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SOTA2 Research · papers
Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.
| Pratyay Banerjee, Kuntal Kumar Pal, Arindam Mitra |
| 2019 |
| arxiv 1907.10738 |
| Question Answering by Reasoning Across Documents with Graph Convolutional Networks | Nicola De Cao, Wilker Aziz, Ivan Titov | 2018 | arxiv 1808.09920 |
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| A Survey of Large Language Model Agents for Question Answering | Murong Yue | 2025 | arxiv 2503.19213 |
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| Prompt-based Personalized Federated Learning for Medical Visual Question Answering | He Zhu, Ren Togo, Takahiro Ogawa | 2024 | arxiv 2402.09677 |
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| Silver Retriever: Advancing Neural Passage Retrieval for Polish Question Answering | Piotr Rybak, Maciej Ogrodniczuk | 2023 | arxiv 2309.08469 |
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| CoSQA: 20,000+ Web Queries for Code Search and Question Answering | Junjie Huang, Duyu Tang, Linjun Shou | 2021 | arxiv 2105.13239 |
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| Full-Time Supervision based Bidirectional RNN for Factoid Question Answering | Dong Xu, Wu-Jun Li | 2016 | arxiv 1606.05854 |
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| CoPA: Benchmarking Personalized Question Answering with Data-Informed Cognitive Factors | Hang Su, Zequn Liu, Chen Hu | 2026 | arxiv 2604.14773 |
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| Psycholinguistics meets Continual Learning: Measuring Catastrophic Forgetting in Visual Question Answering | Claudio Greco, Barbara Plank, Raquel Fernández | 2019 | arxiv 1906.04229 |
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| Multi-step Entity-centric Information Retrieval for Multi-Hop Question Answering | Ameya Godbole, Dilip Kavarthapu, Rajarshi Das | 2019 | arxiv 1909.07598 |
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