Papers with VQA 2.0
ToolScope: An Agentic Framework for Vision-Guided and Long-Horizon Tool Use (2026.findings-acl)
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| Challenge: | Recent advances in large language models have demonstrated remarkable problem-solving capabilities . however, enabling multimodal large language model to flexibly and efficiently utilize external tools remains a challenge . |
| Approach: | They introduce an agentic framework to unify global planning with local multimodal perception . they evaluate ToolScope on four VQA benchmarks across diverse domains . |
| Outcome: | The proposed framework unifies global planning with local multimodal perception . it adopts a specialized Perceive tool to mitigate visual context degradation in long-horizon VQA task. |
Open-Ended Visual Question Answering by Multi-Modal Domain Adaptation (2020.findings-emnlp)
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| Challenge: | Existing approaches to visual question answering (VQA) are not suitable for real-world applications. |
| Approach: | They propose a supervised multi-modal domain adaptation method for visual question answering in images that exploits supervised domain adaptation. |
| Outcome: | The proposed method outperforms state-of-the-art methods on the benchmark VQA 2.0 and VizWiz datasets. |
Co-VQA : Answering by Interactive Sub Question Sequence (2022.findings-acl)
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| Challenge: | Existing approaches to Visual Question Answering (VQA) answer questions directly, but people usually decompose a complex question into a sequence of simple sub questions. |
| Approach: | They propose a conversation-based VQA framework that decomposes questions into sub questions and answers them one-by-one. |
| Outcome: | The proposed framework achieves state-of-the-art on VQA 2.0 and VQA-CP v2 datasets. |