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Author

Han Bao

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Book Open access Aug 2026

AutoDavis: Automatic and Dynamic Evaluation Protocol of Large Vision-Language Models on Visual Question-Answering

AutoDavis is introduced, a first-of-its-kind automatic and dynamic evaluation protocol that enables on-demand benchmarking of LVLMs across specific capability dimensions and shows effectiveness and reliability, offering a new paradigm for dynamic benchmarking of multimodal intelligence.

Han Bao, Yue Huang, Yan-Bo Wang et al. · 0 citations

SpecAlign: Efficient Specification-Grounded Alignment of Large Language Models via Synthetic Data

This paper proposes specification-grounded alignment, a new alignment paradigm that treats provider-authored model specifications as the primary alignment target rather than abstract principles or static benchmarks, and introduces SpecAlign, a framework that synthesizes alignment data directly from specification docume...

Wenjie Wang, Yue Huang, Zheng-Qing Yuan et al. · 4 citations
Jul 2026

MemoHarness: Agent Harnesses That Learn from Experience

MemoHarness is introduced, an adaptive harness optimization framework that learns from its own executions and improves over the fixed harnesses it is compared against and shows selective transfer to unseen suites and base models.

Yue Huang, Wenjie Wang, Han Bao et al. · 4 citations
Book Open access Aug 2026

AutoDavis: Automatic and Dynamic Evaluation Protocol of Large Vision-Language Models on Visual Question-Answering

AutoDavis is introduced, a first-of-its-kind automatic and dynamic evaluation protocol that enables on-demand benchmarking of LVLMs across specific capability dimensions and shows effectiveness and reliability, offering a new paradigm for dynamic benchmarking of multimodal intelligence.

Han Bao, Yue Huang, Yanbo Wang et al. · 0 citations

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