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# Who cites «Bleu: a Method for Automatic Evaluation of Machine Translation» · page 35

10821 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.mova.elamur.ai/free/en/docs/papers/papineni-2002-bleu-method-automatic-evaluation-machine/)

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1. [Assessing Dialogue Systems with Distribution Distances](https://aclanthology.org/2021.findings-acl.193/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
2. [Assessing Evaluation Metrics for Speech-to-Speech Translation](https://arxiv.org/abs/2110.13877) *— 2021 · arXiv:2110.13877*
3. [Assessing Reference-Free Peer Evaluation for Machine Translation](https://aclanthology.org/2021.naacl-main.91/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
4. [Attend, Memorize and Generate: Towards Faithful Table-to-Text Generation in Few Shots](https://aclanthology.org/2021.findings-emnlp.347/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
5. [Attention Calibration for Transformer in Neural Machine Translation](https://aclanthology.org/2021.acl-long.103/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
6. [Attention Is Indeed All You Need: Semantically Attention-Guided Decoding for Data-to-Text NLG](https://aclanthology.org/2021.inlg-1.45/) *— 2021 · Proceedings of the 14th International Conference on Natural Language Generation*
7. [AuGPT: Auxiliary Tasks and Data Augmentation for End-To-End Dialogue with Pre-Trained Language Models](https://aclanthology.org/2021.nlp4convai-1.19/) *— 2021 · Proceedings of the 3rd Workshop on Natural Language Processing for Conversational AI*
8. [AugVic: Exploiting BiText Vicinity for Low-Resource NMT](https://aclanthology.org/2021.findings-acl.267/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
9. [Auto-encodeurs variationnels : contrecarrer le problème de posterior collapse grâce à la régularisation du décodeur (Variational auto-encoders : prevent posterior collapse via decoder regularization)](https://aclanthology.org/2021.jeptalnrecital-taln.1/) *— 2021 · Actes de la 28e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 : conférence principale*
10. [AutoChart: A Dataset for Chart-to-Text Generation Task](https://aclanthology.org/2021.ranlp-1.183/) *— 2021 · Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)*
11. [Autocorrect in the Process of Translation –- Multi-task Learning Improves Dialogue Machine Translation](https://aclanthology.org/2021.naacl-industry.14/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Papers*
12. [Automated Generation of Accurate & Fluent Medical X-ray Reports](https://aclanthology.org/2021.emnlp-main.288/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
13. [Automatic Bilingual Markup Transfer](https://aclanthology.org/2021.findings-emnlp.299/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
14. [Automatic Classification of Human Translation and Machine Translation: A Study from the Perspective of Lexical Diversity](https://aclanthology.org/2021.motra-1.10/) *— 2021 · Proceedings for the First Workshop on Modelling Translation: Translatology in the Digital Age*
15. [Automatic Rephrasing of Transcripts-based Action Items](https://aclanthology.org/2021.findings-acl.253/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
16. [Automatic Text Evaluation through the Lens of Wasserstein Barycenters](https://aclanthology.org/2021.emnlp-main.817/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
17. [Avoiding Overlap in Data Augmentation for AMR-to-Text Generation](https://aclanthology.org/2021.acl-short.132/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)*
18. [BACON: Deep-Learning Powered AI for Poetry Generation with Author Linguistic Style Transfer](https://arxiv.org/abs/2112.11483) *— 2021 · arXiv:2112.11483*
19. [BARTScore: Evaluating Generated Text as Text Generation](https://arxiv.org/abs/2106.11520) *— 2021 · arXiv:2106.11520*
20. [BERT, mBERT, or BiBERT? A Study on Contextualized Embeddings for Neural Machine Translation](https://aclanthology.org/2021.emnlp-main.534/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
21. [BERT-based distractor generation for Swedish reading comprehension questions using a small-scale dataset](https://aclanthology.org/2021.inlg-1.43/) *— 2021 · Proceedings of the 14th International Conference on Natural Language Generation*
22. [BERTTune: Fine-Tuning Neural Machine Translation with BERTScore](https://aclanthology.org/2021.acl-short.115/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)*
23. [BERxiT: Early Exiting for BERT with Better Fine-Tuning and Extension to Regression](https://aclanthology.org/2021.eacl-main.8/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
