---
title: "Who cites Illia Polosukhin — page 4"
description: "18,005 papers of the Elamur Research library cite the works of Illia Polosukhin, found in their bibliographies · page 4 of 12 · 301–400; the most cited…"
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---
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# Who cites Illia Polosukhin

18,396 citations of their works from 18,005 papers of our library (of the 140,884 whose bibliographies we read) · 1,116 with a page here, the most cited first · page 4 of 12 · 301–400 · [← Illia Polosukhin](https://md.research.elamur.ai/free/en/authors/illia-polosukhin/)

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301. [**Mem2Seq: Effectively Incorporating Knowledge Bases into End-to-End Task-Oriented Dialog Systems**Andrea Madotto, Chien-Sheng Wu, Pascale Fung*2018 · 401 citations*](https://md.research.elamur.ai/free/en/papers/madotto-2018-mem2seq-effectively-incorporating-knowledge-bases/)
302. [**Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning**Mitchell Gordon, Kevin Duh, Nicholas Andrews*2020 · 400 citations*](https://md.research.elamur.ai/free/en/papers/gordon-2020-compressing-bert-studying-effects-weight/)
303. [**How to Fine-Tune BERT for Text Classification?**Chi Sun, Xipeng Qiu, Yige Xu, et al.*2019 · 400 citations*](https://md.research.elamur.ai/free/en/papers/sun-2019-fine-tune-bert-text-classification/)
304. [**A Survey on Recent Approaches for Natural Language Processing in Low-Resource Scenarios**Michael A. Hedderich, Lukas Lange, Heike Adel, et al.*2021 · 399 citations*](https://md.research.elamur.ai/free/en/papers/hedderich-2021-survey-recent-approaches-natural-language/)
305. [**LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models**Zhiqiang Hu, Lei Wang, Yihuai Lan, et al.*2023 · 398 citations*](https://md.research.elamur.ai/free/en/papers/hu-2023-llm-adapters-adapter-family-parameter/)
306. [**FLEURS: Few-shot Learning Evaluation of Universal Representations of Speech**Alexis Conneau, Min Ma, Simran Khanuja, et al.*2022 · 398 citations*](https://md.research.elamur.ai/free/en/papers/conneau-2022-fleurs-few-shot-learning-evaluation/)
307. [**LongT5: Efficient Text-To-Text Transformer for Long Sequences**Mandy Guo, Joshua Ainslie, David Uthus, et al.*2022 · 398 citations*](https://md.research.elamur.ai/free/en/papers/guo-2022-longt5-efficient-text-text-transformer/)
308. [**QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization**Ming Zhong, Da Yin, Tao Yu, et al.*2021 · 397 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2021-qmsum-new-benchmark-query-based/)
309. [**A Unified Generative Framework for Aspect-based Sentiment Analysis**Hang Yan, Junqi Dai, Tuo Ji, et al.*2021 · 396 citations*](https://md.research.elamur.ai/free/en/papers/yan-2021-unified-generative-framework-aspect-based/)
310. [**Long Range Arena: A Benchmark for Efficient Transformers**Yi Tay, Mostafa Dehghani, Samira Abnar, et al.*2020 · 396 citations*](https://md.research.elamur.ai/free/en/papers/tay-2020-long-range-arena-benchmark-efficient/)
311. [**A Challenge Dataset and Effective Models for Aspect-Based Sentiment Analysis**Qingnan Jiang, Lei Chen, Ruifeng Xu, et al.*2019 · 393 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2019-challenge-dataset-effective-models-aspect/)
312. [**A Unified Generative Framework for Various NER Subtasks**Hang Yan, Tao Gui, Junqi Dai, et al.*2021 · 392 citations*](https://md.research.elamur.ai/free/en/papers/yan-2021-unified-generative-framework-various-ner/)
313. [**BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models**Elad Ben-Zaken, Shauli Ravfogel, Yoav Goldberg*2021 · 388 citations*](https://md.research.elamur.ai/free/en/papers/ben-zaken-2021-bitfit-simple-parameter-efficient-fine/)
314. [**RULER: What's the Real Context Size of Your Long-Context Language Models?**Cheng-Ping Hsieh, Simeng Sun, Samuel Kriman, et al.*2024 · 386 citations*](https://md.research.elamur.ai/free/en/papers/hsieh-2024-ruler-s-real-context-size/)
315. [**German's Next Language Model**Branden Chan, Stefan Schweter, Timo Möller*2020 · 385 citations*](https://md.research.elamur.ai/free/en/papers/chan-2020-german-s-next-language-model/)
316. [**CMMLU: Measuring massive multitask language understanding in Chinese**Haonan Li, Yixuan Zhang, Fajri Koto, et al.*2023 · 384 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-cmmlu-measuring-massive-multitask-language/)
317. [**A Stack-Propagation Framework with Token-Level Intent Detection for Spoken Language Understanding**Libo Qin, Wanxiang Che, Yangming Li, et al.*2019 · 384 citations*](https://md.research.elamur.ai/free/en/papers/qin-2019-stack-propagation-framework-token-level/)
