--- title: "Who cites Thomas Müller — 399 papers of our library" description: "399 papers of the Elamur Research library cite the works of Thomas Müller, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/thomas-muller/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/thomas-muller/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Thomas Müller](https://md.research.elamur.ai/free/en/authors/thomas-muller/) / cited by # Who cites Thomas Müller 487 citations of their works from 399 papers of our library (of the 141,840 whose bibliographies we read) · 31 with a page here, the most cited first · [← Thomas Müller](https://md.research.elamur.ai/free/en/authors/thomas-muller/) 1. [**Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models arXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5Bvosj**Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.*2022 · 1,703 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2022-imitation-game-quantifying-extrapolating-capabilities/) 2. [**A Survey of Data Augmentation Approaches for NLP arXiv:2105.03075**Steven Y. Feng, Varun Gangal, Jason Wei, et al.*2021 · 937 citations*](https://md.research.elamur.ai/free/en/papers/feng-2021-survey-data-augmentation-approaches-nlp/) **[ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning](https://md.research.elamur.ai/free/en/papers/masry-2022-chartqa-benchmark-question-answering-about/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ahmed Masry, Do Xuan Long, Jia Qing Tan, et al.*2022 · 745 citations* **[A Survey on Automated Fact-Checking](https://md.research.elamur.ai/free/en/papers/guo-2022-survey-automated-fact-checking/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Zhijiang Guo, Michael Schlichtkrull, Andreas Vlachos*2022 · 646 citations* [**75 Languages, 1 Model: Parsing Universal Dependencies Universally**Dan Kondratyuk, Milan Straka*2019 · 414 citations*](https://md.research.elamur.ai/free/en/papers/kondratyuk-2019-75-languages-1-model-parsing/) **[UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models](https://md.research.elamur.ai/free/en/papers/xie-2022-unifiedskg-unifying-multi-tasking-structured/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tianbao Xie, Chen Henry Wu, Peng Shi, et al.*2022 · 406 citations* **[DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correction](https://md.research.elamur.ai/free/en/papers/pourreza-2023-din-sql-decomposed-context-learning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Mohammadreza Pourreza, Davood Rafiei*2023 · 398 citations* **[TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Finance](https://md.research.elamur.ai/free/en/papers/zhu-2021-tat-qa-question-answering-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fengbin Zhu, Wenqiang Lei, Youcheng Huang, et al.*2021 · 397 citations* **[Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology](https://md.research.elamur.ai/free/en/papers/zmigrod-2019-counterfactual-data-augmentation-mitigating-gender/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ran Zmigrod, Sabrina J. Mielke, Hanna Wallach, et al.*2019 · 372 citations* **[Bridging Textual and Tabular Data for Cross-Domain Text-to-SQL Semantic Parsing](https://md.research.elamur.ai/free/en/papers/lin-2020-bridging-textual-tabular-data-cross/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xi Victoria Lin, Richard Socher, Caiming Xiong*2020 · 261 citations* [**TAPEX: Table Pre-training via Learning a Neural SQL Executor arXiv:2107.07653**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/) **[TABBIE: Pretrained Representations of Tabular Data](https://md.research.elamur.ai/free/en/papers/iida-2021-tabbie-pretrained-representations-tabular-data/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Hiroshi Iida, Dung Thai, Varun Manjunatha, et al.*2021 · 186 citations* **[Large Language Models are few(1)-shot Table Reasoners](https://md.research.elamur.ai/free/en/papers/chen-2023-large-language-models-are-few/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenhu Chen*2023 · 182 citations* **[KGPT: Knowledge-Grounded Pre-Training for Data-to-Text Generation](https://md.research.elamur.ai/free/en/papers/chen-2020-kgpt-knowledge-grounded-pre-training/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wenhu Chen, Yu Su, Xifeng Yan, et al.*2020 · 174 citations* [**Binding Language Models in Symbolic Languages arXiv:2210.02875**Zhoujun Cheng, Tianbao Xie, Peng Shi, et al.