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title: "Computer Science — papers, page 5 — Elamur Research"
description: "Computer Science: 9,085 papers of the Elamur Research library · page 5 of 92 · 326–425, the most cited first — our summary of each, its…"
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# 🖥️ Computer Science

9,085 papers · page 5 of 92 · 326–425 · the most cited first · [all shelves](https://md.research.elamur.ai/free/en/shelves/)

Artificial intelligence, language technology, vision, systems, networks, software and the theory of computing.

## Papers (9,085)

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326. [**Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey**Bonan Min, Hayley Ross, Elior Sulem, et al.*2021 · 1,552 citations*](https://md.research.elamur.ai/free/en/papers/min-2021-recent-advances-natural-language-processing/)
327. [**Unifying Large Language Models and Knowledge Graphs: A Roadmap**Shirui Pan, Linhao Luo, Yufei Wang, et al.*2023 · 1,549 citations*](https://md.research.elamur.ai/free/en/papers/pan-2023-unifying-large-language-models-knowledge/)
328. [**Competition-Level Code Generation with AlphaCode**Yujia Li, David Choi, Junyoung Chung, et al.*2022 · 1,545 citations*](https://md.research.elamur.ai/free/en/papers/li-2022-competition-level-code-generation-alphacode/)
329. [**CoQA: A Conversational Question Answering Challenge**Siva Reddy, Danqi Chen, Christopher D. Manning*2019 · 1,545 citations*](https://md.research.elamur.ai/free/en/papers/reddy-2019-coqa-conversational-question-answering-challenge/)
330. [**Universal Sentence Encoder for English**Daniel Cer, Yinfei Yang, Sheng-yi Kong, et al.*2018 · 1,545 citations*](https://md.research.elamur.ai/free/en/papers/cer-2018-universal-sentence-encoder-english/)
331. [**Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision**Chao Jia, Yinfei Yang, Ye Xia, et al.*2021 · 1,537 citations*](https://md.research.elamur.ai/free/en/papers/jia-2021-scaling-up-visual-vision-language/)
332. [**ChatGPT Outperforms Crowd-Workers for Text-Annotation Tasks**Fabrizio Gilardi, Meysam Alizadeh, Maël Kubli*2023 · 1,533 citations*](https://md.research.elamur.ai/free/en/papers/gilardi-2023-chatgpt-outperforms-crowd-workers-text/)
333. [**Score-Based Generative Modeling through Stochastic Differential Equations**Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, et al.*2020 · 1,530 citations*](https://md.research.elamur.ai/free/en/papers/song-2020-score-based-generative-modeling-through/)
334. [**VisualBERT: A Simple and Performant Baseline for Vision and Language**Liunian Harold Li, Mark Yatskar, Da Yin, et al.*2019 · 1,525 citations*](https://md.research.elamur.ai/free/en/papers/li-2019-visualbert-simple-performant-baseline-vision/)
335. [**Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context**Gemini Team, Petko Georgiev, Ving Ian Lei, et al.*2024 · 1,522 citations*](https://md.research.elamur.ai/free/en/papers/gemini-team-2024-gemini-1-5-unlocking-multimodal/)
336. [**Efficient Transformers: A Survey**Yi Tay, Mostafa Dehghani, Dara Bahri, et al.*2020 · 1,522 citations*](https://md.research.elamur.ai/free/en/papers/tay-2020-efficient-transformers-survey/)
337. [**Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned**Elena Voita, David Talbot, Fedor Moiseev, et al.*2019 · 1,520 citations*](https://md.research.elamur.ai/free/en/papers/voita-2019-analyzing-multi-head-self-attention/)
