--- title: "Papers of 2020 — page 2" description: "Papers of 2020: 596 papers of the Elamur Research library — what each work is about in our own words, its ideas, references and who cites it." canonical: "https://research.elamur.ai/free/en/papers/2020/page/2/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/2020/page/2/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / 2020 # Papers of 2020 — page 2 596 papers · [all years](https://md.research.elamur.ai/free/en/papers/) [← prev](https://md.research.elamur.ai/free/en/papers/2020/) [1](https://md.research.elamur.ai/free/en/papers/2020/) **2** [3](https://md.research.elamur.ai/free/en/papers/2020/page/3/) … [6](https://md.research.elamur.ai/free/en/papers/2020/page/6/) [next →](https://md.research.elamur.ai/free/en/papers/2020/page/3/) - [Bridging Anaphora Resolution as Question Answering](https://md.research.elamur.ai/free/en/papers/hou-2020-bridging-anaphora-resolution-as-question/) — Yufang Hou · English - [Bridging Resolution: A Survey of the State of the Art](https://md.research.elamur.ai/free/en/papers/kobayashi-2020-bridging-resolution-survey-state-art/) — Hideo Kobayashi, Vincent Ng · Proceedings of the 28th International… - [Bridging Textual and Tabular Data for Cross-Domain Text-to-SQL Semantic Parsing](https://md.research.elamur.ai/free/en/papers/lin-2020-bridging-textual-tabular-data-cross/) — Xi Victoria Lin, Richard Socher, Caiming Xiong · Findings of the Association for Computational… - [Building a Bridge: A Method for Image-Text Sarcasm Detection Without Pretraining on Image-Text Data](https://md.research.elamur.ai/free/en/papers/wang-2020-building-bridge-method-image-text/) — Xinyu Wang, Xiaowen Sun, Tan Yang, et al. · Proceedings of the First International Workshop… - [Building a Hebrew Semantic Role Labeling Lexical Resource from Parallel Movie Subtitles](https://md.research.elamur.ai/free/en/papers/lingbulk-2020-eyal-building-hebrew-semantic-role-labeling/) — Ben Eyal, Michael Elhadad · Modern Hebrew - [Building the Emirati Arabic FrameNet](https://md.research.elamur.ai/free/en/papers/gargett-2020-building-emirati-arabic-framenet/) — Andrew Gargett, Tommi Leung · Proceedings of the International FrameNet… - [C-Net: Contextual Network for Sarcasm Detection](https://md.research.elamur.ai/free/en/papers/jena-2020-c-net-contextual-network-sarcasm/) — Amit Kumar Jena, Aman Sinha, Rohit Agarwal · Proceedings of the Second Workshop on… - [Cairo Student Code-Switch (CSCS) Corpus: An Annotated Egyptian Arabic-English Corpus](https://md.research.elamur.ai/free/en/papers/balabel-2020-cairo-student-code-switch-cscs/) — Mohamed Balabel, Injy Hamed, Slim Abdennadher, et al. · Proceedings of the Twelfth Language Resources… - [CAMeL Tools: An Open Source Python Toolkit for Arabic Natural Language Processing](https://md.research.elamur.ai/free/en/papers/obeid-2020-camel-tools-open-source-python/) — Ossama Obeid, Nasser Zalmout, Salam Khalifa, et al. · Proceedings of the Twelfth Language Resources… - [Can Multilingual Language Models Transfer to an Unseen Dialect? A Case Study on North African Arabizi](https://md.research.elamur.ai/free/en/papers/muller-2020-multilingual-language-models-transfer-unseen/) — Benjamin Muller, Benoit Sagot, Djame Seddah · arXiv:2005.00318 - [Can You Put it All Together: Evaluating Conversational Agents' Ability to Blend Skills](https://md.research.elamur.ai/free/en/papers/smith-2020-can-you-put-it-all/) — Eric