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percom-author-response

percom-author-response

【开发与工程】Use when drafting an IEEE PerCom rebuttal after being invited following the initial reviews, covering the bounded single-round reply that answers explicit reviewer questions, corrects misreadings, points to evidence already in the paper without promising new experiments, and preserves double-blindness.

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name: percom-author-response description: Use when drafting an IEEE PerCom rebuttal after being invited following the initial reviews, covering the bounded single-round reply that answers explicit reviewer questions, corrects misreadings, points to evidence already in the paper without promising new experiments, and preserves double-blindness.

PerCom Author Response

Use this after PerCom reviews are released and you have been invited to submit a rebuttal. PerCom's rebuttal is a single, bounded turn: it answers the reviewers' explicit questions, resolves misunderstandings, and clarifies — and the call states that new experiments are not expected. There is no journal-style revision that follows, so the rebuttal must win with the paper you already submitted. It remains double-blind: reveal no author, institution, testbed, or dataset-owner identity.

First: did you clear the early-rejection gate?

Papers with no positive review are early-rejected before the rebuttal opens — there is no rebuttal to write for those. If you were invited, at least one reviewer sees a path to publication: your job is to give that advocate the answers they need for the TPC discussion, and to neutralize the specific doubts of the others.

Triage

  • Answer what affects the decision: significance of the contribution, soundness of the method, cross-subject / deployment evaluation, appropriate metrics (F1 vs. pooled accuracy), and clarity.
  • Use evidence that already exists in the submitted paper or dataset — a table, a figure, an appendix result the reviewer overlooked. Do not promise a new experiment; the process does not expect or reward one, and you cannot add it.
  • Correct factual misreadings first; a reviewer who misread which split produced a number is often persuadable with a pointer.
  • Keep every word anonymous — do not name your testbed, deployment site, institution, or a non-anonymized dataset, even to strengthen a point.

Structure the bounded reply

Group by reviewer, lead each item with the reviewer's own question, and answer with a pointer into the existing paper:

[R1.Q1] "Is the eating-recognition result cross-subject or within-subject?"
        -> Table 2 already reports leave-one-subject-out F1 (0.xx, 95% CI ...); the pooled number
           in the abstract is secondary. We will make this ordering explicit in §4.1.
[R2.Q1] "The baseline seems untuned."
        -> The baseline used the same feature budget and a grid search reported in Appendix A;
           we point R2 to Table A1 and will surface it in the body.
[R3.Q1] "How does it behave under confounding non-eating activities?"
        -> Table 4 already measures false positives against typing/brushing; we clarify the caption.

The rule that wins a bounded rebuttal: every explicit question gets a direct, located answer. A question left unaddressed is what the discussion punishes, because there is no later round to fix it.

Reviewer pushback patterns

PushbackWhat it signalsPerCom-ready response
"Evaluation is within-subject"The core ubicomp doubtPoint to your leave-one-subject-out table; if you truly lack it, this is likely fatal — do not fake it
"Accuracy is inflated by class imbalance"Metric-choice doubtPoint to reported F1 / event-level metrics and the class balance; clarify which metric is headline
"The baseline is not fair/tuned"Soundness doubtPoint to the equal-budget tuning already in the paper/appendix; clarify placement
"Does this generalize beyond your subjects?"External-validity limitPoint to the diversity of subjects and the stated limitation; do not overclaim
"The dataset/system is not available"Open-data gapPoint to the (anonymized) release plan; describe what will be public post-acceptance
"Contribution overlaps prior work X"Novelty doubtSharpen the delta in words; point to the comparison already present

Anonymity in the rebuttal (easy to slip)

  • Refer to your own prior work in the third person, as in the paper.
  • Describe the dataset/testbed without naming the site, building, or repository owner; use the anonymized location.
  • Do not thank a named collaborator, funder, or institution inside the reply.

Calibration

  • Respond to the criterion the reviewer actually raised, not the one you would rather defend.
  • The rebuttal length limit and format vary by cycle; confirm the current instructions and stay inside the limit — over-length rebuttals read as unfocused.
  • The TPC discussion decides; write the reply as ammunition for your advocate, and let the paper — not the rebuttal — carry the argument.

Output format

[Gate] invited to rebuttal? yes/no (if no: reroute, do not draft)
[Priority question] <reviewer's explicit question>
[Decision dimension] significance / soundness / cross-subject evaluation / metrics / clarity
[Located answer] <question -> pointer to existing table/figure/appendix; clarification to add>
[No-new-experiment check] <every answer grounded in submitted material? yes/no>
[Anonymity check] <no identity leak in the reply: passed/issues>
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