---
title: "TACL 2021 — all accepted papers with summaries and citations"
description: "All 93 papers of TACL 2021, the most cited first; those with our summary link to it. Among them: A Biologically Plausible Parser ↗."
canonical: "https://research.elamur.ai/free/en/venues/tacl/2021/papers/"
---
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# TACL 2021: all accepted papers

93 papers · the most cited first · [← TACL 2021](https://md.research.elamur.ai/free/en/venues/tacl/2021/)

1. **[A Biologically Plausible Parser ↗](https://aclanthology.org/2021.tacl-1.81/)**Daniel Mitropolsky, Michael J. Collins, Christos H. Papadimitriou
2. **[A Computational Framework for Slang Generation ↗](https://aclanthology.org/2021.tacl-1.28/)**Zhewei Sun, Richard Zemel, Yang Xu
3. **[A Statistical Analysis of Summarization Evaluation Metrics Using Resampling Methods](https://md.research.elamur.ai/free/en/papers/deutsch-2021-statistical-analysis-summarization-evaluation-metrics/)**Daniel Deutsch, Rotem Dror, Dan Roth*our summary*
4. **[Adaptive Semiparametric Language Models ↗](https://aclanthology.org/2021.tacl-1.22/)**Dani Yogatama, Cyprien de Masson d'Autume, Lingpeng Kong
5. **[Aligning Faithful Interpretations with their Social Attribution](https://md.research.elamur.ai/free/en/papers/jacovi-2021-aligning-faithful-interpretations-their-social/)**Alon Jacovi, Yoav Goldberg*our summary*
6. **[Amnesic Probing: Behavioral Explanation with Amnesic Counterfactuals](https://md.research.elamur.ai/free/en/papers/elazar-2021-amnesic-probing-behavioral-explanation-amnesic/)**Yanai Elazar, Shauli Ravfogel, Alon Jacovi et al.*our summary*
7. **[An Error Analysis Framework for Shallow Surface Realization](https://md.research.elamur.ai/free/en/papers/shimorina-2021-error-analysis-framework-shallow-surface/)**Anastasia Shimorina, Yannick Parmentier, Claire Gardent*our summary*
8. **[Augmenting Transformers with KNN-Based Composite Memory for Dialog ↗](https://aclanthology.org/2021.tacl-1.6/)**Angela Fan, Claire Gardent, Chloé Braud et al.
9. **[Characterizing English Variation across Social Media Communities with BERT ↗](https://aclanthology.org/2021.tacl-1.33/)**Li Lucy, David Bamman
10. **[Classifying Argumentative Relations Using Logical Mechanisms and Argumentation Schemes ↗](https://aclanthology.org/2021.tacl-1.44/)**Yohan Jo, Seojin Bang, Chris Reed et al.
11. **[Compressing Large-Scale Transformer-Based Models: A Case Study on BERT](https://md.research.elamur.ai/free/en/papers/ganesh-2021-compressing-large-scale-transformer-based/)**Prakhar Ganesh, Yao Chen, Xin Lou et al.*our summary*
12. **[Context-aware Adversarial Training for Name Regularity Bias in Named Entity Recognition ↗](https://aclanthology.org/2021.tacl-1.36/)**Abbas Ghaddar, Philippe Langlais, Ahmad Rashid et al.
13. **[Continual Learning for Grounded Instruction Generation by Observing Human Following Behavior ↗](https://aclanthology.org/2021.tacl-1.77/)**Noriyuki Kojima, Alane Suhr, Yoav Artzi
14. **[Controllable Summarization with Constrained Markov Decision Process ↗](https://aclanthology.org/2021.tacl-1.72/)**Hou Pong Chan, Lu Wang, Irwin King
15. **[Conversation Graph: Data Augmentation, Training, and Evaluation for Non-Deterministic Dialogue Management ↗](https://aclanthology.org/2021.tacl-1.3/)**Milan Gritta, Gerasimos Lampouras, Ignacio Iacobacci
16. **[Data-to-text Generation with Macro Planning](https://md.research.elamur.ai/free/en/papers/puduppully-2021-data-text-generation-macro-planning/)**Ratish Puduppully, Mirella Lapata*our summary*
17. **[Deciphering Undersegmented Ancient Scripts Using Phonetic Prior](https://md.research.elamur.ai/free/en/papers/luo-2021-deciphering-undersegmented-ancient-scripts-phonetic/)**Jiaming Luo, Frederik Hartmann, Enrico Santus et al.*our summary*
18. **[Decontextualization: Making Sentences Stand-Alone](https://md.research.elamur.ai/free/en/papers/choi-2021-decontextualization-making-sentences-stand-alone/)**Eunsol Choi, Jennimaria Palomaki, Matthew Lamm et al.*our summary*
19. **[Decoupling the Role of Data, Attention, and Losses in Multimodal Transformers ↗](https://aclanthology.org/2021.tacl-1.35/)**Lisa Anne Hendricks, John Mellor, Rosalia Schneider et al.
