---
title: "Who cites Michael Matena — page 3"
description: "7,540 papers of the Elamur Research library cite the works of Michael Matena, found in their bibliographies · page 3 of 6 · 201–300; the most cited first."
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---
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# Who cites Michael Matena

7,577 citations of their works from 7,540 papers of our library (of the 140,884 whose bibliographies we read) · 594 with a page here, the most cited first · page 3 of 6 · 201–300 · [← Michael Matena](https://md.research.elamur.ai/free/en/authors/michael-matena/)

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201. [**ProofWriter: Generating Implications, Proofs, and Abductive Statements over Natural Language**Oyvind Tafjord, Bhavana Dalvi, Peter Clark*2021 · 331 citations*](https://md.research.elamur.ai/free/en/papers/tafjord-2021-proofwriter-generating-implications-proofs-abductive/)
202. [**GraphCodeBERT: Pre-training Code Representations with Data Flow**Daya Guo, Shuo Ren, Shuai Lu, et al.*2021 · 328 citations*](https://md.research.elamur.ai/free/en/papers/guo-2021-graphcodebert-pre-training-code-representations/)
203. [**RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning**Mingkai Deng, Jianyu Wang, Cheng-Ping Hsieh, et al.*2022 · 327 citations*](https://md.research.elamur.ai/free/en/papers/deng-2022-rlprompt-optimizing-discrete-text-prompts/)
204. [**Unsupervised Domain Clusters in Pretrained Language Models**Roee Aharoni, Yoav Goldberg*2020 · 326 citations*](https://md.research.elamur.ai/free/en/papers/aharoni-2020-unsupervised-domain-clusters-pretrained-language/)
205. [**Aspect Sentiment Quad Prediction as Paraphrase Generation**Wenxuan Zhang, Yang Deng, Xin Li, et al.*2021 · 325 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2021-aspect-sentiment-quad-prediction-as/)
206. [**ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation**Yu Sun, Shuohuan Wang, Shikun Feng, et al.*2021 · 324 citations*](https://md.research.elamur.ai/free/en/papers/sun-2021-ernie-3-0-large/)
207. [**LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention**Renrui Zhang, Jiaming Han, Chris Liu, et al.*2023 · 322 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-llama-adapter-efficient-fine-tuning/)
208. [**Probing Pretrained Language Models for Lexical Semantics**Ivan Vulić, Edoardo Maria Ponti, Robert Litschko, et al.*2020 · 320 citations*](https://md.research.elamur.ai/free/en/papers/vulic-2020-probing-pretrained-language-models-lexical/)
209. [**Text and Code Embeddings by Contrastive Pre-Training**Arvind Neelakantan, Tao Xu, Raul Puri, et al.*2022 · 316 citations*](https://md.research.elamur.ai/free/en/papers/neelakantan-2022-text-code-embeddings-contrastive-pre/)
210. [**Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation Models**Chenfei Wu, Shengming Yin, Weizhen Qi, et al.*2023 · 315 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-visual-chatgpt-talking-drawing-editing/)
211. [**How many data points is a prompt worth?**Teven Le Scao, Alexander Rush*2021 · 315 citations*](https://md.research.elamur.ai/free/en/papers/scao-2021-how-many-data-points-is/)
212. [**LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion**Dongfu Jiang, Xiang Ren, Bill Yuchen Lin*2023 · 314 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2023-llm-blender-ensembling-large-language/)
213. [**WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation**Alisa Liu, Swabha Swayamdipta, Noah A. Smith, et al.*2022 · 312 citations*](https://md.research.elamur.ai/free/en/papers/liu-2022-wanli-worker-ai-collaboration-natural/)
214. [**MEDITRON-70B: Scaling Medical Pretraining for Large Language Models**Zeming Chen, Alejandro Hernandez Cano, Angelika Romanou, et al.*2023 · 307 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-meditron-70b-scaling-medical-pretraining/)
215. [**TIES-Merging: Resolving Interference When Merging Models**Prateek Yadav, Derek Tam, Leshem Choshen, et al.*2023 · 306 citations*](https://md.research.elamur.ai/free/en/papers/yadav-2023-ties-merging-resolving-interference-merging/)
216. [**From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models**Shangbin Feng, Chan Young Park, Yuhan Liu, et al.*2023 · 305 citations*](https://md.research.elamur.ai/free/en/papers/feng-2023-pretraining-data-language-models-downstream/)
217. [**Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defense**Kalpesh Krishna, Yixiao Song, Marzena Karpinska, et al.*2023 · 304 citations*](https://md.research.elamur.ai/free/en/papers/krishna-2023-paraphrasing-evades-detectors-ai-generated/)
218. [**Carbon Emissions and Large Neural Network Training**David Patterson, Joseph Gonzalez, Quoc Le, et al.*2021 · 304 citations*](https://md.research.elamur.ai/free/en/papers/patterson-2021-carbon-emissions-large-neural-network/)
219. [**The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)**Zhengyuan Yang, Linjie Li, Kevin Lin, et al.*2023 · 303 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-dawn-lmms-preliminary-explorations-gpt/)
220. [**AugGPT: Leveraging ChatGPT for Text Data Augmentation**Haixing Dai; Zhengliang Liu; Wenxiong Liao; Xiaoke Huang; Yihan Cao; Zihao Wu; Lin Zhao; Shaochen Xu; Wei Liu; Ninghao Liu; Sheng Li; Dajiang Zhu; Hongmin Cai; Lichao Sun; Quanzheng Li; Dinggang Shen; Tianming Liu;, Xiang Li*2023 · 302 citations*](https://md.research.elamur.ai/free/en/papers/dai-2023-auggpt-leveraging-chatgpt-text-data/)
221. [**Can AI-Generated Text be Reliably Detected?**Vinu Sankar Sadasivan, Aounon Kumar, Sriram Balasubramanian, et al.*2023 · 301 citations*](https://md.research.elamur.ai/free/en/papers/sadasivan-2023-ai-generated-text-reliably-detected/)
222. [**ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale Transformers**Zhewei Yao, Reza Yazdani Aminabadi, Minjia Zhang, et al.*2022 · 301 citations*](https://md.research.elamur.ai/free/en/papers/yao-2022-zeroquant-efficient-affordable-post-training/)
223. [**SPoT: Better Frozen Model Adaptation through Soft Prompt Transfer**Tu Vu, Brian Lester, Noah Constant, et al.*2022 · 300 citations*](https://md.research.elamur.ai/free/en/papers/vu-2022-spot-better-frozen-model-adaptation/)
224. [**Muppet: Massive Multi-task Representations with Pre-Finetuning**Armen Aghajanyan, Anchit Gupta, Akshat Shrivastava, et al.*2021 · 299 citations*](https://md.research.elamur.ai/free/en/papers/aghajanyan-2021-muppet-massive-multi-task-representations/)
225. [**Multi-step Jailbreaking Privacy Attacks on ChatGPT**Haoran Li, Dadi Guo, Wei Fan, et al.*2023 · 298 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-multi-step-jailbreaking-privacy-attacks/)
226. [**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/)
227. [**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/)
228. [**Multimodal Chain-of-Thought Reasoning in Language Models**Zhuosheng Zhang, Aston Zhang, Mu Li, et al.*2023 · 296 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-multimodal-chain-thought-reasoning-language/)
229. [**Document-Level Machine Translation with Large Language Models**Longyue Wang, Chenyang Lyu, Tianbo Ji, et al.*2023 · 295 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-document-level-machine-translation-large/)
230. [**Entity-Based Knowledge Conflicts in Question Answering**Shayne Longpre, Kartik Perisetla, Anthony Chen, et al.*2021 · 295 citations*](https://md.research.elamur.ai/free/en/papers/longpre-2021-entity-based-knowledge-conflicts-question/)
231. [**Scalable Multi-Hop Relational Reasoning for Knowledge-Aware Question Answering**Yanlin Feng, Xinyue Chen, Bill Yuchen Lin, et al.*2020 · 295 citations*](https://md.research.elamur.ai/free/en/papers/feng-2020-scalable-multi-hop-relational-reasoning/)
232. [**KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization**Coleman Hooper, Sehoon Kim, Hiva Mohammadzadeh, et al.*2024 · 293 citations*](https://md.research.elamur.ai/free/en/papers/hooper-2024-kvquant-towards-10-million-context/)
233. [**FlauBERT: Unsupervised Language Model Pre-training for French**Hang Le, Loïc Vial, Jibril Frej, et al.*2019 · 293 citations*](https://md.research.elamur.ai/free/en/papers/le-2019-flaubert-unsupervised-language-model-pre/)
234. [**Text Classification via Large Language Models**Xiaofei Sun, Xiaoya Li, Jiwei Li, et al.*2023 · 292 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-text-classification-large-language-models/)
235. [**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/)
236. [**Challenges and Strategies in Cross-Cultural NLP**Daniel Hershcovich, Stella Frank, Heather Lent, et al.*2022 · 290 citations*](https://md.research.elamur.ai/free/en/papers/hershcovich-2022-challenges-strategies-cross-cultural-nlp/)
237. [**CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning**Hung Le, Yue Wang, Akhilesh Deepak Gotmare, et al.*2022 · 290 citations*](https://md.research.elamur.ai/free/en/papers/le-2022-coderl-mastering-code-generation-through/)
238. [**Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence**Tal Schuster, Adam Fisch, Regina Barzilay*2021 · 289 citations*](https://md.research.elamur.ai/free/en/papers/schuster-2021-get-your-vitamin-c-robust/)
239. [**On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes**Rishabh Agarwal, Nino Vieillard, Yongchao Zhou, et al.*2023 · 288 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2023-policy-distillation-language-models-learning/)
240. [**Can language models learn from explanations in context?**Andrew Lampinen, Ishita Dasgupta, Stephanie Chan, et al.*2022 · 288 citations*](https://md.research.elamur.ai/free/en/papers/lampinen-2022-can-language-models-learn-explanations/)
241. [**QAFactEval: Improved QA-Based Factual Consistency Evaluation for Summarization**Alexander Fabbri, Chien-Sheng Wu, Wenhao Liu, et al.*2022 · 288 citations*](https://md.research.elamur.ai/free/en/papers/fabbri-2022-qafacteval-improved-qa-based-factual/)
242. [**Can You Put it All Together: Evaluating Conversational Agents' Ability to Blend Skills**Eric Michael Smith, Mary Williamson, Kurt Shuster, et al.*2020 · 288 citations*](https://md.research.elamur.ai/free/en/papers/smith-2020-can-you-put-it-all/)
243. [**PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them**Patrick Lewis, Yuxiang Wu, Linqing Liu, et al.*2021 · 286 citations*](https://md.research.elamur.ai/free/en/papers/lewis-2021-paq-65-million-probably-asked/)
244. [**AlignScore: Evaluating Factual Consistency with A Unified Alignment Function**Yuheng Zha, Yichi Yang, Ruichen Li, et al.*2023 · 280 citations*](https://md.research.elamur.ai/free/en/papers/zha-2023-alignscore-evaluating-factual-consistency-unified/)
