Sixiao Luo

ChartR: Evaluating Reasoning Accuracy and Robustness in Chart Question Answering

Chart Question Answering (CQA) benchmarks are critical for evaluating Multimodal Large Language Models (MLLMs) on visual data reasoning. Existing benchmarks focus mainly on final-answer correctness, ignoring intermediate reasoning steps and the propagation of errors in multi-step processes. To addre