Runyuan He

Soda Hall, UC Berkeley

Berkeley, CA 94720

I am a junior undergraduate in Computer Science at The Chinese University of Hong Kong, Shenzhen, currently a summer visiting research assistant at UC Berkeley.

My research focuses on LLM-based database testing systems under the supervision of Prof. Alvin Cheung. I am actively seeking Ph.D. opportunities in database systems and software engineering.

Open-source models from my recent work are available on Hugging Face, and code/preprints are on GitHub, Google Scholar, and DBLP.

Research Interests

Database Systems
Large Language Models (LLMs)

Selected Achievements

🥈 Silver Medalist - The 38th National Olympiad in Informatics (NOI 2021)
🌍 24th Place - The 48th ICPC World Final 2024
🏆 8th Place - The 48th ICPC World Final Huawei Challenge 2024
🥇 Gold Medalist - ICPC Regional 2023/2024

selected publications

SIGMOD’26
Automated Discovery of Test Oracles for Database Management Systems Using LLMs

Qiuyang Mang, Runyuan He, Suyang Zhong, and 3 more authors

Proceedings of the ACM on Management of Data (SIGMOD), 2026

SIGMOD 2026 Abs DOI arXiv Bib

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This paper explores the use of large language models (LLMs) to automate the discovery and instantiation of test oracles, addressing a long-standing bottleneck towards fully automated DBMS testing. We introduce Argus, a novel framework built upon the core concept of the Constrained Abstract Query. Argus uses LLMs to generate pairs of SQL skeletons that are asserted to be semantically equivalent, then formally proven using a SQL equivalence solver to ensure soundness.
@article{mang2025argus, title = {Automated Discovery of Test Oracles for Database Management Systems Using LLMs}, author = {Mang, Qiuyang and He, Runyuan and Zhong, Suyang and Liu, Xiaoxuan and Zhang, Huanchen and Cheung, Alvin}, journal = {Proceedings of the ACM on Management of Data (SIGMOD)}, volume = {4}, number = {3}, pages = {Article 140}, year = {2026}, doi = {10.1145/3802017}, }
arXiv
Continuum: Efficient and Robust Multi-Turn LLM Agent Scheduling with KV Cache Time-to-Live

Hanchen Li^*, Runyuan He^*, Qiuyang Mang, and 7 more authors

arXiv preprint arXiv:2511.02230, 2025

Abs arXiv Bib

We present Continuum, a serving system to optimize job completion time for multi-turn agent workloads by introducing time-to-live mechanism for KV cache retaining. For LLM request that generates a tool call, Continuum selectively pins the KV cache in GPU memory with a time-to-live value determined by considering both the reload cost and ordering preserve benefit of retaining KV cache.
@article{li2025continuum, title = {Continuum: Efficient and Robust Multi-Turn LLM Agent Scheduling with KV Cache Time-to-Live}, author = {Li, Hanchen and He, Runyuan and Mang, Qiuyang and Zhang, Qizheng and Mao, Huanzhi and Chen, Xiaokun and Zhou, Hangrui and Cheung, Alvin and Gonzalez, Joseph and Stoica, Ion}, journal = {arXiv preprint arXiv:2511.02230}, year = {2025}, }
arXiv
FrontierSmith: Synthesizing Open-Ended Coding Problems at Scale

Runyuan He^*, Qiuyang Mang^*, Shang Zhou, and 14 more authors

arXiv preprint arXiv:2605.14445, 2026

Abs arXiv Bib

Open-ended coding remains a weak spot for LLMs, largely because open-ended training problems are scarce. FrontierSmith is an automated system that synthesizes such problems by evolving competitive programming tasks through modifying goals, restricting outputs, and generalizing inputs. The system employs a quantitative idea divergence metric to select problems that elicit genuinely diverse approaches, and generates corresponding test cases and verifiers. Models trained on FrontierSmith data show significant improvements on FrontierCS and ALE-bench benchmarks.
@article{he2026frontiersmith, title = {FrontierSmith: Synthesizing Open-Ended Coding Problems at Scale}, author = {He, Runyuan and Mang, Qiuyang and Zhou, Shang and Liu, Kaiyuan and Li, Hanchen and Mao, Huanzhi and Zhang, Qizheng and Li, Zerui and Peng, Bo and Cheng, Lufeng and Fu, Tianfu and Wang, Yichuan and Chai, Wenhao and Shang, Jingbo and Dimakis, Alex and Gonzalez, Joseph E and Cheung, Alvin}, journal = {arXiv preprint arXiv:2605.14445}, year = {2026}, }