338. [**Multi-Task Deep Neural Networks for Natural Language Understanding**Xiaodong Liu, Pengcheng He, Weizhu Chen, et al.*2019 · 1,511 citations*](https://md.research.elamur.ai/free/en/papers/liu-2019-multi-task-deep-neural-networks/)
339. [**Multimodal Language Analysis in the Wild: CMU-MOSEI Dataset and Interpretable Dynamic Fusion Graph**AmirAli Bagher Zadeh, Paul Pu Liang, Soujanya Poria, et al.*2018 · 1,509 citations*](https://md.research.elamur.ai/free/en/papers/zadeh-2018-multimodal-language-analysis-wild-cmu/)
340. [**How Can We Know What Language Models Know?**Zhengbao Jiang, Frank F. Xu, Jun Araki, et al.*2020 · 1,501 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2020-how-can-we-know-what/)
341. [**CLIPScore: A Reference-free Evaluation Metric for Image Captioning**Jack Hessel, Ari Holtzman, Maxwell Forbes, et al.*2021 · 1,499 citations*](https://md.research.elamur.ai/free/en/papers/hessel-2021-clipscore-reference-free-evaluation-metric/)
342. [**Multiword Expressions: A Pain in the Neck for NLP**Ivan A. Sag, Timothy Baldwin, Francis Bond, et al.*2002 · 1,497 citations*](https://md.research.elamur.ai/free/en/papers/sag-2002-multiword-expressions-pain-neck-nlp/)
343. [**Deep Reinforcement Learning for Dialogue Generation**Jiwei Li, Will Monroe, Alan Ritter, et al.*2016 · 1,495 citations*](https://md.research.elamur.ai/free/en/papers/li-2016-deep-reinforcement-learning-dialogue-generation/)
344. [**The State and Fate of Linguistic Diversity and Inclusion in the NLP World**Pratik Joshi, Sebastin Santy, Amar Budhiraja, et al.*2020 · 1,494 citations*](https://md.research.elamur.ai/free/en/papers/joshi-2020-state-fate-linguistic-diversity-inclusion/)
345. [**LEGAL-BERT: The Muppets straight out of Law School**Ilias Chalkidis, Manos Fergadiotis, Prodromos Malakasiotis, et al.*2020 · 1,493 citations*](https://md.research.elamur.ai/free/en/papers/chalkidis-2020-legal-bert-muppets-straight-out/)
346. [**Pre-Training with Whole Word Masking for Chinese BERT**Yiming Cui, Wanxiang Che, Ting Liu, et al.*2019 · 1,490 citations*](https://md.research.elamur.ai/free/en/papers/cui-2019-pre-training-whole-word-masking/)
347. [**Automatic Word Sense Discrimination**Hinrich Schütze*1998 · 1,486 citations*](https://md.research.elamur.ai/free/en/papers/schutze-1998-automatic-word-sense-discrimination/)
348. [**Hedges: A Study in Meaning Criteria and the Logic of Fuzzy Concepts**George Lakoff*1973 · 1,486 citations*](https://md.research.elamur.ai/free/en/papers/lakoff-1973-hedges-study-meaning-criteria/)
349. [**Understanding Black-box Predictions via Influence Functions**Pang Wei Koh, Percy Liang*2017 · 1,481 citations*](https://md.research.elamur.ai/free/en/papers/koh-2017-understanding-black-box-predictions-influence/)
350. [**The Automatic Content Extraction (ACE) Program – Tasks, Data, and Evaluation**George Doddington, Alexis Mitchell, Mark Przybocki, et al.*2004 · 1,470 citations*](https://md.research.elamur.ai/free/en/papers/doddington-2004-automatic-content-extraction-ace-program/)
351. [**BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation**Junnan Li, Dongxu Li, Caiming Xiong, et al.*2022 · 1,469 citations*](https://md.research.elamur.ai/free/en/papers/li-2022-blip-bootstrapping-language-image-pre/)
352. [**Improved Statistical Alignment Models**Franz Josef Och, Hermann Ney*2000 · 1,467 citations*](https://md.research.elamur.ai/free/en/papers/och-2000-improved-statistical-alignment-models/)
