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Respectfully, I think this framing misses the systemic dimension. Individual researchers cannot solve a collective action problem. If you submit to open-access journals and your colleague submits to Nature, your colleague gets the promotion. Until evaluation criteria change at the institutional level.which requires policy intervention.individual choices have minimal impact.
[Moderator note] This thread has been locked as the discussion has moved off-topic. Please keep discussion focused on academic and research topics.
FDR (Benjamini-Hochberg) is widely accepted and preferable to Bonferroni when you have many tests and limited power. The key is to be explicit about which correction you used and why.
On replication: No independent cohort is a genuine limitation but not a dealbreaker for rare disease research, where cohort availability is a known constraint. Many high-quality papers acknowledge this and still get published in good journals. Frame it as future work.
Power analysis: Yes, report it. Showing you are aware of the limitation is better than not mentioning it.
I have a slightly different take from my experience in industry research. The reproducibility crisis is real but unevenly distributed. Fields with strong engineering culture (computational biology, ML with benchmarks) have actually improved significantly in the last 5 years. The bigger problem is in fields where data sharing is structurally difficult.clinical medicine, behavioral economics.
The ML community's move toward open code and reproducibility checklists has been genuinely effective.
The ethics review situation in Indian universities is actually more complex than most people realize.
There is no uniform national framework equivalent to the US Common Rule. Each institution has its own Institutional Ethics Committee (IEC) or Institutional Review Board (IRB).
For anonymous survey research with no identifiable data and no vulnerable populations: most Indian IECs would classify this as exempt, but 'exempt' still needs a formal determination from the IEC.it is not self-certifying.
My practical advice: go to your institution's research ethics office now, describe what you did, and request an exempt determination in writing. Better to have documentation than to discover the issue during thesis review.
Seconding the recommendation for Zotero. Game changer for managing references across multiple projects.
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?
This question comes up a lot. The answer really depends on your specific field and what your committee values.
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?
Seconding the recommendation for Zotero. Game changer for managing references across multiple projects.
I found that writing a paper abstract first (before the paper) and then reverse-engineering the paper from the abstract helped with clarity enormously.
The ethics review situation in Indian universities is actually more complex than most people realize.
There is no uniform national framework equivalent to the US Common Rule. Each institution has its own Institutional Ethics Committee (IEC) or Institutional Review Board (IRB).
For anonymous survey research with no identifiable data and no vulnerable populations: most Indian IECs would classify this as exempt, but 'exempt' still needs a formal determination from the IEC.it is not self-certifying.
My practical advice: go to your institution's research ethics office now, describe what you did, and request an exempt determination in writing. Better to have documentation than to discover the issue during thesis review.
Thank you for this detailed answer! A quick follow-up: when you mention cosine learning rate with warm-up, are you warming up the LoRA parameters specifically or the entire model including the frozen backbone?
This is a known issue with XLM-R on code-mixed data. The MuRIL preprint has a section specifically comparing these.
Really appreciate you taking the time to write this out in detail. This is going straight into my research notes.
For longitudinal data with missing values, mixed-effects models handle this more gracefully than imputation in most cases.
I found that writing a paper abstract first (before the paper) and then reverse-engineering the paper from the abstract helped with clarity enormously.
Respectfully, I think this framing misses the systemic dimension. Individual researchers cannot solve a collective action problem. If you submit to open-access journals and your colleague submits to Nature, your colleague gets the promotion. Until evaluation criteria change at the institutional level.which requires policy intervention.individual choices have minimal impact.
Much appreciated. I will restructure my proposal along these lines. The point about societal impact being substantive is something I would have gotten wrong.
Just to make sure I understand the Zotero workflow correctly.is the .bib file synced to Overleaf automatically every time you add a new paper, or do you need to trigger an export manually?
CSIR-UGC NET preparation: past papers are the most important resource. Everything else is secondary.
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?
For longitudinal data with missing values, mixed-effects models handle this more gracefully than imputation in most cases.
This is a known issue with XLM-R on code-mixed data. The MuRIL preprint has a section specifically comparing these.
This question comes up a lot. The answer really depends on your specific field and what your committee values.
The Fulbright SoP is very different from a typical PhD SoP. It needs to focus on cultural exchange and diplomacy, not just research.
The Fulbright SoP is very different from a typical PhD SoP. It needs to focus on cultural exchange and diplomacy, not just research.
The IEEE TPAMI turnaround in my case was 7 months for the first review. Plan accordingly.
Strongly agree with the point about choosing venues carefully. One paper in NeurIPS > five papers in obscure workshops.
The Fulbright SoP is very different from a typical PhD SoP. It needs to focus on cultural exchange and diplomacy, not just research.
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?
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?
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?
