Use Fewer Instances of the Letter "i": Toward Writing Style Anonymization. - Andrew W. E. McDonald; Sadia Afroz 001; Aylin Caliskan; Ariel Stolerman; Rachel Greenstadt (Privacy Enhancing Technologies, 2012)

Translate Once, Translate Twice, Translate Thrice and Attribute: Identifying Authors and Machine Translation Tools in Translated Text. - Aylin Caliskan; Rachel Greenstadt (ICSC, 2012)

Approaches to adversarial drift. - Alex Kantchelian; Sadia Afroz 001; Ling Huang 001; Aylin Caliskan Islam; Brad Miller 002; Michael Carl Tschantz; Rachel Greenstadt; Anthony D. Joseph; J. D. Tygar (AISec, 2013)

From Language to Family and Back: Native Language and Language Family Identification from English Text. - Ariel Stolerman; Aylin Caliskan; Rachel Greenstadt (HLT-NAACL, 2013)

How Privacy Flaws Affect Consumer Perception. - Sadia Afroz 001; Aylin Caliskan Islam; Jordan Santell; Aaron Chapin; Rachel Greenstadt (STAST, 2013)

Doppelgänger Finder: Taking Stylometry to the Underground. - Sadia Afroz 001; Aylin Caliskan Islam; Ariel Stolerman; Rachel Greenstadt; Damon McCoy (IEEE Symposium on Security and Privacy, 2014)

Privacy Detective: Detecting Private Information and Collective Privacy Behavior in a Large Social Network. - Aylin Caliskan Islam; Jonathan Walsh; Rachel Greenstadt (WPES, 2014)

De-anonymizing Programmers via Code Stylometry. - Aylin Caliskan Islam; Richard E. Harang; Andrew Liu; Arvind Narayanan; Clare R. Voss; Fabian Yamaguchi; Rachel Greenstadt (USENIX Security Symposium, 2015)

How do we decide how much to reveal? - Aylin Caliskan Islam (SIGCAS Comput. Soc., 2015)

Semantics derived automatically from language corpora necessarily contain human biases. - Aylin Caliskan Islam; Joanna J. Bryson; Arvind Narayanan (CoRR, 2016)

Beyond Big Data: What Can We Learn from AI Models?: Invited Keynote. - Aylin Caliskan (AISec@CCS, 2017)

Git blame who?: stylistic authorship attribution of small, incomplete source code fragments. - Edwin Dauber; Aylin Caliskan; Richard E. Harang; Rachel Greenstadt (ICSE (Companion Volume), 2018)

When Coding Style Survives Compilation: De-anonymizing Programmers from Executable Binaries. - Aylin Caliskan; Fabian Yamaguchi; Edwin Dauber; Richard E. Harang; Konrad Rieck; Rachel Greenstadt; Arvind Narayanan (NDSS, 2018)

Can market indicators forecast the port throughput? - Aylin Caliskan; Burcu Karaöz (Int. J. Data Min. Model. Manag., 2019)

Git Blame Who?: Stylistic Authorship Attribution of Small, Incomplete Source Code Fragments. - Edwin Dauber; Aylin Caliskan; Richard E. Harang; Gregory Shearer; Michael J. Weisman; Frederica Free-Nelson; Rachel Greenstadt (Proc. Priv. Enhancing Technol., 2019)

Machines Learn Appearance Bias in Face Recognition. - Ryan Steed; Aylin Caliskan (CoRR, 2020)

Pro-Russian Biases in Anti-Chinese Tweets about the Novel Coronavirus. - Autumn Toney; Akshat Pandey; Wei Guo; David A. Broniatowski; Aylin Caliskan (CoRR, 2020)

ValNorm: A New Word Embedding Intrinsic Evaluation Method Reveals Valence Biases are Consistent Across Languages and Over Decades. - Autumn Toney; Aylin Caliskan (CoRR, 2020)

Iterative Effect-Size Bias in Ridehailing: Measuring Social Bias in Dynamic Pricing of 100 Million Rides. - Akshat Pandey; Aylin Caliskan (CoRR, 2020)

Detecting Emergent Intersectional Biases: Contextualized Word Embeddings Contain a Distribution of Human-like Biases. - Wei Guo; Aylin Caliskan (AIES, 2021)

Disparate Impact of Artificial Intelligence Bias in Ridehailing Economy's Price Discrimination Algorithms. - Akshat Pandey; Aylin Caliskan (AIES, 2021)