318. [**Deep Semantic Role Labeling with Self-Attention**Zhixing Tan, Mingxuan Wang, Jun Xie, et al.*2017 · 384 citations*](https://md.research.elamur.ai/free/en/papers/tan-2017-deep-semantic-role-labeling-self/)
319. [**Query Rewriting in Retrieval-Augmented Large Language Models**Xinbei Ma, Yeyun Gong, Pengcheng He, et al.*2023 · 383 citations*](https://md.research.elamur.ai/free/en/papers/ma-2023-query-rewriting-retrieval-augmented-large/)
320. [**Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms**Dinghan Shen, Guoyin Wang, Wenlin Wang, et al.*2018 · 383 citations*](https://md.research.elamur.ai/free/en/papers/shen-2018-baseline-needs-more-love-simple/)
321. [**Retrieval Augmentation Reduces Hallucination in Conversation**Kurt Shuster, Spencer Poff, Moya Chen, et al.*2021 · 382 citations*](https://md.research.elamur.ai/free/en/papers/shuster-2021-retrieval-augmentation-reduces-hallucination-conversation/)
322. [**Discourse-Aware Neural Extractive Text Summarization**Jiacheng Xu, Zhe Gan, Yu Cheng, et al.*2019 · 382 citations*](https://md.research.elamur.ai/free/en/papers/xu-2019-discourse-aware-neural-extractive-text/)
323. [**Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity**Soyeong Jeong, Jinheon Baek, Sukmin Cho, et al.*2024 · 381 citations*](https://md.research.elamur.ai/free/en/papers/jeong-2024-adaptive-rag-learning-adapt-retrieval/)
324. [**Enhancing Retrieval-Augmented Large Language Models with Iterative Retrieval-Generation Synergy**Zhihong Shao, Yeyun Gong, Yelong Shen, et al.*2023 · 381 citations*](https://md.research.elamur.ai/free/en/papers/shao-2023-enhancing-retrieval-augmented-large-language/)
325. [**UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training**Hangbo Bao, Li Dong, Furu Wei, et al.*2020 · 380 citations*](https://md.research.elamur.ai/free/en/papers/bao-2020-unilmv2-pseudo-masked-language-models/)
326. [**Reasoning with Latent Structure Refinement for Document-Level Relation Extraction**Guoshun Nan, Zhijiang Guo, Ivan Sekulic, et al.*2020 · 379 citations*](https://md.research.elamur.ai/free/en/papers/nan-2020-reasoning-latent-structure-refinement-document/)
327. [**ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension**Sheng Zhang, Xiaodong Liu, Jingjing Liu, et al.*2018 · 379 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2018-record-bridging-gap-between-human/)
328. [**Towards General Text Embeddings with Multi-stage Contrastive Learning**Zehan Li, Xin Zhang, Yanzhao Zhang, et al.*2023 · 378 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-towards-general-text-embeddings-multi/)
329. [**Emerging Cross-lingual Structure in Pretrained Language Models**Alexis Conneau, Shijie Wu, Haoran Li, et al.*2020 · 378 citations*](https://md.research.elamur.ai/free/en/papers/conneau-2020-emerging-cross-lingual-structure-pretrained/)
330. [**ETC: Encoding Long and Structured Inputs in Transformers**Joshua Ainslie, Santiago Ontañón, Chris Alberti, et al.*2020 · 377 citations*](https://md.research.elamur.ai/free/en/papers/ainslie-2020-etc-encoding-long-structured-inputs/)
331. [**Tool Learning with Foundation Models**Yujia Qin, Shengding Hu, Yankai Lin, et al.*2023 · 376 citations*](https://md.research.elamur.ai/free/en/papers/qin-2023-tool-learning-foundation-models/)
332. [**HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Data**Wenhu Chen, Hanwen Zha, Zhiyu Chen, et al.*2020 · 376 citations*](https://md.research.elamur.ai/free/en/papers/chen-2020-hybridqa-dataset-multi-hop-question/)
333. [**FastBERT: a Self-distilling BERT with Adaptive Inference Time**Weijie Liu, Peng Zhou, Zhiruo Wang, et al.*2020 · 374 citations*](https://md.research.elamur.ai/free/en/papers/liu-2020-fastbert-self-distilling-bert-adaptive/)
334. [**ChatDev: Communicative Agents for Software Development**Chen Qian, Wei Liu, Hongzhang Liu, et al.*2023 · 373 citations*](https://md.research.elamur.ai/free/en/papers/qian-2023-chatdev-communicative-agents-software/)
335. [**A Dataset of Information-Seeking Questions and Answers Anchored in Research Papers**Pradeep Dasigi, Kyle Lo, Iz Beltagy, et al.*2021 · 372 citations*](https://md.research.elamur.ai/free/en/papers/dasigi-2021-dataset-information-seeking-questions-answers/)
336. [**WebArena: A Realistic Web Environment for Building Autonomous Agents**Shuyan Zhou, Frank F. Xu, Hao Zhu, et al.*2023 · 371 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-webarena-realistic-web-environment-building/)
