🧑‍🔬 Koushik Sen

🏛️ Affiliations

🎓University of California, BerkeleyBerkeley · United States2007–2026 · 174 paperscurrent🎓Berkeley CollegeNew York · United States2026 · 1 papercurrent🎓University of Illinois Urbana-ChampaignUrbana · United States2003–2022 · 47 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 4 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.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code (2024 · 578 citations)
   Widely used code benchmarks such as HumanEval and MBPP have become saturated. They also risk leaking into training data, and they test only one skill: turning a natural-language description into code. LiveCodeBench addresses these problems with a benchmark that keeps growing. It collects fresh problems from weekly…
2. LLM-Assisted Code Cleaning For Training Accurate Code Generators (2023 · 17 citations)
   Most work on training code-generating LLMs focuses on collecting more data or on functional correctness. It largely ignores whether the training programs are readable and well structured. Jain et al. ask whether code style itself affects data quality. They build an automatic cleaning pipeline in which an…

All works

21 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. LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for CodearXiv:2403.07974Naman Jain, King Han, Alex Gu, et al.2024 · 578 citations
2. PerfFuzz: automatically generating pathological inputs ↗ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA) · no summary yetCaroline Lemieux et al.2018 · 159 citations
3. Ansor: Generating High-Performance Tensor Programs for Deep Learning ↗arXiv:2006.06762 · no summary yetLianmin Zheng et al.2020 · 130 citations
4. LLM-Assisted Code Cleaning For Training Accurate Code GeneratorsarXiv:2311.14904Naman Jain, Tianjun Zhang, Wei-Lin Chiang, et al.2023 · 17 citations
5. Type-Constrained Code Generation with Language Models ↗arXiv:2504.09246 · no summary yetNiels Mündler et al.2025 · 16 citations
6. Barbarians at the Gate: How AI is Upending Systems Research ↗arXiv (Cornell University) · no summary yetAudrey Cheng et al.2025 · 15 citations
7. Benchmarking Language Models for Code Syntax Understanding ↗Findings of the Association for Computational Linguistics: EMNLP 2022 · no summary yetDa Shen et al.2022 · 14 citations
8. AdaEvolve: Adaptive LLM Driven Zeroth-Order Optimization ↗arXiv (Cornell University) · no summary yetMert Cemri et al.2026 · 13 citations
9. Challenges and Paths Towards AI for Software Engineering ↗Qeios · no summary yetAlex Gu et al.2025 · 12 citations
10. DSPy Assertions: Computational Constraints for Self-Refining Language Model Pipelines ↗arXiv (Cornell University) · no summary yetArnav Singhvi et al.2023 · 10 citations
11. GSO: Challenging Software Optimization Tasks for Evaluating SWE-Agents ↗neural information processing systems · no summary yetManish Shetty et al.2025 · 6 citations
12. Specifications: The missing link to making the development of LLM systems an engineering discipline ↗arXiv (Cornell University) · no summary yetIon Gabriel Stoica et al.2024 · 4 citations
13. PALT: Parameter-Lite Transfer of Language Models for Knowledge Graph Completion ↗Findings of the Association for Computational Linguistics: EMNLP 2022 · no summary yetJianhao Shen et al.2022 · 4 citations
14. SkyDiscover: A Flexible, Adaptive Framework for AI-Driven Scientific and Algorithmic Discovery ↗no summary yetShu Liu et al.2026 · 2 citations
15. optimize_anything: A Universal API for Optimizing any Text Parameter ↗arXiv:2605.19633 · Proceedings of the ACM Conference on AI and Agentic Systems (CAIS 26), May 26-29, 2026, San Jose, CA, USA · no summary yetLakshya A Agrawal et al.2026 · 1 citation
16. Automatically Learning Skills for Coding Agents ↗no summary yetShangyin Tan et al.2026 · 1 citation
17. LangProBe: a Language Program Benchmark ↗Findings of the Association for Computational Linguistics: EMNLP 2025 · no summary yetShangyin Tan et al.2025 · 1 citation
18. LangProBe: a Language Programs Benchmark ↗arXiv (Cornell University) · no summary yetShangyin Tan et al.2025 · 1 citation
19. Neural Inference of API Functions from Input–Output Examples ↗no summary yetRohan Bavishi et al.2018 · 1 citation
20. IDEAS: C-to-Rust Translation Using Improved Large Language Model Decoding and Automated Equivalence Testing ↗IEEE Security & Privacy · no summary yetCory T. Cornelius et al.2026
21. CodeScholar: Growing Idiomatic Code Examples ↗arXiv (Cornell University) · no summary yetShetty, Manish, Koushik Sen, Ion Gabriel Stoica2023

🤝 Co-authors here

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

• Ion Gabriel Stoica ×2
• Naman Jain ×2
• Tianjun Zhang ×2
• Alex Gu
• Armando Solar-Lezama
• Joseph E. Gonzalez
• Sida Wang
• Wei-Lin Chiang
• Wen-Ding Li

Venues

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

• Findings of the Association for Computational Linguistics: EMNLP 2022 ×3
• ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA)
• IEEE Security & Privacy
• Qeios
• neural information processing systems

🔗 Cited by

Papers of our library cite their works 617 times (of the 149,439 papers whose bibliographies we read); 230 citing papers with a page here →.

Updated 3 November 2026

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