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Distinguished 690 pts 0 followers
B.M.S. College of Engineering · Posted
Urban Planning Economics

Top Contributors.November 2025

We want to recognize the community members who have been most helpful this month.

Most helpful answers: Faculty and researchers who answered questions that received the most upvotes.

Most active participants: Members who contributed thoughtfully to discussions across multiple threads.

Thank you for making this community valuable. The quality of a research forum depends entirely on the people who contribute to it generously.

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82 Replies

Oldest Top
0
Suresh Iyer · Accepted answer

Great question.I went through something very similar in my second year.

The key insight for me was that LoRA is actually quite well-suited for NER tasks, especially in low-resource settings. I would recommend:

  1. Use LoRA with r=8 or r=16.don't go higher for 8K samples
  2. Apply LoRA to attention layers only, not the feed-forward layers
  3. Use a cosine learning rate schedule with warm-up (10% of steps)

For Telugu-English code-mixed NER specifically, you might also look at MuRIL.it is pretrained on Indian language data and often outperforms XLM-R on Indic tasks even with less fine-tuning data.

0
Ekta Choudhary Starting 45 pts · Accepted answer

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

0
Geeta Rao · Accepted answer

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.

0
Anita Rao · Accepted answer

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.

0
Ekta Choudhary Starting 45 pts · Accepted answer

Seconding the recommendation for Zotero. Game changer for managing references across multiple projects.

0
Prakash Iyer Distinguished 640 pts · Accepted answer

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?

0
Xena D'Souza Starting 25 pts · Accepted answer

+1 to everything said above. My experience was identical.

0
Meena Sharma · Accepted answer

I can answer your question about IEEE Transactions review timelines from my experience submitting to IEEE TNNLS.

For Q1 IEEE journals, expect:

  • Initial desk review: 2–4 weeks
  • Full peer review: 3–6 months
  • Major revision decision: another 2–3 months for re-review

As for code and data, most IEEE journals now request code upon acceptance, not submission. Regarding your 2.3% improvement.that is borderline. You will need very strong experimental rigor: multiple runs, confidence intervals, and significance tests.

0
Hema Suresh Starting 20 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?

0
Ishaan Verma Growing 60 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?

0
Replying to Ishaan Verma
Tara Singh Starting 5 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?

0
Asha Pillai Distinguished 880 pts · Accepted answer

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.

0
Rekha Shetty Starting 40 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.

0
Replying to Rekha Shetty
Kiran Yadav Growing 130 pts · Accepted answer

CSIR-UGC NET preparation: past papers are the most important resource. Everything else is secondary.

0
Replying to Rekha Shetty
Sunil Bhattacharya Active 390 pts · Accepted answer

For longitudinal data with missing values, mixed-effects models handle this more gracefully than imputation in most cases.

0
Replying to Rekha Shetty
Fatima Sheikh Growing 95 pts · Accepted answer

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

0
Farhan Mirza · 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.

0
Om Prakash Growing 55 pts · Accepted answer

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.

0
Geeta Rao · Accepted answer

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

0
Arjun Venkatesan Growing 195 pts · Accepted answer

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.

0
test tester Growing 165 pts · Accepted answer

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.

0
Replying to test tester
Arjun Venkatesan Growing 195 pts · Accepted answer

This is a known issue with XLM-R on code-mixed data. The MuRIL preprint has a section specifically comparing these.

0
Replying to test tester
Prakash Iyer Distinguished 640 pts · Accepted answer

For longitudinal data with missing values, mixed-effects models handle this more gracefully than imputation in most cases.

0
Om Prakash Growing 55 pts · Accepted answer

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.

0
Zara Hussain Growing 55 pts · Accepted answer

Great question.I went through something very similar in my second year.

The key insight for me was that LoRA is actually quite well-suited for NER tasks, especially in low-resource settings. I would recommend:

  1. Use LoRA with r=8 or r=16.don't go higher for 8K samples
  2. Apply LoRA to attention layers only, not the feed-forward layers
  3. Use a cosine learning rate schedule with warm-up (10% of steps)

For Telugu-English code-mixed NER specifically, you might also look at MuRIL.it is pretrained on Indian language data and often outperforms XLM-R on Indic tasks even with less fine-tuning data.

0
Replying to Zara Hussain
Amit Joshi Starting 15 pts · Accepted answer

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.

0
Replying to Zara Hussain
Vikram Bhatia Active 420 pts · Accepted answer

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

0
Pooja Nambiar Growing 115 pts · Accepted answer

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.

0
Replying to Pooja Nambiar
Rekha Shetty Starting 40 pts · Accepted answer

Seconding the recommendation for Zotero. Game changer for managing references across multiple projects.

0
Replying to Pooja Nambiar
Sunil Bhattacharya Active 390 pts · Accepted answer

This is very reassuring. I was worried the null result would kill the paper but your framing around transparency and effect sizes makes a lot of sense.

0
Replying to Pooja Nambiar
Royal Dsouza Starting 30 pts · Accepted answer

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

0
Xena D'Souza Starting 25 pts · Accepted answer

I found that writing a paper abstract first (before the paper) and then reverse-engineering the paper from the abstract helped with clarity enormously.

0
Tara Singh Starting 5 pts · Accepted answer

Open access is the right direction but the APCs are prohibitively expensive for many Indian researchers without institutional funding.

0
Xena D'Souza Starting 25 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?

0
Replying to Xena D'Souza
Rekha Shetty Starting 40 pts · Accepted answer

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?

0
Replying to Xena D'Souza
Sunil Bhattacharya Active 390 pts · Accepted answer

This is a known issue with XLM-R on code-mixed data. The MuRIL preprint has a section specifically comparing these.

0
Manish Tiwari Starting 10 pts · Accepted answer

+1 to everything said above. My experience was identical.

0
Ashwin Murthy Distinguished 560 pts · Accepted answer

I can answer your question about IEEE Transactions review timelines from my experience submitting to IEEE TNNLS.

For Q1 IEEE journals, expect:

  • Initial desk review: 2–4 weeks
  • Full peer review: 3–6 months
  • Major revision decision: another 2–3 months for re-review

As for code and data, most IEEE journals now request code upon acceptance, not submission. Regarding your 2.3% improvement.that is borderline. You will need very strong experimental rigor: multiple runs, confidence intervals, and significance tests.

0
test tester Growing 165 pts · Accepted answer

[Moderator note] Reminder to keep discussion collegial. We can disagree on ideas.and productive disagreement is valuable.but please avoid personal characterizations. Thank you.

0
Ganesh Menon Growing 140 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?

0
Replying to Ganesh Menon
Ashwin Murthy Distinguished 560 pts · Accepted answer

For longitudinal data with missing values, mixed-effects models handle this more gracefully than imputation in most cases.

0
Replying to Ganesh Menon
Amit Joshi Starting 15 pts · Accepted answer

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?

0
Replying to Ganesh Menon
Farhan Mirza · Accepted answer

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

0
Aditya Sharma Starting 45 pts · Accepted answer

Check whether your institution has a Springer/Elsevier waiver agreement.many NITs and IITs do.

0
Nandita Ghosh Distinguished 720 pts · Accepted answer

Check whether your institution has a Springer/Elsevier waiver agreement.many NITs and IITs do.

0
Sanjay Kumar Growing 145 pts · Accepted answer

CSIR-UGC NET preparation: past papers are the most important resource. Everything else is secondary.

0
Deepa Krishnamurthy Distinguished 810 pts · Accepted answer

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.

0
Replying to Deepa Krishnamurthy
Rekha Shetty Starting 40 pts · Accepted answer

Thank you for the honest take. This is the kind of answer I was looking for.not the sanitized version.

0
Replying to Deepa Krishnamurthy
Rohan Desai Distinguished 950 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?

0
Uday Bose Starting 5 pts · Accepted answer

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.

0
Pooja Nambiar Growing 115 pts · Accepted answer

This is a known issue with XLM-R on code-mixed data. The MuRIL preprint has a section specifically comparing these.

0
Fatima Sheikh Growing 95 pts · Accepted answer

I have successfully received PMRF (lateral entry, second year). Happy to share what worked in my proposal.

On the research proposal:

  • 60–70% technical approach, 30% context and impact
  • Preliminary results absolutely help. Coursework projects are fine if genuinely relevant
  • The societal impact section should be substantive.PMRF is a national initiative; reviewers want to see why this matters

On citations: Yes, cite your MTech thesis. Framing your PhD as an extension of prior work you did shows continuity of thought.

0
Rekha Shetty Starting 40 pts · Accepted answer

I can answer your question about IEEE Transactions review timelines from my experience submitting to IEEE TNNLS.

For Q1 IEEE journals, expect:

  • Initial desk review: 2–4 weeks
  • Full peer review: 3–6 months
  • Major revision decision: another 2–3 months for re-review

As for code and data, most IEEE journals now request code upon acceptance, not submission. Regarding your 2.3% improvement.that is borderline. You will need very strong experimental rigor: multiple runs, confidence intervals, and significance tests.

