--- title: "Who cites Sanjit Arunkumar Seshia — 48 papers of our library" description: "48 papers of the Elamur Research library cite the works of Sanjit Arunkumar Seshia, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/sanjit-arunkumar-seshia/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/sanjit-arunkumar-seshia/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Sanjit Arunkumar Seshia](https://md.research.elamur.ai/free/en/authors/sanjit-arunkumar-seshia/) / cited by # Who cites Sanjit Arunkumar Seshia 48 citations of their works from 48 papers of our library (of the 149,439 whose bibliographies we read) · 18 with a page here, the most cited first · [← Sanjit Arunkumar Seshia](https://md.research.elamur.ai/free/en/authors/sanjit-arunkumar-seshia/) 1. [**Program Synthesis with Large Language Models arXiv:2108.07732**Jacob Austin, Augustus Odena, Maxwell Nye, et al.*2021 · 1,192 citations*](https://md.research.elamur.ai/free/en/papers/austin-2021-program-synthesis-large-language-models/) 2. **[cvc5: A Versatile and Industrial-Strength SMT Solver](https://md.research.elamur.ai/free/en/papers/barbosa-2022-cvc5-versatile-industrial-strength-smt/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Haniel Barbosa, Clark Barrett, Martin Brain, et al.*2022 · 487 citations* 3. [**SQLNet: Generating Structured Queries From Natural Language Without Reinforcement Learning arXiv:1711.04436**Xiaojun Xu, Chang Liu, Dawn Song*2017 · 372 citations*](https://md.research.elamur.ai/free/en/papers/xu-2017-sqlnet-generating-structured-queries-natural/) 4. **[Type-and-Example-Directed Program Synthesis](https://md.research.elamur.ai/free/en/papers/osera-2015-type-example-directed-program-synthesis/) [Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-acm-sigplan-conference-on-programming-language-design-and/)**Peter-Michael Osera, Steve Zdancewic*2015 · 198 citations* 5. [**Neuro-Symbolic Program Synthesis arXiv:1611.01855**Emilio Parisotto, Abdel-rahman Mohamed, Rishabh Singh, et al.*2016 · 152 citations*](https://md.research.elamur.ai/free/en/papers/parisotto-2016-neuro-symbolic-program-synthesis/) 6. **[Generalized Planning in PDDL Domains with Pretrained Large Language Models](https://md.research.elamur.ai/free/en/papers/silver-2023-generalized-planning-pddl-domains-pretrained/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Tom Silver, Soham Dan, Kavitha Srinivas, et al.*2023 · 112 citations* 7. [**Mechanistic Interpretability for AI Safety — A Review arXiv:2404.14082**Leonard Bereska, Efstratios Gavves*2024 · 108 citations*](https://md.research.elamur.ai/free/en/papers/bereska-2024-mechanistic-interpretability-ai-safety-review/) 8. [**MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation arXiv:2208.08227**Federico Cassano, John Gouwar, Daniel Nguyen, et al.*2022 · 88 citations*](https://md.research.elamur.ai/free/en/papers/cassano-2022-multipl-e-scalable-extensible-approach/) 9. [**Program Synthesis Foundations and Trends in Programming Languages 4(1-2)**Sumit Gulwani, Oleksandr Polozov, Rishabh Singh*2017 · 63 citations*](https://md.research.elamur.ai/free/en/papers/gulwani-2017-program-synthesis/) 10. **[Clover: Closed-Loop Verifiable Code Generation](https://md.research.elamur.ai/free/en/papers/sun-2024-clover-closed-loop-verifiable-code/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Chuyue Sun, Ying Sheng, Oded Padon, et al.*2024 · 56 citations* 11. **[Just-in-Time Learning for Bottom-Up Enumerative Synthesis](https://md.research.elamur.ai/free/en/papers/barke-2020-just-time-learning-bottom-up/) [Proceedings of the ACM on Programming Languages](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-acm-on-programming-languages/)**Shraddha Barke, Hila Peleg, Nadia Polikarpova*2020 · 38 citations* 12. **[Graph Representations for Higher-Order Logic and Theorem Proving](https://md.research.elamur.ai/free/en/papers/paliwal-2019-graph-representations-higher-order-logic/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Aditya Paliwal, Sarah Loos, Markus Rabe, et al.*2019 · 33 citations* 13. [**Teaching Temporal Logics to Neural Networks arXiv:2003.04218**Christopher Hahn, Frederik Schmitt, Jens U. Kreber, et al.*2020 · 24 citations*](https://md.research.elamur.ai/free/en/papers/hahn-2020-teaching-temporal-logics-neural-networks/) 14. [**Automated Theorem Proving in Intuitionistic Propositional Logic by Deep Reinforcement Learning arXiv:1811.00796**Mitsuru Kusumoto, Keisuke Yahata, Masahiro Sakai*2018 · 15 citations*](https://md.research.elamur.ai/free/en/papers/kusumoto-2018-automated-theorem-proving-intuitionistic-propositional/) 15. [**Generating Code World Models with Large Language Models Guided by Monte Carlo Tree Search arXiv:2405.15383**Nicola Dainese, Matteo Merler, Minttu Alakuijala, et al.*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/dainese-2024-generating-code-world-models/) 16. [**Learning Heuristics for Quantified Boolean Formulas through Deep Reinforcement Learning arXiv:1807.08058**Gil Lederman, Markus N. Rabe, Edward A. Lee, et al.*2018 · 12 citations*](https://md.research.elamur.ai/free/en/papers/lederman-2018-learning-heuristics-quantified-boolean-formulas/) 17. **[PBEBench: A Multi-Step Programming by Examples Reasoning Benchmark inspired by Historical Linguistics](https://md.research.elamur.ai/free/en/papers/naik-2026-pbebench-multi-step-programming-examples/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Atharva Naik, Darsh Agrawal, Prakam, et al.*2026 · 1 citation* 18. [**Accountable Human-AI Deliberation with LLMs: Scaling Collective Intelligence through Symbiotic Scaffolding Proceedings of The 2nd Workshop on Language-driven Deliberation Technology**Wajdi Zaghouani*2026*](https://md.research.elamur.ai/free/en/papers/zaghouani-2026-accountable-human-ai-deliberation-llms/) 30 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/sanjit-arunkumar-seshia/) — Sanjit Arunkumar Seshia