---
title: "Who cites BERT: Pre-training of Deep Bidirectional…"
description: "23,422 papers of the Elamur Research library cite «BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding», found in their…"
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---
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# Who cites «BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding»

23,422 papers of our library cite it (of the 140,884 whose bibliographies we read) · 1500 with a page here, the most cited first · page 5 of 15 · 401–500 · [← the paper](https://md.research.elamur.ai/free/en/papers/devlin-2019-bert-pre-training-deep-bidirectional/)

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401. [**BERTje: A Dutch BERT Model**Wietse de Vries, Andreas van Cranenburgh, Arianna Bisazza, et al.*2019 · 357 citations*](https://md.research.elamur.ai/free/en/papers/de-vries-2019-bertje-dutch-bert-model/)
402. [**XGLUE: A New Benchmark Dataset for Cross-lingual Pre-training, Understanding and Generation**Yaobo Liang, Nan Duan, Yeyun Gong, et al.*2020 · 356 citations*](https://md.research.elamur.ai/free/en/papers/liang-2020-xglue-new-benchmark-dataset-cross/)
403. [**Multilingual Constituency Parsing with Self-Attention and Pre-Training**Nikita Kitaev, Steven Cao, Dan Klein*2019 · 356 citations*](https://md.research.elamur.ai/free/en/papers/kitaev-2019-multilingual-constituency-parsing-self-attention/)
404. [**Utilizing BERT for Aspect-Based Sentiment Analysis via Constructing Auxiliary Sentence**Chi Sun, Luyao Huang, Xipeng Qiu*2019 · 356 citations*](https://md.research.elamur.ai/free/en/papers/sun-2019-utilizing-bert-aspect-based-sentiment/)
405. [**Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference**Benjamin Warner, Antoine Chaffin, Benjamin Clavié, et al.*2024 · 355 citations*](https://md.research.elamur.ai/free/en/papers/warner-2024-smarter-better-faster-longer-modern/)
406. [**QuestEval: Summarization Asks for Fact-based Evaluation**Thomas Scialom, Paul-Alexis Dray, Sylvain Lamprier, et al.*2021 · 353 citations*](https://md.research.elamur.ai/free/en/papers/scialom-2021-questeval-summarization-asks-fact-based/)
407. [**ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate**Chi-Min Chan, Weize Chen, Yusheng Su, et al.*2023 · 351 citations*](https://md.research.elamur.ai/free/en/papers/chan-2023-chateval-better-llm-based/)
408. [**SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection**Dominik Schlechtweg, Barbara McGillivray, Simon Hengchen, et al.*2020 · 351 citations*](https://md.research.elamur.ai/free/en/papers/schlechtweg-2020-semeval-2020-task-1-unsupervised/)
409. [**FEQA: A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive Summarization**Esin Durmus, He He, Mona Diab*2020 · 350 citations*](https://md.research.elamur.ai/free/en/papers/durmus-2020-feqa-question-answering-evaluation-framework/)
410. [**Reformulating Unsupervised Style Transfer as Paraphrase Generation**Kalpesh Krishna, John Wieting, Mohit Iyyer*2020 · 348 citations*](https://md.research.elamur.ai/free/en/papers/krishna-2020-reformulating-unsupervised-style-transfer-as/)
411. [**Do NLP Models Know Numbers? Probing Numeracy in Embeddings**Eric Wallace, Yizhong Wang, Sujian Li, et al.*2019 · 348 citations*](https://md.research.elamur.ai/free/en/papers/wallace-2019-do-nlp-models-know-numbers/)
412. [**RobBERT: a Dutch RoBERTa-based Language Model**Pieter Delobelle, Thomas Winters, Bettina Berendt*2020 · 346 citations*](https://md.research.elamur.ai/free/en/papers/delobelle-2020-robbert-dutch-roberta-based-language/)
413. [**Directed Acyclic Graph Network for Conversational Emotion Recognition**Weizhou Shen, Siyue Wu, Yunyi Yang, et al.*2021 · 344 citations*](https://md.research.elamur.ai/free/en/papers/shen-2021-directed-acyclic-graph-network-conversational/)
414. [**Transformer Feed-Forward Layers Build Predictions by Promoting Concepts in the Vocabulary Space**Mor Geva, Avi Caciularu, Kevin Ro Wang, et al.*2022 · 342 citations*](https://md.research.elamur.ai/free/en/papers/geva-2022-transformer-feed-forward-layers-build/)
415. [**Simple BERT Models for Relation Extraction and Semantic Role Labeling**Peng Shi, Jimmy Lin*2019 · 340 citations*](https://md.research.elamur.ai/free/en/papers/shi-2019-simple-bert-models-relation-extraction/)
