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Roman Abramov

1 accepted papers

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…

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