Michael Smith, Mary Williamson, Kurt Shuster, et al. · Proceedings of the 58th Annual Meeting of the… - [CCAligned: A Massive Collection of Cross-Lingual Web-Document Pairs](https://md.research.elamur.ai/free/en/papers/kishky-2020-ccaligned-massive-collection-cross-lingual/) — Ahmed El-Kishky, Vishrav Chaudhary, Francisco Guzmán, et al. · Proceedings of the 2020 Conference on Empirical… - [CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data](https://md.research.elamur.ai/free/en/papers/wenzek-2020-ccnet-extracting-high-quality-monolingual/) — Guillaume Wenzek, Marie-Anne Lachaux, Alexis Conneau, et al. · Proceedings of the Twelfth Language Resources… - [CCOHA: Clean Corpus of Historical American English](https://md.research.elamur.ai/free/en/papers/alatrash-2020-ccoha-clean-corpus-historical-american/) — Reem Alatrash, Dominik Schlechtweg, Jonas Kuhn, et al. · English - [Character Alignment in Morphologically Complex Translation Sets for Related Languages](https://md.research.elamur.ai/free/en/papers/lingbulk-2020-gasser-character-alignment-morphologically-complex-translation/) — Michael Gasser, Binyam Ephrem Seyoum, Nazareth Amlesom Kifle · Semitic languages - [Ciron: a New Benchmark Dataset for Chinese Irony Detection](https://md.research.elamur.ai/free/en/papers/xiang-2020-ciron-new-benchmark-dataset-chinese/) — Rong Xiang, Xuefeng Gao, Yunfei Long, et al. · Proceedings of the Twelfth Language Resources… - [Classifying Syntactic Errors in Learner Language](https://md.research.elamur.ai/free/en/papers/choshen-2020-classifying-syntactic-errors-learner-language/) — Leshem Choshen, Dmitry Nikolaev, Yevgeni Berzak, et al. · Mova's core list - [Clause Structure Variation in Biblical Hebrew: A Quantitative Approach](https://md.research.elamur.ai/free/en/papers/hbo-2020-naaijer-clause-structure-variation-biblical-hebrew/) — Martijn Naaijer · Ancient Hebrew - [CLIMATE-FEVER: A Dataset for Verification of Real-World Climate Claims](https://md.research.elamur.ai/free/en/papers/diggelmann-2020-climate-fever-dataset-verification-real/) — Thomas Diggelmann, Jordan Boyd-Graber, Jannis Bulian, et al. · arXiv:2012.00614 - [Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data](https://md.research.elamur.ai/free/en/papers/bender-2020-climbing-nlu-meaning-form-understanding/) — Emily M. Bender, Alexander Koller · Proceedings of the 58th Annual Meeting of the… - [CLUE: A Chinese Language Understanding Evaluation Benchmark](https://md.research.elamur.ai/free/en/papers/xu-2020-clue-chinese-language-understanding/) — Liang Xu, Hai Hu, Xuanwei Zhang, et al. · arXiv:2004.05986 - [Clustering Biblical Texts Using Recurrent Neural Networks](https://md.research.elamur.ai/free/en/papers/hbo-2020-schans-clustering-biblical-texts-using-recurrent/) — Yanniek van der Schans, David Ruhe, Wido van Peursen, et al. · Ancient Hebrew - [Code-Switching Patterns Can Be an Effective Route to Improve Performance of Downstream NLP Applications: A Case Study of Humour, Sarcasm and Hate Speech Detection](https://md.research.elamur.ai/free/en/papers/bansal-2020-code-switching-patterns-can-be/) — Srijan Bansal, Vishal Garimella, Ayush Suhane, et al. · Proceedings of the 58th Annual Meeting of the… - [CodeBERT: A Pre-Trained Model for Programming and Natural Languages](https://md.research.elamur.ai/free/en/papers/feng-2020-codebert-pre-trained-model-programming/) — Zhangyin Feng, Daya Guo, Duyu Tang, et