---
title: "Artificial Intelligence — papers, page 11 — Elamur Research"
description: "Artificial Intelligence: 8,886 papers of the Elamur Research library · page 11 of 90 · 926–1025, the most cited first — our summary of each, its…"
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---
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# 🤖 Artificial Intelligence

8,886 papers · page 11 of 90 · 926–1025 · the most cited first · [all shelves](https://md.research.elamur.ai/free/en/shelves/)

Artificial Intelligence is a subfield of Computer Science in the OpenAlex classification of science. The topics most of its papers here are on: «Natural Language Processing Techniques», «Topic Modeling», «Speech and dialogue systems».

## Papers (8,886)

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926. [**A simple neural network module for relational reasoning**Adam Santoro, David Raposo, David G. T. Barrett, et al.*2017 · 593 citations*](https://md.research.elamur.ai/free/en/papers/santoro-2017-simple-neural-network-module-relational/)
927. [**Weakly Supervised Learning of Semantic Parsers for Mapping Instructions to Actions**Yoav Artzi, Luke Zettlemoyer*2013 · 593 citations*](https://md.research.elamur.ai/free/en/papers/artzi-2013-weakly-supervised-learning-semantic-parsers/)
928. [**The Flan Collection: Designing Data and Methods for Effective Instruction Tuning**Shayne Longpre, Le Hou, Tu Vu, et al.*2023 · 592 citations*](https://md.research.elamur.ai/free/en/papers/longpre-2023-flan-collection-designing-data-methods/)
929. [**Deep Semantic Role Labeling: What Works and What's Next**Luheng He, Kenton Lee, Mike Lewis, et al.*2017 · 592 citations*](https://md.research.elamur.ai/free/en/papers/he-2017-deep-semantic-role-labeling-what/)
930. [**Relation Extraction: Perspective from Convolutional Neural Networks**Thien Huu Nguyen, Ralph Grishman*2015 · 592 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2015-relation-extraction-perspective-convolutional-neural/)
931. [**Fine-grained Analysis of Sentence Embeddings Using Auxiliary Prediction Tasks**Yossi Adi, Einat Kermany, Yonatan Belinkov, et al.*2016 · 591 citations*](https://md.research.elamur.ai/free/en/papers/adi-2016-fine-grained-analysis-sentence-embeddings/)
932. [**Fine-grained Opinion Mining with Recurrent Neural Networks and Word Embeddings**Pengfei Liu, Shafiq Joty, Helen Meng*2015 · 590 citations*](https://md.research.elamur.ai/free/en/papers/liu-2015-fine-grained-opinion-mining-recurrent/)
933. [**Automatic Keyphrase Extraction: A Survey of the State of the Art**Kazi Saidul Hasan, Vincent Ng*2014 · 590 citations*](https://md.research.elamur.ai/free/en/papers/hasan-2014-automatic-keyphrase-extraction-survey-state/)
934. [**Evaluating Gender Bias in Machine Translation**Gabriel Stanovsky, Noah A. Smith, Luke Zettlemoyer*2019 · 589 citations*](https://md.research.elamur.ai/free/en/papers/stanovsky-2019-evaluating-gender-bias-machine-translation/)
935. [**Measuring Bias in Contextualized Word Representations**Keita Kurita, Nidhi Vyas, Ayush Pareek, et al.*2019 · 588 citations*](https://md.research.elamur.ai/free/en/papers/kurita-2019-measuring-bias-contextualized-word-representations/)
936. [**What do you learn from context? Probing for sentence structure in contextualized word representations**Ian Tenney, Patrick Xia, Berlin Chen, et al.*2019 · 588 citations*](https://md.research.elamur.ai/free/en/papers/tenney-2019-learn-context-probing-sentence-structure/)
937. [**DataStories at SemEval-2017 Task 4: Deep LSTM with Attention for Message-level and Topic-based Sentiment Analysis**Christos Baziotis, Nikos Pelekis, Christos Doulkeridis*2017 · 588 citations*](https://md.research.elamur.ai/free/en/papers/baziotis-2017-datastories-semeval-2017-task-4/)
