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Found 6 papers, 2 papers with code
Supervised Gradual Machine Learning for Aspect Category Detection
Aspect Category Detection (ACD) aims to identify implicit and explicit aspects in a given review sentence.
Naive Bayes-based Context Extension for Large Language Models
However, conventional In-Context Learning (ICL) approaches are often impeded by length limitations of transformer architecture, which pose challenges when attempting to effectively integrate supervision from a substantial number of demonstration examples.
Relationship of the language distance to English ability of a country
Then, we empirically examine the effectiveness of the proposed semantic language distance (SLD) in explaining the consistent variation in English ability of countries, which is proxied by their performance in the Internet-Based Test of English as Foreign Language (TOEFL iBT).
BERT-ASC: Implicit Aspect Representation Learning through Auxiliary-Sentence Construction for Sentiment Analysis
Unfortunately, the aspect is often expressed implicitly through a set of representatives and thus renders implicit mapping process unattainable unless sufficient labeled examples are available.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
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Gradual Machine Learning for Aspect-level Sentiment Analysis
The state-of-the-art solutions for Aspect-Level Sentiment Analysis (ALSA) were built on a variety of deep neural networks (DNN), whose efficacy depends on large amounts of accurately labeled training data.
