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 …

On the hidden negative transfer in sequential transfer learning for domain adaptation from news to tweets

S Meftah, N Semmar, Y Tamaazousti… - … Second Workshop on …, 2021 - cea.hal.science
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 …

A cross-genre ensemble approach to robust Reddit part of speech tagging

S Behzad, A Zeldes - arXiv preprint arXiv:2004.14312, 2020 - arxiv.org
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 …

Task-adaptive pre-training of language models with word embedding regularization

K Nishida, K Nishida, S Yoshida - arXiv preprint arXiv:2109.08354, 2021 - arxiv.org
Pre-trained language models (PTLMs) acquire domain-independent linguistic knowledge
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 …

Context-specific adaptation of subjective content descriptions

F Kuhr, M Bender, T Braun… - 2021 IEEE 15th …, 2021 - ieeexplore.ieee.org
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 …

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 …

[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 …

Neural supervised domain adaptation by augmenting pre-trained models with random units

S Meftah, N Semmar, Y Tamaazousti, H Essafi… - arXiv preprint arXiv …, 2021 - arxiv.org
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 …

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 …