Reading research papers can feel overwhelming, but there are two main ways to approach it. If you want to build a strong theoretical foundation, start with influential papers and structured resources. If you have a specific goal, focus on practical methods to reach it quickly. This guide covers both paths so you can choose the one that works best for you.

Theoretical Approach

If you want to build strong fundamentals, follow this approach:

  1. Start with highly cited papers
    • These are the most influential works in a field.
    • Use Google Scholar: Search for keywords and filter by citations.
    • Example: “Attention is All You Need” for Transformers.
  2. Find good explanations of key papers
    • Some papers are hard to understand. Look for interpretations:
  3. Use structured repositories
  4. Read smartly
    • Abstract + Conclusion first: See if the paper is useful.
    • Skim figures and tables: They give quick insights.
    • Look at the introduction and related work: Understand the context.
    • Only deep dive if the paper is really relevant.

Practical Approach

If you have a goal, this method is better:

  1. Define your objective
    • Example: “I want to implement a Transformer for time series.”
    • Break it down: “I need to understand self-attention and sequence embeddings.”
  2. Find relevant resources
    • Awesome Lists on GitHub: Search awesome <topic>
    • Survey papers: They summarize the state-of-the-art.
      • Google Scholar: Search “Survey + your topic.”
    • Use citation graphs
      • Connected Papers: Find key references.
      • Google Scholar: Click “Cited by” to see newer works.
  3. Focus on implementation
    • Find code implementations on GitHub.
    • Use Papers With Code to get reproducible results.
    • Check blog posts that explain key concepts in simple terms.
  4. Balance breadth and depth
    • Read multiple papers at a high level before deep-diving into one.
    • Compare different approaches to spot patterns.
    • Don’t get stuck on details unless necessary.

Going Further: Becoming Influential in Research

If you want to go beyond reading and start making an impact, here are some ways to get started:

  1. Implement papers that have no public implementation
    • Look for research papers without code on GitHub.
    • Use Papers With Code to check if an implementation exists.
    • Implement missing papers, document them well, and share on GitHub—this can attract free stars!
    • Use ChatGPT or other AI tools to help kickstart difficult parts.
  2. Participate in beginner-friendly research challenges
    • Some ML and AI competitions are easier to enter:
      • CAP Conference Challenges: AI-focused tasks that are well-structured and accessible.
      • Codalab Competitions: Various research-oriented challenges, often linked to academic conferences.
      • SemEval Tasks: NLP-related challenges with varying difficulty levels.
      • TREC Tracks: Text retrieval competitions useful for NLP and search.
    • Others can be hard and attract strong competitors:
  3. Engage with the research community
    • Join academic Twitter, Reddit, or Discord communities.
    • Read discussions on papers and post insights or questions.
    • Collaborate with others on open-source projects.
  4. Write and share your insights
    • Start a blog summarizing key papers and ideas.
    • Create explainer videos or GitHub repos for niche concepts.
    • Engage with researchers by asking insightful questions on social media.

Final Thoughts

Reading research papers is a skill that gets easier with practice. Whether you take a theoretical or practical approach, stay curious, take notes, and engage with the community. Most importantly, don’t just read—apply what you learn. The best way to understand research is to experiment with it.

If you want to go further, contribute by implementing missing research papers, joining competitions, or engaging with the community. Small contributions can quickly make you recognizable in the field.

Happy reading and hacking! 🚀