--- title: "Charlotte — research institutions and their papers in our library" description: "Charlotte (United States): 1 institutions with papers on Elamur Research — 1 university — and 494 citations of their works." canonical: "https://research.elamur.ai/free/en/agglomerations/charlotte/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/agglomerations/charlotte/) [home](https://md.research.elamur.ai/free/en/) / [institutions](https://md.research.elamur.ai/free/en/orgs/) / [agglomerations](https://md.research.elamur.ai/free/en/agglomerations/) / Charlotte # Charlotte Agglomeration [United States](https://md.research.elamur.ai/free/en/countries/united-states/) · metro population 2,020,478 (functional urban area, GHSL 2015) **1** institution with a page**8** works in our library**494** citations of their works ## Institutions (1) 1 university. ### 🎓 Universities (1) 1. **[University of North Carolina at Charlotte](https://md.research.elamur.ai/free/en/universities/university-of-north-carolina-at-charlotte/)**University · Charlotte, [United States](https://md.research.elamur.ai/free/en/countries/united-states/)*8 works · 494 citations* ## Works in our library (8) Works of its institutions, the most cited first. 1. **[The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics](https://md.research.elamur.ai/free/en/papers/gehrmann-2021-gem-benchmark-natural-language-generation/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Sebastian Gehrmann, Tosin Adewumi, Karmanya Aggarwal, et al.*2021 · 369 citations* 2. **[TeamUNCC at SemEval-2018 Task 1: Emotion Detection in English and Arabic Tweets using Deep Learning](https://md.research.elamur.ai/free/en/papers/abdullah-2018-teamuncc-semeval-2018-task-1/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Malak Abdullah, Samira Shaikh*2018 · 68 citations* 3. [**Can Language Models Employ the Socratic Method? Experiments with Code Debugging arXiv:2310.03210**Erfan Al-Hossami, Razvan Bunescu, Justin Smith, et al.*2023 · 38 citations*](https://md.research.elamur.ai/free/en/papers/al-hossami-2023-language-models-employ-socratic-method/) 4. **[FaithLM: Towards Faithful Explanations for Large Language Models](https://md.research.elamur.ai/free/en/papers/chuang-2026-faithlm-faithful-explanations-large-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yu-Neng Chuang, Guanchu Wang, Chia-Yuan Chang, et al.*2026 · 9 citations* 5. **[AutoL2S: Auto Long-Short Reasoning for Efficient Large Language Models](https://md.research.elamur.ai/free/en/papers/luo-2026-autol2s-auto-long-short-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Feng Luo, Yu-Neng Chuang, Guanchu Wang, et al.*2026 · 7 citations* 6. **[Improving Dialogue Act Recognition with Augmented Data](https://md.research.elamur.ai/free/en/papers/mahajan-2022-improving-dialogue-act-recognition-augmented/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Khyati Mahajan, Soham Parikh, Quaizar Vohra, et al.*2022 · 2 citations* 7. **[From Local to Global: Revisiting Structured Pruning Paradigms for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-local-global-revisiting-structured-pruning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziyan Wang, Enmao Diao, Qi Le, et al.*2026 · 1 citation* 8. **[HyperEdit: Unlocking Instruction-based Text Editing in LLMs via Hypernetworks](https://md.research.elamur.ai/free/en/papers/zeng-2026-hyperedit-unlocking-instruction-based-text/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yiming Zeng, Jinghan Cao, Zexin Li, et al.*2026* ## Works by year ### 2020s [**2026** 4 papers](https://md.research.elamur.ai/free/en/agglomerations/charlotte/year/2026/) · [**2023** 1 paper](https://md.research.elamur.ai/free/en/agglomerations/charlotte/year/2023/) · [**2022** 1 paper](https://md.research.elamur.ai/free/en/agglomerations/charlotte/year/2022/) · [**2021** 1 paper](https://md.research.elamur.ai/free/en/agglomerations/charlotte/year/2021/) ### 2010s [**2018** 1 paper](https://md.research.elamur.ai/free/en/agglomerations/charlotte/year/2018/) ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 10 The field of science this work belongs to (OpenAlex fields).[Computer Science · 8 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 8 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 6 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Language and Linguistics · 6 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/) · [Experimental and Cognitive Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/experimental-and-cognitive-psychology/) · [Social Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/social-psychology/) · [Information Systems · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Computer Science Applications · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-science-applications/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) 🧭 Topics 10 Research subjects and languages the work is about.[Language models & pretraining · 5 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Text generation · 1 work](https://md.research.elamur.ai/free/en/topics/text-generation/) · [English · 1 work](https://md.research.elamur.ai/free/en/topics/english/) · [Semitic languages · 1 work](https://md.research.elamur.ai/free/en/topics/semitic-languages/) · [Sentiment & emotion · 1 work](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Dialogue systems · 1 work](https://md.research.elamur.ai/free/en/topics/dialogue-systems/) · [Speech act theory · 1 work](https://md.research.elamur.ai/free/en/topics/speech-act-theory/) · [Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/) Agglomerations: the GHSL Urban Centre Database 2025; populations: the GHSL functional urban areas 2015 (urban centre and commuting zone), else the urban centre, as each page says (European Commission, Joint Research Centre, CC BY 4.0). An institution belongs to the urban centre its coordinates (ROR, OpenAlex) fall in, or one within 5 km. Land: Natural Earth. - [← back to](https://md.research.elamur.ai/free/en/countries/united-states/) — United States Updated 2 November 2026