Arjun Subramonian

Orcid: 0000-0002-0415-3800

According to our database1, Arjun Subramonian authored at least 19 papers between 2020 and 2024.

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Bibliography

2024
An Effective Theory of Bias Amplification.
CoRR, 2024

Strong Model Collapse.
CoRR, 2024

Stop! In the Name of Flaws: Disentangling Personal Names and Sociodemographic Attributes in NLP.
CoRR, 2024

Theoretical and Empirical Insights into the Origins of Degree Bias in Graph Neural Networks.
CoRR, 2024

Survey of Bias In Text-to-Image Generation: Definition, Evaluation, and Mitigation.
CoRR, 2024

Networked Inequality: Preferential Attachment Bias in Graph Neural Network Link Prediction.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Understanding "Democratization" in NLP and ML Research.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023
Bound by the Bounty: Collaboratively Shaping Evaluation Processes for Queer AI Harms.
CoRR, 2023

Weisfeiler and Lehman Go Measurement Modeling: Probing the Validity of the WL Test.
CoRR, 2023

Queer In AI: A Case Study in Community-Led Participatory AI.
CoRR, 2023


Factoring the Matrix of Domination: A Critical Review and Reimagination of Intersectionality in AI Fairness.
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

Bound by the Bounty: Collaboratively Shaping Evaluation Processes for Queer AI Harms.
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

It Takes Two to Tango: Navigating Conceptualizations of NLP Tasks and Measurements of Performance.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022
Queer in AI.
XRDS, 2022

On the Discrimination Risk of Mean Aggregation Feature Imputation in Graphs.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologies.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

MOTIF-Driven Contrastive Learning of Graph Representations.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Motif-Driven Contrastive Learning of Graph Representations.
CoRR, 2020


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