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.

Fairness

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Objective Fairness

Interaction support/chatbotsRecognition/object detectionUploaded on Jun 5, 2024
Multimodal Large Language Models (MLLMs) excel in generating responses based on visual inputs. However, they often suffer from a bias towards generating responses similar to their ...

Objective(s)


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
In this paper, we introduce an open-vocabulary panoptic segmentation model that effectively unifies the strengths of the Segment Anything Model (SAM) with the vision-language CLIP ...

Objective(s)


Interaction support/chatbotsRecognition/object detectionUploaded on May 21, 2024
Multimodal Large Language Models (MLLMs) excel in generating responses based on visual inputs. However, they often suffer from a bias towards generating responses similar to their ...

Objective(s)


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
In this paper, we introduce an open-vocabulary panoptic segmentation model that effectively unifies the strengths of the Segment Anything Model (SAM) with the vision-language CLIP ...

Objective(s)


Interaction support/chatbotsRecognition/object detectionUploaded on Apr 22, 2024
Multimodal Large Language Models (MLLMs) excel in generating responses based on visual inputs. However, they often suffer from a bias towards generating responses similar to their ...

Objective(s)


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
In this paper, we introduce an open-vocabulary panoptic segmentation model that effectively unifies the strengths of the Segment Anything Model (SAM) with the vision-language CLIP ...

Objective(s)


Interaction support/chatbotsRecognition/object detectionUploaded on Apr 2, 2024
Multimodal Large Language Models (MLLMs) excel in generating responses based on visual inputs. However, they often suffer from a bias towards generating responses similar to their ...

Objective(s)


Recognition/object detectionUploaded on Apr 2, 2024
Object detectors often perform poorly on data that differs from their training set. Domain adaptive object detection (DAOD) methods have recently demonstrated strong results on add...

Recognition/object detectionUploaded on Nov 1, 2023
We observe that despite their hierarchical convolutional nature, the synthesis process of typical generative adversarial networks depends on absolute pixel coordinates in an unheal...

Objective(s)


Recognition/object detectionUploaded on Nov 1, 2023
Learning to reject unknown samples (not present in the source classes) in the target domain is fairly important for unsupervised domain adaptation (UDA). There exist two typical UD...

Objective(s)


Recognition/object detectionUploaded on Nov 1, 2023
Diffusion frameworks have achieved comparable performance with previous state-of-the-art image generation models. Researchers are curious about its variants in discriminative tasks...

Objective(s)


Recognition/object detectionUploaded on Nov 1, 2023
This paper presents a new framework for open-vocabulary semantic segmentation with the pre-trained vision-language model, named Side Adapter Network (SAN). Our approach models the ...

Objective(s)


Recognition/object detectionUploaded on Nov 1, 2023
The growing popularity of Vision Transformers as the go-to models for image classification has led to an explosion of architectural modifications claiming to be more efficient than...

Objective(s)


Event/anomaly detectionRecognition/object detectionUploaded on Nov 1, 2023
The design choices in the Transformer attention mechanism, including weak inductive bias and quadratic computational complexity, have limited its application for modeling long sequ...

Objective(s)


Recognition/object detectionUploaded on Nov 1, 2023
3D softwares are now capable of producing highly realistic images that look nearly indistinguishable from the real images. This raises the question: can real datasets be enhanced w...

Forecasting/predictionUploaded on Nov 1, 2023
During lung radiotherapy, the position of infrared reflective objects on the chest can be recorded to estimate the tumor location. However, radiotherapy systems have a latency inhe...

Event/anomaly detectionInteraction support/chatbotsUploaded on Nov 1, 2023
Question answering (QA) is a fundamental means to facilitate assessment and training of narrative comprehension skills for both machines and young children, yet there is scarcity o...

Objective(s)


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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.