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Osbert Bastani

Osbert Bastani has 2 papers in our library, in 2016–2023, most of them on Language models & pretraining; often with Alex Aiken, Anima Anandkumar, De-An Huang.

2 papers in our library · 2016–2023

OpenAlex · ORCID · Wikidata · h-index 28 · 210 works · 3,216 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 380 times in our library · 11 more in our library without a page yet · ⭐ Paper Stars ranking: #7542

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓University of PennsylvaniaPhiladelphia · United States2018–2026 · 125 papersEmployment 2018–2022 · Research Assistant Professor, Computer and Information ScienceEmployment 2022–2025 · Assistant Professor, Computer and Information ScienceEmployment since 2025 · Associate Professor, Computer and Information Sciencecurrent🏢GoogleMountain View · United States2026 · 1 papercurrent🏢Health DecisionsDurham · United States2026 · 1 papercurrent🎓Stanford UniversityStanford · United States2013–2018 · 16 papers🎓Massachusetts Institute of TechnologyCambridge · United States2018 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 6 more institutions on single bylines are not listed.

 Fields, topics and concepts

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

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksArtificial Intelligence · 2 worksControl and Systems Engineering · 1 workEngineering · 1 workComputational Theory and Mathematics · 1 workSoftware · 1 work

🧭 Topics 1Research subjects and languages the work is about.Language models & pretraining · 1 work

 Works by year

2020s

20231 paper

2010s

20161 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Eureka: Human-Level Reward Design via Coding Large Language Models (2023 · 142 citations)
    Hand-crafting reward functions for reinforcement learning is slow, relies on trial and error, and often yields sub-optimal results.
  2. Synthesizing Program Input Grammars (2016 · 2 citations)
    The paper addresses the problem of automatically inferring a grammar of a program's valid inputs. Official format specifications are often incomplete or not written in machine-readable form. The authors work in a blackbox setting: the program's source code is unavailable, and there are only a few examples of valid…

All works

13 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. Zero-Shot Learning Through Cross-Modal Transfer ↗arXiv (Cornell University) · no summary yetRichard Socher et al.2013 · 863 citations
  2. Open X-Embodiment: Robotic Learning Datasets and RT-X Models ↗arXiv:2310.08864 · no summary yetEmbodiment Collaboration et al.2023 · 204 citations
  3. Eureka: Human-Level Reward Design via Coding Large Language ModelsarXiv:2310.12931Yecheng Jason Ma, William Liang, Guanzhi Wang, et al.2023 · 142 citations
  4. Learning Performance-Improving Code Edits ↗arXiv:2302.07867 · no summary yetAlexander Shypula et al.2024 · 76 citations
  5. DrEureka: Language Model Guided Sim-To-Real Transfer ↗arXiv:2406.01967 · no summary yetYecheng Jason Ma et al.2024 · 44 citations
  6. Automated High-Level Code Optimization for Warehouse Performance ↗IEEE Micro · no summary yetAlexander Shypula et al.2025 · 4 citations
  7. Stanford's 2013 KBP System ↗Theory and applications of categories · no summary yetGabor Angeli et al.2013 · 3 citations
  8. Synthesizing Program Input GrammarsarXiv:1608.01723Osbert Bastani, Rahul Sharma, Alex Aiken, et al.2016 · 2 citations
  9. Understanding Robust Generalization in Learning Regular Languages ↗arXiv (Cornell University) · no summary yetSoham Dan, Osbert Bastani, Dan Roth2022 · 1 citation
  10. Few-Shot Novel Concept Learning for Semantic Parsing ↗Findings of the Association for Computational Linguistics: EMNLP 2021 · no summary yetSoham Dan, Osbert Bastani, Dan Roth2021 · 1 citation
  11. Self-Driving Datasets: From 20 Million Papers to Nuanced Biomedical Knowledge at Scale ↗arXiv (Cornell University) · no summary yetHaydn Jones et al.2026
  12. Purely Agent-Driven Black-Box Optimization for Biological Design ↗arXiv (Cornell University) · no summary yetNatalie Maus et al.2026
  13. We describe Stanford’s entry in the TAC- ↗no summary yetGabor Angeli et al.2015

 Co-authors here

8 co-authors with a page, the most papers together first.

Venues

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

 Cited by

Papers of our library cite their works 380 times (of the 149,439 papers whose bibliographies we read); 59 citing papers with a page here →.

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