--- title: "Computer Networks and Communications — papers" description: "Computer Networks and Communications: 19 papers of the Elamur Research library, the most cited first — our summary of each, its ideas…" canonical: "https://research.elamur.ai/free/en/shelves/computer-science/computer-networks-and-communications/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/shelves/computer-science/computer-networks-and-communications/) [home](https://md.research.elamur.ai/free/en/) / [shelves](https://md.research.elamur.ai/free/en/shelves/) / [Computer Science](https://md.research.elamur.ai/free/en/shelves/computer-science/) / Computer Networks and Communications # 🌐 Computer Networks and Communications 19 papers · the most cited first · [all shelves](https://md.research.elamur.ai/free/en/shelves/) Computer Networks and Communications is a subfield of Computer Science in the OpenAlex classification of science. The topics most of its papers here are on: «Advanced Database Systems and Queries», «Constraint Satisfaction and Optimization», «Distributed Control Multi-Agent Systems». ## Papers (19) 1. [**Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation**Dawei Gao, Haibin Wang, Yaliang Li, et al.*2023 · 461 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-text-sql-empowered-large-language/) 2. [**The Faiss library**Matthijs Douze, Alexandr Guzhva, Chengqi Deng, et al.*2024 · 442 citations*](https://md.research.elamur.ai/free/en/papers/douze-2024-faiss-library/) 3. [**Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs**Jinyang Li, Binyuan Hui, Ge Qu, et al.*2023 · 421 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-llm-already-serve-database-interface/) 4. [**DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correction**Mohammadreza Pourreza, Davood Rafiei*2023 · 398 citations*](https://md.research.elamur.ai/free/en/papers/pourreza-2023-din-sql-decomposed-context-learning/) 5. [**RESDSQL: Decoupling Schema Linking and Skeleton Parsing for Text-to-SQL**Haoyang Li, Jing Zhang, Cuiping Li, et al.*2023 · 277 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-resdsql-decoupling-schema-linking-skeleton/) 6. [**Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing**Ben Bogin, Jonathan Berant, Matt Gardner*2019 · 272 citations*](https://md.research.elamur.ai/free/en/papers/bogin-2019-representing-schema-structure-graph-neural/) 7. [**Bridging Textual and Tabular Data for Cross-Domain Text-to-SQL Semantic Parsing**Xi Victoria Lin, Richard Socher, Caiming Xiong*2020 · 261 citations*](https://md.research.elamur.ai/free/en/papers/lin-2020-bridging-textual-tabular-data-cross/) 8. [**TAPEX: Table Pre-training via Learning a Neural SQL Executor**Qian Liu, Bei Chen, Jiaqi Guo, et al.*2021 · 254 citations*](https://md.research.elamur.ai/free/en/papers/liu-2021-tapex-table-pre-training-learning/) 9. [**AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors**Weize Chen, Yusheng Su, Jingwei Zuo, et al.*2023 · 210 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-agentverse-facilitating-multi-agent/) 10. [**Mesh-TensorFlow: Deep Learning for Supercomputers**Noam Shazeer, Youlong Cheng, Niki Parmar, et al.*2018 · 186 citations*](https://md.research.elamur.ai/free/en/papers/shazeer-2018-mesh-tensorflow-deep-learning-supercomputers/) 11. [**RYANSQL: Recursively Applying Sketch-based Slot Fillings for Complex Text-to-SQL in Cross-Domain Databases**DongHyun Choi, Myeong Cheol Shin, EungGyun Kim, et al.*2021 · 156 citations*](https://md.research.elamur.ai/free/en/papers/choi-2021-ryansql-recursively-applying-sketch-based/) 12. [**Self-Evaluation Guided Beam Search for Reasoning**Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, et al.*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/xie-2023-self-evaluation-guided-beam-search/) 13. [**Iterative Reasoning Preference Optimization**Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, et al.*2024 · 144 citations*](https://md.research.elamur.ai/free/en/papers/pang-2024-iterative-reasoning-preference-optimization/) 14. [**A comprehensive evaluation of ChatGPT's zero-shot Text-to-SQL capability**Aiwei Liu, Xuming Hu, Lijie Wen, et al.*2023 · 127 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-comprehensive-evaluation-chatgpt-s-zero/) 15. [**MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQL**Bing Wang, Changyu Ren, Jian Yang, et al.*2025 · 67 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-mac-sql-multi-agent-collaborative/) 16. [**DuSQL: A Large-Scale and Pragmatic Chinese Text-to-SQL Dataset**Lijie Wang, Ao Zhang, Kun Wu, et al.*2020 · 64 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-dusql-large-scale-pragmatic-chinese/) 17. [**Generating English Paraphrases From Formal Relational Calculus Expressions**A.N. De Roeck, B.G.T. Lowden*1986 · 14 citations*](https://md.research.elamur.ai/free/en/papers/roeck-1986-generating-english-paraphrases-formal-relational/) 18. [**Ar-Spider: Text-to-SQL in Arabic**Saleh Almohaimeed, Saad Almohaimeed, Mansour Al Ghanim, et al.*2024 · 13 citations*](https://md.research.elamur.ai/free/en/papers/almohaimeed-2024-ar-spider-text-sql-arabic/) 19. [**Optimization in Coreference Resolution is not Needed: A Nearly-Optimal Algorithm with Intensional Constraints**Manfred Klenner, Étienne Ailloud*2009 · 5 citations*](https://md.research.elamur.ai/free/en/papers/klenner-2009-optimization-coreference-resolution-is-not/) Updated 24 October 2026 - [← previous subfield Computer Graphics and Computer-Aided Design](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-graphics-and-computer-aided-design/) - [next subfield → Computer Science Applications](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-science-applications/) - [↑ back to Computer Science](https://md.research.elamur.ai/free/en/shelves/computer-science/)