416. [**Information-Theoretic Probing with Minimum Description Length**Elena Voita, Ivan Titov*2020 · 339 citations*](https://md.research.elamur.ai/free/en/papers/voita-2020-information-theoretic-probing-minimum-description/)
417. [**Word-level Textual Adversarial Attacking as Combinatorial Optimization**Yuan Zang, Fanchao Qi, Chenghao Yang, et al.*2020 · 338 citations*](https://md.research.elamur.ai/free/en/papers/zang-2020-word-level-textual-adversarial-attacking/)
418. [**Visualizing and Measuring the Geometry of BERT**Andy Coenen, Emily Reif, Ann Yuan, et al.*2019 · 338 citations*](https://md.research.elamur.ai/free/en/papers/coenen-2019-visualizing-measuring-geometry-bert/)
419. [**Large Language Models for Information Retrieval: A Survey**Yutao Zhu; Huaying Yuan; Shuting Wang; Jiongnan Liu; Wenhan Liu; Chenlong Deng; Haonan Chen; Zheng Liu; Zhicheng Dou;, Ji-Rong Wen*2023 · 335 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-large-language-models-information-retrieval/)
420. [**MultiWOZ 2.2 : A Dialogue Dataset with Additional Annotation Corrections and State Tracking Baselines**Xiaoxue Zang, Abhinav Rastogi, Srinivas Sunkara, et al.*2020 · 335 citations*](https://md.research.elamur.ai/free/en/papers/zang-2020-multiwoz-2-2-dialogue-dataset/)
421. [**SemEval-2019 Task 4: Hyperpartisan News Detection**Johannes Kiesel, Maria Mestre, Rishabh Shukla, et al.*2019 · 335 citations*](https://md.research.elamur.ai/free/en/papers/kiesel-2019-semeval-2019-task-4-hyperpartisan/)
422. [**UL2: Unifying Language Learning Paradigms**Yi Tay, Mostafa Dehghani, Vinh Q. Tran, et al.*2022 · 334 citations*](https://md.research.elamur.ai/free/en/papers/tay-2022-ul2-unifying-language-learning-paradigms/)
423. [**Efficient Attentions for Long Document Summarization**Luyang Huang, Shuyang Cao, Nikolaus Parulian, et al.*2021 · 334 citations*](https://md.research.elamur.ai/free/en/papers/huang-2021-efficient-attentions-long-document-summarization/)
424. [**Few-NERD: A Few-shot Named Entity Recognition Dataset**Ning Ding, Guangwei Xu, Yulin Chen, et al.*2021 · 334 citations*](https://md.research.elamur.ai/free/en/papers/ding-2021-few-nerd-few-shot-named/)
425. [**Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT**Akshay Smit, Saahil Jain, Pranav Rajpurkar, et al.*2020 · 334 citations*](https://md.research.elamur.ai/free/en/papers/smit-2020-combining-automatic-labelers-expert-annotations/)
426. [**Neural Unsupervised Domain Adaptation in NLP–-A Survey**Alan Ramponi, Barbara Plank*2020 · 334 citations*](https://md.research.elamur.ai/free/en/papers/ramponi-2020-neural-unsupervised-domain-adaptation-nlp/)
427. [**Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers**Chengyi Wang, Sanyuan Chen, Yu Wu, et al.*2023 · 333 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-neural-codec-language-models-zero/)
428. [**Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!**Xiangyu Qi, Yi Zeng, Tinghao Xie, et al.*2023 · 331 citations*](https://md.research.elamur.ai/free/en/papers/qi-2023-fine-tuning-aligned-language-models/)
429. [**Scaling Speech Technology to 1,000+ Languages**Vineel Pratap, Andros Tjandra, Bowen Shi, et al.*2023 · 331 citations*](https://md.research.elamur.ai/free/en/papers/pratap-2023-scaling-speech-technology-1-000/)
430. [**TimeLMs: Diachronic Language Models from Twitter**Daniel Loureiro, Francesco Barbieri, Leonardo Neves, et al.*2022 · 331 citations*](https://md.research.elamur.ai/free/en/papers/loureiro-2022-timelms-diachronic-language-models-twitter/)
431. [**Unsupervised Corpus Aware Language Model Pre-training for Dense Passage Retrieval**Luyu Gao, Jamie Callan*2022 · 328 citations*](https://md.research.elamur.ai/free/en/papers/gao-2022-unsupervised-corpus-aware-language-model/)
432. [**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/)
433. [**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/)
434. [**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/)
435. [**CometKiwi: IST-Unbabel 2022 Submission for the Quality Estimation Shared Task**Ricardo Rei, Marcos Treviso, Nuno M. Guerreiro, et al.*2022 · 325 citations*](https://md.research.elamur.ai/free/en/papers/rei-2022-cometkiwi-ist-unbabel-2022-submission/)
436. [**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/)