245. [**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/)
246. [**Intermediate-Task Transfer Learning with Pretrained Language Models: When and Why Does It Work?**Yada Pruksachatkun, Jason Phang, Haokun Liu, et al.*2020 · 279 citations*](https://md.research.elamur.ai/free/en/papers/pruksachatkun-2020-intermediate-task-transfer-learning-pretrained/)
247. [**OpenPrompt: An Open-source Framework for Prompt-learning**Ning Ding, Shengding Hu, Weilin Zhao, et al.*2022 · 278 citations*](https://md.research.elamur.ai/free/en/papers/ding-2022-openprompt-open-source-framework-prompt/)
248. [**RESDSQL: Decoupling Schema Linking and Skeleton Parsing for Text-to-SQL**Haoyang Li, Jing Zhang, Cuiping Li, et al.*2023 · 277 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-resdsql-decoupling-schema-linking-skeleton/)
249. [**XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation**Sebastian Ruder, Noah Constant, Jan Botha, et al.*2021 · 277 citations*](https://md.research.elamur.ai/free/en/papers/ruder-2021-xtreme-r-more-challenging-nuanced/)
250. [**A Survey on LLM-Generated Text Detection: Necessity, Methods, and Future Directions**Junchao Wu, Shu Yang, Runzhe Zhan, et al.*2025 · 276 citations*](https://md.research.elamur.ai/free/en/papers/wu-2025-survey-llm-generated-text-detection/)
251. [**TRUE: Re-evaluating Factual Consistency Evaluation**Or Honovich, Roee Aharoni, Jonathan Herzig, et al.*2022 · 276 citations*](https://md.research.elamur.ai/free/en/papers/honovich-2022-true-re-evaluating-factual-consistency/)
252. [**Large Dual Encoders Are Generalizable Retrievers**Jianmo Ni, Chen Qu, Jing Lu, et al.*2021 · 276 citations*](https://md.research.elamur.ai/free/en/papers/ni-2021-large-dual-encoders-generalizable-retrievers/)
253. [**LLM-QAT: Data-Free Quantization Aware Training for Large Language Models**Zechun Liu, Barlas Oguz, Changsheng Zhao, et al.*2024 · 275 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-llm-qat-data-free-quantization/)
254. [**Corrective Retrieval Augmented Generation**Shi-Qi Yan, Jia-Chen Gu, Yun Zhu, et al.*2024 · 271 citations*](https://md.research.elamur.ai/free/en/papers/yan-2024-corrective-retrieval-augmented-generation/)
255. [**XLM-T: Multilingual Language Models in Twitter for Sentiment Analysis and Beyond**Francesco Barbieri, Luis Espinosa Anke, Jose Camacho-Collados*2022 · 271 citations*](https://md.research.elamur.ai/free/en/papers/barbieri-2022-xlm-t-multilingual-language-models/)
256. [**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/)
257. [**Having Beer after Prayer? Measuring Cultural Bias in Large Language Models**Tarek Naous, Michael J. Ryan, Alan Ritter, et al.*2023 · 268 citations*](https://md.research.elamur.ai/free/en/papers/naous-2023-having-beer-after-prayer-measuring/)
258. [**BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models**Nandan Thakur, Nils Reimers, Andreas Rücklé, et al.*2021 · 262 citations*](https://md.research.elamur.ai/free/en/papers/thakur-2021-beir-heterogenous-benchmark-zero/)
259. [**TLDR: Extreme Summarization of Scientific Documents**Isabel Cachola, Kyle Lo, Arman Cohan, et al.*2020 · 260 citations*](https://md.research.elamur.ai/free/en/papers/cachola-2020-tldr-extreme-summarization-scientific-documents/)
260. [**MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies**Shengding Hu, Yuge Tu, Xu Han, et al.*2024 · 258 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-minicpm-unveiling-potential-small-language/)