353. [**Sentiment Analysis of Twitter Data**Apoorv Agarwal, Boyi Xie, Ilia Vovsha, et al.*2011 · 1,461 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2011-sentiment-analysis-twitter-data/)
354. [**Discriminative Training and Maximum Entropy Models for Statistical Machine Translation**Franz Josef Och, Hermann Ney*2002 · 1,461 citations*](https://md.research.elamur.ai/free/en/papers/och-2002-discriminative-training-maximum-entropy-models/)
355. [**Open Information Extraction from the Web**Michele Banko, Michael J. Cafarella, Stephen Soderland, et al.*2007 · 1,459 citations*](https://md.research.elamur.ai/free/en/papers/banko-2007-open-information-extraction-web/)
356. [**Named Entity Recognition in Tweets: An Experimental Study**Alan Ritter, Sam Clark, Mausam, et al.*2011 · 1,456 citations*](https://md.research.elamur.ai/free/en/papers/ritter-2011-named-entity-recognition-tweets-experimental/)
357. [**GLM: General Language Model Pretraining with Autoregressive Blank Infilling**Zhengxiao Du, Yujie Qian, Xiao Liu, et al.*2022 · 1,452 citations*](https://md.research.elamur.ai/free/en/papers/du-2022-glm-general-language-model-pretraining/)
358. [**Dialogue Act Modeling for Automatic Tagging and Recognition of Conversational Speech**Andreas Stolcke, Klaus Ries, Noah Coccaro, et al.*2000 · 1,450 citations*](https://md.research.elamur.ai/free/en/papers/stolcke-2000-dialogue-act-modeling-automatic-tagging/)
359. [**SemEval-2015 Task 12: Aspect Based Sentiment Analysis**Maria Pontiki, Dimitris Galanis, Haris Papageorgiou, et al.*2015 · 1,448 citations*](https://md.research.elamur.ai/free/en/papers/pontiki-2015-semeval-2015-task-12-aspect/)
360. [**A Probabilistic Earley Parser as a Psycholinguistic Model**John Hale*2001 · 1,448 citations*](https://md.research.elamur.ai/free/en/papers/hale-2001-probabilistic-earley-parser-as-psycholinguistic/)
361. [**Sequence-Level Knowledge Distillation**Yoon Kim, Alexander M. Rush*2016 · 1,445 citations*](https://md.research.elamur.ai/free/en/papers/kim-2016-sequence-level-knowledge-distillation/)
362. [**Zero-Shot Text-to-Image Generation**Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, et al.*2021 · 1,442 citations*](https://md.research.elamur.ai/free/en/papers/ramesh-2021-zero-shot-text-image-generation/)
363. [**Improved Techniques for Training GANs**Tim Salimans, Ian Goodfellow, Wojciech Zaremba, et al.*2016 · 1,428 citations*](https://md.research.elamur.ai/free/en/papers/salimans-2016-improved-techniques-training-gans/)
364. [**Sigmoid Loss for Language Image Pre-Training**Xiaohua Zhai, Basil Mustafa, Alexander Kolesnikov, et al.*2023 · 1,427 citations*](https://md.research.elamur.ai/free/en/papers/zhai-2023-sigmoid-loss-language-image-pre/)
365. [**DINOv2: Learning Robust Visual Features without Supervision**Maxime Oquab, Timothee Darcet, Theo Moutakanni, et al.*2023 · 1,426 citations*](https://md.research.elamur.ai/free/en/papers/oquab-2023-dinov2-learning-robust-visual-features/)
366. [**CoNLL-X Shared Task on Multilingual Dependency Parsing**Sabine Buchholz, Erwin Marsi*2006 · 1,426 citations*](https://md.research.elamur.ai/free/en/papers/buchholz-2006-conll-x-shared-task-multilingual/)
367. [**Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?**Sewon Min, Xinxi Lyu, Ari Holtzman, et al.*2022 · 1,425 citations*](https://md.research.elamur.ai/free/en/papers/min-2022-rethinking-role-demonstrations-what-makes/)
