Large language models for forecasting and anomaly detection: A systematic literature review
This systematic literature review comprehensively examines the application of Large
Language Models (LLMs) in forecasting and anomaly detection, highlighting the current …
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 …
related intelligent robot technologies are essential and interesting contents of research …
BERTweet: A pre-trained language model for English Tweets
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 …
Tweets. Our BERTweet, having the same architecture as BERT-base (Devlin et al., 2019), is …
Lexicon enhanced Chinese sequence labeling using BERT adapter
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 …
Chinese sequence labelling tasks due to their respective strengths. However, existing …
Automated concatenation of embeddings for structured prediction
Pretrained contextualized embeddings are powerful word representations for structured
prediction tasks. Recent work found that better word representations can be obtained by …
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
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 …
which needs to determine entities boundaries and classify them into pre-defined categories …
Dual adversarial neural transfer for low-resource named entity recognition
We propose a new neural transfer method termed Dual Adversarial Transfer Network
(DATNet) for addressing low-resource Named Entity Recognition (NER). Specifically, two …
(DATNet) for addressing low-resource Named Entity Recognition (NER). Specifically, two …
Robust multilingual part-of-speech tagging via adversarial training
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 …
achieve robustness to input perturbations. Yet, the specific effects of the robustness obtained …
Cross-domain label-adaptive stance detection
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 …
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
Computational syntactic processing is a fundamental technique in natural language
processing. It normally serves as a pre-processing method to transform natural language …
processing. It normally serves as a pre-processing method to transform natural language …