--- title: "Who cites The Value of Semantic Parse Labeling for…" description: "254 papers of the Elamur Research library cite «The Value of Semantic Parse Labeling for Knowledge Base Question Answering», found in their…" canonical: "https://research.elamur.ai/free/en/papers/yih-2016-value-semantic-parse-labeling-knowledge/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/yih-2016-value-semantic-parse-labeling-knowledge/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [The Value of Semantic Parse Labeling for…](https://md.research.elamur.ai/free/en/papers/yih-2016-value-semantic-parse-labeling-knowledge/) / cited by # Who cites «The Value of Semantic Parse Labeling for Knowledge Base Question Answering» 254 papers of our library cite it (of the 140,884 whose bibliographies we read) · 14 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/yih-2016-value-semantic-parse-labeling-knowledge/) 1. [**A Survey of Large Language Models**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,847 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) 2. [**Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings**Apoorv Saxena, Aditay Tripathi, Partha Talukdar*2020 · 670 citations*](https://md.research.elamur.ai/free/en/papers/saxena-2020-improving-multi-hop-question-answering/) 3. [**UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models**Tianbao Xie, Chen Henry Wu, Peng Shi, et al.*2022 · 405 citations*](https://md.research.elamur.ai/free/en/papers/xie-2022-unifiedskg-unifying-multi-tasking-structured/) 4. [**HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Data**Wenhu Chen, Hanwen Zha, Zhiyu Chen, et al.*2020 · 376 citations*](https://md.research.elamur.ai/free/en/papers/chen-2020-hybridqa-dataset-multi-hop-question/) 5. [**The Web as a Knowledge-Base for Answering Complex Questions**Alon Talmor, Jonathan Berant*2018 · 316 citations*](https://md.research.elamur.ai/free/en/papers/talmor-2018-web-as-knowledge-base-answering/) 6. [**G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering**Xiaoxin He, Yijun Tian, Yifei Sun, et al.*2024 · 234 citations*](https://md.research.elamur.ai/free/en/papers/he-2024-g-retriever-retrieval-augmented-generation/) 7. [**Break It Down: A Question Understanding Benchmark**Tomer Wolfson, Mor Geva, Ankit Gupta, et al.*2020 · 218 citations*](https://md.research.elamur.ai/free/en/papers/wolfson-2020-break-it-down-question-understanding/) 8. [**Syntax for Semantic Role Labeling, To Be, Or Not To Be**Shexia He, Zuchao Li, Hai Zhao, et al.*2018 · 211 citations*](https://md.research.elamur.ai/free/en/papers/he-2018-syntax-semantic-role-labeling-be/) 9. [**How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition**Guanting Dong, Hongyi Yuan, Keming Lu, et al.*2024 · 145 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-how-abilities-large-language-models/) 10. [**Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answering**Jinheon Baek, Alham Fikri Aji, Amir Saffari*2023 · 118 citations*](https://md.research.elamur.ai/free/en/papers/baek-2023-knowledge-augmented-language-model-prompting/) 11. [**Ontology-Guided Reverse Thinking Makes Large Language Models Stronger on Knowledge Graph Question Answering**Runxuan Liu, Bei Luo, Jiaqi Li, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-ontology-guided-reverse-thinking-makes/) 12. [**QA-KGNet: Language Model-driven Knowledge Graph Question-answering Model (QA-KGNet: 一种语言模型驱动的知识图谱问答模型)**Shaojie Qiao (乔少杰), Guoping Yang (杨国平), Yong Yu (于泳), et al.*2023 · 1 citation*](https://md.research.elamur.ai/free/en/papers/qiao-2023-qa-kgnet-language/) 13. [**PolyglotQL: A Pipeline for Multilingual Text-to-SPARQL Dataset Generation**Julio Perez, Fabio Barth, Georg Rehm*2026*](https://md.research.elamur.ai/free/en/papers/perez-2026-polyglotql-pipeline-multilingual-text-sparql/) 14. [**Recent Advances in Text-attributed Graph Learning via Large Models (大模型驱动的文本属性图学习研究进展)**Yanping Zheng (郑艳萍), Jiarui Ji (季嘉蕊), Yuwei Hu (胡雨韦), et al.*2026*](https://md.research.elamur.ai/free/en/papers/zheng-2026-recent-advances-text/) 240 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/yih-2016-value-semantic-parse-labeling-knowledge/) — The Value of Semantic Parse Labeling for Knowledge Base Question Answering