368. [**Justifying Recommendations using Distantly-Labeled Reviews and Fine-Grained Aspects**Jianmo Ni, Jiacheng Li, Julian McAuley*2019 · 1,424 citations*](https://md.research.elamur.ai/free/en/papers/ni-2019-justifying-recommendations-distantly-labeled-reviews/)
369. [**Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions**Richard Socher, Jeffrey Pennington, Eric H. Huang, et al.*2011 · 1,420 citations*](https://md.research.elamur.ai/free/en/papers/socher-2011-semi-supervised-recursive-autoencoders-predicting/)
370. [**Language-agnostic BERT Sentence Embedding**Fangxiaoyu Feng, Yinfei Yang, Daniel Cer, et al.*2020 · 1,413 citations*](https://md.research.elamur.ai/free/en/papers/feng-2020-language-agnostic-bert-sentence-embedding/)
371. [**Fast Graph Representation Learning with PyTorch Geometric**Matthias Fey, Jan Eric Lenssen*2019 · 1,413 citations*](https://md.research.elamur.ai/free/en/papers/fey-2019-fast-graph-representation-learning-pytorch/)
372. [**Unified Language Model Pre-training for Natural Language Understanding and Generation**Li Dong, Nan Yang, Wenhui Wang, et al.*2019 · 1,406 citations*](https://md.research.elamur.ai/free/en/papers/dong-2019-unified-language-model-pre-training/)
373. [**Sequence Transduction with Recurrent Neural Networks**Alex Graves*2012 · 1,406 citations*](https://md.research.elamur.ai/free/en/papers/graves-2012-sequence-transduction-recurrent-neural-networks/)
374. [**LAION-5B: An open large-scale dataset for training next generation image-text models**Christoph Schuhmann, Romain Beaumont, Richard Vencu, et al.*2022 · 1,403 citations*](https://md.research.elamur.ai/free/en/papers/schuhmann-2022-laion-5b-open-large-scale/)
375. [**Code Llama: Open Foundation Models for Code**Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, et al.*2024 · 1,399 citations*](https://md.research.elamur.ai/free/en/papers/roziere-2024-code-llama-open-foundation-models/)
376. [**Contextual String Embeddings for Sequence Labeling**Alan Akbik, Duncan Blythe, Roland Vollgraf*2018 · 1,398 citations*](https://md.research.elamur.ai/free/en/papers/akbik-2018-contextual-string-embeddings-sequence-labeling/)
377. [**Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data**Emily M. Bender, Alexander Koller*2020 · 1,375 citations*](https://md.research.elamur.ai/free/en/papers/bender-2020-climbing-nlu-meaning-form-understanding/)
378. [**NLTK: The Natural Language Toolkit**Steven Bird*2006 · 1,374 citations*](https://md.research.elamur.ai/free/en/papers/bird-2006-nltk-natural-language-toolkit/)
379. [**TVM: An Automated End-to-End Optimizing Compiler for Deep Learning**Tianqi Chen, Thierry Moreau, Ziheng Jiang, et al.*2018 · 1,372 citations*](https://md.research.elamur.ai/free/en/papers/chen-2018-tvm-automated-end-end-optimizing/)
380. [**brat: a Web-based Tool for NLP-Assisted Text Annotation**Pontus Stenetorp, Sampo Pyysalo, Goran Topić, et al.*2012 · 1,368 citations*](https://md.research.elamur.ai/free/en/papers/stenetorp-2012-brat-web-based-tool-nlp/)
381. [**wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations**Alexei Baevski, Henry Zhou, Abdelrahman Mohamed, et al.*2020 · 1,366 citations*](https://md.research.elamur.ai/free/en/papers/baevski-2020-wav2vec-2-0-framework-self/)
382. [**Let's Verify Step by Step**Hunter Lightman, Vineet Kosaraju, Yura Burda, et al.*2023 · 1,361 citations*](https://md.research.elamur.ai/free/en/papers/lightman-2023-let-s-verify-step-step/)
