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Research: findings phrasing — moderate explanation maximizes agreement (arXiv:2607.24601, 2607.09524) #525

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@ajianaz

Context

Two empirical findings relevant to how Cora presents findings:

  1. XAI & Trust study (arXiv:2607.24601, n=34): full explanations yield highest perceived trust (3.99/5) but NOT highest agreement; moderate explanations achieve highest agreement (89.22%). More explanation makes developers question AI recommendations more often. No explanation = lowest trust and agreement.

  2. CuREV curation pipeline (arXiv:2607.09524): separating high/low-quality review comments via an evaluation framework, then using high-quality ones as in-context exemplars to reformulate low-quality ones, produces more actionable and more stylistically diverse comments.

Proposal

  • Keep findings format at 'moderate explanation': severity + short reason + code evidence; avoid long reasoning dumps → shipped in feat(review): moderate-explanation style in findings prompt #527 (b018eaf)
  • Long-term: use human accept/dismiss history on findings as quality labels; store accepted findings as few-shot exemplars for findings phrasing (exemplar-guided reformulation)

References

Activity

  1. ajianaz commented on Aug 25, 2026

    @ajianaz
    CollaboratorAuthor

    First checklist item landed in #527 (EXPLANATION STYLE section in the review system prompt). The second item (exemplar-guided reformulation from accept/dismiss history) requires an accumulated quality-labeled findings history first — keeping this issue open as the tracking point for that future work.

  2. ajianaz commented on Aug 29, 2026

    @ajianaz
    CollaboratorAuthor

    Implemented via #527 (merged). Follow-up tracked in #545 (search-path vector signal dead in fresh processes). Closing as done.

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