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Study Examines Linear Alignment of Late-Stage Representations Across LLMs
A new arXiv paper investigates whether independently trained language models end up with compatible internal representations in their later layers, despite differing objectives, architectures, and data types. The authors test whether a simple affine mapping can translate the late-stage representations of one model into those of another, exploring how far that compatibility reaches.