20. **[Dialogue State Tracking with Incremental Reasoning ↗](https://aclanthology.org/2021.tacl-1.34/)**Lizi Liao, Le Hong Long, Yunshan Ma et al.
21. **[Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies ↗](https://aclanthology.org/2021.tacl-1.21/)**Mor Geva, Daniel Khashabi, Elad Segal et al.
22. **[Differentiable Subset Pruning of Transformer Heads ↗](https://aclanthology.org/2021.tacl-1.86/)**Jiaoda Li, Ryan Cotterell, Mrinmaya Sachan
23. **[EDITOR: An Edit-Based Transformer with Repositioning for Neural Machine Translation with Soft Lexical Constraints ↗](https://aclanthology.org/2021.tacl-1.19/)**Weijia Xu, Marine Carpuat
24. **[Efficient Computation of Expectations under Spanning Tree Distributions ↗](https://aclanthology.org/2021.tacl-1.41/)**Ran Zmigrod, Tim Vieira, Ryan Cotterell
25. **[Efficient Content-Based Sparse Attention with Routing Transformers ↗](https://aclanthology.org/2021.tacl-1.4/)**Aurko Roy, Mohammad Saffar, Ashish Vaswani et al.
26. **[Erratum: Measuring and Improving Consistency in Pretrained Language Models ↗](https://aclanthology.org/2021.tacl-1.83/)**Yanai Elazar, Nora Kassner, Shauli Ravfogel et al.
27. **[Evaluating Document Coherence Modeling ↗](https://aclanthology.org/2021.tacl-1.38/)**Aili Shen, Meladel Mistica, Bahar Salehi et al.
28. **[Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation](https://md.research.elamur.ai/free/en/papers/freitag-2021-experts-errors-context-large-scale/)**Markus Freitag, George Foster, David Grangier et al.*our summary*
29. **[Explanation-Based Human Debugging of NLP Models: A Survey ↗](https://aclanthology.org/2021.tacl-1.90/)**Piyawat Lertvittayakumjorn, Francesca Toni
30. **[Extractive Opinion Summarization in Quantized Transformer Spaces](https://md.research.elamur.ai/free/en/papers/angelidis-2021-extractive-opinion-summarization-quantized-transformer/)**Stefanos Angelidis, Reinald Kim Amplayo, Yoshihiko Suhara et al.*our summary*
31. **[Gender Bias in Machine Translation](https://md.research.elamur.ai/free/en/papers/savoldi-2021-gender-bias-machine-translation/)**Beatrice Savoldi, Marco Gaido, Luisa Bentivogli et al.*our summary*
32. **[He Thinks He Knows Better than the Doctors: BERT for Event Factuality Fails on Pragmatics](https://md.research.elamur.ai/free/en/papers/jiang-2021-he-thinks-he-knows-better/)**Nanjiang Jiang, Marie-Catherine de Marneffe*our summary*
33. **[How Can We Know When Language Models Know? On the Calibration of Language Models for Question Answering ↗](https://aclanthology.org/2021.tacl-1.57/)**Zhengbao Jiang, Jun Araki, Haibo Ding et al.
34. **[Identity-Based Patterns in Deep Convolutional Networks: Generative Adversarial Phonology and Reduplication ↗](https://aclanthology.org/2021.tacl-1.70/)**Gašper Beguš
35. **[Idiomatic Expression Identification using Semantic Compatibility](https://md.research.elamur.ai/free/en/papers/zeng-2021-idiomatic-expression-identification-semantic-compatibility/)**Ziheng Zeng, Suma Bhat*our summary*
36. **[Infusing Finetuning with Semantic Dependencies ↗](https://aclanthology.org/2021.tacl-1.14/)**Zhaofeng Wu, Hao Peng, Noah A. Smith
37. **[Instance-Based Neural Dependency Parsing ↗](https://aclanthology.org/2021.tacl-1.89/)**Hiroki Ouchi, Jun Suzuki, Sosuke Kobayashi et al.
