AI Papers to Read in 2025

Discover essential AI and Data Science papers to stay informed about both recent and classic breakthroughs. This updated list resumes a popular series of AI paper recommendations, previously published in four editions.

Purpose and Approach

This carefully curated selection reflects personal insights and diverse perspectives rather than showcasing the latest state-of-the-art models. It aims to stimulate critical thinking about AI’s current landscape by highlighting important research and overlooked developments.

Structure of Recommendations

The collection includes ten papers, each accompanied by a concise summary explaining its significance and clear reasons to explore it. Additionally, each paper has a recommended further reading section for deeper exploration of related topics.

“We don’t need larger models; we need solutions” and “do not expect me to suggest GPT nonsense here.”

This statement from the author’s 2022 article emphasizes a focus on meaningful advances over simply bigger or marginally better models. It suggests skepticism toward hype and encourages thoughtful evaluation of AI progress.

Author's Reflection

Originally, the author anticipated that future GPT models would mainly represent incremental improvements rather than groundbreaking innovations, an assessment that remains relevant.

Further Resources

Each paper recommendation includes tangents and additional readings to broaden understanding.
The series serves long-term followers and newcomers alike, offering a meaningful lens on AI's evolution.

“Credit where credit is due.”

Summary: This opinionated and insightful list highlights key AI research papers to critically understand current trends and avoid hype, focusing on impactful solutions rather than just bigger models.

Towards Data Science — 2025-11-06