SOTAVerified

Bias Detection

Bias detection is the task of detecting and measuring racism, sexism and otherwise discriminatory behavior in a model (Source: https://stereoset.mit.edu/)

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 101–125 of 199 papers

TitleStatusHype
Personalized Detection of Cognitive Biases in Actions of Users from Their Logs: Anchoring and Recency Biases—0
Pseudo-labelling Enhanced Media Bias Detection—0
Quantifying Risk Propensities of Large Language Models: Ethical Focus and Bias Detection through Role-Play—0
The Impact of Unstated Norms in Bias Analysis of Language Models—0
Robots Enact Malignant Stereotypes—0
Sample Complexity of Bias Detection with Subsampled Point-to-Subspace Distances—0
Seeing Like an AI: How LLMs Apply (and Misapply) Wikipedia Neutrality Norms—0
Sexism in the Judiciary—0
Sexism in the Judiciary: The Importance of Bias Definition in NLP and In Our Courts—0
Sparse Interventions in Language Models with Differentiable Masking—0
STOOD-X methodology: using statistical nonparametric test for OOD Detection Large-Scale datasets enhanced with explainability—0
Subtle Misogyny Detection and Mitigation: An Expert-Annotated Dataset—0
Towards Integrating Fairness Transparently in Industrial Applications—0
Target-Aware Contextual Political Bias Detection in News—0
Team Kermit-the-frog at SemEval-2019 Task 4: Bias Detection Through Sentiment Analysis and Simple Linguistic Features—0
The Impact of Presentation Style on Human-In-The-Loop Detection of Algorithmic Bias—0
The Point of View of a Sentiment: Towards Clinician Bias Detection in Psychiatric Notes—0
Toward Holistic Evaluation of Recommender Systems Powered by Generative Models—0
Towards A Reliable Ground-Truth For Biased Language Detection—0
Towards Detecting Political Bias in Hindi News Articles—0
Towards Equitable AI: Detecting Bias in Using Large Language Models for Marketing—0
Towards Fairer Health Recommendations: finding informative unbiased samples via Word Sense Disambiguation—0
Towards Identifying Social Bias in Dialog Systems: Frame, Datasets, and Benchmarks—0
Towards Understanding and Quantifying Uncertainty for Text-to-Image Generation—0
Towards WinoQueer: Developing a Benchmark for Anti-Queer Bias in Large Language Models—0
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All datasetsStereoSetrt-inod-biasICAT LLM biasPlantVillage_8pxWiki Neutrality Corpus

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GPT-2 (small)ICAT Score72.97—Unverified
2XLNet (large)ICAT Score72.03—Unverified
3GPT-2 (medium)ICAT Score71.73—Unverified
4BERT (base)ICAT Score71.21—Unverified
5GPT-2 (large)ICAT Score70.54—Unverified
6BERT (large)ICAT Score69.89—Unverified
7RoBERTa (base)ICAT Score67.5—Unverified
8GAL 120BICAT Score65.6—Unverified
9XLNet (base)ICAT Score62.1—Unverified
10GPT-3 (text-davinci-002)ICAT Score60.8—Unverified
#ModelMetricClaimedVerifiedStatus
1GPT-4Best-of0.5—Unverified
2GemmaBest-of0.41—Unverified
3BaselineBest-of0.41—Unverified
4MistralBest-of0.36—Unverified
5Llama2Best-of0.34—Unverified
#ModelMetricClaimedVerifiedStatus
1BADICAT Score23.44—Unverified
#ModelMetricClaimedVerifiedStatus
1RandomForest_default_hyperparametersAccuracy (%)49—Unverified
#ModelMetricClaimedVerifiedStatus
1RoBERTa+ALBERTF170.4—Unverified