qhjqhj00 ai-writing-assistance-eval
Accepted with Minor Revisions: Value of AI-Assisted Scientific Writing — Hazra et al. (2025) (arXiv:2511.12529, 2025)
What this evaluates
Evaluates how source disclosure and perceived AI authorship influence human editing behavior and subsequent peer-review acceptance decisions for scientific abstracts.
Datasets
- CS-Conference-Abstracts — total 45; splits: test (45); repo https://github.com/skai-research/scientific-writing-assistance
Metrics
accept/reject decision(primary) — range: [0, 1]- Binary outcome determined by majority voting among three independent reviewers. An abstract is marked as accepted if it receives at least two Accept votes out of three.
edit_count— range: count- Total number of character-level operations (insertions, deletions, substitutions) recorded by the custom FirePad editing interface during the author's revision process.
Input / output format
Input: Research excerpt extracted from a published CS paper, paired with a provided abstract (either original human-written or AI-generated via GPT-4o), along with a source disclosure condition (with or without information about AI generation).
Output: Edited abstract text produced by the author, followed by a binary accept/reject decision from each of three independent reviewers.
Scoring recipe
def compute_decision(reviewer_votes):
accepts = sum(reviewer_votes)
return 1 if accepts >= 2 else 0
def compute_acceptance_rate(dataset):
total = len(dataset)
accepted = sum(compute_decision(ab['reviewer_votes']) for ab in dataset)
return accepted / total if total > 0 else 0
Common pitfalls
- Researchers may conflate the underlying scientific novelty of the paper with the quality of the abstract's writing, though the study attempts to isolate writing quality by using already published papers.
- Author editing effort is heavily influenced by performance-contingent financial incentives, which may not reflect natural, unpaid academic writing workflows.
- Copy-pasting abstracts to external AI tools or editors was a major protocol violation risk, requiring strict interface constraints to capture genuine keystroke-level edits.
Evidence (verbatim from paper)
We show each edited abstract to three independent reviewers to obtain the final accept/reject decision by majority voting.
Citation
@misc{hazra2025valueofaiassisted,
title={Accepted with Minor Revisions: Value of AI-Assisted Scientific Writing},
author={Hazra et al. (2025)},
year={2025},
note={arXiv:2511.12529}
}
- arXiv: 2511.12529