al. · Findings of the Association for Computational… - [CodeSearchNet Challenge: Evaluating the State of Semantic Code Search](https://md.research.elamur.ai/free/en/papers/husain-2020-codesearchnet-challenge-evaluating-state-semantic/) — Hamel Husain, Ho-Hsiang Wu, Tiferet Gazit, et al. · arXiv:1909.09436 - [ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT](https://md.research.elamur.ai/free/en/papers/khattab-2020-colbert-efficient-effective-passage/) — Omar Khattab, Matei Zaharia · SIGIR 2020 - [Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT](https://md.research.elamur.ai/free/en/papers/smit-2020-combining-automatic-labelers-expert-annotations/) — Akshay Smit, Saahil Jain, Pranav Rajpurkar, et al. · Proceedings of the 2020 Conference on Empirical… - [Combining Event Semantics and Degree Semantics for Natural Language Inference](https://md.research.elamur.ai/free/en/papers/haruta-2020-combining-event-semantics-degree-semantics/) — Izumi Haruta, Koji Mineshima, Daisuke Bekki · English - [COMET-ATOMIC 2020: On Symbolic and Neural Commonsense Knowledge Graphs](https://md.research.elamur.ai/free/en/papers/hwang-2020-comet-atomic-2020-symbolic-neural/) — Jena D. Hwang, Chandra Bhagavatula, Ronan Le Bras, et al. · Mova's core list - [COMET: A Neural Framework for MT Evaluation](https://md.research.elamur.ai/free/en/papers/rei-2020-comet-neural-framework-mt-evaluation/) — Ricardo Rei, Craig Stewart, Ana C Farinha, et al. · Machine translation - [Coming to Terms: Automatic Formation of Neologisms in Hebrew](https://md.research.elamur.ai/free/en/papers/findings-2020-mizrahi-coming-terms-automatic-formation-neologisms/) — Moran Mizrahi, Stav Yardeni Seelig, Dafna Shahaf · Modern Hebrew - [Comparing Neural Network Parsers for a Less-resourced and Morphologically-rich Language: Amharic Dependency Parser](https://md.research.elamur.ai/free/en/papers/aclbulk-2020-seyoum-comparing-neural-network-parsers-less/) — Binyam Ephrem Seyoum, Yusuke Miyao, Baye Yimam Mekonnen · Semitic languages - [Comparing PTB and UD information for PDTB discourse connective identification](https://md.research.elamur.ai/free/en/papers/han-2020-comparing-ptb-ud-information-pdtb/) — Kelvin Han, Phyllicia Leavitt, Srilakshmi Balard · English - [Comparison by Conversion: Reverse-Engineering UCCA from Syntax and Lexical Semantics](https://md.research.elamur.ai/free/en/papers/hershcovich-2020-comparison-conversion-reverse-engineering-ucca/) — Daniel Hershcovich, Nathan Schneider, Dotan Dvir, et al. · Machine translation - [Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning](https://md.research.elamur.ai/free/en/papers/gordon-2020-compressing-bert-studying-effects-weight/) — Mitchell Gordon, Kevin Duh, Nicholas Andrews · Proceedings of the 5th Workshop on… - [Conformer: Convolution-augmented Transformer for Speech Recognition](https://md.research.elamur.ai/free/en/papers/gulati-2020-conformer-convolution-augmented-transformer-speech/) — Anmol Gulati, James Qin, Chung-Cheng Chiu, et al. · arXiv:2005.08100 - [Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps](https://md.research.elamur.ai/free/en/papers/ho-2020-constructing-multi-hop-qa-dataset/) — Xanh Ho, Anh-Khoa Duong Nguyen, Saku Sugawara, et al. · Proceedings of the 28th International… - [Context-Aware Sarcasm Detection Using BERT](https://md.research.elamur.ai/free/en/papers/baruah-2020-context-aware-sarcasm-detection-bert/) — Arup Baruah, Kaushik