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# Works of Microsoft

193 works · page 2 of 2 · the most cited first · [← Microsoft](https://md.research.elamur.ai/free/en/companies/microsoft/)

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101. [**Want To Reduce Labeling Cost? GPT-3 Can Help**Shuohang Wang, Yang Liu, Yichong Xu, et al.*2021 · 298 citations*](https://md.research.elamur.ai/free/en/papers/wang-2021-want-reduce-labeling-cost-gpt/)
102. [**MathPrompter: Mathematical Reasoning using Large Language Models**Shima Imani, Liang Du, Harsh Shrivastava*2023 · 297 citations*](https://md.research.elamur.ai/free/en/papers/imani-2023-mathprompter-mathematical-reasoning-large-language/)
103. [**OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models**Yuliang Liu, Zhang Li, Mingxin Huang, et al.*2023 · 297 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-ocrbench-hidden-mystery-ocr-large/)
104. [**SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization**Haoming Jiang, Pengcheng He, Weizhu Chen, et al.*2020 · 291 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2020-smart-robust-efficient-fine-tuning/)
105. [**Machine Translation of Arabic Dialects**Rabih Zbib, Erika Malchiodi, Jacob Devlin, et al.*2012 · 285 citations*](https://md.research.elamur.ai/free/en/papers/zbib-2012-machine-translation-arabic-dialects/)
106. [**Fine-grained Fact Verification with Kernel Graph Attention Network**Zhenghao Liu, Chenyan Xiong, Maosong Sun, et al.*2020 · 282 citations*](https://md.research.elamur.ai/free/en/papers/liu-2020-fine-grained-fact-verification-kernel/)
107. [**Generate rather than Retrieve: Large Language Models are Strong Context Generators**Wenhao Yu, Dan Iter, Shuohang Wang, et al.*2022 · 280 citations*](https://md.research.elamur.ai/free/en/papers/yu-2022-generate-rather-than-retrieve-large/)
108. [**Otter: A Multi-Modal Model with In-Context Instruction Tuning**Bo Li, Yuanhan Zhang, Liangyu Chen, et al.*2023 · 279 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-otter-multi-modal-model-context/)
109. [**Text Classification Using Label Names Only: A Language Model Self-Training Approach**Yu Meng, Yunyi Zhang, Jiaxin Huang, et al.*2020 · 274 citations*](https://md.research.elamur.ai/free/en/papers/meng-2020-text-classification-label-names-only/)
110. [**POS Tagging of English-Hindi Code-Mixed Social Media Content**Yogarshi Vyas, Spandana Gella, Jatin Sharma, et al.*2014 · 273 citations*](https://md.research.elamur.ai/free/en/papers/vyas-2014-pos-tagging-english-hindi-code/)
111. [**Learning Discriminative Projections for Text Similarity Measures**Wen-tau Yih, Kristina Toutanova, John C. Platt, et al.*2011 · 273 citations*](https://md.research.elamur.ai/free/en/papers/yih-2011-learning-discriminative-projections-text-similarity/)
112. [**Polyjuice: Generating Counterfactuals for Explaining, Evaluating, and Improving Models**Tongshuang Wu, Marco Tulio Ribeiro, Jeffrey Heer, et al.*2021 · 271 citations*](https://md.research.elamur.ai/free/en/papers/wu-2021-polyjuice-generating-counterfactuals-explaining-evaluating/)
113. [**InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training**Zewen Chi, Li Dong, Furu Wei, et al.*2020 · 269 citations*](https://md.research.elamur.ai/free/en/papers/chi-2020-infoxlm-information-theoretic-framework-cross/)
114. [**Results of WMT22 Metrics Shared Task: Stop Using BLEU – Neural Metrics Are Better and More Robust**Markus Freitag, Ricardo Rei, Nitika Mathur, et al.*2022 · 263 citations*](https://md.research.elamur.ai/free/en/papers/freitag-2022-results-wmt22-metrics-shared-task/)
115. [**DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models**Yung-Sung Chuang, Yujia Xie, Hongyin Luo, et al.*2023 · 261 citations*](https://md.research.elamur.ai/free/en/papers/chuang-2023-dola-decoding-contrasting-layers-improves/)
