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
Large Multi-modality Models (LMMs) have made significant progress in visual understanding and generation, but still face challenges in visual editing, particularly in following complex instructions, preserving appearance consistency, and supporting flexible input formats. To study this gap, we introduce RISEBench, the...
Xue Yang, Pei-Yuan Zhang, Yilun Zhu et al.· 0 citations
INSPIRE, a benchmark for evaluating agents that search prior literature to make progress on solution-redacted research problems, enables both end-to-end comparison and stage-resolved diagnosis in a setting where the agent must construct its own working criterion of relevance.
Jian-Rong Ding, Zheng-Yan Shi, Jian-Yuan Zhong et al.· 0 citations
ReDeck is proposed, a step-level render-grounded refinement framework that decomposes slide revision into atomic edit actions and returns renderer-derived observations after each step, turning refinement into"one edit, one observation."
Mu-Zhao Tian, Ze-Zi Zeng, Yi-Fan Yang et al.· 0 citations
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
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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