938. [**PAWS: Paraphrase Adversaries from Word Scrambling**Yuan Zhang, Jason Baldridge, Luheng He*2019 · 587 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2019-paws-paraphrase-adversaries-word-scrambling/)
939. [**Dissecting Contextual Word Embeddings: Architecture and Representation**Matthew E. Peters, Mark Neumann, Luke Zettlemoyer, et al.*2018 · 587 citations*](https://md.research.elamur.ai/free/en/papers/peters-2018-dissecting-contextual-word-embeddings-architecture/)
940. [**Lexical Normalisation of Short Text Messages: Makn Sens a #twitter**Bo Han, Timothy Baldwin*2011 · 587 citations*](https://md.research.elamur.ai/free/en/papers/han-2011-lexical-normalisation-short-text-messages/)
941. [**Instruction-Following Evaluation for Large Language Models**Jeffrey Zhou, Tianjian Lu, Swaroop Mishra, et al.*2023 · 586 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-instruction-following-evaluation-large-language/)
942. [**QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension**Adams Wei Yu, David Dohan, Minh-Thang Luong, et al.*2018 · 586 citations*](https://md.research.elamur.ai/free/en/papers/yu-2018-qanet-combining-local-convolution-global/)
943. [**Deep multi-task learning with low level tasks supervised at lower layers**Anders Søgaard, Yoav Goldberg*2016 · 586 citations*](https://md.research.elamur.ai/free/en/papers/sogaard-2016-deep-multi-task-learning-low/)
944. [**Chinese Segmentation and New Word Detection using Conditional Random Fields**Fuchun Peng, Fangfang Feng, Andrew McCallum*2004 · 586 citations*](https://md.research.elamur.ai/free/en/papers/peng-2004-chinese-segmentation-new-word-detection/)
945. [**The Automated Acquisition of Topic Signatures for Text Summarization**Chin-Yew Lin, Eduard Hovy*2000 · 586 citations*](https://md.research.elamur.ai/free/en/papers/lin-2000-automated-acquisition-topic-signatures-text/)
946. [**A Robustly Optimized BERT Pre-training Approach with Post-training**Liu Zhuang, Lin Wayne, Shi Ya, et al.*2021 · 585 citations*](https://md.research.elamur.ai/free/en/papers/zhuang-2021-robustly-optimized-bert-pre-training/)
947. [**Minimum Bayes-Risk Decoding for Statistical Machine Translation**Shankar Kumar, William Byrne*2004 · 585 citations*](https://md.research.elamur.ai/free/en/papers/kumar-2004-minimum-bayes-risk-decoding-statistical/)
948. [**s1: Simple test-time scaling**Niklas Muennighoff, Zitong Yang, Weijia Shi, et al.*2025 · 584 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2025-s1-simple-test-time-scaling/)
949. [**AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation**Qingyun Wu, Gagan Bansal, Jieyu Zhang, et al.*2023 · 584 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-autogen-enabling-next-gen-llm/)
950. [**Hate Speech Dataset from a White Supremacy Forum**Ona de Gibert, Naiara Perez, Aitor García-Pablos, et al.*2018 · 583 citations*](https://md.research.elamur.ai/free/en/papers/gibert-2018-hate-speech-dataset-white-supremacy/)
951. [**Top Accuracy and Fast Dependency Parsing is not a Contradiction**Bernd Bohnet*2010 · 583 citations*](https://md.research.elamur.ai/free/en/papers/bohnet-2010-top-accuracy-fast-dependency-parsing/)
952. [**Dear Sir or Madam, May I Introduce the GYAFC Dataset: Corpus, Benchmarks and Metrics for Formality Style Transfer**Sudha Rao, Joel Tetreault*2018 · 582 citations*](https://md.research.elamur.ai/free/en/papers/rao-2018-dear-sir-or-madam-may/)
953. [**Unsupervised Large-Vocabulary Word Sense Disambiguation with Graph-based Algorithms for Sequence Data Labeling**Rada Mihalcea*2005 · 582 citations*](https://md.research.elamur.ai/free/en/papers/mihalcea-2005-unsupervised-large-vocabulary-word-sense/)
954. [**Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models**Jianmo Ni, Gustavo Hernandez Abrego, Noah Constant, et al.*2021 · 581 citations*](https://md.research.elamur.ai/free/en/papers/ni-2021-sentence-t5-scalable-sentence-encoders/)
