---
title: "Papers of 2021 — page 4"
description: "Papers of 2021: 368 papers of the Elamur Research library — what each work is about in our own words, its ideas, references and who cites it."
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# Papers of 2021 — page 4

368 papers · [all years](https://md.research.elamur.ai/free/papers/)

[1](https://md.research.elamur.ai/free/papers/2021/) [2](https://md.research.elamur.ai/free/papers/2021/page/2/) [3](https://md.research.elamur.ai/free/papers/2021/page/3/) **4**

- [Structured Denoising Diffusion Models in Discrete State-Spaces](https://md.research.elamur.ai/free/papers/austin-2021-structured-denoising-diffusion-models-discrete/) — Jacob Austin, Daniel D. Johnson, Jonathan Ho, et al. · arXiv:2107.03006
- [Studies in the Grammar and Lexicon of Neo-Aramaic](https://md.research.elamur.ai/free/papers/hbobook-obp0209-khan-studies-grammar-lexicon-neo-aramaic/) — Geoffrey Khan, Paul M. Noorlander · Aramaic
- [Superbizarre Is Not Superb: Derivational Morphology Improves BERT's Interpretation of Complex Words](https://md.research.elamur.ai/free/papers/lex-2021-hofmann-superbizarre-derivational/) — Valentin, Hofmann · English
- [Surface Form Competition: Why the Highest Probability Answer Isn't Always Right](https://md.research.elamur.ai/free/papers/holtzman-2021-surface-form-competition-why-highest/) — Ari Holtzman, Peter West, Vered Shwartz, et al. · Proceedings of the 2021 Conference on Empirical…
- [Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://md.research.elamur.ai/free/papers/liu-2021-swin-transformer-hierarchical-vision-transformer/) — Ze Liu, Yutong Lin, Yue Cao, et al. · arXiv:2103.14030
- [Swiss-Judgment-Prediction: A Multilingual Legal Judgment Prediction Benchmark](https://md.research.elamur.ai/free/papers/niklaus-2021-swiss-judgment-prediction-multilingual-legal/) — Joel Niklaus, Ilias Chalkidis, Matthias Stürmer · Proceedings of the Natural Legal Language…
- [Syntax-augmented Multilingual BERT for Cross-lingual Transfer](https://md.research.elamur.ai/free/papers/ahmad-2021-syntax-augmented-multilingual-bert-cross/) — Wasi Ahmad, Haoran Li, Kai-Wei Chang, et al. · Proceedings of the 59th Annual Meeting of the…
- [Synthetic Examples Improve Cross-Target Generalization: A Study on Stance Detection on a Twitter corpus.](https://md.research.elamur.ai/free/papers/conforti-2021-synthetic-examples-improve-cross-target/) — Costanza Conforti, Jakob Berndt, Mohammad Taher Pilehvar, et al. · Proceedings of the Eleventh Workshop on…
- [Tackling Zero Pronoun Resolution and Non-Zero Coreference Resolution Jointly](https://md.research.elamur.ai/free/papers/chen-2021-tackling-zero-pronoun-resolution-non/) — Shisong Chen, Binbin Gu, Jianfeng Qu, et al. · Proceedings of the 25th Conference on…
- [TAPEX: Table Pre-training via Learning a Neural SQL Executor](https://md.research.elamur.ai/free/papers/liu-2021-tapex-table-pre-training-learning/) — Qian Liu, Bei Chen, Jiaqi Guo, et al. · arXiv:2107.07653
- [Target-Aware Data Augmentation for Stance Detection](https://md.research.elamur.ai/free/papers/li-2021-target-aware-data-augmentation-stance/) — Yingjie Li, Cornelia Caragea · Proceedings of the 2021 Conference of the North…
- [TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Finance](https://md.research.elamur.ai/free/papers/zhu-2021-tat-qa-question-answering-benchmark/) — Fengbin Zhu, Wenqiang Lei, Youcheng Huang, et al. · Proceedings of the 59th Annual Meeting of the…
