---
title: "Who cites Hua Ren Wu — page 2 — 2,904 papers of our library"
description: "2,904 papers of the Elamur Research library cite the works of Hua Ren Wu, found in their bibliographies · page 2 of 5 · 101–200; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/hua-ren-wu/cited-by/page/2/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/hua-ren-wu/cited-by/page/2/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Hua Ren Wu](https://md.research.elamur.ai/free/en/authors/hua-ren-wu/) / [cited by](https://md.research.elamur.ai/free/en/authors/hua-ren-wu/cited-by/) / page 2

# Who cites Hua Ren Wu

3,374 citations of their works from 2,904 papers of our library (of the 149,439 whose bibliographies we read) · 436 with a page here, the most cited first · page 2 of 5 · 101–200 · [← Hua Ren Wu](https://md.research.elamur.ai/free/en/authors/hua-ren-wu/)

[← prev](https://md.research.elamur.ai/free/en/authors/hua-ren-wu/cited-by/) [1](https://md.research.elamur.ai/free/en/authors/hua-ren-wu/cited-by/) **2** [3](https://md.research.elamur.ai/free/en/authors/hua-ren-wu/cited-by/page/3/) [4](https://md.research.elamur.ai/free/en/authors/hua-ren-wu/cited-by/page/4/) [5](https://md.research.elamur.ai/free/en/authors/hua-ren-wu/cited-by/page/5/) [next →](https://md.research.elamur.ai/free/en/authors/hua-ren-wu/cited-by/page/3/)

101. **[A Survey of Domain Adaptation for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/chu-2018-survey-domain-adaptation-neural-machine/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Chenhui Chu, Rui Wang*2018 · 308 citations*
102. [**Retrieval-Augmented Generation for AI-Generated Content: A Survey arXiv:2402.19473**Penghao Zhao, Hailin Zhang, Qinhan Yu, et al.*2024 · 301 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2024-retrieval-augmented-generation-ai-generated/)
103. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 301 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
104. **[Scalable Multi-Hop Relational Reasoning for Knowledge-Aware Question Answering](https://md.research.elamur.ai/free/en/papers/feng-2020-scalable-multi-hop-relational-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yanlin Feng, Xinyue Chen, Bill Yuchen Lin, et al.*2020 · 300 citations*
105. **[Bridging the Gap between Training and Inference for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/zhang-2019-bridging-gap-between-training-inference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wen Zhang, Yang Feng, Fandong Meng, et al.*2019 · 299 citations*
106. **[Copied Monolingual Data Improves Low-Resource Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/currey-2017-copied-monolingual-data-improves-low/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Anna Currey, Antonio Valerio Miceli Barone, Kenneth Heafield*2017 · 298 citations*
107. **[Learning Joint Multilingual Sentence Representations with Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/schwenk-2017-learning-joint-multilingual-sentence-representations/) [Workshop on Representation Learning for NLP](https://md.research.elamur.ai/free/en/venues/repl4nlp/)**Holger Schwenk, Matthijs Douze*2017 · 295 citations*
108. **[Exploiting Cross-Sentence Context for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/wang-2017-exploiting-cross-sentence-context-neural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Longyue Wang, Zhaopeng Tu, Andy Way, et al.*2017 · 293 citations*
109. **[Text Classification via Large Language Models](https://md.research.elamur.ai/free/en/papers/sun-2023-text-classification-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaofei Sun, Xiaoya Li, Jiwei Li, et al.*2023 · 292 citations*
110. **[Ranking Sentences for Extractive Summarization with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/narayan-2018-ranking-sentences-extractive-summarization-reinforcement/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Shashi Narayan, Shay B. Cohen, Mirella Lapata*2018 · 290 citations*
111. **[Variational Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/zhang-2016-variational-neural-machine-translation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Biao Zhang, Deyi Xiong, Jinsong Su, et al.*2016 · 283 citations*
