A first-year PhD student who received modest scores (2.5/3, 3/4, 2.5/4) on a paper in the Interpretability track at the May ACL ARR cycle is weighing whether to withdraw and resubmit to a workshop or stay in the current review round. Reviewers indicated the methodology was sound but the paper's significance was unclear, suggesting a framing issue rather than fundamental flaw.
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A first-year PhD student received below-threshold scores (2.5/3, 3/4, 2.5/4) on an Interpretability track paper submitted to the May ACL ARR cycle and is considering whether to withdraw it, revise the presentation, and submit to the BlackboxNLP workshop instead, or leave it in the review cycle and hope scores improve.
Why it matters
For early-stage researchers, the choice between persisting with a peer-review process and pivoting to a workshop can affect both publication timeline and career momentum. The student's concern that reviewers "didn't fully get the so what" suggests the paper's core contribution may need clearer framing before resubmission to a higher-profile venue.
What to watch
The student has until the end of next week to decide and, if withdrawing, to prepare a revised submission for BlackboxNLP. The outcome will depend on whether a clearer rewrite can address the presentation gaps the current reviewers identified.
The student's dilemma reflects a common fork in the academic publishing pipeline: after receiving lukewarm peer review scores, researchers must decide whether to revise and resubmit to the same venue in hopes of a more favorable outcome, or to pivot to a lower-tier but faster outlet to secure publication credit. In this case, the feedback is encouraging in one respect—reviewers raised no methodological objections—but damaging in another: they did not perceive the paper's core contribution clearly enough. The student's plan to "improve the presentation" suggests they believe the problem is not the research itself but its communication. Withdrawing to revise before submitting to BlackboxNLP (a workshop focused on interpretability in machine learning) may be a sensible path if the student can articulate the "so what" more forcefully. Staying in the ARR cycle carries both risk (scores may not improve) and a longer wait for resolution. For a first-year PhD student unfamiliar with the ACL ARR process, seeking advice from senior colleagues or advisors before deciding is prudent, since the choice will affect both the publication record and the timeline for revisions.
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