How to Approach ML Research Papers?

Hello everyone,

I’ve recently started reading ML research papers, and I’d love to hear your best practices, recommendations, tips on how to find a good research paper, and any personal favorites.

If anyone’s interested, here’s my current approach to reading ML research papers (open to improvements):

  1. Abstract – The abstract is the most important part, as it provides the relevance and main topic of the paper.
  2. Conclusion – This section helps clarify the paper’s direction, allowing me to approach the reading with a clear objective.
  3. Data Section – Understanding the data (X, Y) gives me an initial sense of how the model might work, even before delving into its structure.
  4. Results – This section reveals how the dataset performs and often includes performance comparisons.
  5. Dive In – Read the paper in detail, focusing on how the model is built:
  • Model Architecture
  • Inputs & Outputs
  • New Techniques (usually highlighted in the title/abstract)
  • Loss Calculation
  • Model Training
  • Note any unclear points
  1. Experiment – If possible, try running the code and dataset yourself.

This template helps me read scientific papers on ML, but it’s far from perfect since I’m adapting it as I go, based on limited experience.

Any recommendations would be VERY appreciated, as I’m still a beginner in the research field.

See you guys arround :hugs: !!

7 Likes

One element I always look for is a compare and contrast to previous work, which is generally supported by their references section. I like to know what papers they read, and what issues or limitations discussed in those works the current paper addresses or improves upon. Sometimes this is briefly mentioned in the abstract but usually supported with details, often including tables comparing accuracy, throughput etc.

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I never tried to read research paper unless I had to do it for some work, but this approach looks promising

1 Like

I’m also trying to read research papers more, I think your approach will be really useful because I was struggling. How do you handle the ones with intense mathematical formulas, I obviously don’t want to just skim through them. Is there a way I can approach them and also help myself get familiar with them?