112. [**Generate rather than Retrieve: Large Language Models are Strong Context Generators arXiv:2209.10063**Wenhao Yu, Dan Iter, Shuohang Wang, et al.*2022 · 281 citations*](https://md.research.elamur.ai/free/en/papers/yu-2022-generate-rather-than-retrieve-large/)
113. **[XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation](https://md.research.elamur.ai/free/en/papers/ruder-2021-xtreme-r-more-challenging-nuanced/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sebastian Ruder, Noah Constant, Jan Botha, et al.*2021 · 281 citations*
114. [**Large Dual Encoders Are Generalizable Retrievers arXiv:2112.07899**Jianmo Ni, Chen Qu, Jing Lu, et al.*2021 · 280 citations*](https://md.research.elamur.ai/free/en/papers/ni-2021-large-dual-encoders-generalizable-retrievers/)
115. [**ChatIE: Zero-Shot Information Extraction via Chatting with ChatGPT arXiv:2302.10205**Xiang Wei; Xingyu Cui; Ning Cheng; Xiaobin Wang; Xin Zhang; Shen Huang; Pengjun Xie; Jinan Xu; Yufeng Chen; Meishan Zhang; Yong Jiang;, Wenjuan Han*2023 · 276 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-chatie-zero-shot-information-extraction/)
116. **[ConveRT: Efficient and Accurate Conversational Representations from Transformers](https://md.research.elamur.ai/free/en/papers/henderson-2020-convert-efficient-accurate-conversational-representations/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Matthew Henderson, Iñigo Casanueva, Nikola Mrkšić, et al.*2020 · 269 citations*
117. [**BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models NeurIPS 2021 Datasets and Benchmarks**Nandan Thakur, Nils Reimers, Andreas Rücklé, et al.*2021 · 265 citations*](https://md.research.elamur.ai/free/en/papers/thakur-2021-beir-heterogenous-benchmark-zero/)
118. **[Condenser: a Pre-training Architecture for Dense Retrieval](https://md.research.elamur.ai/free/en/papers/gao-2021-condenser-pre-training-architecture-dense/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Luyu Gao, Jamie Callan*2021 · 261 citations*
119. **[Automatic Machine Translation Evaluation in Many Languages via Zero-Shot Paraphrasing](https://md.research.elamur.ai/free/en/papers/thompson-2020-automatic-machine-translation-evaluation-many/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Brian Thompson, Matt Post*2020 · 260 citations*
120. **[Fairseq S2T: Fast Speech-to-Text Modeling with Fairseq](https://md.research.elamur.ai/free/en/papers/wang-2020-fairseq-s2t-fast-speech-text/) [Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL)](https://md.research.elamur.ai/free/en/venues/aacl/)**Changhan Wang, Yun Tang, Xutai Ma, et al.*2020 · 259 citations*
121. **[Fine-Tuning LLaMA for Multi-Stage Text Retrieval](https://md.research.elamur.ai/free/en/papers/ma-2023-fine-tuning-llama-multi-stage/) [International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)](https://md.research.elamur.ai/free/en/venues/international-acm-sigir-conference-on-research-and-development-in-information/)**Xueguang Ma, Liang Wang, Nan Yang, et al.*2023 · 257 citations*
122. **[Contrastive Learning for Many-to-many Multilingual Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/pan-2021-contrastive-learning-many-many-multilingual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiao Pan, Mingxuan Wang, Liwei Wu, et al.*2021 · 256 citations*
123. **[RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-ranking](https://md.research.elamur.ai/free/en/papers/ren-2021-rocketqav2-joint-training-method-dense/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ruiyang Ren, Yingqi Qu, Jing Liu, et al.*2021 · 256 citations*
124. **[An Empirical Survey of Data Augmentation for Limited Data Learning in NLP](https://md.research.elamur.ai/free/en/papers/chen-2023-empirical-survey-data-augmentation-limited/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jiaao Chen, Derek Tam, Colin Raffel, et al.*2023 · 254 citations*
125. **[Survey of Low-Resource Machine Translation](https://md.research.elamur.ai/free/en/papers/haddow-2022-survey-low-resource-machine-translation/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Barry Haddow, Rachel Bawden, Antonio Valerio Miceli Barone, et al.*2022 · 251 citations*
