[HTML][HTML] Large language models in radiology: fundamentals, applications, ethical considerations, risks, and future directions
With the advent of large language models (LLMs), the artificial intelligence revolution in
medicine and radiology is now more tangible than ever. Every day, an increasingly large …
medicine and radiology is now more tangible than ever. Every day, an increasingly large …
Large language models in radiology: fundamentals, applications, ethical considerations, risks, and future directions
With the advent of large language models (LLMs), the artificial intelligence revolution in
medicine and radiology is now more tangible than ever. Every day, an increasingly large …
medicine and radiology is now more tangible than ever. Every day, an increasingly large …
[HTML][HTML] Recognizing misogynous memes: Biased models and tricky archetypes
Warning: This paper contains examples of language and images which may be offensive.
Misogyny is a form of hate against women and has been spreading exponentially through …
Misogyny is a form of hate against women and has been spreading exponentially through …
FEDS-ICL: Enhancing translation ability and efficiency of large language model by optimizing demonstration selection
Large language models (LLMs) that exhibit a remarkable ability by in-context learning (ICL)
with bilingual demonstrations have been recognized as a potential solution for machine …
with bilingual demonstrations have been recognized as a potential solution for machine …
Causal keyword driven reliable text classification with large language model feedback
Recent studies show Pre-trained Language Models (PLMs) tend to shortcut learning,
reducing effectiveness with Out-Of-Distribution (OOD) samples, prompting research on the …
reducing effectiveness with Out-Of-Distribution (OOD) samples, prompting research on the …
Mitigating social biases of pre-trained language models via contrastive self-debiasing with double data augmentation
Abstract Pre-trained Language Models (PLMs) have been shown to inherit and even amplify
the social biases contained in the training corpus, leading to undesired stereotype in real …
the social biases contained in the training corpus, leading to undesired stereotype in real …
[HTML][HTML] Chinese mineral exploration named entity recognition for literature mining by fusing multi-features with an enhancement domain pre-training model
Field geological work has accumulated a large number of mineral exploration reports, which
comprehensively describe information such as the structure of ore bodies and resource …
comprehensively describe information such as the structure of ore bodies and resource …
[HTML][HTML] The Landscapes of Sustainability in Library and Information Science: Diachronous Citation Perspective
AM Kamińska, Ł Opaliński, Ł Wyciślik - Sustainability, 2024 - mdpi.com
Sustainability issues constitute a distinct subdiscipline of librarianship and information
science, with its own areas of study, methods, and areas of application. Despite being nearly …
science, with its own areas of study, methods, and areas of application. Despite being nearly …
Enhancing abusive language detection: A domain-adapted approach leveraging BERT pre-training tasks
H Jarquín-Vásquez, HJ Escalante… - Pattern Recognition …, 2024 - Elsevier
The widespread adoption of deep learning approaches in natural language processing is
largely attributed to their exceptional performance across diverse tasks. Notably …
largely attributed to their exceptional performance across diverse tasks. Notably …
A Target-Aware Analysis of Data Augmentation for Hate Speech Detection
Hate speech is one of the main threats posed by the widespread use of social networks,
despite efforts to limit it. Although attention has been devoted to this issue, the lack of …
despite efforts to limit it. Although attention has been devoted to this issue, the lack of …