Selective Fine-tuning on LLM-labeled Data May Reduce Reliance on Human Annotation: A Case Study Using Schedule-of-Event Table Detection.
Bhawesh KumarJonathan AmarEric YangNan LiYugang JiaPublished in: CoRR (2024)
Keyphrases
- labeled data
- fine tuning
- active learning
- semi supervised learning
- unlabeled data
- semi supervised
- text classification
- training data
- transfer learning
- supervised learning
- feature engineering
- labeled training data
- domain adaptation
- semi supervised classification
- labeling process
- prior knowledge
- learning algorithm
- labeled examples
- data points
- training examples
- class labels
- label propagation
- co training
- labeled and unlabeled data
- fine tuned
- multiple instance learning
- target domain
- image annotation
- labeled instances
- text categorization
- labeled training set
- object detection
- data mining
- labeled data for training
- supervised methods
- human experts
- multi view
- dimensionality reduction
- machine learning