{
  "id": "2610.30630",
  "title": "Interpreting Model Reasoning through Behavioral Counterfactuals",
  "authors": "Shawn Im, James Oldfield, Adel Bibi, Sharon Li",
  "first_public": "2026-10-22",
  "added_at": "2026-10-23",
  "venue": "arXiv",
  "arxiv": "2610.30630",
  "paper_url": "https://arxiv.org/abs/2610.30630",
  "html_url": "https://arxiv.org/html/2610.30630v1",
  "lens": [
    "analysis"
  ],
  "representation": [
    "hidden-state"
  ],
  "computation": [
    "depth-wise",
    "token-wise"
  ],
  "training": [
    "analysis-only"
  ],
  "questions": [
    "interpretability",
    "controllability",
    "evaluation"
  ],
  "evidence": [
    "empirical",
    "mechanistic"
  ],
  "modality": [
    "language"
  ],
  "summary": "Holds a model response fixed while changing the prompt, then learns hidden-state edits that reproduce the change in token probabilities. Uses these edits and activation patching to show how suggestions can influence reasoning through question and filler-token states without being mentioned in the written response.",
  "provenance": "Primary-source literature review, 2026-10-23",
  "author_names": [
    "Shawn Im",
    "James Oldfield",
    "Adel Bibi",
    "Sharon Li"
  ],
  "record_url": "https://latent-implicit-thinking.github.io/papers/2610.30630/",
  "legacy_record_url": "https://latent-implicit-thinking.github.io/papers/#paper-2610-30630",
  "citation_date": "2026-10-22",
  "json_url": "https://latent-implicit-thinking.github.io/papers/2610.30630/record.json",
  "markdown_url": "https://latent-implicit-thinking.github.io/papers/2610.30630/index.md",
  "bibtex_url": "https://latent-implicit-thinking.github.io/papers/2610.30630/citation.bib",
  "csl_url": "https://latent-implicit-thinking.github.io/papers/2610.30630/citation.csl.json",
  "pdf_url": "https://arxiv.org/pdf/2610.30630"
}