24. [BTS: Back TranScription for Speech-to-Text Post-Processor using Text-to-Speech-to-Text](https://aclanthology.org/2021.wat-1.10/) *— 2021 · Proceedings of the 8th Workshop on Asian Translation (WAT2021)*
25. [Back to Square One: Artifact Detection, Training and Commonsense Disentanglement in the Winograd Schema](https://aclanthology.org/2021.emnlp-main.819/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
26. [Back-Training excels Self-Training at Unsupervised Domain Adaptation of Question Generation and Passage Retrieval](https://aclanthology.org/2021.emnlp-main.566/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
27. [Backtranslation Feedback Improves User Confidence in MT, Not Quality](https://aclanthology.org/2021.naacl-main.14/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
28. [Beam Search with Bidirectional Strategies for Neural Response Generation](https://aclanthology.org/2021.icnlsp-1.16/) *— 2021 · Proceedings of the 4th International Conference on Natural Language and Speech Processing (ICNLSP 2021)*
29. [Better than Average: Paired Evaluation of NLP systems](https://aclanthology.org/2021.acl-long.179/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
30. [Beyond Noise: Mitigating the Impact of Fine-grained Semantic Divergences on Neural Machine Translation](https://aclanthology.org/2021.acl-long.562/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
31. [Beyond Sentence-Level End-to-End Speech Translation: Context Helps](https://aclanthology.org/2021.acl-long.200/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
32. [Beyond Voice Activity Detection: Hybrid Audio Segmentation for Direct Speech Translation](https://aclanthology.org/2021.icnlsp-1.7/) *— 2021 · Proceedings of the 4th International Conference on Natural Language and Speech Processing (ICNLSP 2021)*
33. [BiSECT: Learning to Split and Rephrase Sentences with Bitexts](https://aclanthology.org/2021.emnlp-main.500/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
34. [Biais de genre dans un système de traduction automatiqueneuronale : une étude préliminaire (Gender Bias in Neural Translation : a preliminary study )](https://aclanthology.org/2021.jeptalnrecital-taln.2/) *— 2021 · Actes de la 28e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 : conférence principale*
35. [Boosting Neural Machine Translation from Finnish to Northern Sámi with Rule-Based Backtranslation](https://aclanthology.org/2021.nodalida-main.37/) *— 2021 · Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa)*
36. [Bridging Subword Gaps in Pretrain-Finetune Paradigm for Natural Language Generation](https://aclanthology.org/2021.acl-long.468/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
37. [Building Adaptive Acceptability Classifiers for Neural NLG](https://aclanthology.org/2021.emnlp-main.53/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
38. [Building the Directed Semantic Graph for Coherent Long Text Generation](https://aclanthology.org/2021.emnlp-main.200/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
39. [CAST: Enhancing Code Summarization with Hierarchical Splitting and Reconstruction of Abstract Syntax Trees](https://aclanthology.org/2021.emnlp-main.332/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
40. [CEM: Commonsense-aware Empathetic Response Generation](https://arxiv.org/abs/2109.05739) *— 2021 · arXiv:2109.05739 · Proceedings of the AAAI Conference on Artificial Intelligence 2022*
41. [CIDEr-R: Robust Consensus-based Image Description Evaluation](https://aclanthology.org/2021.wnut-1.39/) *— 2021 · Proceedings of the Seventh Workshop on Noisy User-generated Text (W-NUT 2021)*
42. [CLIPScore: A Reference-free Evaluation Metric for Image Captioning](https://aclanthology.org/2021.emnlp-main.595/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
43. [COINS: Dynamically Generating COntextualized Inference Rules for Narrative Story Completion](https://aclanthology.org/2021.acl-long.395/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
44. [COSMic: A Coherence-Aware Generation Metric for Image Descriptions](https://aclanthology.org/2021.findings-emnlp.291/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
45. [CRSLab: An Open-Source Toolkit for Building Conversational Recommender System](https://aclanthology.org/2021.acl-demo.22/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations*
46. [CTC-based Compression for Direct Speech Translation](https://aclanthology.org/2021.eacl-main.57/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
47. [Can Cognate Prediction Be Modelled as a Low-Resource Machine Translation Task?](https://aclanthology.org/2021.findings-acl.75/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
48. [Can Latent Alignments Improve Autoregressive Machine Translation?](https://aclanthology.org/2021.naacl-main.209/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