116. [**Unicoder: A Universal Language Encoder by Pre-training with Multiple Cross-lingual Tasks**Haoyang Huang, Yaobo Liang, Nan Duan, et al.*2019 · 261 citations*](https://md.research.elamur.ai/free/en/papers/huang-2019-unicoder-universal-language-encoder-pre/)
117. [**DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines**Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, et al.*2023 · 261 citations*](https://md.research.elamur.ai/free/en/papers/khattab-2023-dspy-compiling-declarative-language-model/)
118. [**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/)
119. [**Few-shot Natural Language Generation for Task-Oriented Dialog**Baolin Peng, Chenguang Zhu, Chunyuan Li, et al.*2020 · 253 citations*](https://md.research.elamur.ai/free/en/papers/peng-2020-few-shot-natural-language-generation/)
120. [**Why Can GPT Learn In-Context? Language Models Secretly Perform Gradient Descent as Meta-Optimizers**Damai Dai, Yutao Sun, Li Dong, et al.*2023 · 252 citations*](https://md.research.elamur.ai/free/en/papers/dai-2023-why-can-gpt-learn-context/)
121. [**The Curious Case of Hallucinations in Neural Machine Translation**Vikas Raunak, Arul Menezes, Marcin Junczys-Dowmunt*2021 · 240 citations*](https://md.research.elamur.ai/free/en/papers/raunak-2021-curious-case-hallucinations-neural-machine/)
122. [**Humanity's Last Exam**Long Phan, Alice Gatti, Ziwen Han, et al.*2025 · 235 citations*](https://md.research.elamur.ai/free/en/papers/phan-2025-humanity-s-last-exam/)
123. [**A Study of Reinforcement Learning for Neural Machine Translation**Lijun Wu, Fei Tian, Tao Qin, et al.*2018 · 232 citations*](https://md.research.elamur.ai/free/en/papers/wu-2018-study-reinforcement-learning-neural-machine/)
124. [**SemEval-2015 Task 1: Paraphrase and Semantic Similarity in Twitter (PIT)**Wei Xu, Chris Callison-Burch, Bill Dolan*2015 · 230 citations*](https://md.research.elamur.ai/free/en/papers/xu-2015-semeval-2015-task-1-paraphrase/)
125. [**TrustLLM: Trustworthiness in Large Language Models**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 226 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
126. [**Computational Interpretations of the Gricean Maxims in the Generation of Referring Expressions**Robert Dale, Ehud Reiter*1995 · 225 citations*](https://md.research.elamur.ai/free/en/papers/dale-1995-computational-interpretations-gricean-maxims-generation/)
127. [**Microsoft Translator at WMT 2019: Towards Large-Scale Document-Level Neural Machine Translation**Marcin Junczys-Dowmunt*2019 · 222 citations*](https://md.research.elamur.ai/free/en/papers/dowmunt-2019-microsoft-translator-wmt-2019-large/)
128. [**ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving**Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.*2023 · 222 citations*](https://md.research.elamur.ai/free/en/papers/gou-2023-tora-tool-integrated-reasoning-agent/)
129. [**GLUECoS: An Evaluation Benchmark for Code-Switched NLP**Simran Khanuja, Sandipan Dandapat, Anirudh Srinivasan, et al.*2020 · 222 citations*](https://md.research.elamur.ai/free/en/papers/khanuja-2020-gluecos-evaluation-benchmark-code-switched/)
130. [**Reasoning Over Semantic-Level Graph for Fact Checking**Wanjun Zhong, Jingjing Xu, Duyu Tang, et al.*2020 · 221 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2020-reasoning-over-semantic-level-graph/)
131. [**Making Language Models Better Reasoners with Step-Aware Verifier**Yifei Li, Zeqi Lin, Shizhuo Zhang, et al.*2023 · 216 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-making-language-models-better-reasoners/)
