On the Noise Robustness of In-Context Learning for Text Generation
–Neural Information Processing Systems
Large language models (LLMs) have shown impressive performance on downstream tasks by in-context learning (ICL), which heavily relies on the quality of demonstrations selected from a large set of annotated examples.
Neural Information Processing Systems
Oct-9-2025, 20:21:26 GMT
- Country:
- Africa > Middle East
- Tunisia (0.04)
- Asia
- China
- Guangdong Province > Shenzhen (0.04)
- Jiangsu Province > Nanjing (0.04)
- Shaanxi Province > Xi'an (0.04)
- Middle East > Jordan (0.04)
- Myanmar > Tanintharyi Region
- Dawei (0.04)
- China
- North America > United States
- Africa > Middle East
- Genre:
- Research Report > Experimental Study (0.93)
- Industry:
- Government (0.46)
- Technology: