---
title: "Who cites Kishore Papineni — page 13 — 11,112 citing papers"
description: "11,112 papers of the Elamur Research library cite the works of Kishore Papineni, found in their bibliographies · page 13 of 13 · 1201–1221…"
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# Who cites Kishore Papineni

11,128 citations of their works from 11,112 papers of our library (of the 149,439 whose bibliographies we read) · 1,221 with a page here, the most cited first · page 13 of 13 · 1201–1221 · [← Kishore Papineni](https://md.research.elamur.ai/free/en/authors/kishore-papineni/)

[← prev](https://md.research.elamur.ai/free/en/authors/kishore-papineni/cited-by/page/12/) [1](https://md.research.elamur.ai/free/en/authors/kishore-papineni/cited-by/) … [10](https://md.research.elamur.ai/free/en/authors/kishore-papineni/cited-by/page/10/) [11](https://md.research.elamur.ai/free/en/authors/kishore-papineni/cited-by/page/11/) [12](https://md.research.elamur.ai/free/en/authors/kishore-papineni/cited-by/page/12/) **13**

1201. **[Visual and Memory–Augmented Soccer Commentary Generation](https://md.research.elamur.ai/free/en/papers/sun-2026-visual-memory-augmented-soccer-commentary/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoran Sun, Natthawut Kertkeidkachorn, Kiyoaki Shirai*2026*
1202. **[What Makes a Good Query? Measuring the Impact of Human-Confusing Linguistic Features on LLM Performance](https://md.research.elamur.ai/free/en/papers/watson-2026-what-makes-good-query-measuring/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**William Watson, Nicole Cho, Sumitra Ganesh, et al.*2026*
1203. **[When the Gold Standard Isn't Necessarily Standard: Challenges of Evaluating the Translation of User-Generated Content](https://md.research.elamur.ai/free/en/papers/nishimwe-2026-when-gold-standard-isn-t/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Lydia Nishimwe, Benoît Sagot, Rachel Bawden*2026*
1204. **[Why do Large Language Models Fail in Low-resource Translation? Unraveling the Token Dynamics of Large Language Models for Machine Translation](https://md.research.elamur.ai/free/en/papers/qian-2026-why-do-large-language-models/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Shenbin Qian, Yves Scherrer*2026*
1205. **[ZIP: Quantifying Which Words Matter in Zero-Shot Instructional Prompts](https://md.research.elamur.ai/free/en/papers/sadr-2026-zip-quantifying-which-words-matter/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Nikta Gohari Sadr, Sangmitra Madhusudan, Arash Asgari, et al.*2026*
1206. [**AI-Driven Generation of Old English: A Framework for Low-Resource Languages**Rodrigo Gabriel Salazar Alva, Matias Nunez, Cristian Lopez, et al.*2025*](https://md.research.elamur.ai/free/en/papers/alva-2025-ai-driven-generation-old-english/)
1207. [**Arabic Hate Speech Identification and Masking in Social Media using Deep Learning Models and Pre-trained Models Fine-tuning arXiv:2507.23661**Salam Thabet Doghmash, Motaz Saad*2025*](https://md.research.elamur.ai/free/en/papers/doghmash-2025-arabic-hate-speech-identification-masking/)
1208. [**CourtPressGER: A German Court Decision to Press Release Summarization Dataset arXiv:2512.09434**Sebastian Nagl, Mohamed Elganayni, Melanie Pospisil, et al.*2025*](https://md.research.elamur.ai/free/en/papers/nagl-2025-courtpressger-german-court-decision-press/)
1209. **[Developing A German Document-Level Parallel Dataset For Automatic Text Simplification To Generate Easy Language](https://md.research.elamur.ai/free/en/papers/jiranek-2025-developing-german-document-level-parallel/) [Conference on Natural Language Processing](https://md.research.elamur.ai/free/en/venues/konvens/)**Vivien Jiranek, Stefan Hillmann*2025*
1210. [**Semitic Root Encoding: Tokenization Based on the Templatic Morphology of Semitic Languages in NMT**Brendan T. Hatch, Stephen D. Richardson*2025*](https://md.research.elamur.ai/free/en/papers/hatch-2025-semitic-root-encoding-tokenization-based/)
1211. [**Survey of Tool Use in Large Language Models (大语言模型的工具使用综述) Acta Automatica Sinica (自动化学报)**Yining Zheng (郑逸宁), Zhen Yu (余镇), Bufan Li (李不凡), et al.*2025*](https://md.research.elamur.ai/free/en/papers/zheng-2025-tool-use-large/)
1212. [**Advancing Complex Medical Communication in Arabic with Sporo AraSum: Surpassing Existing Large Language Models arXiv:2411.13518**Chanseo Lee, Sonu Kumar, Kimon A. Vogt, et al.*2024*](https://md.research.elamur.ai/free/en/papers/lee-2024-advancing-complex-medical-communication-arabic/)
1213. [**Generation and Evaluation of English Grammar Multiple-Choice Cloze Exercises**Nicolò Donati, Matteo Periani, Paolo Di Natale, et al.*2024*](https://md.research.elamur.ai/free/en/papers/donati-2024-generation-evaluation-english-grammar-multiple/)
1214. [**Mevaker: Conclusion Extraction and Allocation Resources for the Hebrew Language**Vitaly Shalumov, Harel Haskey, Yuval Solaz*2024*](https://md.research.elamur.ai/free/en/papers/shalumov-2024-mevaker-conclusion-extraction-allocation-resources/)
1215. **[Survey on Document-level Neural Machine Translation (文档级神经机器翻译综述)](https://md.research.elamur.ai/free/en/papers/lv-2024-document-level-neural/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Xinglin Lv (吕星林), Junhui Li (李军辉), Shimin Tao (陶仕敏), et al.*2024*
1216. **[Barch: an English Dataset of Bar Chart Summaries](https://md.research.elamur.ai/free/en/papers/skrjanec-2022-barch-english-dataset-bar-chart/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Iza Škrjanec, Muhammad Salman Edhi, Vera Demberg*2022*
1217. [**Addressing Community Question Answering in English and Arabic arXiv:1610.05522**Giovanni Da San Martino, Alberto Barron-Cedeno, Salvatore Romeo, et al.*2016*](https://md.research.elamur.ai/free/en/papers/martino-2016-addressing-community-question-answering-english/)
1218. [**Enhancing function word translation with syntax-based statistical post-editing**John Richardson, Toshiaki Nakazawa, Sadao Kurohashi*2015*](https://md.research.elamur.ai/free/en/papers/richardson-2015-enhancing-function-word-translation-syntax/)
1219. **[Formal v. Informal: Register-Differentiated Arabic MT Evaluation in the PLATO Paradigm](https://md.research.elamur.ai/free/en/papers/miller-2006-formal-v-informal-register-differentiated/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Keith J. Miller, Michelle Vanni*2006*
1220. [**A trainable transfer-based MT approach for languages with limited resources**Alon Lavie, Katharina Probst, Erik Peterson, et al.*2004*](https://md.research.elamur.ai/free/en/papers/lavie-2004-trainable-transfer-based-mt-approach/)
1221. [**Czech-English Dependency Tree-based Machine Translation**Martin Čmejrek, Jan Cuřín, Jiří Havelka*2003*](https://md.research.elamur.ai/free/en/papers/cmejrek-2003-czech-english-dependency-tree-based/)

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