437. [**Quantifying the Carbon Emissions of Machine Learning**Alexandre Lacoste, Alexandra Luccioni, Victor Schmidt, et al.*2019 · 324 citations*](https://md.research.elamur.ai/free/en/papers/lacoste-2019-quantifying-carbon-emissions-machine-learning/)
438. [**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/)
439. [**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/)
440. [**Compressive Transformers for Long-Range Sequence Modelling**Jack W. Rae, Anna Potapenko, Siddhant M. Jayakumar, et al.*2019 · 320 citations*](https://md.research.elamur.ai/free/en/papers/rae-2019-compressive-transformers-long-range-sequence/)
441. [**MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims**Isabelle Augenstein, Christina Lioma, Dongsheng Wang, et al.*2019 · 318 citations*](https://md.research.elamur.ai/free/en/papers/augenstein-2019-multifc-real-world-multi-domain/)
442. [**Document Expansion by Query Prediction**Rodrigo Nogueira, Wei Yang, Jimmy Lin, et al.*2019 · 317 citations*](https://md.research.elamur.ai/free/en/papers/nogueira-2019-document-expansion-query-prediction/)
443. [**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/)
444. [**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/)
445. [**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/)
446. [**Explainable Automated Fact-Checking for Public Health Claims**Neema Kotonya, Francesca Toni*2020 · 314 citations*](https://md.research.elamur.ai/free/en/papers/kotonya-2020-explainable-automated-fact-checking-public/)
447. [**Towards Multimodal Sarcasm Detection (An _Obviously_ Perfect Paper)**Santiago Castro, Devamanyu Hazarika, Verónica Pérez-Rosas, et al.*2019 · 313 citations*](https://md.research.elamur.ai/free/en/papers/castro-2019-towards-multimodal-sarcasm-detection-obviously/)
448. [**A Transformer-based approach to Irony and Sarcasm detection**Rolandos Alexandros Potamias, Georgios Siolas, Andreas - Georgios Stafylopatis*2019 · 312 citations*](https://md.research.elamur.ai/free/en/papers/potamias-2019-transformer-based-approach-irony-sarcasm/)
449. [**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/)
450. [**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/)
451. [**Multi-hop Reading Comprehension through Question Decomposition and Rescoring**Sewon Min, Victor Zhong, Luke Zettlemoyer, et al.*2019 · 306 citations*](https://md.research.elamur.ai/free/en/papers/min-2019-multi-hop-reading-comprehension-through/)
452. [**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/)
453. [**Challenges and frontiers in abusive content detection**Bertie Vidgen, Alex Harris, Dong Nguyen, et al.*2019 · 305 citations*](https://md.research.elamur.ai/free/en/papers/vidgen-2019-challenges-frontiers-abusive-content-detection/)
454. [**Multi-passage BERT: A Globally Normalized BERT Model for Open-domain Question Answering**Zhiguo Wang, Patrick Ng, Xiaofei Ma, et al.*2019 · 304 citations*](https://md.research.elamur.ai/free/en/papers/wang-2019-multi-passage-bert-globally-normalized/)
455. [**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/)
456. [**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/)
457. [**ZeRO-Offload: Democratizing Billion-Scale Model Training**Jie Ren, Samyam Rajbhandari, Reza Yazdani Aminabadi, et al.*2021 · 302 citations*](https://md.research.elamur.ai/free/en/papers/ren-2021-zero-offload-democratizing-billion-scale/)
458. [**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/)
459. [**Abductive Commonsense Reasoning**Chandra Bhagavatula, Ronan Le Bras, Chaitanya Malaviya, et al.*2019 · 301 citations*](https://md.research.elamur.ai/free/en/papers/bhagavatula-2019-abductive-commonsense-reasoning/)
460. [**Challenges and Applications of Large Language Models**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 300 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
461. [**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/)
462. [**Style Transformer: Unpaired Text Style Transfer without Disentangled Latent Representation**Ning Dai, Jianze Liang, Xipeng Qiu, et al.*2019 · 300 citations*](https://md.research.elamur.ai/free/en/papers/dai-2019-style-transformer-unpaired-text-style/)
463. [**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/)
464. [**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/)
465. [**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/)
