Do CLIP models 'parrot' text from images? This article explores text detection bias in vision-language systems.
In a recent research, a team of researchers examined CLIP (Contrastive Language and Image Pretraining), which is a famous neural ...
Tag: Detection
Meet BarbNet: a specialized deep learning model designed for automated detection and phenotyping of spikes in microscopic edge images
Our daily lives depend on cereal crops such as wheat and barley, and our agricultural achievements depend on our ability ...
Comparing Outlier Detection Methods | by John Andrews | Dec, 2023
Using batting stats from Major League Baseball’s 2023 seasonShohei Ohtani, photo by Erik Drost on Flikr, CC BY 2.0Outlier detection ...
LiDAR: Linear Probing Performance Detection on Co-Integration SSL Architectures
Joint embedding (JE) architectures have emerged as a promising avenue for acquiring transferable data representations. However, a key obstacle to ...
Resource-Efficient Device-Directed Speech Detection and Multimodal Data with Large Base Models
*=Equal taxpayers This article was accepted into the Efficient Natural Language and Speech Processing workshop at NeurIPS 2023. Interactions with ...
FLEEK: Detection and correction of factual errors with evidence obtained from external knowledge
The inability of large linguistic models to attribute their statements to external knowledge and their tendency to hallucinate makes it ...
This AI article introduces ‘Lightning Cat’: a deep learning-based tool for smart contract vulnerability detection
Smart contracts play a fundamental role in blockchain technology for the development of decentralized applications. The susceptibility of smart contracts ...
SeMAnD: Self-supervised anomaly detection in multimodal geospatial datasets
*= Equal taxpayers We propose a self-supervised anomaly detection technique, called SeMAnD, to detect geometric anomalies in multimodal geospatial datasets. ...
Density Kernel Depth for Outlier Detection in Functional Data
Image generated from DALLE-3 In today's era of massive data sets and intricate data patterns, the art and science of ...
Modality Dropout for Multimodal Device-Directed Speech Detection Using Verbal and Nonverbal Features
Device-directed speech detection (DDSD) is the binary classification task of distinguishing between queries directed to a voice assistant and parallel ...
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