Large language models for forecasting and anomaly detection: A systematic literature review

J Su, C Jiang, X Jin, Y Qiao, T Xiao, H Ma… - arXiv preprint arXiv …, 2024 - arxiv.org
This systematic literature review comprehensively examines the application of Large
Language Models (LLMs) in forecasting and anomaly detection, highlighting the current …

A review on human-computer interaction and intelligent robots

F Ren, Y Bao - International Journal of Information Technology & …, 2020 - World Scientific
In the field of artificial intelligence, human–computer interaction (HCI) technology and its
related intelligent robot technologies are essential and interesting contents of research …

BERTweet: A pre-trained language model for English Tweets

DQ Nguyen, T Vu, AT Nguyen - arXiv preprint arXiv:2005.10200, 2020 - arxiv.org
We present BERTweet, the first public large-scale pre-trained language model for English
Tweets. Our BERTweet, having the same architecture as BERT-base (Devlin et al., 2019), is …

Lexicon enhanced Chinese sequence labeling using BERT adapter

W Liu, X Fu, Y Zhang, W Xiao - arXiv preprint arXiv:2105.07148, 2021 - arxiv.org
Lexicon information and pre-trained models, such as BERT, have been combined to explore
Chinese sequence labelling tasks due to their respective strengths. However, existing …

Automated concatenation of embeddings for structured prediction

X Wang, Y Jiang, N Bach, T Wang, Z Huang… - arXiv preprint arXiv …, 2020 - arxiv.org
Pretrained contextualized embeddings are powerful word representations for structured
prediction tasks. Recent work found that better word representations can be obtained by …

Adversarial transfer learning for Chinese named entity recognition with self-attention mechanism

P Cao, Y Chen, K Liu, J Zhao, S Liu - Proceedings of the 2018 …, 2018 - aclanthology.org
Named entity recognition (NER) is an important task in natural language processing area,
which needs to determine entities boundaries and classify them into pre-defined categories …

Dual adversarial neural transfer for low-resource named entity recognition

JT Zhou, H Zhang, D Jin, H Zhu, M Fang… - Proceedings of the …, 2019 - aclanthology.org
We propose a new neural transfer method termed Dual Adversarial Transfer Network
(DATNet) for addressing low-resource Named Entity Recognition (NER). Specifically, two …

Robust multilingual part-of-speech tagging via adversarial training

M Yasunaga, J Kasai, D Radev - arXiv preprint arXiv:1711.04903, 2017 - arxiv.org
Adversarial training (AT) is a powerful regularization method for neural networks, aiming to
achieve robustness to input perturbations. Yet, the specific effects of the robustness obtained …

Cross-domain label-adaptive stance detection

M Hardalov, A Arora, P Nakov, I Augenstein - arXiv preprint arXiv …, 2021 - arxiv.org
Stance detection concerns the classification of a writer's viewpoint towards a target. There
are different task variants, eg, stance of a tweet vs. a full article, or stance with respect to a …

A survey on syntactic processing techniques

X Zhang, R Mao, E Cambria - Artificial Intelligence Review, 2023 - Springer
Computational syntactic processing is a fundamental technique in natural language
processing. It normally serves as a pre-processing method to transform natural language …