Papers with Relative Indirect Effects

1 papers
Crosscoding Through Time: Tracking Emergence & Consolidation Of Linguistic Representations Throughout LLM Pretraining (2026.acl-long)

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Challenge: Large language models learn non-trivial abstractions during pretraining, but it is not well understood when and how these specific linguistic abilities emerge.
Approach: They propose a method to track the evolution of linguistic features during pretraining by using sparse crosscoders to discover and align features across model checkpoints.
Outcome: The proposed approach can detect features emergence, maintenance, and discontinuation during training stages.

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