132. [**A Global Joint Model for Semantic Role Labeling**Kristina Toutanova, Aria Haghighi, Christopher D. Manning*2008 · 214 citations*](https://md.research.elamur.ai/free/en/papers/toutanova-2008-global-joint-model-semantic-role/)
133. [**Unsupervised Morphological Segmentation with Log-Linear Models**Hoifung Poon, Colin Cherry, Kristina Toutanova*2009 · 210 citations*](https://md.research.elamur.ai/free/en/papers/poon-2009-unsupervised-morphological-segmentation-log-linear/)
134. [**Prompting GPT-3 To Be Reliable**Chenglei Si, Zhe Gan, Zhengyuan Yang, et al.*2022 · 206 citations*](https://md.research.elamur.ai/free/en/papers/si-2022-prompting-gpt-3-reliable/)
135. [**Challenges in Detoxifying Language Models**Johannes Welbl, Amelia Glaese, Jonathan Uesato, et al.*2021 · 206 citations*](https://md.research.elamur.ai/free/en/papers/welbl-2021-challenges-detoxifying-language-models/)
136. [**EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty**Yuhui Li, Fangyun Wei, Chao Zhang, et al.*2024 · 204 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-eagle-speculative-sampling-requires-rethinking/)
137. [**Towards a Unified Multi-Dimensional Evaluator for Text Generation**Ming Zhong, Yang Liu, Da Yin, et al.*2022 · 204 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2022-unified-multi-dimensional-evaluator-text/)
138. [**TinyStories: How Small Can Language Models Be and Still Speak Coherent English?**Ronen Eldan, Yuanzhi Li*2023 · 202 citations*](https://md.research.elamur.ai/free/en/papers/eldan-2023-tinystories-small-language-models-still/)
139. [**Dual Conditional Cross-Entropy Filtering of Noisy Parallel Corpora**Marcin Junczys-Dowmunt*2018 · 200 citations*](https://md.research.elamur.ai/free/en/papers/dowmunt-2018-dual-conditional-cross-entropy-filtering/)
140. [**Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs**Suyu Ge, Yunan Zhang, Liyuan Liu, et al.*2023 · 198 citations*](https://md.research.elamur.ai/free/en/papers/ge-2023-model-tells-discard-adaptive-kv/)
141. [**COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining**Yu Meng, Chenyan Xiong, Payal Bajaj, et al.*2021 · 196 citations*](https://md.research.elamur.ai/free/en/papers/meng-2021-coco-lm-correcting-contrasting-text/)
142. [**Paraphrasing for Style**Wei Xu, Alan Ritter, Bill Dolan, et al.*2012 · 196 citations*](https://md.research.elamur.ai/free/en/papers/xu-2012-paraphrasing-style/)
143. [**GEMBA-MQM: Detecting Translation Quality Error Spans with GPT-4**Tom Kocmi, Christian Federmann*2023 · 191 citations*](https://md.research.elamur.ai/free/en/papers/kocmi-2023-gemba-mqm-detecting-translation-quality/)
144. [**Grounded Conversation Generation as Guided Traverses in Commonsense Knowledge Graphs**Houyu Zhang, Zhenghao Liu, Chenyan Xiong, et al.*2020 · 181 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2020-grounded-conversation-generation-as-guided/)
145. [**Representation Degeneration Problem in Training Natural Language Generation Models**Jun Gao, Di He, Xu Tan, et al.*2019 · 179 citations*](https://md.research.elamur.ai/free/en/papers/gao-2019-representation-degeneration-problem-training-natural/)
146. [**Investigating Cultural Alignment of Large Language Models**Badr AlKhamissi, Muhammad ElNokrashy, Mai Alkhamissi, et al.*2024 · 177 citations*](https://md.research.elamur.ai/free/en/papers/alkhamissi-2024-investigating-cultural-alignment-large-language/)
147. [**Findings of the WMT24 General Machine Translation Shared Task: The LLM Era Is Here but MT Is Not Solved Yet**Tom Kocmi, Eleftherios Avramidis, Rachel Bawden, et al.*2024 · 177 citations*](https://md.research.elamur.ai/free/en/papers/kocmi-2024-findings-wmt24-general-machine-translation/)
148. [**MediaSum: A Large-scale Media Interview Dataset for Dialogue Summarization**Chenguang Zhu, Yang Liu, Jie Mei, et al.*2021 · 176 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2021-mediasum-large-scale-media-interview/)