- [Tell Me Everything You Know: A Conversation Update System for the Rational Speech Acts Framework](https://md.research.elamur.ai/free/papers/anderson-2021-tell-me-everything-you-know/) — Carolyn Jane Anderson · English
- [TellMeWhy: A Dataset for Answering Why-Questions in Narratives](https://md.research.elamur.ai/free/papers/lal-2021-tellmewhy-dataset-answering-why-questions/) — Yash Kumar Lal, Nathanael Chambers, Raymond Mooney, et al. · English
- [Text Generation from Discourse Representation Structures](https://md.research.elamur.ai/free/papers/liu-2021-text-generation-discourse-representation-structures/) — Jiangming Liu, Shay B. Cohen, Mirella Lapata · Machine translation
- [Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction](https://md.research.elamur.ai/free/papers/lu-2021-text2event-controllable-sequence-structure-generation/) — Yaojie Lu, Hongyu Lin, Jin Xu, et al. · Proceedings of the 59th Annual Meeting of the…
- [The (Un)Suitability of Automatic Evaluation Metrics for Text Simplification](https://md.research.elamur.ai/free/papers/manchego-2021-un-suitability-automatic-evaluation-metrics/) — Fernando Alva-Manchego, Carolina Scarton, Lucia Specia · Computational Linguistics
- [The CODI-CRAC 2021 Shared Task on Anaphora, Bridging, and Discourse Deixis in Dialogue](https://md.research.elamur.ai/free/papers/khosla-2021-codi-crac-2021-shared-task/) — Sopan Khosla, Juntao Yu, Ramesh Manuvinakurike, et al. · English
- [The CODI-CRAC 2021 Shared Task on Anaphora, Bridging, and Discourse Deixis Resolution in Dialogue: A Cross-Team Analysis](https://md.research.elamur.ai/free/papers/li-2021-codi-crac-2021-shared-task/) — Shengjie Li, Hideo Kobayashi, Vincent Ng · Proceedings of the CODI-CRAC 2021 Shared Task…
- [The Curious Case of Hallucinations in Neural Machine Translation](https://md.research.elamur.ai/free/papers/raunak-2021-curious-case-hallucinations-neural-machine/) — Vikas Raunak, Arul Menezes, Marcin Junczys-Dowmunt · Proceedings of the 2021 Conference of the North…
- [The DCU-EPFL Enhanced Dependency Parser at the IWPT 2021 Shared Task](https://md.research.elamur.ai/free/papers/barry-2021-dcu-epfl-enhanced-dependency-parser/) — James Barry, Alireza Mohammadshahi, Joachim Wagner, et al. · Proceedings of the 17th International…
- [The DISRPT 2021 Shared Task on Elementary Discourse Unit Segmentation, Connective Detection, and Relation Classification](https://md.research.elamur.ai/free/papers/zeldes-2021-disrpt-2021-shared-task-elementary/) — Amir Zeldes, Yang Janet Liu, Mikel Iruskieta, et al. · Proceedings of the 2nd Shared Task on Discourse…
- [The Importance of Modeling Social Factors of Language: Theory and Practice](https://md.research.elamur.ai/free/papers/hovy-2021-importance-modeling-social-factors-language/) — Dirk Hovy, Diyi Yang · Proceedings of the 2021 Conference of the North…
- [The Interplay of Variant, Size, and Task Type in Arabic Pre-trained Language Models](https://md.research.elamur.ai/free/papers/inoue-2021-interplay-variant-size-task-type/) — Go Inoue, Bashar Alhafni, Nurpeiis Baimukan, et al. · arXiv:2103.06678
- [The Lean 4 Theorem Prover and Programming Language (System Description)](https://md.research.elamur.ai/free/papers/moura-2021-lean-4-theorem-prover-programming/) — Leonardo de Moura, Sebastian Ullrich · CADE-28 (LNCS 12699), Springer
- [The Pipeline Model for Resolution of Anaphoric Reference and Resolution of Entity Reference](https://md.research.elamur.ai/free/papers/kim-2021-pipeline-model-resolution-anaphoric-reference/) — Hongjin Kim, Damrin Kim, Harksoo Kim · Proceedings of the CODI-CRAC 2021 Shared Task…
- [The Possible, the Plausible, and the Desirable: Event-Based Modality Detection for Language Processing](https://md.research.elamur.ai/free/papers/pyatkin-2021-possible-plausible-desirable-event-based/) — Valentina Pyatkin, Shoval Sadde, Aynat Rubinstein, et al. · English
- [Thematic role assignment in non-default verb classes: A cross-linguistic comparison of English and German](https://md.research.elamur.ai/free/papers/kyriaki-2021-thematic-role-assignment-non-default/) — Louise Kyriaki, Matthias Schlesewsky, Ina Bornkessel-Schlesewsky · English
- [Top-down Discourse Parsing via Sequence Labelling](https://md.research.elamur.ai/free/papers/koto-2021-top-down-discourse-parsing-sequence/) — Fajri Koto, Jey Han Lau, Timothy Baldwin · Proceedings of the 16th Conference of the…
- [Toward a Perspectivist Turn in Ground Truthing for Predictive Computing](https://md.research.elamur.ai/free/papers/basile-2021-toward-perspectivist-turn-ground-truthing/) — Valerio Basile, Federico Cabitza, Andrea Campagner, et al. · arXiv:2109.04270 · Proceedings of the AAAI…
- [Toward Gender-Inclusive Coreference Resolution: An Analysis of Gender and Bias Throughout the Machine Learning Lifecycle](https://md.research.elamur.ai/free/papers/cao-2021-gender-inclusive-coreference-resolution-analysis/) — Yang Trista Cao, Hal Daumé III · Research library
- [Towards a Decomposable Metric for Explainable Evaluation of Text Generation from AMR](https://md.research.elamur.ai/free/papers/opitz-2021-decomposable-metric-explainable-evaluation-text/) — Juri Opitz, Anette Frank · Machine translation
- [Towards a prosodic model for Tiberian Hebrew: An intonation-based analysis](https://md.research.elamur.ai/free/papers/hbo-2021-pitcher-towards-prosodic-model-tiberian-hebrew/) — Sophia L. Pitcher · Ancient Hebrew
- [Towards a Unified View of Parameter-Efficient Transfer Learning](https://md.research.elamur.ai/free/papers/he-2021-towards-unified-view-parameter-efficient/) — Junxian He, Chunting Zhou, Xuezhe Ma, et al. · arXiv:2110.04366
- [Towards Emotional Support Dialog Systems](https://md.research.elamur.ai/free/papers/liu-2021-emotional-support-dialog-systems/) — Siyang Liu, Chujie Zheng, Orianna Demasi, et al. · Proceedings of the 59th Annual Meeting of the…
- [Towards Understanding and Mitigating Social Biases in Language Models](https://md.research.elamur.ai/free/papers/liang-2021-towards-understanding-mitigating-social-biases/) — Paul Pu Liang, Chiyu Wu, Louis-Philippe Morency, et al. · arXiv:2106.13219
- [Training Verifiers to Solve Math Word Problems](https://md.research.elamur.ai/free/papers/cobbe-2021-training-verifiers-solve-math-word/) — Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, et al. · arXiv:2110.14168
- [Trankit: A Light-Weight Transformer-based Toolkit for Multilingual Natural Language Processing](https://md.research.elamur.ai/free/papers/ud-2021-nguyen-trankit-light-weight-transformer-based/) — Minh Van Nguyen, Viet Dac Lai, Amir Pouran Ben Veyseh, et al. · English
- [Transition-based Bubble Parsing: Improvements on Coordination Structure Prediction](https://md.research.elamur.ai/free/papers/shi-2021-transition-based-bubble-parsing-improvements/) — Tianze Shi, Lillian Lee · English