383. [**Generation and Comprehension of Unambiguous Object Descriptions**Junhua Mao, Jonathan Huang, Alexander Toshev, et al.*2015 · 1,361 citations*](https://md.research.elamur.ai/free/en/papers/mao-2015-generation-comprehension-unambiguous-object-descriptions/)
384. [**Improving Word Representations via Global Context and Multiple Word Prototypes**Eric Huang, Richard Socher, Christopher Manning, et al.*2012 · 1,357 citations*](https://md.research.elamur.ai/free/en/papers/huang-2012-improving-word-representations-global-context/)
385. [**Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments**Peter Anderson, Qi Wu, Damien Teney, et al.*2017 · 1,352 citations*](https://md.research.elamur.ai/free/en/papers/anderson-2017-vision-language-navigation-interpreting-visually/)
386. [**Learning Sentiment-Specific Word Embedding for Twitter Sentiment Classification**Duyu Tang, Furu Wei, Nan Yang, et al.*2014 · 1,346 citations*](https://md.research.elamur.ai/free/en/papers/tang-2014-learning-sentiment-specific-word-embedding/)
387. [**Sequence Level Training with Recurrent Neural Networks**Marc'Aurelio Ranzato, Sumit Chopra, Michael Auli, et al.*2015 · 1,338 citations*](https://md.research.elamur.ai/free/en/papers/ranzato-2015-sequence-level-training-recurrent-neural/)
388. [**Optimizing Semantic Coherence in Topic Models**David Mimno, Hanna Wallach, Edmund Talley, et al.*2011 · 1,338 citations*](https://md.research.elamur.ai/free/en/papers/mimno-2011-optimizing-semantic-coherence-topic-models/)
389. [**Early results for Named Entity Recognition with Conditional Random Fields, Feature Induction and Web-Enhanced Lexicons**Andrew McCallum, Wei Li*2003 · 1,336 citations*](https://md.research.elamur.ai/free/en/papers/mccallum-2003-early-results-named-entity-recognition/)
390. [**LaMDA: Language Models for Dialog Applications**Romal Thoppilan, Daniel De Freitas, Jamie Hall, et al.*2022 · 1,326 citations*](https://md.research.elamur.ai/free/en/papers/thoppilan-2022-lamda-language-models-dialog-applications/)
391. [**Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment**Di Jin, Zhijing Jin, Joey Tianyi Zhou, et al.*2019 · 1,326 citations*](https://md.research.elamur.ai/free/en/papers/jin-2019-bert-really-robust-strong-baseline/)
392. [**Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models**Ryan Kiros, Ruslan Salakhutdinov, Richard S. Zemel*2014 · 1,325 citations*](https://md.research.elamur.ai/free/en/papers/kiros-2014-unifying-visual-semantic-embeddings-multimodal/)
393. [**Parameter-efficient fine-tuning of large-scale pre-trained language models**Ning Ding, Yujia Qin, Guang You Yang, et al.*2023 · 1,324 citations*](https://md.research.elamur.ai/free/en/papers/ding-2023-parameter-efficient-fine-tuning-large/)
394. [**Deep Biaffine Attention for Neural Dependency Parsing**Timothy Dozat, Christopher D. Manning*2016 · 1,323 citations*](https://md.research.elamur.ai/free/en/papers/dozat-2016-deep-biaffine-attention-neural-dependency/)
395. [**Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation**Nils Reimers, Iryna Gurevych*2020 · 1,320 citations*](https://md.research.elamur.ai/free/en/papers/reimers-2020-making-monolingual-sentence-embeddings-multilingual/)
396. [**VideoBERT: A Joint Model for Video and Language Representation Learning**Chen Sun, Austin Myers, Carl Vondrick, et al.*2019 · 1,318 citations*](https://md.research.elamur.ai/free/en/papers/sun-2019-videobert-joint-model-video-language/)