955. [**Towards a Human-like Open-Domain Chatbot**Daniel Adiwardana, Minh-Thang Luong, David R. So, et al.*2020 · 581 citations*](https://md.research.elamur.ai/free/en/papers/adiwardana-2020-towards-human-like-open-domain/)
956. [**Dynamic Coattention Networks For Question Answering**Caiming Xiong, Victor Zhong, Richard Socher*2016 · 581 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2016-dynamic-coattention-networks-question-answering/)
957. [**Racial Bias in Hate Speech and Abusive Language Detection Datasets**Thomas Davidson, Debasmita Bhattacharya, Ingmar Weber*2019 · 580 citations*](https://md.research.elamur.ai/free/en/papers/davidson-2019-racial-bias-hate-speech-abusive/)
958. [**The WebNLG Challenge: Generating Text from RDF Data**Claire Gardent, Anastasia Shimorina, Shashi Narayan, et al.*2017 · 580 citations*](https://md.research.elamur.ai/free/en/papers/gardent-2017-webnlg-challenge-generating-text-rdf/)
959. [**Solving General Arithmetic Word Problems**Subhro Roy, Dan Roth*2015 · 580 citations*](https://md.research.elamur.ai/free/en/papers/roy-2015-solving-general-arithmetic-word-problems/)
960. [**Learning subjective nouns using extraction pattern bootstrapping**Ellen Riloff, Janyce Wiebe, Theresa Wilson*2003 · 580 citations*](https://md.research.elamur.ai/free/en/papers/riloff-2003-learning-subjective-nouns-extraction-pattern/)
961. [**Refining Event Extraction through Cross-Document Inference**Heng Ji, Ralph Grishman*2008 · 577 citations*](https://md.research.elamur.ai/free/en/papers/ji-2008-refining-event-extraction-through-cross/)
962. [**Improving Machine Translation Performance by Exploiting Non-Parallel Corpora**Dragos Stefan Munteanu, Daniel Marcu*2005 · 577 citations*](https://md.research.elamur.ai/free/en/papers/munteanu-2005-improving-machine-translation-performance-exploiting/)
963. [**Relation Classification via Multi-Level Attention CNNs**Linlin Wang, Zhu Cao, Gerard de Melo, et al.*2016 · 576 citations*](https://md.research.elamur.ai/free/en/papers/wang-2016-relation-classification-multi-level-attention/)
964. [**Minimum Risk Training for Neural Machine Translation**Shiqi Shen, Yong Cheng, Zhongjun He, et al.*2015 · 576 citations*](https://md.research.elamur.ai/free/en/papers/shen-2015-minimum-risk-training-neural-machine/)
965. [**An efficient framework for learning sentence representations**Lajanugen Logeswaran, Honglak Lee*2018 · 575 citations*](https://md.research.elamur.ai/free/en/papers/logeswaran-2018-efficient-framework-learning-sentence-representations/)
966. [**Examining Gender and Race Bias in Two Hundred Sentiment Analysis Systems**Svetlana Kiritchenko, Saif Mohammad*2018 · 574 citations*](https://md.research.elamur.ai/free/en/papers/kiritchenko-2018-examining-gender-race-bias-two/)
967. [**Multi-grained Attention Network for Aspect-Level Sentiment Classification**Feifan Fan, Yansong Feng, Dongyan Zhao*2018 · 573 citations*](https://md.research.elamur.ai/free/en/papers/fan-2018-multi-grained-attention-network-aspect/)
968. [**A Hierarchical Bayesian Language Model Based On Pitman-Yor Processes**Yee Whye Teh*2006 · 573 citations*](https://md.research.elamur.ai/free/en/papers/teh-2006-hierarchical-bayesian-language-model-based/)
969. [**ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection**Thomas Hartvigsen, Saadia Gabriel, Hamid Palangi, et al.*2022 · 571 citations*](https://md.research.elamur.ai/free/en/papers/hartvigsen-2022-toxigen-large-scale-machine-generated/)
970. [**PhoBERT: Pre-trained language models for Vietnamese**Dat Quoc Nguyen, Anh Tuan Nguyen*2020 · 571 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2020-phobert-pre-trained-language-models/)
971. [**AudioLM: a Language Modeling Approach to Audio Generation**Zalan Borsos, Raphael Marinier, Damien Vincent, et al.*2022 · 570 citations*](https://md.research.elamur.ai/free/en/papers/borsos-2022-audiolm-language-modeling-approach-audio/)