149. [**Towards Leaving No Indic Language Behind: Building Monolingual Corpora, Benchmark and Models for Indic Languages**Sumanth Doddapaneni, Rahul Aralikatte, Gowtham Ramesh, et al.*2023 · 174 citations*](https://md.research.elamur.ai/free/en/papers/doddapaneni-2023-leaving-no-indic-language-behind/)
150. [**Findings of the WMT 2019 Shared Tasks on Quality Estimation**Erick Fonseca, Lisa Yankovskaya, André F. T. Martins, et al.*2019 · 173 citations*](https://md.research.elamur.ai/free/en/papers/fonseca-2019-findings-wmt-2019-shared-tasks/)
151. [**AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning**Qingru Zhang, Minshuo Chen, Alexander Bukharin, et al.*2023 · 170 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-adalora-adaptive-budget-allocation-parameter/)
152. [**Aligning Large Multimodal Models with Factually Augmented RLHF**Zhiqing Sun, Sheng Shen, Shengcao Cao, et al.*2023 · 168 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-aligning-large-multimodal-models-factually/)
153. [**Structure-Grounded Pretraining for Text-to-SQL**Xiang Deng, Ahmed Hassan Awadallah, Christopher Meek, et al.*2021 · 166 citations*](https://md.research.elamur.ai/free/en/papers/deng-2021-structure-grounded-pretraining-text-sql/)
154. [**Generative Representational Instruction Tuning**Niklas Muennighoff, Hongjin Su, Liang Wang, et al.*2024 · 165 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2024-generative-representational-instruction-tuning/)
155. [**AmericasNLI: Evaluating Zero-shot Natural Language Understanding of Pretrained Multilingual Models in Truly Low-resource Languages**Abteen Ebrahimi, Manuel Mager, Arturo Oncevay, et al.*2022 · 163 citations*](https://md.research.elamur.ai/free/en/papers/ebrahimi-2022-americasnli-evaluating-zero-shot-natural/)
156. [**Impact of Pretraining Term Frequencies on Few-Shot Numerical Reasoning**Yasaman Razeghi, Robert L Logan IV, Matt Gardner, et al.*2022 · 162 citations*](https://md.research.elamur.ai/free/en/papers/razeghi-2022-impact-pretraining-term-frequencies-few/)
157. [**Orca 2: Teaching Small Language Models How to Reason**Arindam Mitra, Luciano Del Corro, Shweti Mahajan, et al.*2023 · 160 citations*](https://md.research.elamur.ai/free/en/papers/mitra-2023-orca-2-teaching-small-language/)
158. [**DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models**Sam Ade Jacobs, Masahiro Tanaka, Chengming Zhang, et al.*2023 · 159 citations*](https://md.research.elamur.ai/free/en/papers/jacobs-2023-deepspeed-ulysses-system-optimizations-enabling/)
159. [**LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression**Zhuoshi Pan, Qianhui Wu, Huiqiang Jiang, et al.*2024 · 159 citations*](https://md.research.elamur.ai/free/en/papers/pan-2024-llmlingua-2-data-distillation-efficient/)
160. [**LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compression**Huiqiang Jiang, Qianhui Wu, Xufang Luo, et al.*2023 · 158 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2023-longllmlingua-accelerating-enhancing-llms-long/)
161. [**Unsupervised Text Style Transfer using Language Models as Discriminators**Zichao Yang, Zhiting Hu, Chris Dyer, et al.*2018 · 157 citations*](https://md.research.elamur.ai/free/en/papers/yang-2018-unsupervised-text-style-transfer-using/)
162. [**A Few Thousand Translations Go a Long Way! Leveraging Pre-trained Models for African News Translation**David Ifeoluwa Adelani, Jesujoba Oluwadara Alabi, Angela Fan, et al.*2022 · 155 citations*](https://md.research.elamur.ai/free/en/papers/adelani-2022-few-thousand-translations-go-long/)