Das, Ferdous Barbhuiya, et al. · Proceedings of the Second Workshop on… - [Contextualized Embeddings for Connective Disambiguation in Shallow Discourse Parsing](https://md.research.elamur.ai/free/en/papers/knaebel-2020-contextualized-embeddings-connective-disambiguation-shallow/) — René Knaebel, Manfred Stede · Proceedings of the First Workshop on… - [Contextualized Embeddings for Enriching Linguistic Analyses on Politeness](https://md.research.elamur.ai/free/en/papers/aljanaideh-2020-contextualized-embeddings-enriching-linguistic-analyses/) — Ahmad Aljanaideh, Eric Fosler-Lussier, Marie-Catherine de Marneffe · English - [Contextualizing Hate Speech Classifiers with Post-hoc Explanation](https://md.research.elamur.ai/free/en/papers/kennedy-2020-contextualizing-hate-speech-classifiers-post/) — Brendan Kennedy, Xisen Jin, Aida Mostafazadeh Davani, et al. · Proceedings of the 58th Annual Meeting of the… - [Controlled Crowdsourcing for High-Quality QA-SRL Annotation](https://md.research.elamur.ai/free/en/papers/roit-2020-controlled-crowdsourcing-high-quality-qa/) — Paul Roit, Ayal Klein, Daniela Stepanov, et al. · English - [Conundrums in Entity Coreference Resolution: Making Sense of the State of the Art](https://md.research.elamur.ai/free/en/papers/lu-2020-conundrums-entity-coreference-resolution-making/) — Jing Lu, Vincent Ng · Proceedings of the 2020 Conference on Empirical… - [ConveRT: Efficient and Accurate Conversational Representations from Transformers](https://md.research.elamur.ai/free/en/papers/henderson-2020-convert-efficient-accurate-conversational-representations/) — Matthew Henderson, Iñigo Casanueva, Nikola Mrkšić, et al. · Findings of the Association for Computational… - [ConvoKit: A Toolkit for the Analysis of Conversations](https://md.research.elamur.ai/free/en/papers/chang-2020-convokit-toolkit-analysis-conversations/) — Jonathan P. Chang, Caleb Chiam, Liye Fu, et al. · Proceedings of the 21th Annual Meeting of the… - [CORD-19: The COVID-19 Open Research Dataset](https://md.research.elamur.ai/free/en/papers/wang-2020-cord-19-covid-19-open/) — Lucy Lu Wang, Kyle Lo, Yoganand Chandrasekhar, et al. · Proceedings of the 1st Workshop on NLP for… - [Coreference for Discourse Parsing: A Neural Approach](https://md.research.elamur.ai/free/en/papers/guz-2020-coreference-discourse-parsing-neural-approach/) — Grigorii Guz, Giuseppe Carenini · Proceedings of the First Workshop on… - [CorefQA: Coreference Resolution as Query-based Span Prediction](https://md.research.elamur.ai/free/en/papers/wu-2020-corefqa-coreference-resolution-as-query/) — Wei Wu, Fei Wang, Arianna Yuan, et al. · Proceedings of the 58th Annual Meeting of the… - [Corpus Creation for Sentiment Analysis in Code-Mixed Tamil-English Text](https://md.research.elamur.ai/free/en/papers/chakravarthi-2020-corpus-creation-sentiment-analysis-code/) — Bharathi Raja Chakravarthi, Vigneshwaran Muralidaran, Ruba Priyadharshini, et al. · Proceedings of the 1st Joint Workshop on Spoken… - [Cross-lingual Semantic Representation for NLP with UCCA](https://md.research.elamur.ai/free/en/papers/abend-2020-cross-lingual-semantic-representation-nlp/) — Omri Abend, Dotan Dvir, Daniel Hershcovich, et al. · Machine translation - [Cross-lingual Zero Pronoun Resolution](https://md.research.elamur.ai/free/en/papers/aloraini-2020-cross-lingual-zero-pronoun-resolution/) — Abdulrahman Aloraini, Massimo Poesio · Proceedings of the Twelfth Language