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cs.CV2026
Visual Reasoning through Tool-supervised Reinforcement Learning
Qihua Dong, Gozde Sahin, Pei Wang +4
In this paper, we investigate the problem of how to effectively master tool-use to solve complex visual reasoning tasks for Multimodal Large Language Models. To achieve that, we pr…
cs.CV2024
BloomVQA: Assessing Hierarchical Multi-modal Comprehension
Yunye Gong, Robik Shrestha, Jared Claypoole +4
We propose a novel VQA dataset, BloomVQA, to facilitate comprehensive evaluation of large vision-language models on comprehension tasks. Unlike current benchmarks that often focus…
cs.CV2024
Visual Grounding Methods for VQA are Working for the Wrong Reasons!
Robik Shrestha, Kushal Kafle, Christopher Kanan
Existing Visual Question Answering (VQA) methods tend to exploit dataset biases and spurious statistical correlations, instead of producing right answers for the right reasons. To…