163. [**AnnoLLM: Making Large Language Models to Be Better Crowdsourced Annotators**Xingwei He, Zhenghao Lin, Yeyun Gong, et al.*2023 · 150 citations*](https://md.research.elamur.ai/free/en/papers/he-2023-annollm-making-large-language-models/)
164. [**Generation-Augmented Retrieval for Open-domain Question Answering**Yuning Mao, Pengcheng He, Xiaodong Liu, et al.*2020 · 150 citations*](https://md.research.elamur.ai/free/en/papers/mao-2020-generation-augmented-retrieval-open-domain/)
165. [**Context-faithful Prompting for Large Language Models**Wenxuan Zhou, Sheng Zhang, Hoifung Poon, et al.*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-context-faithful-prompting-large-language/)
166. [**MiniLLM: On-Policy Distillation of Large Language Models**Yuxian Gu, Li Dong, Furu Wei, et al.*2023 · 143 citations*](https://md.research.elamur.ai/free/en/papers/gu-2023-minillm-policy-distillation-large-language/)
167. [**End-to-End Task-Completion Neural Dialogue Systems**Xiujun Li, Yun-Nung Chen, Lihong Li, et al.*2017 · 141 citations*](https://md.research.elamur.ai/free/en/papers/li-2017-end-end-task-completion-neural/)
168. [**A Token-level Reference-free Hallucination Detection Benchmark for Free-form Text Generation**Tianyu Liu, Yizhe Zhang, Chris Brockett, et al.*2022 · 140 citations*](https://md.research.elamur.ai/free/en/papers/liu-2022-token-level-reference-free-hallucination/)
169. [**LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens**Yiran Ding, Li Lyna Zhang, Chengruidong Zhang, et al.*2024 · 138 citations*](https://md.research.elamur.ai/free/en/papers/ding-2024-longrope-extending-llm-context/)
170. [**EAGLE-2: Faster Inference of Language Models with Dynamic Draft Trees**Yuhui Li, Fangyun Wei, Chao Zhang, et al.*2024 · 131 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-eagle-2-faster-inference-language/)
171. [**Toward Gender-Inclusive Coreference Resolution**Yang Trista Cao, Hal Daumé III*2020 · 125 citations*](https://md.research.elamur.ai/free/en/papers/cao-2020-gender-inclusive-coreference-resolution/)
172. [**Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model**Jingcheng Hu, Yinmin Zhang, Qi Han, et al.*2025 · 121 citations*](https://md.research.elamur.ai/free/en/papers/hu-2025-open-reasoner-zero-open-source/)
173. [**Orca-Math: Unlocking the potential of SLMs in Grade School Math**Arindam Mitra, Hamed Khanpour, Corby Rosset, et al.*2024 · 109 citations*](https://md.research.elamur.ai/free/en/papers/mitra-2024-orca-math-unlocking-potential-slms/)
174. [**ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models**Jinheon Baek, Sujay Kumar Jauhar, Silviu Cucerzan, et al.*2024 · 106 citations*](https://md.research.elamur.ai/free/en/papers/baek-2024-researchagent-iterative-research-idea/)
175. [**Are LLMs Breaking MT Metrics? Results of the WMT24 Metrics Shared Task**Markus Freitag, Nitika Mathur, Daniel Deutsch, et al.*2024 · 106 citations*](https://md.research.elamur.ai/free/en/papers/freitag-2024-are-llms-breaking-mt-metrics/)
176. [**NTREX-128 – News Test References for MT Evaluation of 128 Languages**Christian Federmann, Tom Kocmi, Ying Xin*2022 · 104 citations*](https://md.research.elamur.ai/free/en/papers/federmann-2022-ntrex-128-news-test-references/)
177. [**Findings of the WMT 2019 Shared Task on Automatic Post-Editing**Rajen Chatterjee, Christian Federmann, Matteo Negri, et al.*2019 · 102 citations*](https://md.research.elamur.ai/free/en/papers/chatterjee-2019-findings-wmt-2019-shared-task/)
178. [**Chain-of-Dictionary Prompting Elicits Translation in Large Language Models**Hongyuan Lu, Haoran Yang, Haoyang Huang, et al.*2024 · 81 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-chain-dictionary-prompting-elicits-translation/)