126. **[Knowledge-Grounded Dialogue Generation with Pre-trained Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2020-knowledge-grounded-dialogue-generation-pre/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xueliang Zhao, Wei Wu, Can Xu, et al.*2020 · 246 citations*
127. [**CLUE: A Chinese Language Understanding Evaluation Benchmark arXiv:2004.05986**Liang Xu, Hai Hu, Xuanwei Zhang, et al.*2020 · 244 citations*](https://md.research.elamur.ai/free/en/papers/xu-2020-clue-chinese-language-understanding/)
128. **[Classical Structured Prediction Losses for Sequence to Sequence Learning](https://md.research.elamur.ai/free/en/papers/edunov-2018-classical-structured-prediction-losses-sequence/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Sergey Edunov, Myle Ott, Michael Auli, et al.*2018 · 243 citations*
129. **[Towards Robust Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/cheng-2018-robust-neural-machine-translation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yong Cheng, Zhaopeng Tu, Fandong Meng, et al.*2018 · 238 citations*
130. **[mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval](https://md.research.elamur.ai/free/en/papers/zhang-2024-mgte-generalized-long-context-text/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xin Zhang, Yanzhao Zhang, Dingkun Long, et al.*2024 · 237 citations*
131. **[From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood](https://md.research.elamur.ai/free/en/papers/guu-2017-language-programs-bridging-reinforcement-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kelvin Guu, Panupong Pasupat, Evan Liu, et al.*2017 · 236 citations*
132. **[SemEval-2022 Task 5: Multimedia Automatic Misogyny Identification](https://md.research.elamur.ai/free/en/papers/fersini-2022-semeval-2022-task-5-multimedia/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Elisabetta Fersini, Francesca Gasparini, Giulia Rizzi, et al.*2022 · 234 citations*
133. **[A Study of Reinforcement Learning for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/wu-2018-study-reinforcement-learning-neural-machine/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Lijun Wu, Fei Tian, Tao Qin, et al.*2018 · 234 citations*
134. **[Evaluating Open-Domain Question Answering in the Era of Large Language Models](https://md.research.elamur.ai/free/en/papers/kamalloo-2023-evaluating-open-domain-question-answering/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ehsan Kamalloo, Nouha Dziri, Charles Clarke, et al.*2023 · 233 citations*
135. [**Gradient Surgery for Multi-Task Learning arXiv:2001.06782**Tianhe Yu, Saurabh Kumar, Abhishek Gupta, et al.*2020 · 233 citations*](https://md.research.elamur.ai/free/en/papers/yu-2020-gradient-surgery-multi-task-learning/)
136. **[Towards Conversational Recommendation over Multi-Type Dialogs](https://md.research.elamur.ai/free/en/papers/liu-2020-conversational-recommendation-over-multi-type/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zeming Liu, Haifeng Wang, Zheng-Yu Niu, et al.*2020 · 230 citations*
137. [**Not All Languages Are Created Equal in LLMs: Improving Multilingual Capability by Cross-Lingual-Thought Prompting arXiv:2305.07004**Haoyang Huang, Tianyi Tang, Dongdong Zhang, et al.*2023 · 224 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-all-languages-created-equal-llms/)
138. **[Beyond BLEU: Training Neural Machine Translation with Semantic Similarity](https://md.research.elamur.ai/free/en/papers/wieting-2019-beyond-bleu-training-neural-machine/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**John Wieting, Taylor Berg-Kirkpatrick, Kevin Gimpel, et al.*2019 · 223 citations*
139. [**Correcting Length Bias in Neural Machine Translation arXiv:1808.10006**Kenton Murray, David Chiang*2018 · 221 citations*](https://md.research.elamur.ai/free/en/papers/murray-2018-correcting-length-bias-neural-machine/)
140. **[Multilingual Translation from Denoising Pre-Training](https://md.research.elamur.ai/free/en/papers/tang-2021-multilingual-translation-denoising-pre-training/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuqing Tang, Chau Tran, Xian Li, et al.*2021 · 220 citations*
141. **[Incorporating Global Visual Features into Attention-Based Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/calixto-2017-incorporating-global-visual-features-attention/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Iacer Calixto, Qun Liu, Nick Campbell*2017 · 217 citations*
