SPIN Unprocessed October 15, 2026 ai_technology research
Tracing Morphology, Semantics, and Divergence in Language Acquisition
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arXiv:2610.19041v1 Announce Type: new Abstract: Understanding the dynamics of language acquisition in Large Language Models (LLMs) is crucial for uncovering how statistical representations evolve into structured linguistic capabilities. However, most existing studies focus primarily on fully trained models, leaving the developmental trajectory across intermediate training stages largely underexplored. In this work, we leverage intermediate checkpoints from open-source models (e.g., Pythia and OL
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