Adversarial training lattice lstm for named entity recognition of rail fault texts
S Su, J Qu, Y Cao, R Li, G Wang - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Learning and identifying key concepts from past fault records are essential for us to
understand the causes of these faults, which lay the foundation for the fault diagnosis and …
understand the causes of these faults, which lay the foundation for the fault diagnosis and …
[HTML][HTML] Who evaluates the evaluators? On automatic metrics for assessing AI-based offensive code generators
AI-based code generators are an emerging solution for automatically writing programs
starting from descriptions in natural language, by using deep neural networks (Neural …
starting from descriptions in natural language, by using deep neural networks (Neural …
End-to-end entity-aware neural machine translation
Accurate translation of entities (eg, person names, organizations, geography) is important in
neural machine translation (briefly, NMT), as they are usually more difficult to translate than …
neural machine translation (briefly, NMT), as they are usually more difficult to translate than …
Vulnerabilities in ai code generators: Exploring targeted data poisoning attacks
AI-based code generators have become pivotal in assisting developers in writing software
starting from natural language (NL). However, they are trained on large amounts of data …
starting from natural language (NL). However, they are trained on large amounts of data …
DEEP: denoising entity pre-training for neural machine translation
It has been shown that machine translation models usually generate poor translations for
named entities that are infrequent in the training corpus. Earlier named entity translation …
named entities that are infrequent in the training corpus. Earlier named entity translation …
Lingua Franca–Entity-Aware Machine Translation Approach for Question Answering over Knowledge Graphs
N Srivastava, A Perevalov, D Kuchelev… - Proceedings of the 12th …, 2023 - dl.acm.org
This research paper proposes an approach called Lingua Franca that improves machine
translation quality by utilizing information from a knowledge graph to translate named …
translation quality by utilizing information from a knowledge graph to translate named …
Challenges in context-aware neural machine translation
Context-aware neural machine translation involves leveraging information beyond sentence-
level context to resolve inter-sentential discourse dependencies and improve document …
level context to resolve inter-sentential discourse dependencies and improve document …
Adam Mickiewicz University at WMT 2022: NER-assisted and quality-aware neural machine translation
A Nowakowski, G Pałka, K Guttmann… - arXiv preprint arXiv …, 2022 - arxiv.org
This paper presents Adam Mickiewicz University's (AMU) submissions to the constrained
track of the WMT 2022 General MT Task. We participated in the Ukrainian $\leftrightarrow …
track of the WMT 2022 General MT Task. We participated in the Ukrainian $\leftrightarrow …
Enhancing robustness of ai offensive code generators via data augmentation
Since manually writing software exploits for offensive security is time-consuming and
requires expert knowledge, AI-base code generators are an attractive solution to enhance …
requires expert knowledge, AI-base code generators are an attractive solution to enhance …
Analysis of Digital Information in Storage Devices Using Supervised and Unsupervised Natural Language Processing Techniques
LA Martínez Hernández, AL Sandoval Orozco… - Future Internet, 2023 - mdpi.com
Due to the advancement of technology, cybercrime has increased considerably, making
digital forensics essential for any organisation. One of the most critical challenges is to …
digital forensics essential for any organisation. One of the most critical challenges is to …