142. [**LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders arXiv:2404.05961**Parishad BehnamGhader, Vaibhav Adlakha, Marius Mosbach, et al.*2024 · 213 citations*](https://md.research.elamur.ai/free/en/papers/behnamghader-2024-llm2vec-large-language-models-secretly/)
143. **[Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!](https://md.research.elamur.ai/free/en/papers/ma-2023-large-language-model-is-not/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yubo Ma, Yixin Cao, Yong Hong, et al.*2023 · 212 citations*
144. **[CharacterBERT: Reconciling ELMo and BERT for Word-Level Open-Vocabulary Representations From Characters](https://md.research.elamur.ai/free/en/papers/boukkouri-2020-characterbert-reconciling-elmo-bert-word/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Hicham El Boukkouri, Olivier Ferret, Thomas Lavergne, et al.*2020 · 206 citations*
145. **[On Exposure Bias, Hallucination and Domain Shift in Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/wang-2020-exposure-bias-hallucination-domain-shift/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chaojun Wang, Rico Sennrich*2020 · 206 citations*
146. **[Contextual Parameter Generation for Universal Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/platanios-2018-contextual-parameter-generation-universal-neural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Emmanouil Antonios Platanios, Mrinmaya Sachan, Graham Neubig, et al.*2018 · 206 citations*
147. **[Nematus: a Toolkit for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/sennrich-2017-nematus-toolkit-neural-machine-translation/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Rico Sennrich, Orhan Firat, Kyunghyun Cho, et al.*2017 · 206 citations*
148. **[PRIMERA: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization](https://md.research.elamur.ai/free/en/papers/xiao-2022-primera-pyramid-based-masked-sentence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wen Xiao, Iz Beltagy, Giuseppe Carenini, et al.*2022 · 205 citations*
149. **[A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-safety-trustworthiness-large-language/) [Artificial Intelligence Review](https://md.research.elamur.ai/free/en/venues/artificial-intelligence-review/)**Xiaowei Huang, Wenjie Ruan, Wei Huang, et al.*2023 · 199 citations*
150. [**InstructUIE: Multi-task Instruction Tuning for Unified Information Extraction arXiv:2304.08085**Xiao Wang, Weikang Zhou, Can Zu, et al.*2023 · 194 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-instructuie-multi-task-instruction-tuning/)
151. **[MuTual: A Dataset for Multi-Turn Dialogue Reasoning](https://md.research.elamur.ai/free/en/papers/cui-2020-mutual-dataset-multi-turn-dialogue/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Leyang Cui, Yu Wu, Shujie Liu, et al.*2020 · 190 citations*
152. **[GLiNER: Generalist Model for Named Entity Recognition using Bidirectional Transformer](https://md.research.elamur.ai/free/en/papers/zaratiana-2024-gliner-generalist-model-named-entity/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Urchade Zaratiana, Nadi Tomeh, Pierre Holat, et al.*2024 · 189 citations*
153. **[Packed Levitated Marker for Entity and Relation Extraction](https://md.research.elamur.ai/free/en/papers/ye-2022-packed-levitated-marker-entity-relation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Deming Ye, Yankai Lin, Peng Li, et al.*2022 · 189 citations*
154. [**SGPT: GPT Sentence Embeddings for Semantic Search arXiv:2202.08904**Niklas Muennighoff*2022 · 189 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-sgpt-gpt-sentence-embeddings-semantic/)
155. [**Evaluating Large Language Models: A Comprehensive Survey arXiv:2310.19736**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
156. **[A neural interlingua for multilingual machine translation](https://md.research.elamur.ai/free/en/papers/lu-2018-neural-interlingua-multilingual-machine-translation/) [Conference on Machine Translation: Research Papers](https://md.research.elamur.ai/free/en/venues/conference-on-machine-translation-research-papers/)**Yichao Lu, Phillip Keung, Faisal Ladhak, et al.*2018 · 180 citations*