49. [Can Question Generation Debias Question Answering Models? A Case Study on Question–Context Lexical Overlap](https://aclanthology.org/2021.mrqa-1.6/) *— 2021 · Proceedings of the 3rd Workshop on Machine Reading for Question Answering*
50. [ChainCQG: Flow-Aware Conversational Question Generation](https://aclanthology.org/2021.eacl-main.177/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
51. [Chinese Character Decomposition for Neural MT with Multi-Word Expressions](https://aclanthology.org/2021.nodalida-main.35/) *— 2021 · Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa)*
52. [Civil Rephrases Of Toxic Texts With Self-Supervised Transformers](https://aclanthology.org/2021.eacl-main.124/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
53. [CoDesc: A Large Code–Description Parallel Dataset](https://aclanthology.org/2021.findings-acl.18/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
54. [CoLV: A Collaborative Latent Variable Model for Knowledge-Grounded Dialogue Generation](https://aclanthology.org/2021.emnlp-main.172/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
55. [CoMAE: A Multi-factor Hierarchical Framework for Empathetic Response Generation](https://aclanthology.org/2021.findings-acl.72/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
56. [CoMeT: Towards Code-Mixed Translation Using Parallel Monolingual Sentences](https://aclanthology.org/2021.calcs-1.7/) *— 2021 · Proceedings of the Fifth Workshop on Computational Approaches to Linguistic Code-Switching*
57. [Code to Comment Translation: A Comparative Study on Model Effectiveness & Errors](https://aclanthology.org/2021.nlp4prog-1.1/) *— 2021 · Proceedings of the 1st Workshop on Natural Language Processing for Programming (NLP4Prog 2021)*
58. [CodeQA: A Question Answering Dataset for Source Code Comprehension](https://aclanthology.org/2021.findings-emnlp.223/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
59. [CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation](https://arxiv.org/abs/2102.04664) *— 2021 · arXiv:2102.04664*
60. [Combining Curriculum Learning and Knowledge Distillation for Dialogue Generation](https://aclanthology.org/2021.findings-emnlp.111/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
61. [CommitBERT: Commit Message Generation Using Pre-Trained Programming Language Model](https://aclanthology.org/2021.nlp4prog-1.3/) *— 2021 · Proceedings of the 1st Workshop on Natural Language Processing for Programming (NLP4Prog 2021)*
62. [Common Sense Beyond English: Evaluating and Improving Multilingual Language Models for Commonsense Reasoning](https://aclanthology.org/2021.acl-long.102/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
63. [Competence-based Multimodal Curriculum Learning for Medical Report Generation](https://aclanthology.org/2021.acl-long.234/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
64. [Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation](https://aclanthology.org/2021.emnlp-main.599/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
65. [ConQuest: Contextual Question Paraphrasing through Answer-Aware Synthetic Question Generation](https://aclanthology.org/2021.wnut-1.25/) *— 2021 · Proceedings of the Seventh Workshop on Noisy User-generated Text (W-NUT 2021)*
66. [Constraint based Knowledge Base Distillation in End-to-End Task Oriented Dialogs](https://aclanthology.org/2021.findings-acl.448/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
67. [Constructing Emotional Consensus and Utilizing Unpaired Data for Empathetic Dialogue Generation](https://aclanthology.org/2021.findings-emnlp.268/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
68. [Context-aware Adversarial Training for Name Regularity Bias in Named Entity Recognition](https://aclanthology.org/2021.tacl-1.36/) *— 2021 · Transactions of the Association for Computational Linguistics*
69. [Context-aware Decoder for Neural Machine Translation using a Target-side Document-Level Language Model](https://aclanthology.org/2021.naacl-main.461/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
70. [Context-aware Neural Machine Translation with Mini-batch Embedding](https://aclanthology.org/2021.eacl-main.214/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
71. [Contextualizing Variation in Text Style Transfer Datasets](https://aclanthology.org/2021.inlg-1.22/) *— 2021 · Proceedings of the 14th International Conference on Natural Language Generation*
72. [Continual Learning for Grounded Instruction Generation by Observing Human Following Behavior](https://aclanthology.org/2021.tacl-1.77/) *— 2021*
73. [Continual Learning for Task-oriented Dialogue System with Iterative Network Pruning, Expanding and Masking](https://aclanthology.org/2021.acl-short.66/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)*