972. [**Multilingual Universal Sentence Encoder for Semantic Retrieval**Yinfei Yang, Daniel Cer, Amin Ahmad, et al.*2020 · 570 citations*](https://md.research.elamur.ai/free/en/papers/yang-2020-multilingual-universal-sentence-encoder-semantic/)
973. [**An Unsupervised Aspect-Sentiment Model for Online Reviews**Samuel Brody, Noemie Elhadad*2010 · 570 citations*](https://md.research.elamur.ai/free/en/papers/brody-2010-unsupervised-aspect-sentiment-model-online/)
974. [**Extractive Summarization as Text Matching**Ming Zhong, Pengfei Liu, Yiran Chen, et al.*2020 · 569 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2020-extractive-summarization-as-text-matching/)
975. [**A Survey on Recent Advances in Named Entity Recognition from Deep Learning models**Vikas Yadav, Steven Bethard*2018 · 569 citations*](https://md.research.elamur.ai/free/en/papers/yadav-2018-survey-recent-advances-named-entity/)
976. [**Collecting Image Annotations Using Amazon's Mechanical Turk**Cyrus Rashtchian, Peter Young, Micah Hodosh, et al.*2010 · 569 citations*](https://md.research.elamur.ai/free/en/papers/rashtchian-2010-collecting-image-annotations-amazon-s/)
977. [**Representing Text Chunks**Erik F. Tjong Kim Sang, Jorn Veenstra*1999 · 569 citations*](https://md.research.elamur.ai/free/en/papers/sang-1999-representing-text-chunks/)
978. [**Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting**Miles Turpin, Julian Michael, Ethan Perez, et al.*2023 · 568 citations*](https://md.research.elamur.ai/free/en/papers/turpin-2023-language-models-don-t-always/)
979. [**Learning How to Ask: Querying LMs with Mixtures of Soft Prompts**Guanghui Qin, Jason Eisner*2021 · 568 citations*](https://md.research.elamur.ai/free/en/papers/qin-2021-learning-ask-querying-lms-mixtures/)
980. [**Massive Exploration of Neural Machine Translation Architectures**Denny Britz, Anna Goldie, Minh-Thang Luong, et al.*2017 · 568 citations*](https://md.research.elamur.ai/free/en/papers/britz-2017-massive-exploration-neural-machine-translation/)
981. [**Sentence Simplification with Deep Reinforcement Learning**Xingxing Zhang, Mirella Lapata*2017 · 568 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2017-sentence-simplification-deep-reinforcement-learning/)
982. [**Incremental Parsing with the Perceptron Algorithm**Michael Collins, Brian Roark*2004 · 568 citations*](https://md.research.elamur.ai/free/en/papers/collins-2004-incremental-parsing-perceptron-algorithm/)
983. [**Development and Use of a Gold-Standard Data Set for Subjectivity Classifications**Janyce M. Wiebe, Rebecca F. Bruce, Thomas P. O'Hara*1999 · 568 citations*](https://md.research.elamur.ai/free/en/papers/wiebe-1999-development-use-gold-standard-data/)
984. [**Plug and Play Language Models: A Simple Approach to Controlled Text Generation**Sumanth Dathathri, Andrea Madotto, Janice Lan, et al.*2019 · 567 citations*](https://md.research.elamur.ai/free/en/papers/dathathri-2019-plug-play-language-models-simple/)
985. [**Supertagging: An Approach to Almost Parsing**Srinivas Bangalore, Aravind K. Joshi*1999 · 567 citations*](https://md.research.elamur.ai/free/en/papers/bangalore-1999-supertagging-approach-almost-parsing/)
986. [**ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs**Yujia Qin, Shihao Liang, Yining Ye, et al.*2023 · 566 citations*](https://md.research.elamur.ai/free/en/papers/qin-2023-toolllm-facilitating-large-language-models/)
987. [**Parallel Implementations of Word Alignment Tool**Qin Gao, Stephan Vogel*2008 · 566 citations*](https://md.research.elamur.ai/free/en/papers/gao-2008-parallel-implementations-word-alignment-tool/)
988. [**Improving Factuality and Reasoning in Language Models through Multiagent Debate**Yilun Du, Shuang Li, Antonio Torralba, et al.*2023 · 565 citations*](https://md.research.elamur.ai/free/en/papers/du-2023-improving-factuality-reasoning-language-models/)
