Prompt Transfer (PoT) is a recently-proposed approach to improve prompt-tuning, by
initializing the target prompt with the existing prompt trained on similar source tasks …

The impact of price and price changes should not be ignored while designing algorithms for
predicting customer choice. Consumer preferences should be modeled with consideration of …

Aspect level sentiment analysis is a fine grained task in sentiment analysis which identifies
the product features from an opinionated piece of text and maps the sentiment towards each …

Abstract Although the existing Named Entity Recognition (NER) models have achieved
promising performance, they suffer from certain drawbacks. The sequence labeling-based …

Abstract Named Entity Recognition (NER) aims to automatically extract specific entities from
the unstructured text. Compared with performing NER in English, Chinese NER is more …

Sequence-to-sequence (seq2seq) learning is a popular fashion for large-scale pretraining
language models. However, the previous seq2seq pretraining models generally focus on …

Relation Extraction (RE) is a vital step to complete Knowledge Graph (KG) by extracting
entity relations from texts. However, it usually suffers from the long-tail issue. The training …

Recent studies revealed that even the most widely used benchmark dataset still contains
more than 5% sample-level annotation noise in Named Entity Recognition (NER). Hence …

Since the outbreak of COVID-19, it has had a huge impact on the whole world. In China,
there have been a large number of epidemiological investigation reports in response to …

Named Entity Recognition (NER) is a fundamental problem in Natural Language Processing
and has received much research attention. Although the current neural-based NER …