179. [**MLQE-PE: A Multilingual Quality Estimation and Post-Editing Dataset**Marina Fomicheva, Shuo Sun, Erick Fonseca, et al.*2022 · 76 citations*](https://md.research.elamur.ai/free/en/papers/fomicheva-2022-mlqe-pe-multilingual-quality-estimation/)
180. [**Findings of the WMT25 General Machine Translation Shared Task: Time to Stop Evaluating on Easy Test Sets**Tom Kocmi, Ekaterina Artemova, Eleftherios Avramidis, et al.*2025 · 73 citations*](https://md.research.elamur.ai/free/en/papers/kocmi-2025-findings-wmt25-general-machine-translation/)
181. [**A global model for joint lemmatization and part-of-speech prediction**Kristina Toutanova, Colin Cherry*2009 · 58 citations*](https://md.research.elamur.ai/free/en/papers/toutanova-2009-global-model-joint-lemmatization-part/)
182. [**Frame Semantic Tree Kernels for Social Network Extraction from Text**Apoorv Agarwal, Sriramkumar Balasubramanian, Anup Kotalwar, et al.*2014 · 40 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2014-frame-semantic-tree-kernels-social/)
183. [**Findings of the Second WMT Shared Task on Sign Language Translation (WMT-SLT23)**Mathias Müller, Malihe Alikhani, Eleftherios Avramidis, et al.*2023 · 39 citations*](https://md.research.elamur.ai/free/en/papers/muller-2023-findings-second-wmt-shared-task/)
184. [**OG-RAG: Ontology-grounded retrieval-augmented generation for large language models**Kartik Sharma, Peeyush Kumar, Yunqing Li*2025 · 37 citations*](https://md.research.elamur.ai/free/en/papers/sharma-2025-og-rag-ontology-grounded-retrieval/)
185. [**Machine Translation Meta Evaluation through Translation Accuracy Challenge Sets**Nikita Moghe, Arnisa Fazla, Chantal Amrhein, et al.*2025 · 28 citations*](https://md.research.elamur.ai/free/en/papers/moghe-2025-machine-translation-meta-evaluation-through/)
186. [**Machine-learned contexts for linguistic operations in German sentence realization**Michael Gamon, Eric Ringger, Simon Corston-Oliver, et al.*2002 · 20 citations*](https://md.research.elamur.ai/free/en/papers/gamon-2002-machine-learned-contexts-linguistic-operations/)
187. [**Syntactic Models for Structural Word Insertion and Deletion during Translation**Arul Menezes, Chris Quirk*2008 · 17 citations*](https://md.research.elamur.ai/free/en/papers/menezes-2008-syntactic-models-structural-word-insertion/)
188. [**Using the Penn Treebank to Evaluate Non-Treebank Parsers**Eric K. Ringger, Robert C. Moore, Eugene Charniak, et al.*2004 · 16 citations*](https://md.research.elamur.ai/free/en/papers/ringger-2004-penn-treebank-evaluate-non-treebank/)
189. [**Joint Universal Syntactic and Semantic Parsing**Elias Stengel-Eskin, Kenton Murray, Sheng Zhang, et al.*2021 · 15 citations*](https://md.research.elamur.ai/free/en/papers/eskin-2021-joint-universal-syntactic-semantic-parsing/)
190. [**Multilingual Coreference Resolution in Multiparty Dialogue**Boyuan Zheng, Patrick Xia, Mahsa Yarmohammadi, et al.*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2023-multilingual-coreference-resolution-multiparty-dialogue/)
191. [**The Persian Dependency Treebank Made Universal**Pegah Safari, Mohammad Sadegh Rasooli, Amirsaeid Moloodi, et al.*2022 · 5 citations*](https://md.research.elamur.ai/free/en/papers/safari-2022-persian-dependency-treebank-made-universal/)
192. [**High quality machine translation using a machine-learned sentence realization component**Martine Smets, Michael Gamon, Jessie Pinkham, et al.*2003 · 3 citations*](https://md.research.elamur.ai/free/en/papers/smets-2003-high-quality-machine-translation-machine/)
193. [**PEAR: Pairwise Evaluation for Automatic Relative Scoring in Machine Translation**Lorenzo Proietti, Roman Grundkiewicz, Matt Post*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/proietti-2026-pear-pairwise-evaluation-automatic-relative/)

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