Resources… - [CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models](https://md.research.elamur.ai/free/en/papers/nangia-2020-crows-pairs-challenge-dataset-measuring/) — Nikita Nangia, Clara Vania, Rasika Bhalerao, et al. · Proceedings of the 2020 Conference on Empirical… - [Curriculum Learning for Natural Language Understanding](https://md.research.elamur.ai/free/en/papers/xu-2020-curriculum-learning-natural-language-understanding/) — Benfeng Xu, Licheng Zhang, Zhendong Mao, et al. · Proceedings of the 58th Annual Meeting of the… - [DAICT: A Dialectal Arabic Irony Corpus Extracted from Twitter](https://md.research.elamur.ai/free/en/papers/abbes-2020-daict-dialectal-arabic-irony-corpus/) — Ines Abbes, Wajdi Zaghouani, Omaima El-Hardlo, et al. · Proceedings of the Twelfth Language Resources… - [DART: Open-Domain Structured Data Record to Text Generation](https://md.research.elamur.ai/free/en/papers/nan-2020-dart-open-domain-structured-data/) — Linyong Nan, Dragomir Radev, Rui Zhang, et al. · arXiv:2007.02871 - [Data Augmentation using Pre-trained Transformer Models](https://md.research.elamur.ai/free/en/papers/kumar-2020-data-augmentation-using-pre-trained/) — Varun Kumar, Ashutosh Choudhary, Eunah Cho · arXiv:2003.02245 - [Data-Driven Sentence Simplification: Survey and Benchmark](https://md.research.elamur.ai/free/en/papers/manchego-2020-data-driven-sentence-simplification-survey/) — Fernando Alva-Manchego, Carolina Scarton, Lucia Specia · Computational Linguistics - [DeBERTa: Decoding-enhanced BERT with Disentangled Attention](https://md.research.elamur.ai/free/en/papers/he-2020-deberta-decoding-enhanced-bert-disentangled/) — Pengcheng He, Xiaodong Liu, Jianfeng Gao, et al. · arXiv:2006.03654 - [Decolonising Speech and Language Technology](https://md.research.elamur.ai/free/en/papers/bird-2020-decolonising-speech-language-technology/) — Steven Bird · Proceedings of the 28th International… - [DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference](https://md.research.elamur.ai/free/en/papers/xin-2020-deebert-dynamic-early-exiting-accelerating/) — Ji Xin, Raphael Tang, Jaejun Lee, et al. · Proceedings of the 58th Annual Meeting of the… - [Deep Encoder, Shallow Decoder: Reevaluating Non-autoregressive Machine Translation](https://md.research.elamur.ai/free/en/papers/kasai-2020-deep-encoder-shallow-decoder-reevaluating/) — Jungo Kasai, Nikolaos Pappas, Hao Peng, et al. · arXiv:2006.10369 - [Denoising Diffusion Implicit Models](https://md.research.elamur.ai/free/en/papers/song-2020-denoising-diffusion-implicit-models/) — Jiaming Song, Chenlin Meng, Stefano Ermon · arXiv:2010.02502 - [Dense Passage Retrieval for Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/karpukhin-2020-dense-passage-retrieval-open-domain/) — Vladimir Karpukhin, Barlas Oguz, Sewon Min, et al. · Proceedings of the 2020 Conference on Empirical… - [Detecting Sarcasm in Conversation Context Using Transformer-Based Models](https://md.research.elamur.ai/free/en/papers/avvaru-2020-detecting-sarcasm-conversation-context-transformer/) — Adithya Avvaru, Sanath Vobilisetty, Radhika Mamidi · Proceedings of the Second Workshop on… - [Developing a Corpus of Indirect Speech Act Schemas](https://md.research.elamur.ai/free/en/papers/roque-2020-developing-corpus-indirect-speech-act/) — Antonio Roque, Alexander Tsuetaki, Vasanth Sarathy, et al. · English - [Dice Loss for Data-imbalanced NLP