337. [**Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction**Yaojie Lu, Hongyu Lin, Jin Xu, et al.*2021 · 370 citations*](https://md.research.elamur.ai/free/en/papers/lu-2021-text2event-controllable-sequence-structure-generation/)
338. [**Green AI**Roy Schwartz, Jesse Dodge, Noah A. Smith, et al.*2019 · 370 citations*](https://md.research.elamur.ai/free/en/papers/schwartz-2019-green-ai/)
339. [**Knowledge-Enriched Transformer for Emotion Detection in Textual Conversations**Peixiang Zhong, Di Wang, Chunyan Miao*2019 · 370 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2019-knowledge-enriched-transformer-emotion-detection/)
340. [**Training Tips for the Transformer Model**Martin Popel, Ondřej Bojar*2018 · 369 citations*](https://md.research.elamur.ai/free/en/papers/popel-2018-training-tips-transformer-model/)
341. [**Heterogeneous Graph Neural Networks for Extractive Document Summarization**Danqing Wang, Pengfei Liu, Yining Zheng, et al.*2020 · 368 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-heterogeneous-graph-neural-networks-extractive/)
342. [**VILA: On Pre-training for Visual Language Models**Ji Lin, Hongxu Yin, Wei Ping, et al.*2023 · 367 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-vila-pre-training-visual-language/)
343. [**Massively Multilingual Neural Machine Translation**Roee Aharoni, Melvin Johnson, Orhan Firat*2019 · 367 citations*](https://md.research.elamur.ai/free/en/papers/aharoni-2019-massively-multilingual-neural-machine-translation/)
344. [**A Survey on Large Language Models for Code Generation**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 366 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/)
345. [**An Analysis of Encoder Representations in Transformer-Based Machine Translation**Alessandro Raganato, Jörg Tiedemann*2018 · 366 citations*](https://md.research.elamur.ai/free/en/papers/raganato-2018-analysis-encoder-representations-transformer-based/)
346. [**The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery**Chris Lu, Cong Lu, Robert Tjarko Lange, et al.*2024 · 362 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-ai-scientist-fully-automated/)
347. [**Revisiting Few-sample BERT Fine-tuning**Tianyi Zhang, Felix Wu, Arzoo Katiyar, et al.*2020 · 361 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2020-revisiting-few-sample-bert-fine/)
348. [**The FLORES Evaluation Datasets for Low-Resource Machine Translation: Nepali–English and Sinhala–English**Francisco Guzmán, Peng-Jen Chen, Myle Ott, et al.*2019 · 361 citations*](https://md.research.elamur.ai/free/en/papers/guzman-2019-flores-evaluation-datasets-low-resource/)
349. [**TOD-BERT: Pre-trained Natural Language Understanding for Task-Oriented Dialogue**Chien-Sheng Wu, Steven C.H. Hoi, Richard Socher, et al.*2020 · 360 citations*](https://md.research.elamur.ai/free/en/papers/wu-2020-tod-bert-pre-trained-natural/)
350. [**Mind the GAP: A Balanced Corpus of Gendered Ambiguous Pronouns**Kellie Webster, Marta Recasens, Vera Axelrod, et al.*2018 · 358 citations*](https://md.research.elamur.ai/free/en/papers/webster-2018-mind-gap-balanced-corpus-gendered/)
351. [**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/)
352. [**Universal Neural Machine Translation for Extremely Low Resource Languages**Jiatao Gu, Hany Hassan, Jacob Devlin, et al.*2018 · 356 citations*](https://md.research.elamur.ai/free/en/papers/gu-2018-universal-neural-machine-translation-extremely/)
353. [**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/)
354. [**Synthetic QA Corpora Generation with Roundtrip Consistency**Chris Alberti, Daniel Andor, Emily Pitler, et al.*2019 · 355 citations*](https://md.research.elamur.ai/free/en/papers/alberti-2019-synthetic-qa-corpora-generation-roundtrip/)
355. [**Large Language Models Struggle to Learn Long-Tail Knowledge**Nikhil Kandpal, Haikang Deng, Adam Roberts, et al.*2022 · 352 citations*](https://md.research.elamur.ai/free/en/papers/kandpal-2022-large-language-models-struggle-learn/)
356. [**RARR: Researching and Revising What Language Models Say, Using Language Models**Luyu Gao, Zhuyun Dai, Panupong Pasupat, et al.*2023 · 351 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-rarr-researching-revising-what-language/)
357. [**TinyLlama: An Open-Source Small Language Model**Peiyuan Zhang, Guangtao Zeng, Tianduo Wang, et al.*2024 · 350 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-tinyllama-open-source-small-language/)
