Sylvia Chung Yan Shan — accepted AI-conference papers

2026

AtelierEval: Agentic Evaluation of Humans & LLMs as Text-to-Image Prompters

Hanjun Luo, Zhimu Huang, Sylvia Chung Yan Shan, Yiran Wang, Yingbin Jin, Jialin Li +3

ICML 2026poster

Text-to-image (T2I) systems increasingly rely on upstream prompters, either humans or multimodal large language models (MLLMs), to translate user intent into detailed prompts. Yet current benchmarks fix the prompt and only evaluate T2I models, leaving the prompting proficiency of this upstream compo…

Cited by 0 Source ↗Scholar ↗

2026

CentaurEval: Benchmarking Human-in-the-Loop Value in Agentic Coding

Hanjun Luo, Chiming Ni, Jiaheng Wen, Zhimu Huang, Bingduo Liao, Yiran Wang +7

ICML 2026poster

LLM-powered coding agents are reshaping the development paradigm. However, existing evaluation systems, neither traditional tests for humans nor benchmarks for LLMs, fail to capture this shift, excluding problems that require both human reasoning to guide solutions and AI efficiency for implementati…

Cited by 7 Source ↗Scholar ↗