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Aylin Caliskan
Aylin Caliskan Islam
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2020 – today
- 2024
- [c36]Yiwei Yang, Anthony Z. Liu, Robert Wolfe, Aylin Caliskan, Bill Howe:
Label-Efficient Group Robustness via Out-of-Distribution Concept Curation. CVPR 2024: 12426-12434 - [c35]Chahat Raj, Anjishnu Mukherjee, Aylin Caliskan, Antonios Anastasopoulos, Ziwei Zhu:
BiasDora: Exploring Hidden Biased Associations in Vision-Language Models. EMNLP (Findings) 2024: 10439-10455 - [c34]Anjishnu Mukherjee, Aylin Caliskan, Ziwei Zhu, Antonios Anastasopoulos:
Global Gallery: The Fine Art of Painting Culture Portraits through Multilingual Instruction Tuning. NAACL-HLT 2024: 6398-6415 - [i32]Steven A. Lehr, Aylin Caliskan, Suneragiri Liyanage, Mahzarin R. Banaji:
ChatGPT as Research Scientist: Probing GPT's Capabilities as a Research Librarian, Research Ethicist, Data Generator and Data Predictor. CoRR abs/2406.14765 (2024) - [i31]Chahat Raj, Anjishnu Mukherjee, Aylin Caliskan, Antonios Anastasopoulos, Ziwei Zhu:
Breaking Bias, Building Bridges: Evaluation and Mitigation of Social Biases in LLMs via Contact Hypothesis. CoRR abs/2407.02030 (2024) - [i30]Chahat Raj, Anjishnu Mukherjee, Aylin Caliskan, Antonios Anastasopoulos, Ziwei Zhu:
BiasDora: Exploring Hidden Biased Associations in Vision-Language Models. CoRR abs/2407.02066 (2024) - [i29]Sourojit Ghosh, Pranav Narayanan Venkit, Sanjana Gautam, Shomir Wilson, Aylin Caliskan:
Do Generative AI Models Output Harm while Representing Non-Western Cultures: Evidence from A Community-Centered Approach. CoRR abs/2407.14779 (2024) - [i28]Kyra Wilson, Aylin Caliskan:
Gender, Race, and Intersectional Bias in Resume Screening via Language Model Retrieval. CoRR abs/2407.20371 (2024) - [i27]Gandalf Nicolas, Aylin Caliskan:
A Taxonomy of Stereotype Content in Large Language Models. CoRR abs/2408.00162 (2024) - [i26]Sourojit Ghosh, Nina Lutz, Aylin Caliskan:
"I don't see myself represented here at all": User Experiences of Stable Diffusion Outputs Containing Representational Harms across Gender Identities and Nationalities. CoRR abs/2408.01594 (2024) - 2023
- [j7]Munsif Jan
, Asifa Ashraf, Abdul Basit
Traversable Wormhole in f(Q) Gravity Using Conformal Symmetry. Symmetry 15(4): 859 (2023) - [c33]Shiva Omrani Sabbaghi
Evaluating Biased Attitude Associations of Language Models in an Intersectional Context. AIES 2023: 542-553 - [c32]Sourojit Ghosh
ChatGPT Perpetuates Gender Bias in Machine Translation and Ignores Non-Gendered Pronouns: Findings across Bengali and Five other Low-Resource Languages. AIES 2023: 901-912 - [c31]Sourojit Ghosh, Aylin Caliskan:
'Person' == Light-skinned, Western Man, and Sexualization of Women of Color: Stereotypes in Stable Diffusion. EMNLP (Findings) 2023: 6971-6985 - [c30]Isaac Slaughter, Craig Greenberg, Reva Schwartz, Aylin Caliskan:
Pre-trained Speech Processing Models Contain Human-Like Biases that Propagate to Speech Emotion Recognition. EMNLP (Findings) 2023: 8967-8989 - [c29]Robert Wolfe
Contrastive Language-Vision AI Models Pretrained on Web-Scraped Multimodal Data Exhibit Sexual Objectification Bias. FAccT 2023: 1174-1185 - [c28]Federico Bianchi
Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale. FAccT 2023: 1493-1504 - [c27]Katelyn Mei