38. **[Iterative Paraphrastic Augmentation with Discriminative Span Alignment ↗](https://aclanthology.org/2021.tacl-1.30/)**Ryan Culkin, J. Edward Hu, Elias Stengel-Eskin et al.
39. **[Joint Universal Syntactic and Semantic Parsing](https://md.research.elamur.ai/free/en/papers/eskin-2021-joint-universal-syntactic-semantic-parsing/)**Elias Stengel-Eskin, Kenton Murray, Sheng Zhang et al.*our summary*
40. **[KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation ↗](https://aclanthology.org/2021.tacl-1.11/)**Xiaozhi Wang, Tianyu Gao, Zhaocheng Zhu et al.
41. **[Latent Compositional Representations Improve Systematic Generalization in Grounded Question Answering ↗](https://aclanthology.org/2021.tacl-1.12/)**Ben Bogin, Sanjay Subramanian, Matt Gardner et al.
42. **[Let's Play Mono-Poly: BERT Can Reveal Words' Polysemy Level and Partitionability into Senses ↗](https://aclanthology.org/2021.tacl-1.50/)**Aina Garí Soler, Marianna Apidianaki
43. **[Lexically Aware Semi-Supervised Learning for OCR Post-Correction ↗](https://aclanthology.org/2021.tacl-1.76/)**Shruti Rijhwani, Daisy Rosenblum, Antonios Anastasopoulos et al.
44. **[MKQA: A Linguistically Diverse Benchmark for Multilingual Open Domain Question Answering ↗](https://aclanthology.org/2021.tacl-1.82/)**Shayne Longpre, Yi Lu, Joachim Daiber
45. **[Maintaining Common Ground in Dynamic Environments](https://md.research.elamur.ai/free/en/papers/udagawa-2021-maintaining-common-ground-dynamic-environments/)**Takuma Udagawa, Akiko Aizawa*our summary*
46. **[MasakhaNER: Named Entity Recognition for African Languages](https://md.research.elamur.ai/free/en/papers/adelani-2021-masakhaner-named-entity-recognition-african/)**David Ifeoluwa Adelani, Jade Abbott, Graham Neubig et al.*our summary*
47. **[Measuring and Improving Consistency in Pretrained Language Models ↗](https://aclanthology.org/2021.tacl-1.60/)**Yanai Elazar, Nora Kassner, Shauli Ravfogel et al.
48. **[Memory-Based Semantic Parsing ↗](https://aclanthology.org/2021.tacl-1.71/)**Parag Jain, Mirella Lapata
49. **[Model Compression for Domain Adaptation through Causal Effect Estimation ↗](https://aclanthology.org/2021.tacl-1.80/)**Guy Rotman, Amir Feder, Roi Reichart
50. **[Modeling Content and Context with Deep Relational Learning ↗](https://aclanthology.org/2021.tacl-1.7/)**Maria Leonor Pacheco, Dan Goldwasser
51. **[Morphology Matters: A Multilingual Language Modeling Analysis ↗](https://aclanthology.org/2021.tacl-1.16/)**Hyunji Hayley Park, Katherine J. Zhang, Coleman Haley et al.
52. **[Multimodal Pretraining Unmasked: A Meta-Analysis and a Unified Framework of Vision-and-Language BERTs ↗](https://aclanthology.org/2021.tacl-1.58/)**Emanuele Bugliarello, Ryan Cotterell, Naoaki Okazaki et al.
53. **[Narrative Question Answering with Cutting-Edge Open-Domain QA Techniques: A Comprehensive Study ↗](https://aclanthology.org/2021.tacl-1.61/)**Xiangyang Mou, Chenghao Yang, Mo Yu et al.
54. **[Neural Event Semantics for Grounded Language Understanding ↗](https://aclanthology.org/2021.tacl-1.52/)**Shyamal Buch, Li Fei-Fei, Noah D. Goodman
55. **[Neural Modeling for Named Entities and Morphology (NEMO2)](https://md.research.elamur.ai/free/en/papers/bareket-2021-neural-modeling-named-entities-morphology/)**Dan Bareket, Reut Tsarfaty*our summary*
56. **[Neural OCR Post-Hoc Correction of Historical Corpora ↗](https://aclanthology.org/2021.tacl-1.29/)**Lijun Lyu, Maria Koutraki, Martin Krickl et al.
