Embodied agents executing tasks from natural language instructions face the challenge of interpreting ambiguous commands that may lead to inconsistent planning. Conventional uncertainty estimation methods, reliant on token-level probabilities or semantic embeddings, struggle to capture task-level intent divergence, whi...
Hai-Yu Zhao, Xing-Lei Hao, Chun-Hong Zhang et al.· IEEE Robotics and Automation...· 0 citations
DuoOPD is introduced, in which the student's outcome sets the direction of feedback and the joint teacher-student outcome decides how the teacher supports it: when only the teacher succeeds, its verified answer becomes context for scoring the student's failed response.
This work designs two tasks, basic question answering (BasicQA) and reasoning-based question answering (ReaQA), to evaluate the models' ability to directly extract information from charts, and understand the textual and visual information for reasoning.
Tan Yue, Rui Mao, Xuzhao Shi et al.· Proceedings of the 32nd ACM...· 1 citation
Charts play a key role in scientific research, offering a concise and visual way to present complex data. For Multimodal Large Language Models (MLLMs), the ability to comprehend charts is critical, as it requires both visual perception and reasoning that bridges graphical and textual information. However, existing char...
Tan Yue, Rui Mao, Xuzhao Shi et al.· Proceedings of the 32nd ACM...· 1 citation
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