397. [**DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing**Pengcheng He, Jianfeng Gao, Weizhu Chen*2021 · 1,316 citations*](https://md.research.elamur.ai/free/en/papers/he-2021-debertav3-improving-deberta-using-electra/)
398. [**Language Modeling with Gated Convolutional Networks**Yann N. Dauphin, Angela Fan, Michael Auli, et al.*2016 · 1,315 citations*](https://md.research.elamur.ai/free/en/papers/dauphin-2016-language-modeling-gated-convolutional-networks/)
399. [**SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter**Valerio Basile, Cristina Bosco, Elisabetta Fersini, et al.*2019 · 1,312 citations*](https://md.research.elamur.ai/free/en/papers/basile-2019-semeval-2019-task-5-multilingual/)
400. [**Coarse-to-Fine n-Best Parsing and MaxEnt Discriminative Reranking**Eugene Charniak, Mark Johnson*2005 · 1,312 citations*](https://md.research.elamur.ai/free/en/papers/charniak-2005-coarse-fine-n-best-parsing/)
401. [**Long Short-Term Memory-Networks for Machine Reading**Jianpeng Cheng, Li Dong, Mirella Lapata*2016 · 1,307 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2016-long-short-term-memory-networks/)
402. [**AraBERT: Transformer-based Model for Arabic Language Understanding**Wissam Antoun, Fady Baly, Hazem Hajj*2020 · 1,302 citations*](https://md.research.elamur.ai/free/en/papers/antoun-2020-arabert-transformer-based-model-arabic/)
403. [**BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions**Christopher Clark, Kenton Lee, Ming-Wei Chang, et al.*2019 · 1,301 citations*](https://md.research.elamur.ai/free/en/papers/clark-2019-boolq-exploring-surprising-difficulty-natural/)
404. [**A Machine Learning Approach to Coreference Resolution of Noun Phrases**Wee Meng Soon, Hwee Tou Ng, Daniel Chung Yong Lim*2001 · 1,289 citations*](https://md.research.elamur.ai/free/en/papers/soon-2001-machine-learning-approach-coreference-resolution/)
405. [**COMET: Commonsense Transformers for Automatic Knowledge Graph Construction**Antoine Bosselut, Hannah Rashkin, Maarten Sap, et al.*2019 · 1,287 citations*](https://md.research.elamur.ai/free/en/papers/bosselut-2019-comet-commonsense-transformers-automatic-knowledge/)
406. [**A Comprehensive Overview of Large Language Models**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,286 citations*](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/)
407. [**A Program for Aligning Sentences in Bilingual Corpora**William A. Gale, Kenneth W. Church*1993 · 1,284 citations*](https://md.research.elamur.ai/free/en/papers/gale-1993-program-aligning-sentences-bilingual-corpora/)
408. [**ReferItGame: Referring to Objects in Photographs of Natural Scenes**Sahar Kazemzadeh, Vicente Ordonez, Mark Matten, et al.*2014 · 1,282 citations*](https://md.research.elamur.ai/free/en/papers/kazemzadeh-2014-referitgame-referring-objects-photographs-natural/)
409. [**RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models**Samuel Gehman, Suchin Gururangan, Maarten Sap, et al.*2020 · 1,281 citations*](https://md.research.elamur.ai/free/en/papers/gehman-2020-realtoxicityprompts-evaluating-neural-toxic-degeneration/)
410. [**CTRL: A Conditional Transformer Language Model for Controllable Generation**Nitish Shirish Keskar, Bryan McCann, Lav R. Varshney, et al.*2019 · 1,280 citations*](https://md.research.elamur.ai/free/en/papers/keskar-2019-ctrl-conditional-transformer-language-model/)
411. [**End-to-end Neural Coreference Resolution**Kenton Lee, Luheng He, Mike Lewis, et al.*2017 · 1,280 citations*](https://md.research.elamur.ai/free/en/papers/lee-2017-end-end-neural-coreference-resolution/)