- [True Few-Shot Learning with Language Models](https://md.research.elamur.ai/free/papers/perez-2021-true-few-shot-learning-language/) — Ethan Perez, Douwe Kiela, Kyunghyun Cho · arXiv:2105.11447
- [Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metrics](https://md.research.elamur.ai/free/papers/pagnoni-2021-understanding-factuality-abstractive-summarization-frank/) — Artidoro Pagnoni, Vidhisha Balachandran, Yulia Tsvetkov · Proceedings of the 2021 Conference of the North…
- [Understanding Mention Detector-Linker Interaction in Neural Coreference Resolution](https://md.research.elamur.ai/free/papers/wu-2021-understanding-mention-detector-linker-interaction/) — Zhaofeng Wu, Matt Gardner · Proceedings of the Fourth Workshop on…
- [Unified Pre-training for Program Understanding and Generation](https://md.research.elamur.ai/free/papers/ahmad-2021-unified-pre-training-program-understanding/) — Wasi Ahmad, Saikat Chakraborty, Baishakhi Ray, et al. · Proceedings of the 2021 Conference of the North…
- [Universal Dependencies](https://md.research.elamur.ai/free/papers/demarneffe-2021-universal-dependencies/) — Marie-Catherine de Marneffe, Christopher D. Manning, Joakim Nivre, et al. · Mova's core list
- [Unsupervised Dense Information Retrieval with Contrastive Learning](https://md.research.elamur.ai/free/papers/izacard-2021-unsupervised-dense-information-retrieval-contrastive/) — Gautier Izacard, Mathilde Caron, Lucas Hosseini, et al. · arXiv:2112.09118
- [Validation of Universal Dependencies by regeneration](https://md.research.elamur.ai/free/papers/ud-2021-lapalme-validation-universal-dependencies-regeneration/) — Guy Lapalme · English
- [ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision](https://md.research.elamur.ai/free/papers/kim-2021-vilt-vision-language-transformer-convolution/) — Wonjae Kim, Bokyung Son, Ildoo Kim · arXiv:2102.03334
- [VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation](https://md.research.elamur.ai/free/papers/wang-2021-voxpopuli-large-scale-multilingual-speech/) — Changhan Wang, Morgane Riviere, Ann Lee, et al. · Proceedings of the 59th Annual Meeting of the…
- [WANLP 2021 Shared-Task: Towards Irony and Sentiment Detection in Arabic Tweets using Multi-headed-LSTM-CNN-GRU and MaRBERT](https://md.research.elamur.ai/free/papers/salam-2021-wanlp-2021-shared-task-irony/) — Reem Abdel-Salam · Proceedings of the Sixth Arabic Natural…
- [Want To Reduce Labeling Cost? GPT-3 Can Help](https://md.research.elamur.ai/free/papers/wang-2021-want-reduce-labeling-cost-gpt/) — Shuohang Wang, Yang Liu, Yichong Xu, et al. · Findings of the Association for Computational…
- [We Need to Consider Disagreement in Evaluation](https://md.research.elamur.ai/free/papers/basile-2021-we-need-consider-disagreement-evaluation/) — Valerio Basile, Michael Fell, Tommaso Fornaciari, et al. · Proceedings of the 1st Workshop on…
- [WebGPT: Browser-assisted question-answering with human feedback](https://md.research.elamur.ai/free/papers/nakano-2021-webgpt-browser-assisted-question-answering/) — Reiichiro Nakano, Jacob Hilton, Suchir Balaji, et al. · arXiv:2112.09332
- [WEC: Deriving a Large-scale Cross-document Event Coreference dataset from Wikipedia](https://md.research.elamur.ai/free/papers/eirew-2021-wec-deriving-large-scale-cross/) — Alon Eirew, Arie Cattan, Ido Dagan · Proceedings of the 2021 Conference of the North…
- [Weisfeiler-Leman in the Bamboo: Novel AMR Graph Metrics and a Benchmark for AMR Graph Similarity](https://md.research.elamur.ai/free/papers/opitz-2021-weisfeiler-leman-bamboo-novel-amr/) — Juri Opitz, Angel Daza, Anette Frank · Machine translation
