🔗 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»

1. A Corpus for Reasoning About Natural Language Grounded in Photographs (NLVR2)Alane Suhr, Stephanie Zhou, Ally Zhang, et al.2019 · 670 citations
2. A-OKVQA: A Benchmark for Visual Question Answering using World KnowledgeLecture notes in computer scienceDustin Schwenk, Apoorv Khandelwal, Christopher Clark, et al.2022 · 509 citations
3. ViperGPT: Visual Inference via Python Execution for ReasoningIEEE/CVF International Conference on Computer Vision (ICCV)Didac Suris, Sachit Menon, Carl Vondrick2023 · 383 citations
4. Chameleon: Plug-and-Play Compositional Reasoning with Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Pan Lu, Baolin Peng, Hao Cheng, et al.2023 · 327 citations
5. Learning to Speak and Act in a Fantasy Text Adventure GamearXiv:1903.03094Jack Urbanek, Angela Fan, Siddharth Karamcheti, et al.2019 · 243 citations
6. The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural SupervisionarXiv:1904.12584Jiayuan Mao, Chuang Gan, Pushmeet Kohli, et al.2019 · 241 citations
7. Towards Faithful Model Explanation in NLP: A SurveyComputational LinguisticsQing Lyu, Marianna Apidianaki, Chris Callison-Burch2024 · 197 citations
8. GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical ReasoningFindings of the Association for Computational LinguisticsJiaqi Chen, Jianheng Tang, Jinghui Qin, et al.2021 · 184 citations
9. Large Language Models are In-Context Semantic Reasoners rather than Symbolic ReasonersarXiv:2305.14825Xiaojuan Tang, Zilong Zheng, Jiaqi Li, et al.2023 · 52 citations
10. Neuro-Symbolic Artificial Intelligence: Current TrendsarXiv:2105.05330Md Kamruzzaman Sarker, Lu Zhou, Aaron Eberhart, et al.2021 · 12 citations
11. Evidence Grounding vs. Memorization: Why Neural Semantics Matter for Knowledge Graph Fact VerificationFact Extraction and VERification Workshop (FEVER)Ankit Kumar Upadhyay, John S. Erickson, Deborah L. McGuinness2026

76 more papers of our library cite it; they have no page here yet.

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