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How are you using LLMs in your day-to-day research work? (94)

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Distinguished 640 pts 0 followers
B.M.S. College of Engineering · Posted
Psychology Pharmaceutical Sciences

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This is a space to share what is actually working for you in terms of research productivity tools. Be specific.what exactly do you use it for and why does it work?

I'll start:

I use Obsidian as my primary research knowledge base. Each paper I read gets a note with:

  • 3-sentence summary
  • Key contributions
  • Limitations (often more useful than contributions)
  • Connection to my work

I also maintain a 'daily research log' where I write for 15 minutes each morning about what I am stuck on. This has been more valuable than any productivity system I have tried.

For writing: Overleaf for LaTeX, but I draft initial versions in plain markdown.

For references: Zotero with the Better BibTeX plugin. Essential.

What is working for you?

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31 Replies

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Chetan Jain Growing 100 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?

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Neha Agarwal Growing 90 pts · Accepted answer

Flower (flwr) is the most actively maintained and research-friendly federated learning framework right now. My group has been using it for 18 months on a healthcare project with 4 hospital sites.

Strengths:

  • Clean simulation API that lets you test on a single machine before deploying
  • Good support for custom aggregation strategies (FedProx, FedNova)
  • Active Discord community with quick responses from the maintainers

For non-IID data specifically, look at the FedProx strategy.it handles heterogeneous data distributions much better than FedAvg.

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Replying to Neha Agarwal
Nandita Ghosh Distinguished 720 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 Neha Agarwal
Arjun Venkatesan Growing 195 pts · Accepted answer

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

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Sunil Bhattacharya Active 390 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.

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Rohan Desai Distinguished 950 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.

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Kavitha Subramanian Active 365 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.

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Om Prakash Growing 55 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.

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Replying to Om Prakash
Ekta Choudhary Starting 45 pts · Accepted answer

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

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Replying to Om Prakash
Arjun Venkatesan Growing 195 pts · Accepted answer

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

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Yogesh Pandey Growing 70 pts · Accepted answer

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

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Replying to Yogesh Pandey
Royal Dsouza Starting 30 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 Yogesh Pandey
Harini Balakrishnan Active 215 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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Chirag Mehta Starting 15 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.

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Replying to Chirag Mehta
Varsha Pillai Growing 60 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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Preethi Anand Distinguished 690 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.

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Wajid Khan Growing 110 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.

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Divya Krishnan Growing 85 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.

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Karthik Rajan Growing 180 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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Replying to Karthik Rajan
Pooja Nambiar Growing 115 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 Karthik Rajan
Rajesh Kumar · 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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Harini Balakrishnan Active 215 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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Tara Singh Starting 5 pts · Accepted answer

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

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Replying to Tara Singh
Sowmya Narayanan Active 310 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.

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Tara Singh Starting 5 pts · Accepted answer

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

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Preethi Anand Distinguished 690 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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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.

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Geeta Rao · 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?

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Replying to Geeta Rao
Asha Pillai Distinguished 880 pts · Accepted answer

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

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Replying to Geeta Rao
Fatima Sheikh Growing 95 pts · Accepted answer

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

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Replying to Geeta Rao
Ashwin Murthy Distinguished 560 pts · Accepted answer

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