# Self-training for few-shot NLP

Area: [Synthetic data and self-improvement for LLMs](https://mlsanity.com/synth/index.md). HTML: https://mlsanity.com/synth/self-training-for-few-shot-nlp/

## Key facts

- Self-training for few-shot NLP: 28 papers on arXiv since 2021 (data through 14 Oct 2026).
- 4 of its 28 mapped papers (14%) cite “STraTA: Self-Training with Task Augmentation for Better Few-shot Learning” (2021, arXiv 2109.06270).
- 2 of its 28 mapped papers (7%) cite “Self-training with Few-shot Rationalization: Teacher Explanations Aid Student in Few-shot NLU” (2021, arXiv 2109.08259).

## Most cited here

- [STraTA: Self-Training with Task Augmentation for Better Few-shot Learning](https://mlsanity.com/paper/2109.06270/) (2021), cited by 4 papers here
- [Self-training with Few-shot Rationalization: Teacher Explanations Aid Student in Few-shot NLU](https://mlsanity.com/paper/2109.08259/) (2021), cited by 2 papers here
- [Revisiting Self-Training for Few-Shot Learning of Language Model](https://mlsanity.com/paper/2110.01256/) (2021), cited by 2 papers here
- [LiST: Lite Prompted Self-training Makes Parameter-Efficient Few-shot Learners](https://mlsanity.com/paper/2110.06274/) (2021), cited by 2 papers here
- [Zero-Shot Text Classification with Self-Training](https://mlsanity.com/paper/2210.17541/) (2022), cited by 2 papers here
- [Self-Generated In-Context Learning: Leveraging Auto-regressive Language Models as a Demonstration Generator](https://mlsanity.com/paper/2206.08082/) (2022), cited by 1 papers here
- [Self-ICL: Zero-Shot In-Context Learning with Self-Generated Demonstrations](https://mlsanity.com/paper/2305.15035/) (2023), cited by 1 papers here
- [Self-Improving for Zero-Shot Named Entity Recognition with Large Language Models](https://mlsanity.com/paper/2311.08921/) (2023), cited by 1 papers here