Aspect-based argument mining
D Trautmann - arXiv preprint arXiv:2011.00633, 2020 - arxiv.org
Computational Argumentation in general and Argument Mining in particular are important
research fields. In previous works, many of the challenges to automatically extract and to …
research fields. In previous works, many of the challenges to automatically extract and to …
On the hidden negative transfer in sequential transfer learning for domain adaptation from news to tweets
Transfer Learning has been shown to be a powerful tool for Natural Language Processing
(NLP) and has outperformed the standard supervised learning paradigm, as it takes benefit …
(NLP) and has outperformed the standard supervised learning paradigm, as it takes benefit …
A cross-genre ensemble approach to robust Reddit part of speech tagging
Part of speech tagging is a fundamental NLP task often regarded as solved for high-
resource languages such as English. Current state-of-the-art models have achieved high …
resource languages such as English. Current state-of-the-art models have achieved high …
Task-adaptive pre-training of language models with word embedding regularization
Pre-trained language models (PTLMs) acquire domain-independent linguistic knowledge
through pre-training with massive textual resources. Additional pre-training is effective in …
through pre-training with massive textual resources. Additional pre-training is effective in …
Domain adaptation for pos tagging with contrastive monotonic chunk-wise attention
RK Mundotiya, A Mehta, R Baruah - Neural Processing Letters, 2022 - Springer
Part of Speech (POS) tagging is a sequential labelling task and one of the core applications
of Natural Language Processing. It has been a challenging problem for the low resource …
of Natural Language Processing. It has been a challenging problem for the low resource …
Context-specific adaptation of subjective content descriptions
An agent in pursuit of a task may work with an individual collection of documents, which is
known as a corpus. We assume that each document in the corpus is associated with …
known as a corpus. We assume that each document in the corpus is associated with …
Evaluation of Explainable Artificial Intelligence Methods in Language Learning Classification of Spanish Tertiary Education Students
G Tzionis, G Antzoulatos, P Papaioannou… - Interactive Mobile …, 2023 - Springer
With the increasing prevalence of AI, significant advancements have been made across
various domains, such as healthcare, learning, industry, etc. However, challenges persist in …
various domains, such as healthcare, learning, industry, etc. However, challenges persist in …
[PDF][PDF] POS Tagging Model for Malay Tweets Using New POS Tagset and BiLTSM-CRF Approach.
S Tiun, SNAN Ariffin, YD Chew - ALTNLP, 2022 - ceur-ws.org
This paper proposes a Malay Part-of-Speech (POS) tagger using a new set of POS tags and
a deep learning classifier. A new set of POS tags was proposed, and the POS classifier was …
a deep learning classifier. A new set of POS tags was proposed, and the POS classifier was …
Neural supervised domain adaptation by augmenting pre-trained models with random units
Neural Transfer Learning (TL) is becoming ubiquitous in Natural Language Processing
(NLP), thanks to its high performance on many tasks, especially in low-resourced scenarios …
(NLP), thanks to its high performance on many tasks, especially in low-resourced scenarios …
Neural Transfer Learning for Domain Adaptation in Natural Language Processing
S Meftah - 2021 - theses.hal.science
Recent approaches based on end-to-end deep neural networks have revolutionised Natural
Language Processing (NLP), achieving remarkable results in several tasks and languages …
Language Processing (NLP), achieving remarkable results in several tasks and languages …