157. **[Pre-training Multilingual Neural Machine Translation by Leveraging Alignment Information](https://md.research.elamur.ai/free/en/papers/lin-2020-pre-training-multilingual-neural-machine/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zehui Lin, Xiao Pan, Mingxuan Wang, et al.*2020 · 178 citations*
158. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations*
159. [**StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding arXiv:1908.04577**Wei Wang, Bin Bi, Ming Yan, et al.*2019 · 175 citations*](https://md.research.elamur.ai/free/en/papers/wang-2019-structbert-incorporating-language-structures-pre/)
160. [**Generative Representational Instruction Tuning arXiv:2402.09906**Niklas Muennighoff, Hongjin Su, Liang Wang, et al.*2024 · 172 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2024-generative-representational-instruction-tuning/)
161. [**Seamless: Multilingual Expressive and Streaming Speech Translation arXiv:2312.05187**Seamless Communication, Loic Barrault, Yu-An Chung, et al.*2023 · 172 citations*](https://md.research.elamur.ai/free/en/papers/communication-2023-seamless-multilingual-expressive-streaming-speech/)
162. **[Soft Contextual Data Augmentation for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/gao-2019-soft-contextual-data-augmentation-neural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fei Gao, Jinhua Zhu, Lijun Wu, et al.*2019 · 172 citations*
163. [**Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity arXiv:2310.07521**Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.*2023 · 171 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-factuality-large-language-models/)
164. **[Detecting Harmful Memes and Their Targets](https://md.research.elamur.ai/free/en/papers/pramanick-2021-detecting-harmful-memes-their-targets/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shraman Pramanick, Dimitar Dimitrov, Rituparna Mukherjee, et al.*2021 · 171 citations*
165. [**Promptagator: Few-shot Dense Retrieval From 8 Examples arXiv:2209.11755**Zhuyun Dai, Vincent Y. Zhao, Ji Ma, et al.*2022 · 170 citations*](https://md.research.elamur.ai/free/en/papers/dai-2022-promptagator-few-shot-dense-retrieval/)
166. **[Quark: Controllable Text Generation with Reinforced Unlearning](https://md.research.elamur.ai/free/en/papers/lu-2022-quark-controllable-text-generation-reinforced/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Ximing Lu, Sean Welleck, Jack Hessel, et al.*2022 · 170 citations*
167. **[Simple Entity-Centric Questions Challenge Dense Retrievers](https://md.research.elamur.ai/free/en/papers/sciavolino-2021-simple-entity-centric-questions-challenge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Christopher Sciavolino, Zexuan Zhong, Jinhyuk Lee, et al.*2021 · 169 citations*
168. **[Is MAP Decoding All You Need? The Inadequacy of the Mode in Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/eikema-2020-is-map-decoding-all-you/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Bryan Eikema, Wilker Aziz*2020 · 167 citations*
169. **[Target-Guided Open-Domain Conversation](https://md.research.elamur.ai/free/en/papers/tang-2019-target-guided-open-domain-conversation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianheng Tang, Tiancheng Zhao, Chenyan Xiong, et al.*2019 · 166 citations*
170. [**Style Transfer as Unsupervised Machine Translation arXiv:1808.07894**Zhirui Zhang, Shuo Ren, Shujie Liu, et al.*2018 · 165 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2018-style-transfer-unsupervised-machine-translation/)
171. **[ERNIE-GEN: An Enhanced Multi-Flow Pre-training and Fine-tuning Framework for Natural Language Generation](https://md.research.elamur.ai/free/en/papers/xiao-2020-ernie-gen-enhanced-multi/) [International Joint Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/international-joint-conference-on-artificial-intelligence/)**Dongling Xiao, Han Zhang, Yukun Li, et al.*2020 · 163 citations*
172. **[If beam search is the answer, what was the question?](https://md.research.elamur.ai/free/en/papers/meister-2020-if-beam-search-is-answer/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Clara Meister, Ryan Cotterell, Tim Vieira*2020 · 163 citations*
