arXiv:1704.08531
A Survey of Neural Network Techniques for Feature Extraction from Text
원문 초록
This paper aims to catalyze the discussions about text feature extraction techniques using neural network architectures. The research questions discussed in the paper focus on the state-of-the-art neural network techniques that have proven to be useful tools for language processing, language generation, text classification and other computational linguistics tasks.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Making Language Model a Hierarchical Classifier and Generator
Survey of Abstract Meaning Representation: Then, Now, Future
Specialized text classification: an approach to classifying Open Banking transactions
Robustness of Misinformation Classification Systems to Adversarial Examples Through BeamAttack
Prompt Candidates, then Distill: A Teacher-Student Framework for LLM-driven Data Annotation
AppealCase: A Dataset and Benchmark for Civil Case Appeal Scenarios
토론
이 논문과 연결된 포럼 글이 아직 없습니다.