*2022 · 167 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2022-binding-language-models-symbolic-languages/) **[Structure-Grounded Pretraining for Text-to-SQL](https://md.research.elamur.ai/free/en/papers/deng-2021-structure-grounded-pretraining-text-sql/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Xiang Deng, Ahmed Hassan Awadallah, Christopher Meek, et al.*2021 · 166 citations* **[Understanding tables with intermediate pre-training](https://md.research.elamur.ai/free/en/papers/eisenschlos-2020-understanding-tables-intermediate-pre-training/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Julian Eisenschlos, Syrine Krichene, Thomas Müller*2020 · 158 citations* **[Open Domain Question Answering over Tables via Dense Retrieval](https://md.research.elamur.ai/free/en/papers/herzig-2021-open-domain-question-answering-over/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jonathan Herzig, Thomas Müller, Syrine Krichene, et al.*2021 · 133 citations* **[MultiHiertt: Numerical Reasoning over Multi Hierarchical Tabular and Textual Data](https://md.research.elamur.ai/free/en/papers/zhao-2022-multihiertt-numerical-reasoning-over-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yilun Zhao, Yunxiang Li, Chenying Li, et al.*2022 · 128 citations* **[DePlot: One-shot visual language reasoning by plot-to-table translation](https://md.research.elamur.ai/free/en/papers/liu-2023-deplot-one-shot-visual-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fangyu Liu, Julian Eisenschlos, Francesco Piccinno, et al.*2023 · 121 citations* **[UniChart: A Universal Vision-language Pretrained Model for Chart Comprehension and Reasoning](https://md.research.elamur.ai/free/en/papers/masry-2023-unichart-universal-vision-language-pretrained/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ahmed Masry, Parsa Kavehzadeh, Xuan Long Do, et al.*2023 · 119 citations* [**Joint Diacritization, Lemmatization, Normalization, and Fine-Grained Morphological Tagging**Nasser Zalmout, Nizar Habash*2020 · 44 citations*](https://md.research.elamur.ai/free/en/papers/zalmout-2020-joint-diacritization-lemmatization-normalization-fine/) [**A Simple Joint Model for Improved Contextual Neural Lemmatization**Chaitanya Malaviya, Shijie Wu, Ryan Cotterell*2019 · 39 citations*](https://md.research.elamur.ai/free/en/papers/malaviya-2019-simple-joint-model-improved-contextual/) **[Exploring the Numerical Reasoning Capabilities of Language Models: A Comprehensive Analysis on Tabular Data](https://md.research.elamur.ai/free/en/papers/akhtar-2023-exploring-numerical-reasoning-capabilities-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mubashara Akhtar, Abhilash Shankarampeta, Vivek Gupta, et al.*2023 · 38 citations* [**A Rich Morphological Tagger for English: Exploring the Cross-Linguistic Tradeoff Between Morphology and Syntax**Christo Kirov, John Sylak-Glassman, Rebecca Knowles, et al.*2017 · 21 citations*](https://md.research.elamur.ai/free/en/papers/kirov-2017-rich-morphological-tagger-english-exploring/) [**Lemmatization and POS-tagging process by using joint learning approach. Experimental results on Classical Armenian, Old Georgian, and Syriac**Chahan Vidal-Gorène, Bastien Kindt*2020 · 14 citations*](https://md.research.elamur.ai/free/en/papers/gorene-2020-lemmatization-pos-tagging-process-joint/) [**Neural Lemmatization of Multiword Expressions**Marine Schmitt, Mathieu Constant*2019 · 4 citations*](https://md.research.elamur.ai/free/en/papers/schmitt-2019-neural-lemmatization-multiword-expressions/) [**Lemmatization as a Classification Task: Results from Arabic across Multiple Genres**Mostafa Saeed, Nizar Habash*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/saeed-2025-lemmatization-as-classification-task-results/) [**Allen Institute for AI @ SIGTYP 2024 Shared Task on Word Embedding Evaluation for Ancient and Historical Languages**Lester James V. Miranda*2024 · 1 citation*](https://md.research.elamur.ai/free/en/papers/miranda-2024-allen-institute-ai-sigtyp-2024/) **[Questionnaire Meets LLM: A Benchmark and Empirical Study of Structural Skills for Understanding Questions and Responses](https://md.research.elamur.ai/free/en/papers/nguyen-2026-questionnaire-meets-llm-benchmark-empirical/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Duc-Hai Nguyen, Vijayakumar Nanjappan, Barry O'Sullivan, et al.*2026* **[The UD-NewsCrawl Treebank: Reflections and Challenges from a Large-scale Tagalog Syntactic Annotation Project](https://md.research.elamur.ai/free/en/papers/aquino-2025-ud-newscrawl-treebank-reflections-challenges/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Angelina Aspra Aquino, Lester James Validad Miranda, Elsie Marie T. Or*2025* 368 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/thomas-muller/) — Thomas Müller