989. [**Galactica: A Large Language Model for Science**Ross Taylor, Marcin Kardas, Guillem Cucurull, et al.*2022 · 565 citations*](https://md.research.elamur.ai/free/en/papers/taylor-2022-galactica-large-language-model-science/)
990. [**AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models**Wanjun Zhong, Ruixiang Cui, Yiduo Guo, et al.*2024 · 564 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2024-agieval-human-centric-benchmark-evaluating/)
991. [**LLM-Planner: Few-Shot Grounded Planning for Embodied Agents with Large Language Models**Chan Hee Song, Jiaman Wu, Clayton Washington, et al.*2022 · 564 citations*](https://md.research.elamur.ai/free/en/papers/song-2022-llm-planner-few-shot-grounded/)
992. [**Improving Multimodal Fusion with Hierarchical Mutual Information Maximization for Multimodal Sentiment Analysis**Wei Han, Hui Chen, Soujanya Poria*2021 · 564 citations*](https://md.research.elamur.ai/free/en/papers/han-2021-improving-multimodal-fusion-hierarchical-mutual/)
993. [**Large Language Models Can Self-Improve**Jiaxin Huang, Shixiang Gu, Le Hou, et al.*2023 · 563 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-large-language-models-can-self/)
994. [**Leveraging Pre-trained Checkpoints for Sequence Generation Tasks**Sascha Rothe, Shashi Narayan, Aliaksei Severyn*2019 · 563 citations*](https://md.research.elamur.ai/free/en/papers/rothe-2019-leveraging-pre-trained-checkpoints-sequence/)
995. [**MIND: A Large-scale Dataset for News Recommendation**Fangzhao Wu, Ying Qiao, Jiun-Hung Chen, et al.*2020 · 562 citations*](https://md.research.elamur.ai/free/en/papers/wu-2020-mind-large-scale-dataset-news/)
996. [**Unsupervised Modeling of Twitter Conversations**Alan Ritter, Colin Cherry, Bill Dolan*2010 · 561 citations*](https://md.research.elamur.ai/free/en/papers/ritter-2010-unsupervised-modeling-twitter-conversations/)
997. [**Finding Parts in Very Large Corpora**Matthew Berland, Eugene Charniak*1999 · 561 citations*](https://md.research.elamur.ai/free/en/papers/berland-1999-finding-parts-very-large-corpora/)
998. [**Extracting Opinions, Opinion Holders, and Topics Expressed in Online News Media Text**Soo-Min Kim, Eduard Hovy*2006 · 560 citations*](https://md.research.elamur.ai/free/en/papers/kim-2006-extracting-opinions-opinion-holders-topics/)
999. [**The Fisher Corpus: a Resource for the Next Generations of Speech-to-Text**Christopher Cieri, David Miller, Kevin Walker*2004 · 560 citations*](https://md.research.elamur.ai/free/en/papers/cieri-2004-fisher-corpus-resource-next-generations/)
1000. [**Sentence Level Discourse Parsing using Syntactic and Lexical Information**Radu Soricut, Daniel Marcu*2003 · 560 citations*](https://md.research.elamur.ai/free/en/papers/soricut-2003-sentence-level-discourse-parsing-syntactic/)
1001. [**A Categorical Archive of ChatGPT Failures**Ali Borji*2023 · 558 citations*](https://md.research.elamur.ai/free/en/papers/borji-2023-categorical-archive-chatgpt-failures/)
1002. [**Neural Legal Judgment Prediction in English**Ilias Chalkidis, Ion Androutsopoulos, Nikolaos Aletras*2019 · 558 citations*](https://md.research.elamur.ai/free/en/papers/chalkidis-2019-neural-legal-judgment-prediction-english/)
1003. [**Neural Text Summarization: A Critical Evaluation**Wojciech Kryscinski, Nitish Shirish Keskar, Bryan McCann, et al.*2019 · 558 citations*](https://md.research.elamur.ai/free/en/papers/kryscinski-2019-neural-text-summarization-critical-evaluation/)
1004. [**Simple and Effective Multi-Paragraph Reading Comprehension**Christopher Clark, Matt Gardner*2017 · 558 citations*](https://md.research.elamur.ai/free/en/papers/clark-2017-simple-effective-multi-paragraph-reading/)
1005. [**MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models**Longhui Yu, Weisen Jiang, Han Shi, et al.*2023 · 556 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-metamath-bootstrap-your-own-mathematical/)