- [What Does Your Smile Mean? Jointly Detecting Multi-Modal Sarcasm and Sentiment Using Quantum Probability](https://md.research.elamur.ai/free/papers/liu-2021-what-does-your-smile-mean/) — Yaochen Liu, Yazhou Zhang, Qiuchi Li, et al. · Findings of the Association for Computational…
- [What Helps Transformers Recognize Conversational Structure? Importance of Context, Punctuation, and Labels in Dialog Act Recognition](https://md.research.elamur.ai/free/papers/elasko-2021-what-helps-transformers-recognize-conversational/) — Piotr Żelasko, Raghavendra Pappagari, Najim Dehak · Research library
- [When Being Unseen from mBERT is just the Beginning: Handling New Languages With Multilingual Language Models](https://md.research.elamur.ai/free/papers/muller-2021-when-being-unseen-mbert-is/) — Benjamin Muller, Antonios Anastasopoulos, Benoît Sagot, et al. · Proceedings of the 2021 Conference of the North…
- [Where Are We in Discourse Relation Recognition?](https://md.research.elamur.ai/free/papers/atwell-2021-where-are-we-discourse-relation/) — Katherine Atwell, Junyi Jessy Li, Malihe Alikhani · Proceedings of the 22nd Annual Meeting of the…
- [Which Linguist Invented the Lightbulb? Presupposition Verification for Question-Answering](https://md.research.elamur.ai/free/papers/kim-2021-which-linguist-invented-lightbulb-presupposition/) — Najoung Kim, Ellie Pavlick, Burcu Karagol Ayan, et al. · English
- [Whit's the Richt Pairt o Speech: PoS tagging for Scots](https://md.research.elamur.ai/free/papers/lameris-2021-whit-s-richt-pairt-o/) — Harm Lameris, Sara Stymne · English
- [Wino-X: Multilingual Winograd Schemas for Commonsense Reasoning and Coreference Resolution](https://md.research.elamur.ai/free/papers/emelin-2021-wino-x-multilingual-winograd-schemas/) — Denis Emelin, Rico Sennrich · Proceedings of the 2021 Conference on Empirical…
- [Word Sense Induction with Attentive Context Clustering](https://md.research.elamur.ai/free/papers/aclbulk-2021-stekel-word-sense-induction-attentive-context/) — Moshe Stekel, Amos Azaria, Shai Gordin · Ancient Hebrew
- [Word-Level Coreference Resolution](https://md.research.elamur.ai/free/papers/dobrovolskii-2021-word-level-coreference-resolution/) — Vladimir Dobrovolskii · Proceedings of the 2021 Conference on Empirical…
- [XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale](https://md.research.elamur.ai/free/papers/babu-2021-xls-r-self-supervised-cross/) — Arun Babu, Changhan Wang, Andros Tjandra, et al. · arXiv:2111.09296
- [XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation](https://md.research.elamur.ai/free/papers/ruder-2021-xtreme-r-more-challenging-nuanced/) — Sebastian Ruder, Noah Constant, Jan Botha, et al. · Proceedings of the 2021 Conference on Empirical…
- [ZeRO-Offload: Democratizing Billion-Scale Model Training](https://md.research.elamur.ai/free/papers/ren-2021-zero-offload-democratizing-billion-scale/) — Jie Ren, Samyam Rajbhandari, Reza Yazdani Aminabadi, et al. · arXiv:2101.06840
- [Zero-Shot Text-to-Image Generation](https://md.research.elamur.ai/free/papers/ramesh-2021-zero-shot-text-image-generation/) — Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, et al. · arXiv:2102.12092
- [知识图谱嵌入技术研究综述](https://md.research.elamur.ai/free/papers/zhang-2021-overview-knowledge-graph/) — 张天成, 田雪, 孙相会, et al. · 软件学报 (Journal of Software)

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