@ArjunCodess

• replaced the evidence summary with a clearer evidence table linking each claim to its supporting results and limitations.
• added a section explaining the main lessons for mechanistic interpretability.
• expanded the limitations section with clearer discussion of the study’s scope and assumptions.

image: source control image showing the main changes i did in the paper.

• added a glossary for the main biology terms.
• explained why the selected motifs are biologically important.
• simplified the theory section.
• moved detailed proofs to the appendix.
• clearly defined how nucleotide motifs are mapped to tokens.
• added a simple workflow diagram for the full analysis pipeline.

image: source control image showing changes that i made in the code.

made the entire pipeline fully reproducible, without any caps, including the threshold analysis and result generation.

image: screenshot of the pipeline being run.

• showed model performance before the interpretability analysis.
• separated task performance from probe results.

• combined all interpretability analyses into one pipeline.
• made CTCF the main case study.
• made the overall framing clearer.

• explained every analysis threshold.
• validated thresholds with sensitivity tests and control experiments.
• showed that the main results stay consistent across different thresholds.