1006. [**Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges**Naveen Arivazhagan, Ankur Bapna, Orhan Firat, et al.*2019 · 556 citations*](https://md.research.elamur.ai/free/en/papers/arivazhagan-2019-massively-multilingual-neural-machine-translation/)
1007. [**gpt-oss-120b & gpt-oss-20b Model Card**OpenAI: Sandhini Agarwal, Lama Ahmad, Jason Ai, et al.*2025 · 555 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2025-gpt-oss-120b-gpt-oss/)
1008. [**Style Transfer Through Back-Translation**Shrimai Prabhumoye, Yulia Tsvetkov, Ruslan Salakhutdinov, et al.*2018 · 555 citations*](https://md.research.elamur.ai/free/en/papers/prabhumoye-2018-style-transfer-through-back-translation/)
1009. [**Event Detection and Domain Adaptation with Convolutional Neural Networks**Thien Huu Nguyen, Ralph Grishman*2015 · 555 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2015-event-detection-domain-adaptation-convolutional/)
1010. [**A Monolingual Tree-based Translation Model for Sentence Simplification**Zhemin Zhu, Delphine Bernhard, Iryna Gurevych*2010 · 555 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2010-monolingual-tree-based-translation-model/)
1011. [**Reducing Transformer Depth on Demand with Structured Dropout**Angela Fan, Edouard Grave, Armand Joulin*2019 · 554 citations*](https://md.research.elamur.ai/free/en/papers/fan-2019-reducing-transformer-depth-demand-structured/)
1012. [**The Best of Both Worlds: Combining Recent Advances in Neural Machine Translation**Mia Xu Chen, Orhan Firat, Ankur Bapna, et al.*2018 · 554 citations*](https://md.research.elamur.ai/free/en/papers/chen-2018-best-both-worlds-combining-recent/)
1013. [**Cross-Sentence N-ary Relation Extraction with Graph LSTMs**Nanyun Peng, Hoifung Poon, Chris Quirk, et al.*2017 · 554 citations*](https://md.research.elamur.ai/free/en/papers/peng-2017-cross-sentence-n-ary-relation/)
1014. [**How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection**Biyang Guo, Xin Zhang, Ziyuan Wang, et al.*2023 · 553 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-close-chatgpt-human-experts-comparison/)
1015. [**XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization**Junjie Hu, Sebastian Ruder, Aditya Siddhant, et al.*2020 · 552 citations*](https://md.research.elamur.ai/free/en/papers/hu-2020-xtreme-massively-multilingual-multi-task/)
1016. [**Learning to Compose Neural Networks for Question Answering**Jacob Andreas, Marcus Rohrbach, Trevor Darrell, et al.*2016 · 552 citations*](https://md.research.elamur.ai/free/en/papers/andreas-2016-learning-compose-neural-networks-question/)
1017. [**Deterministic Non-Autoregressive Neural Sequence Modeling by Iterative Refinement**Jason Lee, Elman Mansimov, Kyunghyun Cho*2018 · 551 citations*](https://md.research.elamur.ai/free/en/papers/lee-2018-deterministic-non-autoregressive-neural-sequence/)
1018. [**Fully Character-Level Neural Machine Translation without Explicit Segmentation**Jason Lee, Kyunghyun Cho, Thomas Hofmann*2017 · 551 citations*](https://md.research.elamur.ai/free/en/papers/lee-2017-fully-character-level-neural-machine/)
1019. [**Batch Tuning Strategies for Statistical Machine Translation**Colin Cherry, George Foster*2012 · 549 citations*](https://md.research.elamur.ai/free/en/papers/cherry-2012-batch-tuning-strategies-statistical-machine/)
1020. [**Dependency Treelet Translation: Syntactically Informed Phrasal SMT**Chris Quirk, Arul Menezes, Colin Cherry*2005 · 549 citations*](https://md.research.elamur.ai/free/en/papers/quirk-2005-dependency-treelet-translation-syntactically-informed/)
1021. [**Sentence Fusion for Multidocument News Summarization**Regina Barzilay, Kathleen R. McKeown*2005 · 549 citations*](https://md.research.elamur.ai/free/en/papers/barzilay-2005-sentence-fusion-multidocument-news-summarization/)
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