Building strong chart-to-code systems increasingly relies on reinforcement learning, whose effectiveness depends critically on the quality of the reward signal. Large Multimodal Models (LMMs) play a natural critical role in jointly assessing chart visual appearance and task requirements. They are therefore increasingly...
Li-Jian Wu, Henry Hengyuan Zhao, Zi-Jian Zhang et al.· 0 citations
Long-term agents must remember not only what is true about a user, but also how a particular agent should work with that user as their shared history evolves. Existing benchmarks primarily supervise user facts and preferences or experience reusable across users, leaving this relationship-specific agent memory implicit....
Yi-Fei Tao, Xin-Yue Zhong, Henry Hengyuan Zhao et al.· 0 citations
Temporal reasoning benchmarks for Video-LLMs are often mediated by language, leaving room for linguistic shortcuts from option wording, answer correlations, or language priors, so TempCloze is introduced, a video cloze benchmark for evaluating visual temporal reasoning in Video-LLMs.
Wen-Qi Pei, Henry Hengyuan Zhao, Yi-Lai Liu et al.· 0 citations
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