173. **[Towards Persona-Based Empathetic Conversational Models](https://md.research.elamur.ai/free/en/papers/zhong-2020-persona-based-empathetic-conversational-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Peixiang Zhong, Chen Zhang, Hao Wang, et al.*2020 · 162 citations*
174. [**PanGu-α: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation arXiv:2104.12369**Wei Zeng, Xiaozhe Ren, Teng Su, et al.*2021 · 161 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2021-pangu-alpha-large-scale/)
175. [**A Span-Extraction Dataset for Chinese Machine Reading Comprehension arXiv:1810.07366 · EMNLP 2019 5886-5891**Yiming Cui, Ting Liu, Wanxiang Che, et al.*2018 · 160 citations*](https://md.research.elamur.ai/free/en/papers/cui-2018-span-extraction-dataset-chinese/)
176. [**CLIPort: What and Where Pathways for Robotic Manipulation arXiv:2109.12098**Mohit Shridhar, Lucas Manuelli, Dieter Fox*2021 · 159 citations*](https://md.research.elamur.ai/free/en/papers/shridhar-2021-cliport-where-pathways-robotic-manipulation/)
177. **[MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models](https://md.research.elamur.ai/free/en/papers/wen-2024-mindmap-knowledge-graph-prompting-sparks/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yilin Wen, Zifeng Wang, Jimeng Sun*2024 · 158 citations*
178. [**Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models arXiv:2503.16419**Yang Sui, Yu-Neng Chuang, Guanchu Wang, et al.*2025 · 157 citations*](https://md.research.elamur.ai/free/en/papers/sui-2025-stop-overthinking-survey-efficient-reasoning/)
179. **[Breaking the Beam Search Curse: A Study of (Re-)Scoring Methods and Stopping Criteria for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/yang-2018-breaking-beam-search-curse-study/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yilin Yang, Liang Huang, Mingbo Ma*2018 · 157 citations*
180. **[GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval](https://md.research.elamur.ai/free/en/papers/wang-2022-gpl-generative-pseudo-labeling-unsupervised/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kexin Wang, Nandan Thakur, Nils Reimers, et al.*2022 · 155 citations*
181. **[Modeling Multi-turn Conversation with Deep Utterance Aggregation](https://md.research.elamur.ai/free/en/papers/zhang-2018-modeling-multi-turn-conversation-deep/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Zhuosheng Zhang, Jiangtong Li, Pengfei Zhu, et al.*2018 · 154 citations*
182. [**AnnoLLM: Making Large Language Models to Be Better Crowdsourced Annotators arXiv:2303.16854**Xingwei He, Zhenghao Lin, Yeyun Gong, et al.*2023 · 152 citations*](https://md.research.elamur.ai/free/en/papers/he-2023-annollm-making-large-language-models/)
183. **[FINDINGS OF THE IWSLT 2023 EVALUATION CAMPAIGN](https://md.research.elamur.ai/free/en/papers/agarwal-2023-findings-iwslt-2023-evaluation-campaign/) [International Conference on Spoken Language Translation (IWSLT)](https://md.research.elamur.ai/free/en/venues/iwslt/)**Milind Agarwal, Sweta Agrawal, Antonios Anastasopoulos, et al.*2023 · 152 citations*
184. **[Neural Path Hunter: Reducing Hallucination in Dialogue Systems via Path Grounding](https://md.research.elamur.ai/free/en/papers/dziri-2021-neural-path-hunter-reducing-hallucination/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Nouha Dziri, Andrea Madotto, Osmar Zaïane, et al.*2021 · 152 citations*
185. [**ERNIE-ViL: Knowledge Enhanced Vision-Language Representations Through Scene Graph arXiv:2006.16934**Fei Yu, Jiji Tang, Weichong Yin, et al.*2020 · 152 citations*](https://md.research.elamur.ai/free/en/papers/yu-2020-ernie-vil-knowledge-enhanced/)
186. [**The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset arXiv:2303.03915**Hugo Laurençon, Lucile Saulnier, Thomas Wang, et al.*2023 · 150 citations*](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2023-bigscience-roots-corpus-1-6tb/)
187. [**A Review on Language Models as Knowledge Bases arXiv:2204.06031**Badr AlKhamissi, Millicent Li, Asli Celikyilmaz, et al.*2022 · 150 citations*](https://md.research.elamur.ai/free/en/papers/alkhamissi-2022-review-language-models-knowledge-bases/)
188. **[CPM: A Large-scale Generative Chinese Pre-trained Language Model](https://md.research.elamur.ai/free/en/papers/zhang-2020-cpm-large-scale-generative/) [AI Open](https://md.research.elamur.ai/free/en/venues/ai-open/)**Zhengyan Zhang, Xu Han, Hao Zhou, et al.*2020 · 150 citations*