358. [**STACL: Simultaneous Translation with Implicit Anticipation and Controllable Latency using Prefix-to-Prefix Framework**Mingbo Ma, Liang Huang, Hao Xiong, et al.*2019 · 349 citations*](https://md.research.elamur.ai/free/en/papers/ma-2019-stacl-simultaneous-translation-implicit-anticipation/)
359. [**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/)
360. [**Improving alignment of dialogue agents via targeted human judgements**Amelia Glaese, Nat McAleese, Maja Trębacz, et al.*2022 · 346 citations*](https://md.research.elamur.ai/free/en/papers/glaese-2022-improving-alignment-dialogue-agents-targeted/)
361. [**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/)
362. [**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/)
363. [**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/)
364. [**PaLI: A Jointly-Scaled Multilingual Language-Image Model**Xi Chen, Xiao Wang, Soravit Changpinyo, et al.*2022 · 339 citations*](https://md.research.elamur.ai/free/en/papers/chen-2022-pali-jointly-scaled-multilingual-language/)
365. [**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/)
366. [**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/)
367. [**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/)
368. [**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/)
369. [**DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models**DeepSeek-AI, Aixin Liu, Aoxue Mei, et al.*2025 · 333 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2025-deepseek-v3-2-pushing/)
370. [**Kimi K2: Open Agentic Intelligence**Kimi Team, Yifan Bai, Yiping Bao, et al.*2025 · 331 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-k2-open-agentic/)
371. [**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/)
372. [**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/)
373. [**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/)
374. [**Textbooks Are All You Need II: phi-1.5 technical report**Yuanzhi Li, Sébastien Bubeck, Ronen Eldan, et al.*2023 · 327 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-textbooks-all-need-ii-phi/)
375. [**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/)
376. [**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/)
377. [**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/)
378. [**Are Emergent Abilities of Large Language Models a Mirage?**Rylan Schaeffer, Brando Miranda, Sanmi Koyejo*2023 · 323 citations*](https://md.research.elamur.ai/free/en/papers/schaeffer-2023-emergent-abilities-large-language-models/)
379. [**Robust Neural Machine Translation with Doubly Adversarial Inputs**Yong Cheng, Lu Jiang, Wolfgang Macherey*2019 · 321 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2019-robust-neural-machine-translation-doubly/)
380. [**When a Good Translation is Wrong in Context: Context-Aware Machine Translation Improves on Deixis, Ellipsis, and Lexical Cohesion**Elena Voita, Rico Sennrich, Ivan Titov*2019 · 321 citations*](https://md.research.elamur.ai/free/en/papers/voita-2019-when-good-translation-is-wrong/)
381. [**"Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models**Xinyue Shen, Zeyuan Chen, Michael Backes, et al.*2023 · 320 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-anything-now-characterizing-evaluating-wild/)
382. [**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/)
383. [**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/)
384. [**GSum: A General Framework for Guided Neural Abstractive Summarization**Zi-Yi Dou, Pengfei Liu, Hiroaki Hayashi, et al.*2021 · 317 citations*](https://md.research.elamur.ai/free/en/papers/dou-2021-gsum-general-framework-guided-neural/)
385. [**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/)
386. [**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/)
387. [**CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing**Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.*2023 · 315 citations*](https://md.research.elamur.ai/free/en/papers/gou-2023-critic-large-language-models-self/)
388. [**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/)
389. [**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/)
390. [**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/)
391. [**Hallucination is Inevitable: An Innate Limitation of Large Language Models**Ziwei Xu, Sanjay Jain, Mohan Kankanhalli*2024 · 309 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-hallucination-inevitable-innate-limitation-large/)
392. [**Generating Wikipedia by Summarizing Long Sequences**Peter J. Liu, Mohammad Saleh, Etienne Pot, et al.*2018 · 308 citations*](https://md.research.elamur.ai/free/en/papers/liu-2018-generating-wikipedia-summarizing-long-sequences/)
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