Svetlana Kiritchenko

Fine-Tuning Lowers Safety and Disrupts Evaluation Consistency ACL 2025 Tackling Social Bias against the Poor: a Dataset and a Taxonomy on Aporophobia NAACL 2025 Uncovering Bias in Large Vision-Language Models at Scale with Counterfactuals NAACL 2025 When Detection Fails: The Power of Fine-Tuned Models to Generate Human-Like Social Media Text ACL 2025 Adaptable Moral Stances of Large Language Models on Sexist Content: Implications for Society and Gender Discourse EMNLP 2024 Challenging Negative Gender Stereotypes: A Study on the Effectiveness of Automated Counter-Stereotypes COLING 2024 Examining Gender and Racial Bias in Large Vision–Language Models Using a Novel Dataset of Parallel Images EACL 2024 How Does Stereotype Content Differ across Data Sources? NAACL 2024 The Crime of Being Poor: Associations between Crime and Poverty on Social Media in Eight Countries NAACL 2024 Aporophobia: An Overlooked Type of Toxic Language Targeting the Poor ACL 2023 Concept-Based Explanations to Test for False Causal Relationships Learned by Abusive Language Classifiers ACL 2023 What Makes a Good Counter-Stereotype? Evaluating Strategies for Automated Responses to Stereotypical Text ACL 2023 Challenges in Applying Explainability Methods to Improve the Fairness of NLP Models NAACL 2022 Does Moral Code have a Moral Code? Probing Delphi’s Moral Philosophy NAACL 2022 Improving Generalizability in Implicitly Abusive Language Detection with Concept Activation Vectors ACL 2022 Necessity and Sufficiency for Explaining Text Classifiers: A Case Study in Hate Speech Detection NAACL 2022 Towards Procedural Fairness: Uncovering Biases in How a Toxic Language Classifier Uses Sentiment Information EMNLP 2022 Understanding and Countering Stereotypes: A Computational Approach to the Stereotype Content Model ACL 2021 On Cross-Dataset Generalization in Automatic Detection of Online Abuse EMNLP 2020 Big BiRD: A Large, Fine-Grained, Bigram Relatedness Dataset for Examining Semantic Composition NAACL 2019 DeepMiner at SemEval-2018 Task 1: Emotion Intensity Recognition Using Deep Representation Learning SemEval 2018 SemEval-2018 Task 1: Affect in Tweets SemEval 2018 Best-Worst Scaling More Reliable than Rating Scales: A Case Study on Sentiment Intensity Annotation ACL 2017 Capturing Reliable Fine-Grained Sentiment Associations by Crowdsourcing and Best–Worst Scaling NAACL 2016 SemEval-2016 Task 6: Detecting Stance in Tweets SemEval 2016 SemEval-2016 Task 7: Determining Sentiment Intensity of English and Arabic Phrases SemEval 2016 Sentiment Composition of Words with Opposing Polarities NAACL 2016 SemEval-2015 Task 10: Sentiment Analysis in Twitter SemEval 2015 Sentiment after Translation: A Case-Study on Arabic Social Media Posts NAACL 2015 An Empirical Study on the Effect of Negation Words on Sentiment ACL 2014 NRC-Canada-2014: Detecting Aspects and Sentiment in Customer Reviews SemEval 2014 NRC-Canada-2014: Recent Improvements in the Sentiment Analysis of Tweets SemEval 2014 NRC-Canada: Building the State-of-the-Art in Sentiment Analysis of Tweets SemEval 2013 Lexically-Triggered Hidden Markov Models for Clinical Document Coding ACL 2011 Keyword Optimization in Sponsored Search via Feature Selection AISTATS 2003