261. [**How Can We Accelerate Progress Towards Human-like Linguistic Generalization?**Tal Linzen*2020 · 257 citations*](https://md.research.elamur.ai/free/en/papers/linzen-2020-how-can-we-accelerate-progress/)
262. [**LexGLUE: A Benchmark Dataset for Legal Language Understanding in English**Ilias Chalkidis; Abhik Jana; Dirk Hartung; Michael Bommarito; Ion Androutsopoulos; Daniel Martin Katz;, Nikolaos Aletras*2021 · 256 citations*](https://md.research.elamur.ai/free/en/papers/chalkidis-2021-lexglue-benchmark-dataset-legal-language/)
263. [**Re-evaluating Evaluation in Text Summarization**Manik Bhandari, Pranav Narayan Gour, Atabak Ashfaq, et al.*2020 · 256 citations*](https://md.research.elamur.ai/free/en/papers/bhandari-2020-re-evaluating-evaluation-text-summarization/)
264. [**Multilingual is not enough: BERT for Finnish**Antti Virtanen, Jenna Kanerva, Rami Ilo, et al.*2019 · 256 citations*](https://md.research.elamur.ai/free/en/papers/virtanen-2019-multilingual-enough-bert-finnish/)
265. [**Fine-Tuning LLaMA for Multi-Stage Text Retrieval**Xueguang Ma, Liang Wang, Nan Yang, et al.*2023 · 254 citations*](https://md.research.elamur.ai/free/en/papers/ma-2023-fine-tuning-llama-multi-stage/)
266. [**DeepSpeed-MoE: Advancing Mixture-of-Experts Inference and Training to Power Next-Generation AI Scale**Samyam Rajbhandari, Conglong Li, Zhewei Yao, et al.*2022 · 254 citations*](https://md.research.elamur.ai/free/en/papers/rajbhandari-2022-deepspeed-moe-advancing-mixture-experts/)
267. [**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/)
268. [**An Empirical Survey of Data Augmentation for Limited Data Learning in NLP**Jiaao Chen, Derek Tam, Colin Raffel, et al.*2023 · 253 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-empirical-survey-data-augmentation-limited/)
269. [**GPT-RE: In-context Learning for Relation Extraction using Large Language Models**Zhen Wan, Fei Cheng, Zhuoyuan Mao, et al.*2023 · 252 citations*](https://md.research.elamur.ai/free/en/papers/wan-2023-gpt-re-context-learning-relation/)
270. [**Societal Biases in Language Generation: Progress and Challenges**Emily Sheng, Kai-Wei Chang, Prem Natarajan, et al.*2021 · 252 citations*](https://md.research.elamur.ai/free/en/papers/sheng-2021-societal-biases-language-generation-progress/)
271. [**Measuring and Reducing Gendered Correlations in Pre-trained Models**Kellie Webster, Xuezhi Wang, Ian Tenney, et al.*2020 · 252 citations*](https://md.research.elamur.ai/free/en/papers/webster-2020-measuring-reducing-gendered-correlations-pre/)
272. [**Survey of Low-Resource Machine Translation**Barry Haddow, Rachel Bawden, Antonio Valerio Miceli Barone, et al.*2022 · 251 citations*](https://md.research.elamur.ai/free/en/papers/haddow-2022-survey-low-resource-machine-translation/)
273. [**Generating Datasets with Pretrained Language Models**Timo Schick, Hinrich Schutze*2021 · 250 citations*](https://md.research.elamur.ai/free/en/papers/schick-2021-generating-datasets-pretrained-language-models/)
274. [**LeanDojo: Theorem Proving with Retrieval-Augmented Language Models**Kaiyu Yang, Aidan M. Swope, Alex Gu, et al.*2023 · 248 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-leandojo-theorem-proving-retrieval-augmented/)
275. [**Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks**Rabeeh Karimi Mahabadi, Sebastian Ruder, Mostafa Dehghani, et al.*2021 · 248 citations*](https://md.research.elamur.ai/free/en/papers/mahabadi-2021-parameter-efficient-multi-task-fine/)
276. [**RedPajama: an Open Dataset for Training Large Language Models**Maurice Weber, Daniel Fu, Quentin Anthony, et al.*2024 · 247 citations*](https://md.research.elamur.ai/free/en/papers/weber-2024-redpajama-open-dataset-training-large/)
