🧑‍🔬 Nick Haber

🏛️ Affiliations

🎓Stanford UniversityStanford · United States2012–2026 · 103 paperscurrent🏥Stanford MedicineStanford · United States2016–2022 · 9 papers🤝Mathematical Sciences Research InstituteBerkeley · United States2016 · 2 papers🎓McGill UniversityMontreal · Canada2016 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

🧭 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. Parsel: Algorithmic Reasoning with Language Models by Composing Decompositions (2023 · 56 citations)
   Large language models that write code tend to break down on long, multi-step tasks, because a single wrong token can ruin an entire program.
2. 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.
3. Learning Formal Mathematics From Intrinsic Motivation (2024 · 23 citations)
   Most AI theorem provers depend on human-written formal proofs, which are scarce. They are also evaluated on fixed problem sets chosen by people. This paper asks whether an agent can build mathematical skill from a domain's axioms alone, deciding for itself which statements to work on. The authors present MINIMO, in…
4. ResearchCodeBench: Benchmarking LLMs on Implementing Novel Machine Learning Research Code (2025 · 16 citations)
   Can LLMs turn genuinely new ML ideas, ones published after their training data was gathered, into working code? ResearchCodeBench tests this with an execution-based benchmark built from 20 recent machine learning papers.

All works

13 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

1. Holodeck: Language Guided Generation of 3D Embodied AI Environments ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetYue Yang et al.2024 · 115 citations
2. Parsel: Algorithmic Reasoning with Language Models by Composing DecompositionsConference on Neural Information Processing Systems (NeurIPS)Eric Zelikman, Qian Huang, Gabriel Poesia, et al.2023 · 56 citations
3. Big-Math: A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language ModelsarXiv:2502.17387Alon Albalak, Duy Phung, Nathan Lile, et al.2025 · 43 citations
4. Learning Formal Mathematics From Intrinsic MotivationConference on Neural Information Processing Systems (NeurIPS)Gabriel Poesia, David Broman, Nick Haber, et al.2024 · 23 citations
5. ResearchCodeBench: Benchmarking LLMs on Implementing Novel Machine Learning Research CodeConference on Neural Information Processing Systems (NeurIPS)Tianyu Hua; Harper Hua; Violet Xiang; Benjamin Klieger; Sang T. Truong; Weixin Liang; Fan-Yun Sun;, Nick Haber2025 · 16 citations
6. Generating and Evaluating Tests for K-12 Students with Language Model Simulations: A Case Study on Sentence Reading Efficiency ↗Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing · no summary yetEric Zelikman et al.2023 · 16 citations
7. Learning Next Action Predictors from Human-Computer Interaction ↗arXiv (Cornell University) · no summary yetOmar Shaikh et al.2026 · 3 citations
8. ContextRef: Evaluating Referenceless Metrics For Image Description Generation ↗arXiv (Cornell University) · no summary yetElisa Kreiss et al.2023 · 3 citations
9. Just One Byte (per gradient): A Note on Low-Bandwidth Decentralized Language Model Finetuning Using Shared Randomness ↗arXiv (Cornell University) · no summary yetEric Zelikman et al.2023 · 3 citations
10. When Models Know More Than They Can Explain: Quantifying Knowledge Transfer in Human-AI Collaboration ↗neural information processing systems · no summary yetQuan Shi et al.2025 · 2 citations
11. Data-efficient pre-training by scaling synthetic megadocs ↗arXiv (Cornell University) · no summary yetKonwoo Kim et al.2026 · 1 citation
12. DelusionEval: Measuring Delusion-Linked Behaviors in AI Chatbots ↗arXiv (Cornell University) · no summary yetJared Moore et al.2026
13. Neural Nonmyopic Bayesian Optimization in Dynamic Cost Settings ↗arXiv (Cornell University) · no summary yetSang Truong et al.2026

🤝 Co-authors here

12 of 15 co-authors with a page, the most papers together first.

• Gabriel Poesia ×2
• Noah D. Goodman ×2
• Alon Albalak
• Anikait Singh
• Chase Blagden
• Dakota Mahan
• David Broman
• Duy Phung
• Eric Zelikman
• Kanishk Gandhi
• Louis Castricato
• Nathan Lile

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Conference on Neural Information Processing Systems (NeurIPS) ×3: NeurIPS 2025, NeurIPS 2024, NeurIPS 2023
• IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
• Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
• neural information processing systems

🔗 Cited by

Papers of our library cite their works 198 times (of the 149,439 papers whose bibliographies we read); 80 citing papers with a page here →.

Updated 3 November 2026

↑ back to top

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