ValNorm Quantifies Semantics to Reveal Consistent Valence Biases Across Languages and Over Centuries. - Autumn Toney; Aylin Caliskan (EMNLP (1), 2021)

Low Frequency Names Exhibit Bias and Overfitting in Contextualizing Language Models. - Robert Wolfe; Aylin Caliskan (EMNLP (1), 2021)

Image Representations Learned With Unsupervised Pre-Training Contain Human-like Biases. - Ryan Steed; Aylin Caliskan (FAccT, 2021)

Automatically Characterizing Targeted Information Operations Through Biases Present in Discourse on Twitter. - Autumn Toney; Akshat Pandey; Wei Guo; David A. Broniatowski; Aylin Caliskan (ICSC, 2021)

A set of distinct facial traits learned by machines is not predictive of appearance bias in the wild. - Ryan Steed; Aylin Caliskan (AI Ethics, 2021)

Digital transformation of traditional marketing business model in new industry era. - Aylin Caliskan; Yesim Deniz Ozkan-Ozen; Yucel Ozturkoglu (J. Enterp. Inf. Manag., 2021)

VAST: The Valence-Assessing Semantics Test for Contextualizing Language Models. - Robert Wolfe; Aylin Caliskan (AAAI, 2022)

Contrastive Visual Semantic Pretraining Magnifies the Semantics of Natural Language Representations. - Robert Wolfe; Aylin Caliskan (ACL (1), 2022)

Gender Bias in Word Embeddings: A Comprehensive Analysis of Frequency, Syntax, and Semantics. - Aylin Caliskan; Pimparkar Parth Ajay; Tessa Charlesworth; Robert Wolfe; Mahzarin R. Banaji (AIES, 2022)

Measuring Gender Bias in Word Embeddings of Gendered Languages Requires Disentangling Grammatical Gender Signals. - Shiva Omrani Sabbaghi; Aylin Caliskan (AIES, 2022)

American == White in Multimodal Language-and-Image AI. - Robert Wolfe; Aylin Caliskan (AIES, 2022)

Evidence for Hypodescent in Visual Semantic AI. - Robert Wolfe; Mahzarin R. Banaji; Aylin Caliskan (FAccT, 2022)

Markedness in Visual Semantic AI. - Robert Wolfe; Aylin Caliskan (FAccT, 2022)

Detecting Emerging Associations and Behaviors With Regional and Diachronic Word Embeddings. - Robert Wolfe; Aylin Caliskan (ICSC, 2022)

Learning to Behave: Improving Covert Channel Security with Behavior-Based Designs. - Ryan Wails; Andrew Stange; Eliana Troper; Aylin Caliskan; Roger Dingledine; Rob Jansen; Micah Sherr (Proc. Priv. Enhancing Technol., 2022)

ChatGPT Perpetuates Gender Bias in Machine Translation and Ignores Non-Gendered Pronouns: Findings across Bengali and Five other Low-Resource Languages. - Sourojit Ghosh; Aylin Caliskan (AIES, 2023)

Evaluating Biased Attitude Associations of Language Models in an Intersectional Context. - Shiva Omrani Sabbaghi; Robert Wolfe; Aylin Caliskan (AIES, 2023)

'Person' == Light-skinned, Western Man, and Sexualization of Women of Color: Stereotypes in Stable Diffusion. - Sourojit Ghosh; Aylin Caliskan (EMNLP (Findings), 2023)

Pre-trained Speech Processing Models Contain Human-Like Biases that Propagate to Speech Emotion Recognition. - Isaac Slaughter; Craig Greenberg; Reva Schwartz; Aylin Caliskan (EMNLP (Findings), 2023)

Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale. - Federico Bianchi 001; Pratyusha Kalluri; Esin Durmus; Faisal Ladhak; Myra Cheng; Debora Nozza; Tatsunori Hashimoto; Dan Jurafsky; James Zou 001; Aylin Caliskan (FAccT, 2023)

Bias Against 93 Stigmatized Groups in Masked Language Models and Downstream Sentiment Classification Tasks. - Katelyn Mei; Sonia Fereidooni; Aylin Caliskan (FAccT, 2023)

Contrastive Language-Vision AI Models Pretrained on Web-Scraped Multimodal Data Exhibit Sexual Objectification Bias. - Robert Wolfe; Yiwei Yang 009; Bill Howe; Aylin Caliskan (FAccT, 2023)

