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SOTA2 Research · papers
Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.
| Improving Skin Condition Classification with a Question Answering Model | Mohamed Akrout, Amir-massoud Farahmand, Tory Jarmain | 2018 | arxiv 1811.06165 |
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| Probabilistic Neural-symbolic Models for Interpretable Visual Question Answering | Ramakrishna Vedantam, Karan Desai, Stefan Lee | 2019 | arxiv 1902.07864 |
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| Evaluating LLMs' Mathematical Reasoning in Financial Document Question Answering | Pragya Srivastava, Manuj Malik, Vivek Gupta | 2024 | arxiv 2402.11194 |
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| Modeling Global Semantics for Question Answering over Knowledge Bases | Peiyun Wu, Yunjie Wu, Linjuan Wu | 2021 | arxiv 2101.01510 |
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| Knowledge Distillation for Improved Accuracy in Spoken Question Answering | Chenyu You, Nuo Chen, Yuexian Zou | 2020 | arxiv 2010.11067 |
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| Generating Natural Language Explanations for Visual Question Answering using Scene Graphs and Visual Attention | Shalini Ghosh, Giedrius Burachas, Arijit Ray | 2019 | arxiv 1902.05715 |
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| keqing: knowledge-based question answering is a nature chain-of-thought mentor of LLM | Chaojie Wang, Yishi Xu, Zhong Peng | 2023 | arxiv 2401.00426 |
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| Recent Advances in Video Question Answering: A Review of Datasets and Methods | Devshree Patel, Ratnam Parikh, Yesha Shastri | 2021 | arxiv 2101.05954 |
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| ESGBench: A Benchmark for Explainable ESG Question Answering in Corporate Sustainability Reports | Sherine George, Nithish Saji | 2025 | arxiv 2511.16438 |
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| Greedy Gradient Ensemble for Robust Visual Question Answering | Xinzhe Han, Shuhui Wang, Chi Su | 2021 | arxiv 2107.12651 |
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