57. **[On Generative Spoken Language Modeling from Raw Audio](https://md.research.elamur.ai/free/en/papers/lakhotia-2021-generative-spoken-language-modeling-raw/)**Kushal Lakhotia, Eugene Kharitonov, Wei-Ning Hsu et al.*our summary*
58. **[On the Difficulty of Translating Free-Order Case-Marking Languages ↗](https://aclanthology.org/2021.tacl-1.73/)**Arianna Bisazza, Ahmet Üstün, Stephan Sportel
59. **[On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs ↗](https://aclanthology.org/2021.tacl-1.9/)**Adina Williams, Ryan Cotterell, Lawrence Wolf-Sonkin et al.
60. **[Optimizing over subsequences generates context-sensitive languages ↗](https://aclanthology.org/2021.tacl-1.32/)**Andrew Lamont
61. **[PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them](https://md.research.elamur.ai/free/en/papers/lewis-2021-paq-65-million-probably-asked/)**Patrick Lewis, Yuxiang Wu, Linqing Liu et al.*our summary*
62. **[Parameter Space Factorization for Zero-Shot Learning across Tasks and Languages ↗](https://aclanthology.org/2021.tacl-1.25/)**Edoardo M. Ponti, Ivan Vulić, Ryan Cotterell et al.
63. **[ParsiNLU: A Suite of Language Understanding Challenges for Persian ↗](https://aclanthology.org/2021.tacl-1.68/)**Daniel Khashabi, Arman Cohan, Siamak Shakeri et al.
64. **[Partially Supervised Named Entity Recognition via the Expected Entity Ratio Loss ↗](https://aclanthology.org/2021.tacl-1.78/)**Thomas Effland, Michael Collins
65. **[Planning with Learned Entity Prompts for Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/narayan-2021-planning-learned-entity-prompts-abstractive/)**Shashi Narayan, Yao Zhao, Joshua Maynez et al.*our summary*
66. **[Pretraining the Noisy Channel Model for Task-Oriented Dialogue ↗](https://aclanthology.org/2021.tacl-1.40/)**Qi Liu, Lei Yu, Laura Rimell et al.
67. **[Provable Limitations of Acquiring Meaning from Ungrounded Form: What Will Future Language Models Understand?](https://md.research.elamur.ai/free/en/papers/merrill-2021-provable-limitations-acquiring-meaning-ungrounded/)**William Merrill, Yoav Goldberg, Roy Schwartz et al.*our summary*
68. **[QED: A Framework and Dataset for Explanations in Question Answering](https://md.research.elamur.ai/free/en/papers/lamm-2021-qed-framework-dataset-explanations-question/)**Matthew Lamm, Jennimaria Palomaki, Chris Alberti et al.*our summary*
69. **[Quantifying Cognitive Factors in Lexical Decline ↗](https://aclanthology.org/2021.tacl-1.91/)**David Francis, Ella Rabinovich, Farhan Samir et al.
70. **[Quantifying Social Biases in NLP: A Generalization and Empirical Comparison of Extrinsic Fairness Metrics](https://md.research.elamur.ai/free/en/papers/czarnowska-2021-quantifying-social-biases-nlp-generalization/)**Paula Czarnowska, Yogarshi Vyas, Kashif Shah*our summary*
71. **[Recursive Non-Autoregressive Graph-to-Graph Transformer for Dependency Parsing with Iterative Refinement](https://md.research.elamur.ai/free/en/papers/mohammadshahi-2021-recursive-non-autoregressive-graph-graph/)**Alireza Mohammadshahi, James Henderson*our summary*
72. **[Reducing Confusion in Active Learning for Part-Of-Speech Tagging ↗](https://aclanthology.org/2021.tacl-1.1/)**Aditi Chaudhary, Antonios Anastasopoulos, Zaid Sheikh et al.
73. **[Relevance-guided Supervision for OpenQA with ColBERT](https://md.research.elamur.ai/free/en/papers/khattab-2021-relevance-guided-supervision-openqa-colbert/)**Omar Khattab, Christopher Potts, Matei Zaharia*our summary*
74. **[Revisiting Few-shot Relation Classification: Evaluation Data and Classification Schemes ↗](https://aclanthology.org/2021.tacl-1.42/)**Ofer Sabo, Yanai Elazar, Yoav Goldberg et al.