Bias Against 93 Stigmatized Groups in Masked Language Models and Downstream Sentiment Classification Tasks. FAccT 2023: 1699-1710 - [c26]Aylin Caliskan:
Artificial Intelligence, Bias, and Ethics. IJCAI 2023: 7007-7013 - [i25]Sourojit Ghosh, Aylin Caliskan:
ChatGPT Perpetuates Gender Bias in Machine Translation and Ignores Non-Gendered Pronouns: Findings across Bengali and Five other Low-Resource Languages. CoRR abs/2305.10510 (2023) - [i24]Katelyn X. Mei, Sonia Fereidooni, Aylin Caliskan:
Bias Against 93 Stigmatized Groups in Masked Language Models and Downstream Sentiment Classification Tasks. CoRR abs/2306.05550 (2023) - [i23]Shiva Omrani Sabbaghi, Robert Wolfe, Aylin Caliskan:
Evaluating Biased Attitude Associations of Language Models in an Intersectional Context. CoRR abs/2307.03360 (2023) - [i22]Inyoung Cheong, Aylin Caliskan, Tadayoshi Kohno:
Is the U.S. Legal System Ready for AI's Challenges to Human Values? CoRR abs/2308.15906 (2023) - [i21]Isaac Slaughter
Pre-trained Speech Processing Models Contain Human-Like Biases that Propagate to Speech Emotion Recognition. CoRR abs/2310.18877 (2023) - [i20]Sourojit Ghosh, Aylin Caliskan:
'Person' == Light-skinned, Western Man, and Sexualization of Women of Color: Stereotypes in Stable Diffusion. CoRR abs/2310.19981 (2023) - 2022
- [j6]Ryan Wails, Andrew Stange, Eliana Troper, Aylin Caliskan, Roger Dingledine, Rob Jansen, Micah Sherr:
Learning to Behave: Improving Covert Channel Security with Behavior-Based Designs. Proc. Priv. Enhancing Technol. 2022(3): 179-199 (2022) - [c25]Robert Wolfe, Aylin Caliskan:
VAST: The Valence-Assessing Semantics Test for Contextualizing Language Models. AAAI 2022: 11477-11485 - [c24]Robert Wolfe, Aylin Caliskan:
Contrastive Visual Semantic Pretraining Magnifies the Semantics of Natural Language Representations. ACL (1) 2022: 3050-3061 - [c23]Aylin Caliskan, Pimparkar Parth Ajay, Tessa Charlesworth
Gender Bias in Word Embeddings: A Comprehensive Analysis of Frequency, Syntax, and Semantics. AIES 2022: 156-170 - [c22]Shiva Omrani Sabbaghi
Measuring Gender Bias in Word Embeddings of Gendered Languages Requires Disentangling Grammatical Gender Signals. AIES 2022: 518-531 - [c21]Robert Wolfe, Aylin Caliskan:
American == White in Multimodal Language-and-Image AI. AIES 2022: 800-812 - [c20]Robert Wolfe, Aylin Caliskan:
Markedness in Visual Semantic AI. FAccT 2022: 1269-1279 - [c19]Robert Wolfe, Mahzarin R. Banaji, Aylin Caliskan:
Evidence for Hypodescent in Visual Semantic AI. FAccT 2022: 1293-1304 - [c18]Robert Wolfe, Aylin Caliskan:
Detecting Emerging Associations and Behaviors With Regional and Diachronic Word Embeddings. ICSC 2022: 91-98 - [i19]Robert Wolfe, Aylin Caliskan:
VAST: The Valence-Assessing Semantics Test for Contextualizing Language Models. CoRR abs/2203.07504 (2022) - [i18]Robert Wolfe, Aylin Caliskan:
Contrastive Visual Semantic Pretraining Magnifies the Semantics of Natural Language Representations. CoRR abs/2203.07511 (2022) - [i17]Robert Wolfe, Mahzarin R. Banaji, Aylin Caliskan:
Evidence for Hypodescent in Visual Semantic AI. CoRR abs/2205.10764 (2022) - [i16]Robert Wolfe, Aylin Caliskan:
Markedness in Visual Semantic AI. CoRR abs/2205.11378 (2022) - [i15]Shiva Omrani Sabbaghi, Aylin Caliskan:
Measuring Gender Bias in Word Embeddings of Gendered Languages Requires Disentangling Grammatical Gender Signals. CoRR abs/2206.01691 (2022) - [i14]Aylin Caliskan, Pimparkar Parth Ajay, Tessa Charlesworth
Gender Bias in Word Embeddings: A Comprehensive Analysis of Frequency, Syntax, and Semantics. CoRR abs/2206.03390 (2022) - [i13]Robert Wolfe, Aylin Caliskan:
American == White in Multimodal Language-and-Image AI. CoRR abs/2207.00691 (2022) - [i12]Federico Bianchi, Pratyusha Kalluri, Esin Durmus, Faisal Ladhak, Myra Cheng, Debora Nozza, Tatsunori Hashimoto, Dan Jurafsky, James Zou, Aylin Caliskan:
Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale. CoRR abs/2211.03759 (2022) - [i11]Robert Wolfe, Yiwei Yang, Bill Howe, Aylin Caliskan:
Contrastive Language-Vision AI Models Pretrained on Web-Scraped Multimodal Data Exhibit Sexual Objectification Bias. CoRR abs/2212.11261 (2022) - 2021
- [j5]Ryan Steed
A set of distinct facial traits learned by machines is not predictive of appearance bias in the wild. AI Ethics 1(3): 249-260 (2021) - [j4]Aylin Caliskan, Yesim Deniz Ozkan-Ozen
Digital transformation of traditional marketing business model in new industry era. J. Enterp. Inf. Manag. 34(4): 1252-1273 (2021) - [c17]Wei Guo, Aylin Caliskan:
Detecting Emergent Intersectional Biases: Contextualized Word Embeddings Contain a Distribution of Human-like Biases. AIES 2021: 122-133 - [c16]Akshat Pandey, Aylin Caliskan:
Disparate Impact of Artificial Intelligence Bias in Ridehailing Economy's Price Discrimination Algorithms. AIES 2021: 822-833 - [c15]Robert Wolfe, Aylin Caliskan:
Low Frequency Names Exhibit Bias and Overfitting in Contextualizing Language Models. EMNLP (1) 2021: 518-532 - [c14]Autumn Toney, Aylin Caliskan:
ValNorm Quantifies Semantics to Reveal Consistent Valence Biases Across Languages and Over Centuries. EMNLP (1) 2021: 7203-7218 - [c13]Ryan Steed
Image Representations Learned With Unsupervised Pre-Training Contain Human-like Biases. FAccT 2021: 701-713 - [c12]Autumn Toney, Akshat Pandey, Wei Guo, David A. Broniatowski, Aylin Caliskan:
Automatically Characterizing Targeted Information Operations Through Biases Present in Discourse on Twitter. ICSC 2021: 82-83 - [i10]Robert Wolfe, Aylin Caliskan:
Low Frequency Names Exhibit Bias and Overfitting in Contextualizing Language Models. CoRR abs/2110.00672 (2021) - 2020
- [i9]Ryan Steed, Aylin Caliskan:
Machines Learn Appearance Bias in Face Recognition. CoRR abs/2002.05636 (2020) - [i8]Autumn Toney, Akshat Pandey, Wei Guo, David A. Broniatowski, Aylin Caliskan:
Pro-Russian Biases in Anti-Chinese Tweets about the Novel Coronavirus. CoRR abs/2004.08726 (2020) - [i7]Autumn Toney, Aylin Caliskan:
ValNorm: A New Word Embedding Intrinsic Evaluation Method Reveals Valence Biases are Consistent Across Languages and Over Decades. CoRR abs/2006.03950 (2020) - [i6]Wei Guo, Aylin Caliskan:
Detecting Emergent Intersectional Biases: Contextualized Word Embeddings Contain a Distribution of Human-like Biases. CoRR abs/2006.03955 (2020) - [i5]Akshat Pandey, Aylin Caliskan:
Iterative Effect-Size Bias in Ridehailing: Measuring Social Bias in Dynamic Pricing of 100 Million Rides. CoRR abs/2006.04599 (2020) - [i4]Ryan Steed, Aylin Caliskan:
Image Representations Learned With Unsupervised Pre-Training Contain Human-like Biases. CoRR abs/2010.15052 (2020)
