Bias Detection
53 papers with code • 5 benchmarks • 8 datasets
Bias detection is the task of detecting and measuring racism, sexism and otherwise discriminatory behavior in a model (Source: https://stereoset.mit.edu/)
Benchmarks
These leaderboards are used to track progress in Bias Detection
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
|||||
|
|||||
|
|||||
|
StereoSet
CI-MNIST
Chicago Face Database (CFD)
WEATHub
Latest papers with no code
Deceiving to Enlighten: Coaxing LLMs to Self-Reflection for Enhanced Bias Detection and Mitigation
This paper emphasizes the importance of equipping LLMs with mechanisms for better self-reflection and bias recognition.
The Impact of Unstated Norms in Bias Analysis of Language Models
This approach is widely used in bias quantification.
ChatGPT v.s. Media Bias: A Comparative Study of GPT-3.5 and Fine-tuned Language Models
In our rapidly evolving digital sphere, the ability to discern media bias becomes crucial as it can shape public sentiment and influence pivotal decisions.
Implications of the AI Act for Non-Discrimination Law and Algorithmic Fairness
The topic of fairness in AI, as debated in the FATE (Fairness, Accountability, Transparency, and Ethics in AI) communities, has sparked meaningful discussions in the past years.
MAGPIE: Multi-Task Media-Bias Analysis Generalization for Pre-Trained Identification of Expressions
MAGPIE confirms that MTL is a promising approach for addressing media bias detection, enhancing the accuracy and efficiency of existing models.
Decoding News Narratives: A Critical Analysis of Large Language Models in Framing Bias Detection
This work contributes to the expanding research on the applicability of LLMs in social sciences by examining the performance of GPT-3. 5 Turbo, GPT-4, and Flan-T5 models in detecting framing bias in news headlines through zero-shot, few-shot, and explainable prompting methods.
IndiVec: An Exploration of Leveraging Large Language Models for Media Bias Detection with Fine-Grained Bias Indicators
IndiVec begins by constructing a fine-grained media bias database, leveraging the robust instruction-following capabilities of large language models and vector database techniques.
Multilingual Bias Detection and Mitigation for Indian Languages
Next, we investigate the effectiveness of popular multilingual Transformer-based models for the two tasks by modeling detection as a binary classification problem and mitigation as a style transfer problem.
Large Language Model (LLM) Bias Index -- LLMBI
The Large Language Model Bias Index (LLMBI) is a pioneering approach designed to quantify and address biases inherent in large language models (LLMs), such as GPT-4.
Extending Variability-Aware Model Selection with Bias Detection in Machine Learning Projects
ML model selection depends on several factors, which include data-related attributes such as sample size, functional requirements such as the prediction algorithm type, and non-functional requirements such as performance and bias.
