Article

In-Context Learning for Data Generation in Aspect-Based Opinion Extraction

2023-07-19

Abstract excerpt

<title>Abstract</title> <p>In-Context Learning (ICL), a strategy that generates text by passing a list of input-output examples to a Large Language Model, has shown state-of-the-art performance (SOTA) for many Natural Language Processing tasks. In this work, we aim to apply ICL for the synthetic generation of opinionated triples (sentence, aspect, and opinion) to enhance the training of models in two Aspect-Based...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 8307e036-c91f-5385-ae2f-2eb966b8c62f
DOI: 10.21203/rs.3.rs-3170766/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

In-Context Learning for Data Generation in Aspect-Based Opinion ExtractionDOI 10.21203/rs.3.rs-3170766/v1Read

Evaluating the BERTScore of synthetic text and its sentiment analysisSemantic proximity Read

A Multi-Model, Multi-Domain Benchmark of Large Language Model Agreement with Humans and with Each Other in Sentiment ClassificationSemantic proximity Read

How Well Do Large Language Models Agree with Humans — and Each Other? A Multi-Model, Multi-Domain Sentiment Benchmark StudySemantic proximity Read

Enhancing Contextual Understanding in Large Language Models with Dynamic Dependency Structures: A Methodological ApproachSemantic proximity Read

Balancing AI and Human Judgment for Text Refinement: A Step Toward Intercultural Competence in Language ProcessingSemantic proximity Read

Enhancing Text Quality with Human-Machine Collaboration: A Refinement ApproachSemantic proximity Read

Dynamic Probabilistic Contextual Realignment in Transformer-Based Large Language Models for Semantic ConsistencySemantic proximity Read

Boosting Domain Knowledge Understanding of LLMs through Fine-Tuning with a Novel KNN AlgorithmSemantic proximity Read

Upscaling A Smaller LLM to More Parameters via Manual Regressive DistillationSemantic proximity Read

A Hybrid Transformer-Driven and Embedding-Augmented Framework for Automated Contextual MCQ Generation with Semantic Distractor Engineering and Difficulty-Aware ClassificationSemantic proximity Read

Trends in Natural Language Understanding with sentence representation and sentiment analysisSemantic proximity Read

Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generation ModelSemantic proximity Read