Papers with multi-round distillation framework
Distilling Instruction-following Abilities of Large Language Models with Task-aware Curriculum Planning (2024.findings-emnlp)
Copied to clipboard
| Challenge: | Instruction tuning aims to align large language models (LLMs) with open-domain instructions and human-preferred responses. |
| Approach: | They propose a multi-round distillation framework that uses an oracle LLM to select instructions that are difficult for a student LLM. |
| Outcome: | The proposed framework outperforms large language models and user-tuned models on several widely recognized benchmarks and multiple student LLMs. |