Search Results - "Subramonian, Arjun"

Motif-Driven Contrastive Learning of Graph Representations by Zhang, Shichang, Hu, Ziniu, Subramonian, Arjun, Sun, Yizhou

“…Pre-training Graph Neural Networks (GNN) via self-supervised contrastive learning has recently drawn lots of attention. However, most existing works focus on…”
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Automated, Cost-Effective Optical System for Accelerated Antimicrobial Susceptibility Testing (AST) Using Deep Learning by Brown, Calvin, Tseng, Derek, Larkin, Paige M. K, Realegeno, Susan, Mortimer, Leanne, Subramonian, Arjun, Di Carlo, Dino, Garner, Omai B, Ozcan, Aydogan

“…Antimicrobial susceptibility testing (AST) is a standard clinical procedure used to quantify antimicrobial resistance (AMR). Currently, the gold standard…”
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Theoretical and Empirical Insights into the Origins of Degree Bias in Graph Neural Networks by Subramonian, Arjun, Kang, Jian, Sun, Yizhou

“…Graph Neural Networks (GNNs) often perform better for high-degree nodes than low-degree nodes on node classification tasks. This degree bias can reinforce…”
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Networked Inequality: Preferential Attachment Bias in Graph Neural Network Link Prediction by Subramonian, Arjun, Sagun, Levent, Sun, Yizhou

“…Graph neural network (GNN) link prediction is increasingly deployed in citation, collaboration, and online social networks to recommend academic literature,…”
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Strong Model Collapse by Dohmatob, Elvis, Feng, Yunzhen, Subramonian, Arjun, Kempe, Julia

“…Within the scaling laws paradigm, which underpins the training of large neural networks like ChatGPT and Llama, we consider a supervised regression setting and…”
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An Effective Theory of Bias Amplification by Subramonian, Arjun, Bell, Samuel J, Sagun, Levent, Dohmatob, Elvis

“…Machine learning models may capture and amplify biases present in data, leading to disparate test performance across social groups. To better understand,…”
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Understanding "Democratization" in NLP and ML Research by Subramonian, Arjun, Gautam, Vagrant, Klakow, Dietrich, Talat, Zeerak

“…Recent improvements in natural language processing (NLP) and machine learning (ML) and increased mainstream adoption have led to researchers frequently…”
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Stop! In the Name of Flaws: Disentangling Personal Names and Sociodemographic Attributes in NLP by Gautam, Vagrant, Subramonian, Arjun, Lauscher, Anne, Keyes, Os

“…Personal names simultaneously differentiate individuals and categorize them in ways that are important in a given society. While the natural language…”
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Weisfeiler and Leman Go Measurement Modeling: Probing the Validity of the WL Test by Subramonian, Arjun, Williams, Adina, Nickel, Maximilian, Sun, Yizhou, Sagun, Levent

“…The expressive power of graph neural networks is usually measured by comparing how many pairs of graphs or nodes an architecture can possibly distinguish as…”
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It Takes Two to Tango: Navigating Conceptualizations of NLP Tasks and Measurements of Performance by Subramonian, Arjun, Yuan, Xingdi, DauméIII, Hal, Blodgett, Su Lin

“…Findings of the Association for Computational Linguistics: ACL 2023 Progress in NLP is increasingly measured through benchmarks; hence, contextualizing…”
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Rebuilding Trust: Queer in AI Approach to Artificial Intelligence Risk Management by Ashwin, Agnew, William, Pajaro, Umut, Jethwani, Hetvi, Subramonian, Arjun

“…Trustworthy artificial intelligence (AI) has become an important topic because trust in AI systems and their creators has been lost. Researchers, corporations,…”
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Survey of Bias In Text-to-Image Generation: Definition, Evaluation, and Mitigation by Wan, Yixin, Subramonian, Arjun, Ovalle, Anaelia, Lin, Zongyu, Suvarna, Ashima, Chance, Christina, Bansal, Hritik, Pattichis, Rebecca, Chang, Kai-Wei

“…The recent advancement of large and powerful models with Text-to-Image (T2I) generation abilities -- such as OpenAI's DALLE-3 and Google's Gemini -- enables…”
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Factoring the Matrix of Domination: A Critical Review and Reimagination of Intersectionality in AI Fairness by Ovalle, Anaelia, Subramonian, Arjun, Gautam, Vagrant, Gee, Gilbert, Chang, Kai-Wei

“…2023 AAAI/ACM Conference on AI, Ethics, and Society Intersectionality is a critical framework that, through inquiry and praxis, allows us to examine how social…”
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Motif-Driven Contrastive Learning of Graph Representations by Zhang, Shichang, Hu, Ziniu, Subramonian, Arjun, Sun, Yizhou