0
Replying to Rekha Shetty
Admin NITK · Accepted answer

This is very reassuring. I was worried the null result would kill the paper but your framing around transparency and effect sizes makes a lot of sense.

0
Deepa Krishnamurthy Distinguished 810 pts · Accepted answer

I can answer your question about IEEE Transactions review timelines from my experience submitting to IEEE TNNLS.

For Q1 IEEE journals, expect:

  • Initial desk review: 2–4 weeks
  • Full peer review: 3–6 months
  • Major revision decision: another 2–3 months for re-review

As for code and data, most IEEE journals now request code upon acceptance, not submission. Regarding your 2.3% improvement.that is borderline. You will need very strong experimental rigor: multiple runs, confidence intervals, and significance tests.

0
Replying to Deepa Krishnamurthy
Dinesh Kulkarni Distinguished 730 pts · Accepted answer

+1 to everything said above. My experience was identical.

0
Replying to Deepa Krishnamurthy
Farhan Mirza · 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?

0
Om Prakash Growing 55 pts · 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.

0
Replying to Om Prakash
Chirag Mehta Starting 15 pts · Accepted answer

This is very reassuring. I was worried the null result would kill the paper but your framing around transparency and effect sizes makes a lot of sense.

0
Replying to Om Prakash
Revathi Chandrasekaran Active 410 pts · Accepted answer

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.

0
Replying to Om Prakash
Lakshmi Devi Growing 75 pts · Accepted answer

CSIR-UGC NET preparation: past papers are the most important resource. Everything else is secondary.

0
Dinesh Kulkarni Distinguished 730 pts · Accepted answer

I have successfully received PMRF (lateral entry, second year). Happy to share what worked in my proposal.

On the research proposal:

  • 60–70% technical approach, 30% context and impact
  • Preliminary results absolutely help. Coursework projects are fine if genuinely relevant
  • The societal impact section should be substantive.PMRF is a national initiative; reviewers want to see why this matters

On citations: Yes, cite your MTech thesis. Framing your PhD as an extension of prior work you did shows continuity of thought.

0
Rekha Shetty Starting 40 pts · Accepted answer

I found that writing a paper abstract first (before the paper) and then reverse-engineering the paper from the abstract helped with clarity enormously.

0
Uday Bose Starting 5 pts · Accepted answer

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.

0
Replying to Uday Bose
Gopal Naidu · Accepted answer

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

0
Replying to Uday Bose
Ishaan Verma Growing 60 pts · Accepted answer

Thank you! The reference to MuRIL is particularly useful.I had not considered it as an alternative to XLM-R for Indic languages.

0
Replying to Uday Bose
Aditya Sharma Starting 45 pts · Accepted answer

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.

0
Deepa Krishnamurthy Distinguished 810 pts · Accepted answer

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.

0
Replying to Deepa Krishnamurthy
test tester Growing 165 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?

0
Replying to Deepa Krishnamurthy
Hema Suresh Starting 20 pts · Accepted answer

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?

0
Sanjay Kumar Growing 145 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?

0
Ravi Patel Starting 25 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?

0
Replying to Ravi Patel
test tester Growing 165 pts · Accepted answer

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

0
Ashwin Murthy Distinguished 560 pts · Accepted answer

As a senior faculty member (25 years in the system), I want to offer a different perspective. Yes, the pressures are real. But I have also seen the other side: students who produce excellent work, publish honestly, and build reputations over time. The system is imperfect but not entirely broken.

What has actually helped my students: choosing venues carefully (a few strong papers rather than many weak ones), developing genuine collaborations rather than transactional coauthorships.

0
Eshan Patil Growing 70 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?

0
Replying to Eshan Patil
Hema Suresh Starting 20 pts · Accepted answer

CSIR-UGC NET preparation: past papers are the most important resource. Everything else is secondary.

0
Replying to Eshan Patil
Indira Balan · Accepted answer

CSIR-UGC NET preparation: past papers are the most important resource. Everything else is secondary.

0
Pooja Nambiar Growing 115 pts · Accepted answer

This is a known issue with XLM-R on code-mixed data. The MuRIL preprint has a section specifically comparing these.

0
Replying to Pooja Nambiar
Varsha Pillai Growing 60 pts · Accepted answer

This is very reassuring. I was worried the null result would kill the paper but your framing around transparency and effect sizes makes a lot of sense.

0
Divya Krishnan Growing 85 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?

0
Meena Sharma · Accepted answer

This question comes up a lot. The answer really depends on your specific field and what your committee values.

0
Dinesh Kulkarni Distinguished 730 pts · Accepted answer

+1 to everything said above. My experience was identical.