412. [**Deep Convolutional Neural Networks for Sentiment Analysis of Short Texts**Cícero dos Santos, Maíra Gatti*2014 · 1,279 citations*](https://md.research.elamur.ai/free/en/papers/santos-2014-deep-convolutional-neural-networks-sentiment/)
413. [**V-Measure: A Conditional Entropy-Based External Cluster Evaluation Measure**Andrew Rosenberg, Julia Hirschberg*2007 · 1,279 citations*](https://md.research.elamur.ai/free/en/papers/rosenberg-2007-vmeasure-conditional-entropy-cluster-evaluation/)
414. [**CamemBERT: a Tasty French Language Model**Louis Martin, Benjamin Muller, Pedro Javier Ortiz Suárez, et al.*2019 · 1,267 citations*](https://md.research.elamur.ai/free/en/papers/martin-2019-camembert-tasty-french-language-model/)
415. [**The Rise and Potential of Large Language Model Based Agents: A Survey**Zhiheng Xi, Wenxiang Chen, Xin Guo, et al.*2023 · 1,264 citations*](https://md.research.elamur.ai/free/en/papers/xi-2023-rise-potential-large-language/)
416. [**Non-Projective Dependency Parsing using Spanning Tree Algorithms**Ryan McDonald, Fernando Pereira, Kiril Ribarov, et al.*2005 · 1,259 citations*](https://md.research.elamur.ai/free/en/papers/mcdonald-2005-non-projective-dependency-parsing-spanning/)
417. [**Neural Responding Machine for Short-Text Conversation**Lifeng Shang, Zhengdong Lu, Hang Li*2015 · 1,253 citations*](https://md.research.elamur.ai/free/en/papers/shang-2015-neural-responding-machine-short-text/)
418. [**Optuna: A Next-generation Hyperparameter Optimization Framework**Takuya Akiba, Shotaro Sano, Toshihiko Yanase, et al.*2019 · 1,246 citations*](https://md.research.elamur.ai/free/en/papers/akiba-2019-optuna-next-generation-hyperparameter-optimization/)
419. [**Learning Accurate, Compact, and Interpretable Tree Annotation**Slav Petrov, Leon Barrett, Romain Thibaux, et al.*2006 · 1,244 citations*](https://md.research.elamur.ai/free/en/papers/petrov-2006-learning-accurate-compact-interpretable-tree/)
420. [**Assessing the Ability of LSTMs to Learn Syntax-Sensitive Dependencies**Tal Linzen, Emmanuel Dupoux, Yoav Goldberg*2016 · 1,243 citations*](https://md.research.elamur.ai/free/en/papers/linzen-2016-assessing-ability-lstms-learn-syntax/)
421. [**What Makes Good In-Context Examples for GPT-3?**Jiachang Liu, Dinghan Shen, Yizhe Zhang, et al.*2022 · 1,238 citations*](https://md.research.elamur.ai/free/en/papers/liu-2022-what-makes-good-context-examples/)
422. [**Observed versus latent features for knowledge base and text inference**Kristina Toutanova, Danqi Chen*2015 · 1,238 citations*](https://md.research.elamur.ai/free/en/papers/toutanova-2015-observed-versus-latent-features-knowledge/)
423. [**Latent Retrieval for Weakly Supervised Open Domain Question Answering**Kenton Lee, Ming-Wei Chang, Kristina Toutanova*2019 · 1,236 citations*](https://md.research.elamur.ai/free/en/papers/lee-2019-latent-retrieval-weakly-supervised-open/)
424. [**A Structural Probe for Finding Syntax in Word Representations**John Hewitt, Christopher D. Manning*2019 · 1,232 citations*](https://md.research.elamur.ai/free/en/papers/hewitt-2019-structural-probe-finding-syntax-word/)
425. [**Publicly Available Clinical BERT Embeddings**Emily Alsentzer, John R. Murphy, Willie Boag, et al.*2019 · 1,226 citations*](https://md.research.elamur.ai/free/en/papers/alsentzer-2019-publicly-available-clinical-bert-embeddings/)

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