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Bei Liu

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#software testing Review Oct 2026

OfficeTown: Generative Organizations for Evolving Agent Intelligence

The introduction of OfficeTown, a generative simulation framework for professional organizations in which tasks and their context arise from continuing organizational work, highlights the value of organizational simulation in generating work-grounded data and environments for the continued development of generalist age...

Hong-Chen Wei, Dao-Hong Ying, Zhi-Cong Hong et al. · 0 citations
#machine learning Preprint Sep 2026

YuE2: Unifying Symbolic and Audio Music Generation at Frontier Quality

Symbolic models make melody, harmony, rhythm, and form explicit but typically stop before a finished recording; audio models produce complete songs while leaving composition implicit. We introduce YuE2, which unifies symbolic and audio music generation at frontier quality through symbolic planning. A single AR-NAR Mixt...

Rui-Bin Yuan, Jia-Hao Pan, Jun-Yan Jiang et al. · 1 citation
#artificial intelligence Preprint Jun 2026

Planning Takes More Than Token Prediction: Causal Plan for Benchmarking and Building Physically Grounded Embodied Reasoners

This work introduces Causal-Plan-Bench, a high-fidelity diagnostic suite spanning four causal dimensions, curated via multi-stage verification, and initiate the first effort to turn agents from superficial token predictors into physically grounded causal reasoners, bridging language modeling and world modeling.

Zi-Rong Song, Zheng Lu, Ming-Qi Gao et al. · 3 citations
Preprint Jul 2026

XL-DocBench: Benchmarking Evidence-Grounded Extra-Long Document Understanding

XL-DocBench is introduced, a fully human-verified benchmark for extra-long document understanding, with 1,519 retained questions from six professional domains and contexts up to 2,303 pages, and fills a gap left by prior single-page, short multi-page, or text-only long-context benchmarks.

Hongchen Wei, Yuanzhe Wang, Bei Liu et al. · 0 citations
Review Jul 2026

DocAtlas: Long-Document Understanding as Mutable-State Interaction

DocAtlas is presented, a system that treats long-document understanding as a mutable-state information-seeking process and instantiate DocAtlas as a mutable document harness: an external environment that determines what document information is searched, read, stored, reviewed, and shown to the model at each step.

Hongchen Wei, Yuanzhe Wang, Bei Liu et al. · 0 citations

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