277. [**DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models**Boxin Wang, Weixin Chen, Hengzhi Pei, et al.*2023 · 246 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-decodingtrust-comprehensive-assessment-trustworthiness-gpt/)
278. [**Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model**Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.*2024 · 245 citations*](https://md.research.elamur.ai/free/en/papers/ustun-2024-aya-model-instruction-finetuned-open/)
279. [**NLP Evaluation in trouble: On the Need to Measure LLM Data Contamination for each Benchmark**Oscar Sainz, Jon Campos, Iker García-Ferrero, et al.*2023 · 245 citations*](https://md.research.elamur.ai/free/en/papers/sainz-2023-nlp-evaluation-trouble-need-measure/)
280. [**Ignore Previous Prompt: Attack Techniques For Language Models**Fabio Perez, Ian Ribeiro*2022 · 244 citations*](https://md.research.elamur.ai/free/en/papers/perez-2022-ignore-previous-prompt-attack-techniques/)
281. [**Structured Denoising Diffusion Models in Discrete State-Spaces**Jacob Austin, Daniel D. Johnson, Jonathan Ho, et al.*2021 · 244 citations*](https://md.research.elamur.ai/free/en/papers/austin-2021-structured-denoising-diffusion-models-discrete/)
282. [**Knowledge-Grounded Dialogue Generation with Pre-trained Language Models**Xueliang Zhao, Wei Wu, Can Xu, et al.*2020 · 244 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2020-knowledge-grounded-dialogue-generation-pre/)
283. [**Automatic Detection of Machine Generated Text: A Critical Survey**Ganesh Jawahar, Muhammad Abdul-Mageed, Laks Lakshmanan V.S.*2020 · 243 citations*](https://md.research.elamur.ai/free/en/papers/jawahar-2020-automatic-detection-machine-generated-text/)
284. [**CLUE: A Chinese Language Understanding Evaluation Benchmark**Liang Xu, Hai Hu, Xuanwei Zhang, et al.*2020 · 242 citations*](https://md.research.elamur.ai/free/en/papers/xu-2020-clue-chinese-language-understanding/)
285. [**ASQA: Factoid Questions Meet Long-Form Answers**Ivan Stelmakh, Yi Luan, Bhuwan Dhingra, et al.*2022 · 239 citations*](https://md.research.elamur.ai/free/en/papers/stelmakh-2022-asqa-factoid-questions-meet-long/)
286. [**Curriculum Learning for Natural Language Understanding**Benfeng Xu, Licheng Zhang, Zhendong Mao, et al.*2020 · 239 citations*](https://md.research.elamur.ai/free/en/papers/xu-2020-curriculum-learning-natural-language-understanding/)
287. [**MinTL: Minimalist Transfer Learning for Task-Oriented Dialogue Systems**Zhaojiang Lin, Andrea Madotto, Genta Indra Winata, et al.*2020 · 239 citations*](https://md.research.elamur.ai/free/en/papers/lin-2020-mintl-minimalist-transfer-learning-task/)
288. [**Knowledge Graph Based Synthetic Corpus Generation for Knowledge-Enhanced Language Model Pre-training**Oshin Agarwal, Heming Ge, Siamak Shakeri, et al.*2021 · 238 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2021-knowledge-graph-based-synthetic-corpus/)
289. [**Multimodal Few-Shot Learning with Frozen Language Models**Maria Tsimpoukelli, Jacob Menick, Serkan Cabi, et al.*2021 · 238 citations*](https://md.research.elamur.ai/free/en/papers/tsimpoukelli-2021-multimodal-few-shot-learning-frozen/)
290. [**OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization**Srinivasan Iyer, Xi Victoria Lin, Ramakanth Pasunuru, et al.*2022 · 237 citations*](https://md.research.elamur.ai/free/en/papers/iyer-2022-opt-iml-scaling-language-model/)
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