I have a slightly different take from my experience in industry research. The reproducibility crisis is real but unevenly distributed. Fields with strong engineering culture (computational biology, ML with benchmarks) have actually improved significantly in the last 5 years. The bigger problem is in fields where data sharing is structurally difficult.clinical medicine, behavioral economics.
The ML community's move toward open code and reproducibility checklists has been genuinely effective.
Respectfully, I think this framing misses the systemic dimension. Individual researchers cannot solve a collective action problem. If you submit to open-access journals and your colleague submits to Nature, your colleague gets the promotion. Until evaluation criteria change at the institutional level.which requires policy intervention.individual choices have minimal impact.
This is a known issue with XLM-R on code-mixed data. The MuRIL preprint has a section specifically comparing these.
I am in a very similar situation. Would you be willing to share the outline of your PMRF proposal? Not the content.just the section headings and approximate word allocation.
For longitudinal data with missing values, mixed-effects models handle this more gracefully than imputation in most cases.
Thank you for this detailed answer! A quick follow-up: when you mention cosine learning rate with warm-up, are you warming up the LoRA parameters specifically or the entire model including the frozen backbone?
This is exactly what I needed. Thank you so much.I have been going back and forth on this for weeks and this clears it up completely.
For Zotero vs BibTeX management, I moved to Zotero + Better BibTeX 3 years ago and have not looked back.
My workflow:
.bib file that auto-updates whenever I add a paper.bib file via Dropbox syncOne tip: create a Zotero collection per paper/project. When you export the .bib, export only that collection to keep it clean.
+1 to everything said above. My experience was identical.
Highly recommend checking out the PMRF portal for the actual numbers.they update the stipend structure annually.
The ethics review situation in Indian universities is actually more complex than most people realize.
There is no uniform national framework equivalent to the US Common Rule. Each institution has its own Institutional Ethics Committee (IEC) or Institutional Review Board (IRB).
For anonymous survey research with no identifiable data and no vulnerable populations: most Indian IECs would classify this as exempt, but 'exempt' still needs a formal determination from the IEC.it is not self-certifying.
My practical advice: go to your institution's research ethics office now, describe what you did, and request an exempt determination in writing. Better to have documentation than to discover the issue during thesis review.
Overleaf + GitHub integration is underrated. You get version control and collaboration in one place.
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.
If you are not already using a reading group format with your students, I would strongly recommend it. Forces everyone to articulate what they read.
If you are not already using a reading group format with your students, I would strongly recommend it. Forces everyone to articulate what they read.
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?
The ethics review situation in Indian universities is actually more complex than most people realize.
There is no uniform national framework equivalent to the US Common Rule. Each institution has its own Institutional Ethics Committee (IEC) or Institutional Review Board (IRB).
For anonymous survey research with no identifiable data and no vulnerable populations: most Indian IECs would classify this as exempt, but 'exempt' still needs a formal determination from the IEC.it is not self-certifying.
My practical advice: go to your institution's research ethics office now, describe what you did, and request an exempt determination in writing. Better to have documentation than to discover the issue during thesis review.
This is exactly what I needed. Thank you so much.I have been going back and forth on this for weeks and this clears it up completely.
Thank you! The reference to MuRIL is particularly useful.I had not considered it as an alternative to XLM-R for Indic languages.
Seconding the recommendation for Zotero. Game changer for managing references across multiple projects.
For longitudinal data with missing values, mixed-effects models handle this more gracefully than imputation in most cases.
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?
I found that writing a paper abstract first (before the paper) and then reverse-engineering the paper from the abstract helped with clarity enormously.
CSIR-UGC NET preparation: past papers are the most important resource. Everything else is secondary.
I am in a very similar situation. Would you be willing to share the outline of your PMRF proposal? Not the content.just the section headings and approximate word allocation.
FDR (Benjamini-Hochberg) is widely accepted and preferable to Bonferroni when you have many tests and limited power. The key is to be explicit about which correction you used and why.
On replication: No independent cohort is a genuine limitation but not a dealbreaker for rare disease research, where cohort availability is a known constraint. Many high-quality papers acknowledge this and still get published in good journals. Frame it as future work.
Power analysis: Yes, report it. Showing you are aware of the limitation is better than not mentioning it.
Overleaf + GitHub integration is underrated. You get version control and collaboration in one place.
+1 to everything said above. My experience was identical.
Marking this as the accepted answer. Incredibly helpful and specific. Really appreciate you taking the time.
Marking this as the accepted answer. Incredibly helpful and specific. Really appreciate you taking the time.
This question comes up a lot. The answer really depends on your specific field and what your committee values.
Thank you for this detailed answer! A quick follow-up: when you mention cosine learning rate with warm-up, are you warming up the LoRA parameters specifically or the entire model including the frozen backbone?
Seconding the recommendation for Zotero. Game changer for managing references across multiple projects.