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.

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Precision

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Precision is the fraction of correctly labeled positive examples out of all of the examples that were labeled as positive. It is computed via the equation: Precision = TP / (TP + FP) where TP is the True positives (i.e. the examples correctly labeled as positive) and FP is the False positive examples (i.e. the examples incorrectly labeled as positive).

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A survey of cross-validation procedures for model selection

Uploaded on Oct 21, 2022

Used to estimate the risk of an estimator or to perform model selection, cross-validation is a widespread strategy because of its simplicity and its apparent universality. Many...

Encode, Tag, Realize: High-Precision Text Editing

Uploaded on Nov 1, 2022

We propose LaserTagger – a sequence tagging approach that casts text generation as a text editing task. Target texts are reconstructed from the inputs using three main ed...

A Data Set and a Convolutional Model for Iconography Classification in Paintings

Uploaded on Nov 1, 2023
Mathematical reasoning skills are essential for general-purpose intelligent systems to perform tasks from grocery shopping to climate modeling. Towards evaluating and improving AI ...

A Label Attention Model for ICD Coding from Clinical Text

Uploaded on Nov 1, 2023
Multi-modal fusion approaches aim to integrate information from different data sources. Unlike natural datasets, such as in audio-visual applications, where samples consist of "pai...

Accurate and Real-time 3D Pedestrian Detection Using an Efficient Attentive Pillar Network

Uploaded on Nov 1, 2023
Learning specific hands-on skills such as cooking, car maintenance, and home repairs increasingly happens via instructional videos. The user experience with such videos is known to...

Deep learning for time series classification

Uploaded on Nov 1, 2023
Time series analysis is a field of data science which is interested in analyzing sequences of numerical values ordered in time. Time series are particularly interesting because the...

I3CL:Intra- and Inter-Instance Collaborative Learning for Arbitrary-shaped Scene Text Detection

Uploaded on Nov 1, 2023
One fundamental challenge of vehicle re-identification (re-id) is to learn robust and discriminative visual representation, given the significant intra-class vehicle variations acr...

Less Is More: Linear Layers on CLIP Features as Powerful VizWiz Model

Uploaded on Nov 1, 2023
Multispectral image pairs can provide the combined information, making object detection applications more reliable and robust in the open world. To fully exploit the different moda...

May the Force Be with Your Copy Mechanism: Enhanced Supervised-Copy Method for Natural Language Generation

Uploaded on Nov 1, 2023
Driving 3D characters to dance following a piece of music is highly challenging due to the spatial constraints applied to poses by choreography norms. In addition, the generated da...

ResNet strikes back: An improved training procedure in timm

Uploaded on Nov 1, 2023
Graph and hypergraph representation learning has attracted increasing attention from various research fields. Despite the decent performance and fruitful applications of Graph Neur...

ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision

Uploaded on Nov 1, 2023
A key function of auditory cognition is the association of characteristic sounds with their corresponding semantics over time. Humans attempting to discriminate between fine-graine...

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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.