Tasks](https://md.research.elamur.ai/free/en/papers/li-2020-dice-loss-data-imbalanced-nlp/) — Xiaoya Li, Xiaofei Sun, Yuxian Meng, et al. · Proceedings of the 58th Annual Meeting of the… - [Discourse particles in early English: Clause structure, pragmatics and discourse management](https://md.research.elamur.ai/free/en/papers/kemenade-2020-discourse-particles-early-english-clause/) — Ans van Kemenade, Meta Links · English - [Distilling Neural Networks for Greener and Faster Dependency Parsing](https://md.research.elamur.ai/free/en/papers/anderson-2020-distilling-neural-networks-greener-faster/) — Mark Anderson, Carlos Gómez-Rodríguez · Proceedings of the 16th International… - [Distinguish Confusing Law Articles for Legal Judgment Prediction](https://md.research.elamur.ai/free/en/papers/xu-2020-distinguish-confusing-law-articles-legal/) — Nuo Xu, Pinghui Wang, Long Chen, et al. · Proceedings of the 58th Annual Meeting of the… - [Document Ranking with a Pretrained Sequence-to-Sequence Model](https://md.research.elamur.ai/free/en/papers/nogueira-2020-document-ranking-pretrained-sequence-sequence/) — Rodrigo Nogueira, Zhiying Jiang, Ronak Pradeep, et al. · Findings of the Association for Computational… - [Document-level Neural MT: A Systematic Comparison](https://md.research.elamur.ai/free/en/papers/lopes-2020-document-level-neural-mt-systematic/) — António Lopes, M. Amin Farajian, Rachel Bawden, et al. · Proceedings of the 22nd Annual Conference of… - [DocVQA: A Dataset for VQA on Document Images](https://md.research.elamur.ai/free/en/papers/mathew-2020-docvqa-dataset-vqa-document-images/) — Minesh Mathew, Dimosthenis Karatzas, C.V. Jawahar · arXiv:2007.00398 - [Does Syntax Need to Grow on Trees? Sources of Hierarchical Inductive Bias in Sequence-to-Sequence Networks](https://md.research.elamur.ai/free/en/papers/mccoy-2020-does-syntax-need-grow-trees/) — R. Thomas McCoy, Robert Frank, Tal Linzen · Transactions of the Association for… - [Domain Robustness in Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/muller-2020-domain-robustness-neural-machine-translation/) — Mathias Müller, Annette Rios, Rico Sennrich · Proceedings of the 14th Conference of the… - [Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing](https://md.research.elamur.ai/free/en/papers/gu-2020-domain-specific-language-model-pretraining/) — Yu Gu; Robert Tinn; Hao Cheng; Michael Lucas; Naoto Usuyama; Xiaodong Liu; Tristan Naumann; Jianfeng Gao;, Hoifung Poon · arXiv:2007.15779 - [Don't Say That! Making Inconsistent Dialogue Unlikely with Unlikelihood Training](https://md.research.elamur.ai/free/en/papers/li-2020-don-t-say-that-making/) — Margaret Li, Stephen Roller, Ilia Kulikov, et al. · Proceedings of the 58th Annual Meeting of the… - [DRS at MRP 2020: Dressing up Discourse Representation Structures as Graphs](https://md.research.elamur.ai/free/en/papers/abzianidze-2020-drs-mrp-2020-dressing-up/) — Lasha Abzianidze, Johan Bos, Stephan Oepen · Machine translation - [DuSQL: A Large-Scale and Pragmatic Chinese Text-to-SQL Dataset](https://md.research.elamur.ai/free/en/papers/wang-2020-dusql-large-scale-pragmatic-chinese/) — Lijie Wang, Ao Zhang, Kun Wu, et al. · Proceedings of the 2020 Conference on Empirical… - [Edition 1.2 of the PARSEME Shared Task on Semi-supervised Identification of Verbal Multiword Expressions](https://md.research.elamur.ai/free/en/papers/ramisch-2020-edition-1-2-parseme-shared/) — Carlos Ramisch, Agata Savary, Bruno