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Best conferences to submit ML/AI papers in 2025–2026 (50)

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Growing 60 pts 0 followers
National Institute of Technology Karnataka · Posted
Machine Learning & AI Biomedical Engineering

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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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4 Replies

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Meghana Rao Growing 170 pts · Accepted answer

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

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Bhavana Reddy Starting 30 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.

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Replying to Bhavana Reddy
Manish Tiwari Starting 10 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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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.