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.
SUBMIT A METRIC USE CASE
If you have a metric use case that you think should be featured in the Catalogue of Tools & Metrics for Trustworthy AI, we would love to hear from you!
SUBMITShapeLLM: Universal 3D Object Understanding for Embodied Interaction
Reasoning with knowledge structures/planningRecognition/object detectionUploaded on Jun 5, 2024The BigCode project, an open-scientific collaboration focused on the
responsible development of Large Language Models for Code (Code LLMs),
introduces StarCoder2. In partnership wi...
Objective(s)
MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining
Recognition/object detectionUploaded on Jun 5, 2024We propose a novel model-selection method for dynamic real-life networks. Our
approach involves training a classifier on a large body of synthetic network
data. The data is generat...
Objective(s)
Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations
Recognition/object detectionUploaded on Jun 5, 2024The 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...
Objective(s)
ShapeLLM: Universal 3D Object Understanding for Embodied Interaction
Reasoning with knowledge structures/planningRecognition/object detectionUploaded on May 21, 2024The BigCode project, an open-scientific collaboration focused on the
responsible development of Large Language Models for Code (Code LLMs),
introduces StarCoder2. In partnership wi...
Objective(s)
MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining
Recognition/object detectionUploaded on May 21, 2024We propose a novel model-selection method for dynamic real-life networks. Our
approach involves training a classifier on a large body of synthetic network
data. The data is generat...
Objective(s)
Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations
Recognition/object detectionUploaded on May 21, 2024The 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...
Objective(s)
ShapeLLM: Universal 3D Object Understanding for Embodied Interaction
Reasoning with knowledge structures/planningRecognition/object detectionUploaded on Apr 22, 2024The BigCode project, an open-scientific collaboration focused on the
responsible development of Large Language Models for Code (Code LLMs),
introduces StarCoder2. In partnership wi...
Objective(s)
MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining
Recognition/object detectionUploaded on Apr 22, 2024We propose a novel model-selection method for dynamic real-life networks. Our
approach involves training a classifier on a large body of synthetic network
data. The data is generat...
Objective(s)
Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations
Recognition/object detectionUploaded on Apr 22, 2024The 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...
Objective(s)
The VampPrior Mixture Model
Recognition/object detectionUploaded on Apr 2, 2024Language models (LMs) have proven to be powerful tools for psycholinguistic
research, but most prior work has focused on purely behavioural measures (e.g.,
surprisal comparisons). ...
Objective(s)
PUAD: Frustratingly Simple Method for Robust Anomaly Detection
Reasoning with knowledge structures/planningRecognition/object detectionUploaded on Apr 2, 2024The BigCode project, an open-scientific collaboration focused on the
responsible development of Large Language Models for Code (Code LLMs),
introduces StarCoder2. In partnership wi...
Objective(s)
MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Representations
Recognition/object detectionUploaded on Apr 2, 2024Object 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...
Objective(s)
SARDet-100K: Towards Open-Source Benchmark and ToolKit for Large-Scale SAR Object Detection
Recognition/object detectionUploaded on Mar 15, 2024Language models (LMs) have proven to be powerful tools for psycholinguistic
research, but most prior work has focused on purely behavioural measures (e.g.,
surprisal comparisons). ...
Objective(s)
EnCLAP: Combining Neural Audio Codec and Audio-Text Joint Embedding for Automated Audio Captioning
Recognition/object detectionUploaded on Mar 15, 2024The 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...
Objective(s)
SpiderMesh: Spatial-aware Demand-guided Recursive Meshing for RGB-T Semantic Segmentation
Recognition/object detectionUploaded on Nov 1, 2023Numerical validation is at the core of machine learning research as it allows
to assess the actual impact of new methods, and to confirm the agreement
between theory and practice. ...
Objective(s)
Slow-Fast Auditory Streams For Audio Recognition
Recognition/object detectionUploaded on Nov 1, 2023Language agents, which use a large language model (LLM) capable of in-context
learning to interact with an external environment, have recently emerged as a
promising approach to co...
Objective(s)
Shape-Biased Domain Generalization via Shock Graph Embeddings
Event/anomaly detectionUploaded on Nov 1, 2023Contrastive learning-based video-language representation learning approaches,
e.g., CLIP, have achieved outstanding performance, which pursue semantic
interaction upon pre-defined ...
Objective(s)
SP-ViT: Learning 2D Spatial Priors for Vision Transformers
Reasoning with knowledge structures/planningRecognition/object detectionUploaded on Nov 1, 2023Automatic pulmonary nodules classification is significant for early diagnosis
of lung cancers. Recently, deep learning techniques have enabled remarkable
progress in this field. Ho...
Objective(s)
SNoRe: Scalable Unsupervised Learning of Symbolic Node Representations
Recognition/object detectionUploaded on Nov 1, 2023Learning from complex real-life networks is a lively research area, with
recent advances in learning information-rich, low-dimensional network node
representations. However, state-...
Objective(s)
ResNet strikes back: An improved training procedure in timm
Recognition/object detectionUploaded on Nov 1, 2023Graph and hypergraph representation learning has attracted increasing
attention from various research fields. Despite the decent performance and
fruitful applications of Graph Neur...
Objective(s)
