Haiyu Xu — accepted AI-conference papers

2026

Beyond Multiple Choice: Verifiable OpenQA for Robust Vision-Language RFT

Yesheng Liu, Hao Li, Haiyu Xu, Baoqi Pei, Jiahao Wang, Mingxuan Zhao +6

CVPR 2026

Multiple-choice question answering (MCQA) has been a popular format for evaluating and reinforcement fine-tuning (RFT) of modern multimodal language models. Its constrained output format allows for simplified, deterministic automatic verification.However, we find that the options may leak exploitabl

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2026

Do Vision-Language Models Measure Up? Benchmarking Visual Measurement Reading with MeasureBench

Fenfen Lin, Yesheng Liu, Haiyu Xu, Yue Chen, Zheqi He, Mingxuan Zhao +3

CVPR 2026

Reading measurement instruments is effortless for humans and requires relatively little domain expertise, yet it remains surprisingly challenging for current vision-language models (VLMs) as we find in preliminary evaluation. In this work, we introduce MeasureBench, a benchmark on visual measurement

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