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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.
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...
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