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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SUBMITShrinking Your TimeStep: Towards Low-Latency Neuromorphic Object Recognition with Spiking Neural Network
Interaction support/chatbotsRecognition/object detectionUploaded on Jun 5, 2024Multimodal 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)
ShapeLLM: 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)
Proprioception Is All You Need: Terrain Classification for Boreal Forests
Recognition/object detectionUploaded on Jun 5, 2024In 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...
Objective(s)
ProMISe: Promptable Medical Image Segmentation using SAM
Recognition/object detectionUploaded on Jun 5, 2024This 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...
Objective(s)
PLAPT: Protein-Ligand Binding Affinity Prediction Using Pretrained Transformers
Recognition/object detectionUploaded on Jun 5, 2024Retrieval-Augmented Generation (RAG) is a prevalent approach to infuse a
private knowledge base of documents with Large Language Models (LLM) to build
Generative Q\&A (Question-Ans...
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)
HANet: A Hierarchical Attention Network for Change Detection With Bitemporal Very-High-Resolution Remote Sensing Images
Recognition/object detectionUploaded on Jun 5, 2024Multimodal Large Language Models (MLLMs) have experienced significant
advancements recently. Nevertheless, challenges persist in the accurate
recognition and comprehension of intri...
Objective(s)
Efficient Image Super-Resolution via Symmetric Visual Attention Network
Recognition/object detectionUploaded on Jun 5, 2024In 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)
Do You Remember? Dense Video Captioning with Cross-Modal Memory Retrieval
Recognition/object detectionUploaded on Jun 5, 2024Vision 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...
Objective(s)
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
Reasoning with knowledge structures/planningRecognition/object detectionUploaded on Jun 5, 2024In this work, we introduce Mini-Gemini, a simple and effective framework
enhancing multi-modality Vision Language Models (VLMs). Despite the
advancements in VLMs facilitating basic...
Objective(s)
DDMI: Domain-Agnostic Latent Diffusion Models for Synthesizing High-Quality Implicit Neural Representations
Recognition/object detectionUploaded on Jun 5, 2024Today'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...
Objective(s)