene Font Peradejordi, Zeerak Talat, Mayra Russo, Jess de Jesus de Pinho Pinhal:
Bound by the Bounty: Collaboratively Shaping Evaluation Processes for Queer AI Harms. CoRR abs/2307.10223 (2023) - [i3]Arjun Subramonian, Levent Sagun, Yizhou Sun:
Networked Inequality: Preferential Attachment Bias in Graph Neural Network Link Prediction. CoRR abs/2309.17417 (2023) - 2022
- [j1]Hetvi Jethwani, Arjun Subramonian, William Agnew, MaryLena Bleile, Sarthak Arora, Maria Ryskina, Jeffrey Xiong:
Queer in AI. XRDS 28(4): 18-21 (2022) - [c3]Arjun Subramonian, Kai-Wei Chang, Yizhou Sun:
On the Discrimination Risk of Mean Aggregation Feature Imputation in Graphs. NeurIPS 2022 - 2021
- [c2]Arjun Subramonian:
MOTIF-Driven Contrastive Learning of Graph Representations. AAAI 2021: 15980-15981 - [c1]Sunipa Dev, Masoud Monajatipoor, Anaelia Ovalle, Arjun Subramonian, Jeff M. Phillips, Kai-Wei Chang:
Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologies. EMNLP (1) 2021: 1968-1994 - [i2]Sunipa Dev, Masoud Monajatipoor, Anaelia Ovalle, Arjun Subramonian, Jeff M. Phillips, Kai-Wei Chang:
Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologies. CoRR abs/2108.12084 (2021) - 2020
- [i1]Shichang Zhang, Ziniu Hu, Arjun Subramonian, Yizhou Sun:
Motif-Driven Contrastive Learning of Graph Representations. CoRR abs/2012.12533 (2020)
Coauthor Index
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