189. **[Chain-of-Note: Enhancing Robustness in Retrieval-Augmented Language Models](https://md.research.elamur.ai/free/en/papers/yu-2024-chain-note-enhancing-robustness-retrieval/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wenhao Yu, Hongming Zhang, Xiaoman Pan, et al.*2024 · 149 citations*
190. **[Quality-Aware Decoding for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/fernandes-2022-quality-aware-decoding-neural-machine/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Patrick Fernandes, António Farinhas, Ricardo Rei, et al.*2022 · 146 citations*
191. [**SemEval-2022 Task 6: iSarcasmEval, Intended Sarcasm Detection in English and Arabic**Ibrahim Abu Farha, Silviu Vlad Oprea, Steven Wilson, et al.*2022 · 146 citations*](https://md.research.elamur.ai/free/en/papers/farha-2022-semeval-2022-task-6-isarcasmeval/)
192. **[How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition](https://md.research.elamur.ai/free/en/papers/dong-2024-how-abilities-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guanting Dong, Hongyi Yuan, Keming Lu, et al.*2024 · 145 citations*
193. **[RetroMAE: Pre-Training Retrieval-oriented Language Models Via Masked Auto-Encoder](https://md.research.elamur.ai/free/en/papers/xiao-2022-retromae-pre-training-retrieval-oriented/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shitao Xiao, Zheng Liu, Yingxia Shao, et al.*2022 · 145 citations*
194. **[PLATO-2: Towards Building an Open-Domain Chatbot via Curriculum Learning](https://md.research.elamur.ai/free/en/papers/bao-2021-plato-2-building-open-domain/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Siqi Bao, Huang He, Fan Wang, et al.*2021 · 145 citations*
195. **[SIMULEVAL: An Evaluation Toolkit for Simultaneous Translation](https://md.research.elamur.ai/free/en/papers/ma-2020-simuleval-evaluation-toolkit-simultaneous-translation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xutai Ma, Mohammad Javad Dousti, Changhan Wang, et al.*2020 · 144 citations*
196. [**Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness arXiv:2304.11633**Bo Li, Gexiang Fang, Yang Yang, et al.*2023 · 142 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-evaluating-chatgpt-s-information-extraction/)
197. **[SemEval 2021 Task 7: HaHackathon, Detecting and Rating Humor and Offense](https://md.research.elamur.ai/free/en/papers/meaney-2021-semeval-2021-task-7-hahackathon/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**J. A. Meaney, Steven Wilson, Luis Chiruzzo, et al.*2021 · 142 citations*
198. **[Increasing Faithfulness in Knowledge-Grounded Dialogue with Controllable Features](https://md.research.elamur.ai/free/en/papers/rashkin-2021-increasing-faithfulness-knowledge-grounded-dialogue/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hannah Rashkin, David Reitter, Gaurav Singh Tomar, et al.*2021 · 141 citations*
199. **[Multimodal Pretraining Unmasked: A Meta-Analysis and a Unified Framework of Vision-and-Language BERTs](https://md.research.elamur.ai/free/en/papers/bugliarello-2021-multimodal-pretraining-unmasked-meta-analysis/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Emanuele Bugliarello, Ryan Cotterell, Naoaki Okazaki, et al.*2021 · 141 citations*
200. **[Trivial Transfer Learning for Low-Resource Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/kocmi-2018-trivial-transfer-learning-low-resource/) [Conference on Machine Translation: Research Papers](https://md.research.elamur.ai/free/en/venues/conference-on-machine-translation-research-papers/)**Tom Kocmi, Ondřej Bojar*2018 · 141 citations*

[← prev](https://md.research.elamur.ai/free/en/authors/hua-ren-wu/cited-by/) [1](https://md.research.elamur.ai/free/en/authors/hua-ren-wu/cited-by/) **2** [3](https://md.research.elamur.ai/free/en/authors/hua-ren-wu/cited-by/page/3/) [4](https://md.research.elamur.ai/free/en/authors/hua-ren-wu/cited-by/page/4/) [5](https://md.research.elamur.ai/free/en/authors/hua-ren-wu/cited-by/page/5/) [next →](https://md.research.elamur.ai/free/en/authors/hua-ren-wu/cited-by/page/3/)

- [← back to](https://md.research.elamur.ai/free/en/authors/hua-ren-wu/) — Hua Ren Wu
