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← Application Areas
Machine Learning
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Application Areas
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Fairness
3337 directly classified papers
Papers per year
2011: 1
2013: 3
2014: 2
2016: 6
2017: 30
2018: 65
2019: 182
2020: 239
2021: 373
2022: 456
2023: 533
2024: 648
2025: 644
2026: 155
Papers
Beyond the Safety Bundle: Auditing the Helpful and Harmless Dataset
NAACL 2025
Fooling the LVLM Judges: Visual Biases in LVLM-Based Evaluation
EMNLP 2025
Federated Learning at the Forefront of Fairness: A Multifaceted Perspective
IJCAI 2025
On The Origin of Cultural Biases in Language Models: From Pre-training Data to Linguistic Phenomena
NAACL 2025
Fairness Shields: Safeguarding against Biased Decision Makers
AAAI 2025
My LLM might Mimic AAE - But When Should It?
NAACL 2025
CSEval: Towards Automated, Multi-Dimensional, and Reference-Free Counterspeech Evaluation using Auto-Calibrated LLMs
NAACL 2025
Federated Domain Generalization with Decision Insight Matrix
IJCAI 2025
High School Course Scheduling: Student Preferences and Fairness Constraints (Student Abstract)
AAAI 2025
The Mainstays of Trustworthy Machine Learning
AAAI 2025
Uncovering Bias in Large Vision-Language Models at Scale with Counterfactuals
NAACL 2025
FedAA: A Reinforcement Learning Perspective on Adaptive Aggregation for Fair and Robust Federated Learning
AAAI 2025
Stop Diverse OOD Attacks: Knowledge Ensemble for Reliable Defense
AAAI 2025
Evaluating Index-based Treatment Allocation in Underresourced Communities
AAAI 2025
Building Trust in Clinical LLMs: Bias Analysis and Dataset Transparency
EMNLP 2025
Ensuring Reliable and Transparent Algorithmic Fairness Through Optimal Transport and Uncertainty Quantification
IJCAI 2025
GENDER1PERSON: Test Suite for Estimating Gender Bias of First-person Singular Forms
EMNLP 2025
Debiasing Multilingual LLMs in Cross-lingual Latent Space
EMNLP 2025
PlagBench: Exploring the Duality of Large Language Models in Plagiarism Generation and Detection
NAACL 2025
Data Attribution: A Data-Centric Approach for Trustworthy AI Development
AAAI 2025
Why AI Is WEIRD and Shouldn't Be This Way: Towards AI for Everyone, with Everyone, by Everyone
AAAI 2025
Fair Graph U-Net: A Fair Graph Learning Framework Integrating Group and Individual Awareness
AAAI 2025
Causal Explanation of Quality of Parent-Child Interactions with Multimodal Behavioral Features (Student Abstract)
AAAI 2025
Blind Men and the Elephant: Diverse Perspectives on Gender Stereotypes in Benchmark Datasets
EMNLP 2025
Self-Pluralising Culture Alignment for Large Language Models
NAACL 2025
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