2025
Grokking in the Wild: Data Augmentation for Real-World Multi-Hop Reasoning with Transformers
ICML 2025poster
Transformers have achieved great success in numerous NLP tasks but continue to exhibit notable gaps in multi-step factual reasoning, especially when real-world knowledge is sparse. Recent advances in grokking have demonstrated that neural networks can transition from memorizing to perfectly generali…