Qiuyang Mang (忙秋阳)
Hi, I’m Qiuyang Mang, a second-year CS PhD student in the Sky Computing Lab at UC Berkeley, advised by Prof. Alvin Cheung. I lead FrontierCS and FrontierSmith, a benchmark and data synthesis system for LLM-driven algorithm evolution on open-ended coding tasks. My research interests center on two themes:
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Long-Horizon LLM Agents: Understanding, developing, and improving LLM agents for complex, multi-step optimization across data synthesis, test-time scaling, post-training algorithms, and domain-specific applications. Elo-per-token, FrontierCS, FrontierSmith, Argus, Combee, SkyDiscover
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Machine Learning Systems: Efficient algorithms for ML workloads, from data-processing to inference scheduling. SVG-EAR, Continuum, PLOP
Prior to joining Berkeley, I received my B.E. from The Chinese University of Hong Kong, Shenzhen, where I was advised by Prof. Pinjia He. I also spent an unforgettable year as a research assistant at the National University of Singapore with Prof. Manuel Rigger. I was in the 46th ICPC World Finalist 🎈 and served as problem setters for regionals.
Mentees: Runyuan He, Kaiyuan Liu, Xuanyi Zhou
Selected Publications
* Equal contribution
When Agents Slow Down: Understanding LLM Agents' Test-Time Strategies via Elo-per-token Analysis
An analysis of how agents convert test-time tokens into progress, revealing where their gains fall below independent sampling while expert humans continue improving.
FrontierCS: Evolving Challenges for Evolving Intelligence
A benchmark of unsolved, open-ended, verifiable computer science challenges that can evolve with increasingly capable agents.
Argus: Automated Discovery of Test Oracles for Database Management Systems Using LLMs
A framework that discovers and verifies DBMS test oracles with LLMs, finding previously unknown logic bugs in widely used databases.
SVG-EAR: Parameter-Free Linear Compensation for Sparse Video Generation via Error-aware Routing
A parameter-free linear compensation method that mitigates sparse-attention error, accelerating video generation without retraining.
Continuum: Efficient and Robust Multi-Turn LLM Agent Scheduling with KV Cache Time-to-Live
A KV-cache time-to-live and program-level scheduling system for efficient, robust multi-turn LLM agent serving.