466. [**S2ORC: The Semantic Scholar Open Research Corpus**Kyle Lo, Lucy Lu Wang, Mark Neumann, et al.*2019 · 297 citations*](https://md.research.elamur.ai/free/en/papers/lo-2019-s2orc-semantic-scholar-open-research/)
467. [**BanglaBERT: Language Model Pretraining and Benchmarks for Low-Resource Language Understanding Evaluation in Bangla**Abhik Bhattacharjee, Tahmid Hasan, Wasi Ahmad, et al.*2022 · 296 citations*](https://md.research.elamur.ai/free/en/papers/bhattacharjee-2022-banglabert-language-model-pretraining-benchmarks/)
468. [**Towards Debiasing Fact Verification Models**Tal Schuster, Darsh Shah, Yun Jie Serene Yeo, et al.*2019 · 296 citations*](https://md.research.elamur.ai/free/en/papers/schuster-2019-debiasing-fact-verification-models/)
469. [**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/)
470. [**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/)
471. [**AdapterDrop: On the Efficiency of Adapters in Transformers**Andreas Rücklé, Gregor Geigle, Max Glockner, et al.*2021 · 294 citations*](https://md.research.elamur.ai/free/en/papers/ruckle-2021-adapterdrop-efficiency-adapters-transformers/)
472. [**Cross-Lingual Alignment of Contextual Word Embeddings, with Applications to Zero-shot Dependency Parsing**Tal Schuster, Ori Ram, Regina Barzilay, et al.*2019 · 294 citations*](https://md.research.elamur.ai/free/en/papers/schuster-2019-cross-lingual-alignment-contextual-word/)
473. [**Matching the Blanks: Distributional Similarity for Relation Learning**Livio Baldini Soares, Nicholas FitzGerald, Jeffrey Ling, et al.*2019 · 294 citations*](https://md.research.elamur.ai/free/en/papers/soares-2019-matching-blanks-distributional-similarity-relation/)
474. [**Prompting Large Language Model for Machine Translation: A Case Study**Biao Zhang, Barry Haddow, Alexandra Birch*2023 · 293 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-prompting-large-language-model-machine/)
475. [**Information-Theoretic Probing for Linguistic Structure**Tiago Pimentel, Josef Valvoda, Rowan Hall Maudslay, et al.*2020 · 293 citations*](https://md.research.elamur.ai/free/en/papers/pimentel-2020-information-theoretic-probing-linguistic-structure/)
476. [**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/)
477. [**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/)
478. [**Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little**Koustuv Sinha, Robin Jia, Dieuwke Hupkes, et al.*2021 · 292 citations*](https://md.research.elamur.ai/free/en/papers/sinha-2021-masked-language-modeling-distributional-hypothesis/)
479. [**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/)
480. [**Build it Break it Fix it for Dialogue Safety: Robustness from Adversarial Human Attack**Emily Dinan, Samuel Humeau, Bharath Chintagunta, et al.*2019 · 291 citations*](https://md.research.elamur.ai/free/en/papers/dinan-2019-build-it-break-it-fix/)
481. [**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/)
482. [**SemEval-2019 Task 7: RumourEval, Determining Rumour Veracity and Support for Rumours**Genevieve Gorrell, Elena Kochkina, Maria Liakata, et al.*2019 · 290 citations*](https://md.research.elamur.ai/free/en/papers/gorrell-2019-semeval-2019-task-7-rumoureval/)
483. [**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/)
484. [**From Words to Watts: Benchmarking the Energy Costs of Large Language Model Inference**Siddharth Samsi, Dan Zhao, Joseph McDonald, et al.*2023 · 288 citations*](https://md.research.elamur.ai/free/en/papers/samsi-2023-words-watts-benchmarking-energy-costs/)
485. [**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/)
486. [**CAMeL Tools: An Open Source Python Toolkit for Arabic Natural Language Processing**Ossama Obeid, Nasser Zalmout, Salam Khalifa, et al.*2020 · 288 citations*](https://md.research.elamur.ai/free/en/papers/obeid-2020-camel-tools-open-source-python/)
487. [**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/)
488. [**Structural Scaffolds for Citation Intent Classification in Scientific Publications**Arman Cohan, Waleed Ammar, Madeleine van Zuylen, et al.*2019 · 287 citations*](https://md.research.elamur.ai/free/en/papers/cohan-2019-structural-scaffolds-citation-intent-classification/)
489. [**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/)
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