Artificial Intelligence, Bias, and Ethics. - Aylin Caliskan (IJCAI, 2023)

Is the U.S. Legal System Ready for AI's Challenges to Human Values? - Inyoung Cheong; Aylin Caliskan; Tadayoshi Kohno (CoRR, 2023)

Traversable Wormhole in f(Q) Gravity Using Conformal Symmetry. - Munsif Jan; Asifa Ashraf; Abdul Basit; Aylin Caliskan; Ertan Güdekli (Symmetry, 2023)

"I Don't See Myself Represented Here at All": User Experiences of Stable Diffusion Outputs Containing Representational Harms across Gender Identities and Nationalities. - Sourojit Ghosh; Nina Lutz; Aylin Caliskan (AIES (1), 2024)

Do Generative AI Models Output Harm while Representing Non-Western Cultures: Evidence from A Community-Centered Approach. - Sourojit Ghosh; Pranav Narayanan Venkit; Sanjana Gautam; Shomir Wilson; Aylin Caliskan (AIES (1), 2024)

Breaking Bias, Building Bridges: Evaluation and Mitigation of Social Biases in LLMs via Contact Hypothesis. - Chahat Raj; Anjishnu Mukherjee; Aylin Caliskan; Antonios Anastasopoulos; Ziwei Zhu 001 (AIES (1), 2024)

Gender, Race, and Intersectional Bias in Resume Screening via Language Model Retrieval. - Kyra Wilson; Aylin Caliskan (AIES (1), 2024)

Label-Efficient Group Robustness via Out-of-Distribution Concept Curation. - Yiwei Yang 009; Anthony Z. Liu; Robert Wolfe; Aylin Caliskan; Bill Howe (CVPR, 2024)

BiasDora: Exploring Hidden Biased Associations in Vision-Language Models. - Chahat Raj; Anjishnu Mukherjee; Aylin Caliskan; Antonios Anastasopoulos; Ziwei Zhu 001 (EMNLP (Findings), 2024)

Global Gallery: The Fine Art of Painting Culture Portraits through Multilingual Instruction Tuning. - Anjishnu Mukherjee; Aylin Caliskan; Ziwei Zhu 001; Antonios Anastasopoulos (NAACL-HLT, 2024)

ChatGPT as Research Scientist: Probing GPT's Capabilities as a Research Librarian, Research Ethicist, Data Generator and Data Predictor. - Steven A. Lehr; Aylin Caliskan; Suneragiri Liyanage; Mahzarin R. Banaji (CoRR, 2024)

A Taxonomy of Stereotype Content in Large Language Models. - Gandalf Nicolas; Aylin Caliskan (CoRR, 2024)

Biases Propagate in Encoder-based Vision-Language Models: A Systematic Analysis From Intrinsic Measures to Zero-shot Retrieval Outcomes. - Kshitish Ghate; Tessa Charlesworth; Mona T. Diab; Aylin Caliskan (ACL (Findings), 2025)

Intrinsic Bias is Predicted by Pretraining Data and Correlates with Downstream Performance in Vision-Language Encoders. - Kshitish Ghate; Isaac Slaughter; Kyra Wilson; Mona T. Diab; Aylin Caliskan (NAACL (Long Papers), 2025)

Safeguarding human values: rethinking US law for generative AI's societal impacts. - Inyoung Cheong; Aylin Caliskan; Tadayoshi Kohno (AI Ethics, 2025)

Personalized Safety in LLMs: A Benchmark and A Planning-Based Agent Approach. - Yuchen Wu; Edward Sun; Kaijie Zhu; Jianxun Lian; José Hernández-Orallo; Aylin Caliskan; Jindong Wang 001 (CoRR, 2025)

VIGNETTE: Socially Grounded Bias Evaluation for Vision-Language Models. - Chahat Raj; Bowen Wei; Aylin Caliskan; Antonios Anastasopoulos; Ziwei Zhu 001 (CoRR, 2025)

Talent or Luck? Evaluating Attribution Bias in Large Language Models. - Chahat Raj; Mahika Banerjee; Aylin Caliskan; Antonios Anastasopoulos; Ziwei Zhu 001 (CoRR, 2025)

Persona-Assigned Large Language Models Exhibit Human-Like Motivated Reasoning. - Saloni Dash; Amélie Reymond; Emma S. Spiro; Aylin Caliskan (CoRR, 2025)