QuestA: Expanding Reasoning Capacity in LLMs via Question Augmentation
📰 ArXiv cs.AI
QuestA expands LLM reasoning capacity via question augmentation
Action Steps
- Introduce partial supervision to question augmentation
- Apply reinforcement learning to adapt to harder reasoning problems
- Evaluate the effectiveness of question augmentation on LLMs
- Fine-tune LLMs with augmented questions to improve reasoning capacity
Who Needs to Know This
ML researchers and engineers can benefit from this approach to improve LLM performance on reasoning tasks, and it can be applied by AI engineers and data scientists working on NLP projects
Key Insight
💡 Question augmentation can improve LLM reasoning capacity beyond base model capabilities
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🤖 QuestA: Expand LLM reasoning capacity with question augmentation!
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