Guillaume, et al. · Proceedings of the Joint Workshop on Multiword… - [Efficient Arabic emotion recognition using deep neural networks](https://md.research.elamur.ai/free/en/papers/ali-2020-efficient-arabic-emotion-recognition-using/) — Ahmed Ali, Yasser Hifny · arXiv:2011.00346 - [Efficient Content-Based Sparse Attention with Routing Transformers](https://md.research.elamur.ai/free/en/papers/roy-2020-efficient-content-based-sparse-attention/) — Aurko Roy, Mohammad Saffar, Ashish Vaswani, et al. · arXiv:2003.05997 - [Efficient Dialogue State Tracking by Selectively Overwriting Memory](https://md.research.elamur.ai/free/en/papers/kim-2020-efficient-dialogue-state-tracking-selectively/) — Sungdong Kim, Sohee Yang, Gyuwan Kim, et al. · Proceedings of the 58th Annual Meeting of the… - [Efficient Intent Detection with Dual Sentence Encoders](https://md.research.elamur.ai/free/en/papers/casanueva-2020-efficient-intent-detection-dual-sentence/) — Iñigo Casanueva, Tadas Temčinas, Daniela Gerz, et al. · Proceedings of the 2nd Workshop on Natural… - [Efficient Second-Order TreeCRF for Neural Dependency Parsing](https://md.research.elamur.ai/free/en/papers/acl-2020-zhang-efficient-second-order-treecrf-neural/) — Yu Zhang, Zhenghua Li, Min Zhang · English - [Efficient Transformers: A Survey](https://md.research.elamur.ai/free/en/papers/tay-2020-efficient-transformers-survey/) — Yi Tay, Mostafa Dehghani, Dara Bahri, et al. · arXiv:2009.06732 - [Emerging Cross-lingual Structure in Pretrained Language Models](https://md.research.elamur.ai/free/en/papers/conneau-2020-emerging-cross-lingual-structure-pretrained/) — Alexis Conneau, Shijie Wu, Haoran Li, et al. · Proceedings of the 58th Annual Meeting of the… - [Enabling Language Models to Fill in the Blanks](https://md.research.elamur.ai/free/en/papers/donahue-2020-enabling-language-models-fill-blanks/) — Chris Donahue, Mina Lee, Percy Liang · Proceedings of the 58th Annual Meeting of the… - [End-to-End Bias Mitigation by Modelling Biases in Corpora](https://md.research.elamur.ai/free/en/papers/mahabadi-2020-end-end-bias-mitigation-modelling/) — Rabeeh Karimi Mahabadi, Yonatan Belinkov, James Henderson · Proceedings of the 58th Annual Meeting of the… - [End-to-End Object Detection with Transformers](https://md.research.elamur.ai/free/en/papers/carion-2020-end-end-object-detection-transformers/) — Nicolas Carion, Francisco Massa, Gabriel Synnaeve, et al. · arXiv:2005.12872 - [End-to-End Slot Alignment and Recognition for Cross-Lingual NLU](https://md.research.elamur.ai/free/en/papers/xu-2020-end-end-slot-alignment-recognition/) — Weijia Xu, Batool Haider, Saab Mansour · Proceedings of the 2020 Conference on Empirical… - [Enhancing Cross-target Stance Detection with Transferable Semantic-Emotion Knowledge](https://md.research.elamur.ai/free/en/papers/zhang-2020-enhancing-cross-target-stance-detection/) — Bowen Zhang, Min Yang, Xutao Li, et al. · Proceedings of the 58th Annual Meeting of the… - [Entities as Experts: Sparse Memory Access with Entity Supervision](https://md.research.elamur.ai/free/en/papers/fevry-2020-entities-as-experts-sparse-memory/) — Thibault Févry, Livio Baldini Soares, Nicholas FitzGerald, et al. · Proceedings of the 2020 Conference on Empirical… - [Entity Linking in 100 Languages](https://md.research.elamur.ai/free/en/papers/botha-2020-entity-linking-100-languages/) — Jan A. 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