74. [Continual Learning in Task-Oriented Dialogue Systems](https://aclanthology.org/2021.emnlp-main.590/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
75. [Continual Mixed-Language Pre-Training for Extremely Low-Resource Neural Machine Translation](https://aclanthology.org/2021.findings-acl.239/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
76. [Continuous Language Generative Flow](https://aclanthology.org/2021.acl-long.355/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
77. [Continuous Learning in Neural Machine Translation using Bilingual Dictionaries](https://aclanthology.org/2021.eacl-main.70/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
78. [Contrastive Attention for Automatic Chest X-ray Report Generation](https://aclanthology.org/2021.findings-acl.23/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
79. [Contrastive Conditioning for Assessing Disambiguation in MT: A Case Study of Distilled Bias](https://aclanthology.org/2021.emnlp-main.803/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
80. [Contrastive Learning for Context-aware Neural Machine Translation Using Coreference Information](https://aclanthology.org/2021.wmt-1.121/) *— 2021 · Proceedings of the Sixth Conference on Machine Translation*
81. [Contrastive Multi-document Question Generation](https://aclanthology.org/2021.eacl-main.2/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
82. [Contrastive Representation Learning for Exemplar-Guided Paraphrase Generation](https://aclanthology.org/2021.findings-emnlp.409/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
83. [Control Image Captioning Spatially and Temporally](https://aclanthology.org/2021.acl-long.157/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
84. [Controllable Abstractive Dialogue Summarization with Sketch Supervision](https://aclanthology.org/2021.findings-acl.454/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
85. [Controllable Open-ended Question Generation with A New Question Type Ontology](https://aclanthology.org/2021.acl-long.502/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
86. [Controllable Sentence Simplification with a Unified Text-to-Text Transfer Transformer](https://aclanthology.org/2021.inlg-1.38/) *— 2021 · Proceedings of the 14th International Conference on Natural Language Generation*
87. [Controllable Text Simplification with Explicit Paraphrasing](https://aclanthology.org/2021.naacl-main.277/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
88. [Controlling Text Edition by Changing Answers of Specific Questions](https://aclanthology.org/2021.findings-acl.110/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
89. [Conversational Multi-Hop Reasoning with Neural Commonsense Knowledge and Symbolic Logic Rules](https://aclanthology.org/2021.emnlp-main.588/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
90. [Conversations Are Not Flat: Modeling the Dynamic Information Flow across Dialogue Utterances](https://aclanthology.org/2021.acl-long.11/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
91. [Could you give me a hint ? Generating inference graphs for defeasible reasoning](https://aclanthology.org/2021.findings-acl.456/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
92. [Counter-Interference Adapter for Multilingual Machine Translation](https://aclanthology.org/2021.findings-emnlp.240/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
93. [Covering a sentence in form and meaning with fewer retrieved sentences](https://aclanthology.org/2021.paclic-1.54/) *— 2021 · Proceedings of the 35th Pacific Asia Conference on Language, Information and Computation*
94. [Crafting Adversarial Examples for Neural Machine Translation](https://aclanthology.org/2021.acl-long.153/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
95. [Cross Attention Augmented Transducer Networks for Simultaneous Translation](https://aclanthology.org/2021.emnlp-main.4/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
96. [Cross-Lingual Wolastoqey-English Definition Modelling](https://aclanthology.org/2021.ranlp-1.17/) *— 2021 · Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)*
97. [Cross-modal Memory Networks for Radiology Report Generation](https://aclanthology.org/2021.acl-long.459/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
98. [CrossVQA: Scalably Generating Benchmarks for Systematically Testing VQA Generalization](https://aclanthology.org/2021.emnlp-main.164/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
99. [DIRECT: Direct and Indirect Responses in Conversational Text Corpus](https://aclanthology.org/2021.findings-emnlp.170/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
100. [DOBF: A Deobfuscation Pre-Training Objective for Programming Languages](https://arxiv.org/abs/2102.07492) *— 2021 · arXiv:2102.07492*

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