2010 – 2019
- 2019
- [j3]Aylin Caliskan, Burcu Karaöz:
Can market indicators forecast the port throughput? Int. J. Data Min. Model. Manag. 11(1): 45-63 (2019) - [j2]Edwin Dauber
Git Blame Who?: Stylistic Authorship Attribution of Small, Incomplete Source Code Fragments. Proc. Priv. Enhancing Technol. 2019(3): 389-408 (2019) - 2018
- [c11]Edwin Dauber
Git blame who?: stylistic authorship attribution of small, incomplete source code fragments. ICSE (Companion Volume) 2018: 356-357 - [c10]Aylin Caliskan, Fabian Yamaguchi, Edwin Dauber, Richard E. Harang, Konrad Rieck, Rachel Greenstadt, Arvind Narayanan:
When Coding Style Survives Compilation: De-anonymizing Programmers from Executable Binaries. NDSS 2018 - 2017
- [c9]Aylin Caliskan:
Beyond Big Data: What Can We Learn from AI Models?: Invited Keynote. AISec@CCS 2017: 1 - [i3]Edwin Dauber, Aylin Caliskan Islam, Richard E. Harang, Rachel Greenstadt:
Git Blame Who?: Stylistic Authorship Attribution of Small, Incomplete Source Code Fragments. CoRR abs/1701.05681 (2017) - 2016
- [i2]Aylin Caliskan Islam, Joanna J. Bryson
Semantics derived automatically from language corpora necessarily contain human biases. CoRR abs/1608.07187 (2016) - 2015
- [j1]Aylin Caliskan Islam:
How do we decide how much to reveal? SIGCAS Comput. Soc. 45(1): 14-15 (2015) - [c8]Aylin Caliskan Islam, Richard E. Harang, Andrew Liu, Arvind Narayanan, Clare R. Voss, Fabian Yamaguchi, Rachel Greenstadt:
De-anonymizing Programmers via Code Stylometry. USENIX Security Symposium 2015: 255-270 - [i1]Aylin Caliskan Islam, Fabian Yamaguchi, Edwin Dauber, Richard E. Harang, Konrad Rieck, Rachel Greenstadt, Arvind Narayanan:
When Coding Style Survives Compilation: De-anonymizing Programmers from Executable Binaries. CoRR abs/1512.08546 (2015) - 2014
- [c7]Sadia Afroz, Aylin Caliskan Islam, Ariel Stolerman, Rachel Greenstadt, Damon McCoy:
Doppelgänger Finder: Taking Stylometry to the Underground. IEEE Symposium on Security and Privacy 2014: 212-226 - [c6]Aylin Caliskan Islam, Jonathan Walsh, Rachel Greenstadt:
Privacy Detective: Detecting Private Information and Collective Privacy Behavior in a Large Social Network. WPES 2014: 35-46 - 2013
- [c5]Alex Kantchelian, Sadia Afroz, Ling Huang, Aylin Caliskan Islam, Brad Miller, Michael Carl Tschantz, Rachel Greenstadt, Anthony D. Joseph
Approaches to adversarial drift. AISec 2013: 99-110 - [c4]Ariel Stolerman, Aylin Caliskan, Rachel Greenstadt:
From Language to Family and Back: Native Language and Language Family Identification from English Text. HLT-NAACL 2013: 32-39 - [c3]Sadia Afroz, Aylin Caliskan Islam, Jordan Santell, Aaron Chapin, Rachel Greenstadt:
How Privacy Flaws Affect Consumer Perception. STAST 2013: 10-17 - 2012
- [c2]Andrew W. E. McDonald, Sadia Afroz, Aylin Caliskan, Ariel Stolerman, Rachel Greenstadt:
Use Fewer Instances of the Letter "i": Toward Writing Style Anonymization. Privacy Enhancing Technologies 2012: 299-318 - [c1]Aylin Caliskan, Rachel Greenstadt:
Translate Once, Translate Twice, Translate Thrice and Attribute: Identifying Authors and Machine Translation Tools in Translated Text. ICSC 2012: 121-125
Coauthor Index
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last updated on 2024-11-15 19:29 CET by the dblp team
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