--- title: "Who cites Neural-Symbolic VQA: — 87 citing papers" description: "87 papers of the Elamur Research library cite «Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding»…" canonical: "https://research.elamur.ai/free/en/papers/yi-2018-neural-symbolic-vqa-disentangling-reasoning/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/yi-2018-neural-symbolic-vqa-disentangling-reasoning/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Neural-Symbolic VQA: Disentangling Reasoning from…](https://md.research.elamur.ai/free/en/papers/yi-2018-neural-symbolic-vqa-disentangling-reasoning/) / cited by # Who cites «Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding» 87 papers of our library cite it (of the 149,439 whose bibliographies we read) · 11 with a page here, the most cited first · [← back to «Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding»](https://md.research.elamur.ai/free/en/papers/yi-2018-neural-symbolic-vqa-disentangling-reasoning/) 1. [**A Corpus for Reasoning About Natural Language Grounded in Photographs (NLVR2)**Alane Suhr, Stephanie Zhou, Ally Zhang, et al.*2019 · 670 citations*](https://md.research.elamur.ai/free/en/papers/suhr-2019-corpus-reasoning-natural-language-grounded/) 2. **[A-OKVQA: A Benchmark for Visual Question Answering using World Knowledge](https://md.research.elamur.ai/free/en/papers/schwenk-2022-okvqa-benchmark-visual-question-answering/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Dustin Schwenk, Apoorv Khandelwal, Christopher Clark, et al.*2022 · 509 citations* 3. **[ViperGPT: Visual Inference via Python Execution for Reasoning](https://md.research.elamur.ai/free/en/papers/suris-2023-vipergpt-visual-inference-python-execution/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Didac Suris, Sachit Menon, Carl Vondrick*2023 · 383 citations* 4. **[Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models](https://md.research.elamur.ai/free/en/papers/lu-2023-chameleon-plug-play-compositional-reasoning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Pan Lu, Baolin Peng, Hao Cheng, et al.*2023 · 327 citations* 5. [**Learning to Speak and Act in a Fantasy Text Adventure Game arXiv:1903.03094**Jack Urbanek, Angela Fan, Siddharth Karamcheti, et al.*2019 · 243 citations*](https://md.research.elamur.ai/free/en/papers/urbanek-2019-learning-speak-act-fantasy-text/) 6. [**The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision arXiv:1904.12584**Jiayuan Mao, Chuang Gan, Pushmeet Kohli, et al.*2019 · 241 citations*](https://md.research.elamur.ai/free/en/papers/mao-2019-neuro-symbolic-concept-learner-interpreting/) 7. **[Towards Faithful Model Explanation in NLP: A Survey](https://md.research.elamur.ai/free/en/papers/lyu-2024-faithful-model-explanation-nlp-survey/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Qing Lyu, Marianna Apidianaki, Chris Callison-Burch*2024 · 197 citations* 8. **[GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning](https://md.research.elamur.ai/free/en/papers/chen-2021-geoqa-geometric-question-answering-benchmark/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaqi Chen, Jianheng Tang, Jinghui Qin, et al.*2021 · 184 citations* 9. [**Large Language Models are In-Context Semantic Reasoners rather than Symbolic Reasoners arXiv:2305.14825**Xiaojuan Tang, Zilong Zheng, Jiaqi Li, et al.*2023 · 52 citations*](https://md.research.elamur.ai/free/en/papers/tang-2023-large-language-models-context-semantic/) 10. [**Neuro-Symbolic Artificial Intelligence: Current Trends arXiv:2105.05330**Md Kamruzzaman Sarker, Lu Zhou, Aaron Eberhart, et al.*2021 · 12 citations*](https://md.research.elamur.ai/free/en/papers/sarker-2021-neuro-symbolic-artificial-intelligence/) 11. **[Evidence Grounding vs. Memorization: Why Neural Semantics Matter for Knowledge Graph Fact Verification](https://md.research.elamur.ai/free/en/papers/upadhyay-2026-evidence-grounding-vs-memorization-why/) [Fact Extraction and VERification Workshop (FEVER)](https://md.research.elamur.ai/free/en/venues/fever/)**Ankit Kumar Upadhyay, John S. Erickson, Deborah L. McGuinness*2026* 76 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/yi-2018-neural-symbolic-vqa-disentangling-reasoning/) — Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding