Catalogue of Tools & Metrics for Trustworthy AI

These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.

Robustness & digital security

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Objective Robustness & digital security

Recognition/object detectionUploaded on Jun 5, 2024
In Multiple Object Tracking (MOT), tracking-by-detection methods have stood the test for a long time, which split the process into two parts according to the definition: object det...

Recognition/object detectionUploaded on Jun 5, 2024
This paper introduces fourteen novel datasets for the evaluation of Large Language Models' safety in the context of enterprise tasks. A method was devised to evaluate a model's saf...

Recognition/object detectionUploaded on Jun 5, 2024
Multimodal Large Language Models (MLLMs) have experienced significant advancements recently. Nevertheless, challenges persist in the accurate recognition and comprehension of intri...

Recognition/object detectionUploaded on Jun 5, 2024
Vision Transformer (ViT) self-attention mechanism is characterized by feature collapse in deeper layers, resulting in the vanishing of low-level visual features. However, such feat...

Recognition/object detectionUploaded on Jun 5, 2024
Today's deep learning methods focus on how to design the most appropriate objective functions so that the prediction results of the model can be closest to the ground truth. Meanwh...

Event/anomaly detectionReasoning with knowledge structures/planningRecognition/object detectionUploaded on Jun 5, 2024
Table-based reasoning with large language models (LLMs) is a promising direction to tackle many table understanding tasks, such as table-based question answering and fact verificat...

Recognition/object detectionUploaded on Jun 5, 2024
The task of stock earnings forecasting has received considerable attention due to the demand investors in real-world scenarios. However, compared with financial institutions, it is...

Recognition/object detectionUploaded on May 21, 2024
In Multiple Object Tracking (MOT), tracking-by-detection methods have stood the test for a long time, which split the process into two parts according to the definition: object det...

Recognition/object detectionUploaded on May 21, 2024
This paper introduces fourteen novel datasets for the evaluation of Large Language Models' safety in the context of enterprise tasks. A method was devised to evaluate a model's saf...

Recognition/object detectionUploaded on May 21, 2024
Multimodal Large Language Models (MLLMs) have experienced significant advancements recently. Nevertheless, challenges persist in the accurate recognition and comprehension of intri...

Recognition/object detectionUploaded on May 21, 2024
Vision Transformer (ViT) self-attention mechanism is characterized by feature collapse in deeper layers, resulting in the vanishing of low-level visual features. However, such feat...

Recognition/object detectionUploaded on May 21, 2024
Today's deep learning methods focus on how to design the most appropriate objective functions so that the prediction results of the model can be closest to the ground truth. Meanwh...

Event/anomaly detectionReasoning with knowledge structures/planningRecognition/object detectionUploaded on May 21, 2024
Table-based reasoning with large language models (LLMs) is a promising direction to tackle many table understanding tasks, such as table-based question answering and fact verificat...

Recognition/object detectionUploaded on May 21, 2024
The task of stock earnings forecasting has received considerable attention due to the demand investors in real-world scenarios. However, compared with financial institutions, it is...

Recognition/object detectionUploaded on Apr 22, 2024
In Multiple Object Tracking (MOT), tracking-by-detection methods have stood the test for a long time, which split the process into two parts according to the definition: object det...

Recognition/object detectionUploaded on Apr 22, 2024
This paper introduces fourteen novel datasets for the evaluation of Large Language Models' safety in the context of enterprise tasks. A method was devised to evaluate a model's saf...

Recognition/object detectionUploaded on Apr 22, 2024
Multimodal Large Language Models (MLLMs) have experienced significant advancements recently. Nevertheless, challenges persist in the accurate recognition and comprehension of intri...

Recognition/object detectionUploaded on Apr 22, 2024
Vision Transformer (ViT) self-attention mechanism is characterized by feature collapse in deeper layers, resulting in the vanishing of low-level visual features. However, such feat...

Recognition/object detectionUploaded on Apr 22, 2024
Today's deep learning methods focus on how to design the most appropriate objective functions so that the prediction results of the model can be closest to the ground truth. Meanwh...

Event/anomaly detectionReasoning with knowledge structures/planningRecognition/object detectionUploaded on Apr 22, 2024
Table-based reasoning with large language models (LLMs) is a promising direction to tackle many table understanding tasks, such as table-based question answering and fact verificat...

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Disclaimer: The tools and metrics featured herein are solely those of the originating authors and are not vetted or endorsed by the OECD or its member countries. The Organisation cannot be held responsible for possible issues resulting from the posting of links to third parties' tools and metrics on this catalogue. More on the methodology can be found at https://oecd.ai/catalogue/faq.