🧑‍🔬 Chase Blagden

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Generative Reward Models (2024 · 58 citations)
   Reward models trained with the Bradley-Terry objective on human preference pairs score well on familiar data but generalize poorly to unseen tasks.
2. Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Thought (2025 · 47 citations)
   Large language models handle routine math well but still fail on harder problems. The authors argue that ordinary Chain-of-Thought (CoT) is part of the cause. Written solutions in training data show only the polished final derivation. They omit the hidden, non-linear work of trying options, checking them and…
3. Big-Math: A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language Models (2025 · 43 citations)
   Reinforcement learning for reasoning in LLMs needs math problems whose answers can be checked automatically.

🤝 Co-authors here

12 of 13 co-authors with a page, the most papers together first.

• Alon Albalak ×3
• Dakota Mahan ×3
• Duy Phung ×3
• Louis Castricato ×3
• Nathan Lile ×3
• Rafael Rafailov ×3
• Anikait Singh ×2
• Jan-Philipp Franken ×2
• Kanishk Gandhi ×2
• Violet Xiang ×2
• Charlie Snell
• Chelsea Finn

🔗 Cited by

Papers of our library cite their works 146 times (of the 149,439 papers whose bibliographies we read); 62 citing papers with a page here →.

Updated 3 November 2026

This page in Markdown → https://md.research.elamur.ai/free/en/authors/chase-blagden/