“…Pre-training Graph Neural Networks (GNN) via self-supervised contrastive learning has recently drawn lots of attention. However, most existing works focus on…”
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Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologies by Dev, Sunipa, Monajatipoor, Masoud, Ovalle, Anaelia, Subramonian, Arjun, Phillips, Jeff M, Chang, Kai-Wei

“…EMNLP 2021 Gender is widely discussed in the context of language tasks and when examining the stereotypes propagated by language models. However, current…”
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Bound by the Bounty: Collaboratively Shaping Evaluation Processes for Queer AI Harms by QueerInAI, Organizers of, Dennler, Nathan, Ovalle, Anaelia, Singh, Ashwin, Soldaini, Luca, Subramonian, Arjun, Tu, Huy, Agnew, William, Ghosh, Avijit, Yee, Kyra, Peradejordi, Irene Font, Talat, Zeerak, Russo, Mayra, Pinhal, Jess de Jesus de Pinho

“…2023 AAAI/ACM Conference on AI, Ethics, and Society Bias evaluation benchmarks and dataset and model documentation have emerged as central processes for…”
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Prompting Multilingual Large Language Models to Generate Code-Mixed Texts: The Case of South East Asian Languages by Yong, Zheng-Xin, Zhang, Ruochen, Forde, Jessica Zosa, Wang, Skyler, Subramonian, Arjun, Lovenia, Holy, Cahyawijaya, Samuel, Winata, Genta Indra, Sutawika, Lintang, Cruz, Jan Christian Blaise, Tan, Yin Lin, Phan, Long, Garcia, Rowena, Solorio, Thamar, Aji, Alham Fikri

“…While code-mixing is a common linguistic practice in many parts of the world, collecting high-quality and low-cost code-mixed data remains a challenge for…”
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Evaluating the Social Impact of Generative AI Systems in Systems and Society by Solaiman, Irene, Talat, Zeerak, Agnew, William, Ahmad, Lama, Baker, Dylan, Blodgett, Su Lin, Chen, Canyu, DauméIII, Hal, Dodge, Jesse, Duan, Isabella, Evans, Ellie, Friedrich, Felix, Ghosh, Avijit, Gohar, Usman, Hooker, Sara, Jernite, Yacine, Kalluri, Ria, Lusoli, Alberto, Leidinger, Alina, Lin, Michelle, Lin, Xiuzhu, Luccioni, Sasha, Mickel, Jennifer, Mitchell, Margaret, Newman, Jessica, Ovalle, Anaelia, Png, Marie-Therese, Singh, Shubham, Strait, Andrew, Struppek, Lukas, Subramonian, Arjun

“…Generative AI systems across modalities, ranging from text (including code), image, audio, and video, have broad social impacts, but there is no official…”
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Queer In AI: A Case Study in Community-Led Participatory AI by QueerInAI, Organizers Of, :, Ovalle, Anaelia, Subramonian, Arjun, Singh, Ashwin, Voelcker, Claas, Sutherland, Danica J, Locatelli, Davide, Breznik, Eva, Klubička, Filip, Yuan, Hang, J, Hetvi, Zhang, Huan, Shriram, Jaidev, Lehman, Kruno, Soldaini, Luca, Sap, Maarten, Deisenroth, Marc Peter, Pacheco, Maria Leonor, Ryskina, Maria, Mundt, Martin, Agarwal, Milind, McLean, Nyx, Xu, Pan, Pranav, A, Korpan, Raj, Ray, Ruchira, Mathew, Sarah, Arora, Sarthak, John, ST, Anand, Tanvi, Agrawal, Vishakha, Agnew, William, Long, Yanan, Wang, Zijie J, Talat, Zeerak, Ghosh, Avijit, Dennler, Nathaniel, Noseworthy, Michael, Jha, Sharvani, Baylor, Emi, Joshi, Aditya, Bilenko, Natalia Y, McNamara, Andrew, Gontijo-Lopes, Raphael, Markham, Alex, Dǒng, Evyn, Kay, Jackie, Saraswat, Manu, Vytla, Nikhil, Stark, Luke

“…2023 ACM Conference on Fairness, Accountability, and Transparency We present Queer in AI as a case study for community-led participatory design in AI. We…”
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An Automated, Cost-Effective Optical System for Accelerated Anti-microbial Susceptibility Testing (AST) using Deep Learning by Brown, Calvin, Tseng, Derek, Larkin, Paige M. K, Realegeno, Susan, Mortimer, Leanne, Subramonian, Arjun, Di Carlo, Dino, Garner, Omai B, Ozcan, Aydogan

“…ACS Photonics (2020) Antimicrobial susceptibility testing (AST) is a standard clinical procedure used to quantify antimicrobial resistance (AMR). Currently,…”
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