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How do you handle long-form writing blocks during thesis writing?

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Growing 55 pts 0 followers
N.M.A.M. Institute of Technology · Posted
Financial Engineering Natural Language Processing Computer Vision

I have been on both sides.as a reviewer for IEEE and ACM journals, and as an author who has received peer review. The experience has made me wonder whether the current closed peer review model is serving science well.

As a reviewer: I put significant effort into reviews (usually 1500–2500 words). But I occasionally see reviews from other reviewers that are 3 sentences and completely uninformative.

As an author: I have received reviews that clearly misunderstood the paper's contribution. I have also received brilliant reviews that genuinely improved the paper.

Discussion question: What changes to peer review would actually improve quality? Open peer review? Paid reviewing? Double-blind everywhere?

Interested to hear from people across different fields and career stages.

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19 Replies

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Royal Dsouza Starting 30 pts · Accepted answer

Strongly agree with the point about choosing venues carefully. One paper in NeurIPS > five papers in obscure workshops.

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Replying to Royal Dsouza
Bindiya Thomas Growing 65 pts · Accepted answer

When you say 'multiple runs with confidence intervals', do you mean running the full training pipeline multiple times with different random seeds and reporting mean ± std? Or something more statistically rigorous?

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Xena D'Souza Starting 25 pts · Accepted answer

I think you are conflating two separate problems here. The publish-or-perish culture creates pressure, yes.but the solution is not to criticize researchers who are navigating an unfair system. The real problem is with evaluation committees who treat publication count as a proxy for research quality. Fix the evaluation, and the incentives change.

Also worth noting: open review has been implemented in some fields and has its own problems. It can disadvantage early-career researchers who fear retaliation from senior colleagues they have reviewed critically.

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Replying to Xena D'Souza
Neha Agarwal Growing 90 pts · Accepted answer

This is really helpful context. One more question: for the ethics committee approval, does the institution where the data is collected or the institution where the analysis is performed need to be the primary ethics approver?

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Replying to Xena D'Souza
Quamar Ahmed Growing 65 pts · Accepted answer

Really appreciate you taking the time to write this out in detail. This is going straight into my research notes.

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Replying to Xena D'Souza
Asha Pillai Distinguished 880 pts · Accepted answer

The IEEE TPAMI turnaround in my case was 7 months for the first review. Plan accordingly.

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Shiva Prasad Active 480 pts · Accepted answer

This is exactly what I needed to hear. One clarifying question: you mentioned FedProx handles non-IID data better.does that mean I should switch to FedProx by default, or only if I observe poor convergence with FedAvg first?

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Tara Singh Starting 5 pts · Accepted answer

Highly recommend checking out the PMRF portal for the actual numbers.they update the stipend structure annually.

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Preethi Anand Distinguished 690 pts · Accepted answer

Could you clarify what you mean by results-blind review? I have heard of it but never understood how it works in practice. Wouldn't reviewers need to see results to evaluate whether the methodology is sound?

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Shiva Prasad Active 480 pts · Accepted answer

This is exactly what I needed to hear. One clarifying question: you mentioned FedProx handles non-IID data better.does that mean I should switch to FedProx by default, or only if I observe poor convergence with FedAvg first?

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Replying to Shiva Prasad
test tester Growing 165 pts · Accepted answer

Could you clarify what you mean by results-blind review? I have heard of it but never understood how it works in practice. Wouldn't reviewers need to see results to evaluate whether the methodology is sound?

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Nandita Ghosh Distinguished 720 pts · Accepted answer

The IEEE TPAMI turnaround in my case was 7 months for the first review. Plan accordingly.

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Meghana Rao Growing 170 pts · Accepted answer

Overleaf + GitHub integration is underrated. You get version control and collaboration in one place.

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Replying to Meghana Rao
Ekta Choudhary Starting 45 pts · Accepted answer

The Fulbright SoP is very different from a typical PhD SoP. It needs to focus on cultural exchange and diplomacy, not just research.

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Replying to Meghana Rao
Ekta Choudhary Starting 45 pts · Accepted answer

The Fulbright SoP is very different from a typical PhD SoP. It needs to focus on cultural exchange and diplomacy, not just research.

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Suresh Iyer · Accepted answer

When you say 'multiple runs with confidence intervals', do you mean running the full training pipeline multiple times with different random seeds and reporting mean ± std? Or something more statistically rigorous?

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Quamar Ahmed Growing 65 pts · Accepted answer

The IEEE TPAMI turnaround in my case was 7 months for the first review. Plan accordingly.

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Hema Suresh Starting 20 pts · Accepted answer

For Zotero vs BibTeX management, I moved to Zotero + Better BibTeX 3 years ago and have not looked back.

My workflow:

  1. Zotero browser connector captures papers instantly from ArXiv, Google Scholar, ACM DL, IEEE Xplore
  2. Better BibTeX generates a clean .bib file that auto-updates whenever I add a paper
  3. Overleaf directly pulls from the .bib file via Dropbox sync

One tip: create a Zotero collection per paper/project. When you export the .bib, export only that collection to keep it clean.

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Hemant Patwa · Accepted answer

The short answer: it depends heavily on the journal and field, but here is a general framework.

If your null result is well-powered and the hypothesis was reasonable: Absolutely publish it. Null results in well-designed studies are as valuable as positive results. Journals like PLOS ONE explicitly welcome them.

If your study is underpowered: Be transparent about it. Report effect sizes and confidence intervals, not just p-values. A small, underpowered study with honest reporting is still a contribution.

What kills papers is when limitations are obvious but the authors have not addressed them.