75. **[Revisiting Multi-Domain Machine Translation ↗](https://aclanthology.org/2021.tacl-1.2/)**MinhQuang Pham, Josep Maria Crego, François Yvon
76. **[Revisiting Negation in Neural Machine Translation ↗](https://aclanthology.org/2021.tacl-1.45/)**Gongbo Tang, Philipp Rönchen, Rico Sennrich et al.
77. **[Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP ↗](https://aclanthology.org/2021.tacl-1.84/)**Timo Schick, Sahana Udupa, Hinrich Schütze
78. **[Self-supervised Regularization for Text Classification ↗](https://aclanthology.org/2021.tacl-1.39/)**Meng Zhou, Zechen Li, Pengtao Xie
79. **[Sensitivity as a Complexity Measure for Sequence Classification Tasks ↗](https://aclanthology.org/2021.tacl-1.53/)**Michael Hahn, Dan Jurafsky, Richard Futrell
80. **[Soloist: Building Task Bots at Scale with Transfer Learning and Machine Teaching ↗](https://aclanthology.org/2021.tacl-1.49/)**Baolin Peng, Chunyuan Li, Jinchao Li et al.
81. **[Sparse, Dense, and Attentional Representations for Text Retrieval](https://md.research.elamur.ai/free/en/papers/luan-2021-sparse-dense-attentional-representations-text/)**Yi Luan, Jacob Eisenstein, Kristina Toutanova et al.*our summary*
82. **[Strong Equivalence of TAG and CCG ↗](https://aclanthology.org/2021.tacl-1.43/)**Lena Katharina Schiffer, Andreas Maletti
83. **[Structured Self-Supervised Pretraining for Commonsense Knowledge Graph Completion ↗](https://aclanthology.org/2021.tacl-1.75/)**Jiayuan Huang, Yangkai Du, Shuting Tao et al.
84. **[SummEval: Re-evaluating Summarization Evaluation ↗](https://aclanthology.org/2021.tacl-1.24/)**Alexander R. Fabbri, Wojciech Kryściński, Bryan McCann et al.
85. **[Supertagging the Long Tail with Tree-Structured Decoding of Complex Categories ↗](https://aclanthology.org/2021.tacl-1.15/)**Jakob Prange, Nathan Schneider, Vivek Srikumar
86. **[There Once Was a Really Bad Poet, It Was Automated but You Didn't Know It ↗](https://aclanthology.org/2021.tacl-1.37/)**Jianyou Wang, Xiaoxuan Zhang, Yuren Zhou et al.
87. **[Towards Question-Answering as an Automatic Metric for Evaluating the Content Quality of a Summary](https://md.research.elamur.ai/free/en/papers/deutsch-2021-question-answering-as-automatic-metric/)**Daniel Deutsch, Tania Bedrax-Weiss, Dan Roth*our summary*
88. **[Unsupervised Abstractive Opinion Summarization by Generating Sentences with Tree-Structured Topic Guidance ↗](https://aclanthology.org/2021.tacl-1.56/)**Masaru Isonuma, Junichiro Mori, Danushka Bollegala et al.
89. **[Unsupervised Learning of KB Queries in Task-Oriented Dialogs ↗](https://aclanthology.org/2021.tacl-1.23/)**Dinesh Raghu, Nikhil Gupta, Mausam
90. **[Weisfeiler-Leman in the Bamboo: Novel AMR Graph Metrics and a Benchmark for AMR Graph Similarity](https://md.research.elamur.ai/free/en/papers/opitz-2021-weisfeiler-leman-bamboo-novel-amr/)**Juri Opitz, Angel Daza, Anette Frank*our summary*
91. **[What Helps Transformers Recognize Conversational Structure? Importance of Context, Punctuation, and Labels in Dialog Act Recognition](https://md.research.elamur.ai/free/en/papers/zelasko-2021-what-helps-transformers-recognize-conversational/)**Piotr Żelasko, Raghavendra Pappagari, Najim Dehak*our summary*
92. **[WikiAsp: A Dataset for Multi-domain Aspect-based Summarization ↗](https://aclanthology.org/2021.tacl-1.13/)**Hiroaki Hayashi, Prashant Budania, Peng Wang et al.
93. **[Word Representation Learning in Multimodal Pre-Trained Transformers: An Intrinsic Evaluation ↗](https://aclanthology.org/2021.tacl-1.93/)**Sandro Pezzelle, Ece Takmaz, Raquel Fernández
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