Video understanding benchmarks are the primary yardstick for measuring progress in video-language modeling, and a growing body of work relies on them to claim improvements. The reported benchmark scores in these works, however, are almost always produced by frameworks (e.g., lmms eval) used as black boxes: certain eval...
Soumya Jahagirdar, A. Kukleva, Vishaal Udandarao et al.· 0 citations
EpiCon, a shared multimodal memory framework for agent collective learning without updating host model parameters, links question-level memory evolution to a persistent experience bank through two independently trained 2B models: a memory controller and a tree self-organizer.
Ziyun Zeng, Hang Hua, S. Alshammari et al.· 1 citation
Chart editing requires cross-modal edit grounding, realizing a requested visual change in the code that draws it, with necessary related updates and without altering unrelated content. Existing benchmarks emphasize either code executability or chart quality, but their metrics do not clearly distinguish request completi...
Jia-Xiang Tang, Yi Zhou, Chad DeLuca et al.· 0 citations
This work introduces DocHop, a benchmark for integrated chart--context reasoning in document-style images and constructs DocHop via a stochastic logic-first generation pipeline with controllable reasoning depth and visual density, to enable systematic evaluation.
Zhuo-Ran Yu, Le Thien Phuc Nguyen, Jaden Park et al.· 1 citation
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