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mechanisticinterpretability

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Investigating implicit reasoning in GPT-2-like Transformers through mechanistic interpretability (Logit Lens and Causal Tracing). Building on NeurIPS 2024 research, this work demonstrates how a targeted training-data intervention overcomes the OOD compositionality gap in a controlled two-hop reasoning task.

  • Updated Oct 27, 2026
  • Python

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