---
title: "Findings of the Association for Computational Linguistics 2021 —"
description: "50 works of Findings of the Association for Computational Linguistics 2021 in our library, the most cited first."
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# Findings of the Association for Computational Linguistics 2021: all papers in our library

50 works · the most cited first · [← Findings of the Association for Computational Linguistics 2021](https://md.research.elamur.ai/free/en/venues/findings/2021/)

1. **[Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models](https://md.research.elamur.ai/free/en/papers/ni-2021-sentence-t5-scalable-sentence-encoders/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jianmo Ni, Gustavo Hernandez Abrego, Noah Constant, et al.*2021 · 581 citations*
2. **[GeDi: Generative Discriminator Guided Sequence Generation](https://md.research.elamur.ai/free/en/papers/krause-2021-gedi-generative-discriminator-guided-sequence/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ben Krause, Akhilesh Deepak Gotmare, Bryan McCann, et al.*2021 · 446 citations*
3. **[Template-Based Named Entity Recognition Using BART](https://md.research.elamur.ai/free/en/papers/cui-2021-template-based-named-entity-recognition/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Leyang Cui, Yu Wu, Jian Liu, et al.*2021 · 420 citations*
4. **[ProofWriter: Generating Implications, Proofs, and Abductive Statements over Natural Language](https://md.research.elamur.ai/free/en/papers/tafjord-2021-proofwriter-generating-implications-proofs-abductive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Oyvind Tafjord, Bhavana Dalvi, Peter Clark*2021 · 331 citations*
5. **[DialogSum: A Real-Life Scenario Dialogue Summarization Dataset](https://md.research.elamur.ai/free/en/papers/chen-2021-dialogsum-real-life-scenario-dialogue/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yulong Chen, Yang Liu, Liang Chen, et al.*2021 · 301 citations*
6. **[Want To Reduce Labeling Cost? GPT-3 Can Help](https://md.research.elamur.ai/free/en/papers/wang-2021-want-reduce-labeling-cost-gpt/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shuohang Wang, Yang Liu, Yichong Xu, et al.*2021 · 298 citations*
7. **[GPT3Mix: Leveraging Large-scale Language Models for Text Augmentation](https://md.research.elamur.ai/free/en/papers/yoo-2021-gpt3mix-leveraging-large-scale-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kang Min Yoo, Dongju Park, Jaewook Kang, et al.*2021 · 268 citations*
8. **[Detecting Hallucinated Content in Conditional Neural Sequence Generation](https://md.research.elamur.ai/free/en/papers/zhou-2021-detecting-hallucinated-content-conditional-neural/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chunting Zhou, Graham Neubig, Jiatao Gu, et al.*2021 · 229 citations*
9. **[Multilingual Translation from Denoising Pre-Training](https://md.research.elamur.ai/free/en/papers/tang-2021-multilingual-translation-denoising-pre-training/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuqing Tang, Chau Tran, Xian Li, et al.*2021 · 219 citations*
10. **[MOMENTA: A Multimodal Framework for Detecting Harmful Memes and Their Targets](https://md.research.elamur.ai/free/en/papers/pramanick-2021-momenta-multimodal-framework-detecting-harmful/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shraman Pramanick, Shivam Sharma, Dimitar Dimitrov, et al.*2021 · 212 citations*
11. **[Challenges in Detoxifying Language Models](https://md.research.elamur.ai/free/en/papers/welbl-2021-challenges-detoxifying-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Johannes Welbl, Amelia Glaese, Jonathan Uesato, et al.*2021 · 207 citations*
12. **[Retrieval Augmented Code Generation and Summarization](https://md.research.elamur.ai/free/en/papers/parvez-2021-retrieval-augmented-code-generation-summarization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Md Rizwan Parvez, Wasi Ahmad, Saikat Chakraborty, et al.*2021 · 191 citations*
13. **[GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning](https://md.research.elamur.ai/free/en/papers/chen-2021-geoqa-geometric-question-answering-benchmark/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaqi Chen, Jianheng Tang, Jinghui Qin, et al.*2021 · 183 citations*
14. **[ContractNLI: A Dataset for Document-level Natural Language Inference for Contracts](https://md.research.elamur.ai/free/en/papers/koreeda-2021-contractnli-dataset-document-level-natural/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuta Koreeda, Christopher Manning*2021 · 177 citations*
15. **[Detecting Harmful Memes and Their Targets](https://md.research.elamur.ai/free/en/papers/pramanick-2021-detecting-harmful-memes-their-targets/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shraman Pramanick, Dimitar Dimitrov, Rituparna Mukherjee, et al.*2021 · 171 citations*
16. **[P-Stance: A Large Dataset for Stance Detection in Political Domain](https://md.research.elamur.ai/free/en/papers/li-2021-p-stance-large-dataset-stance/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yingjie Li, Tiberiu Sosea, Aditya Sawant, et al.*2021 · 169 citations*
17. **[Sustainable Modular Debiasing of Language Models](https://md.research.elamur.ai/free/en/papers/lauscher-2021-sustainable-modular-debiasing-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Anne Lauscher, Tobias Lueken, Goran Glavaš*2021 · 165 citations*
18. **[Explaining NLP Models via Minimal Contrastive Editing (MiCE)](https://md.research.elamur.ai/free/en/papers/ross-2021-explaining-nlp-models-minimal-contrastive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Alexis Ross, Ana Marasović, Matthew Peters*2021 · 154 citations*
19. **[PLATO-2: Towards Building an Open-Domain Chatbot via Curriculum Learning](https://md.research.elamur.ai/free/en/papers/bao-2021-plato-2-building-open-domain/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Siqi Bao, Huang He, Fan Wang, et al.*2021 · 145 citations*
20. **[Out of Order: How important is the sequential order of words in a sentence in Natural Language Understanding tasks?](https://md.research.elamur.ai/free/en/papers/pham-2021-out-order-how-important-is/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Thang Pham, Trung Bui, Long Mai, et al.*2021 · 145 citations*
21. **[Fully Non-autoregressive Neural Machine Translation: Tricks of the Trade](https://md.research.elamur.ai/free/en/papers/gu-2021-fully-non-autoregressive-neural-machine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiatao Gu, Xiang Kong*2021 · 141 citations*
22. **[TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text Generation](https://md.research.elamur.ai/free/en/papers/uchendu-2021-turingbench-benchmark-environment-turing-test/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Adaku Uchendu, Zeyu Ma, Thai Le, et al.*2021 · 140 citations*
23. **[Enhancing Zero-shot and Few-shot Stance Detection with Commonsense Knowledge Graph](https://md.research.elamur.ai/free/en/papers/liu-2021-enhancing-zero-shot-few-shot/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rui Liu, Zheng Lin, Yutong Tan, et al.*2021 · 134 citations*
24. **[MAD-G: Multilingual Adapter Generation for Efficient Cross-Lingual Transfer](https://md.research.elamur.ai/free/en/papers/ansell-2021-mad-g-multilingual-adapter-generation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Alan Ansell, Edoardo Maria Ponti, Jonas Pfeiffer, et al.*2021 · 129 citations*
25. **[GO FIGURE: A Meta Evaluation of Factuality in Summarization](https://md.research.elamur.ai/free/en/papers/gabriel-2021-go-figure-meta-evaluation-factuality/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Saadia Gabriel, Asli Celikyilmaz, Rahul Jha, et al.*2021 · 129 citations*
26. **[Evidence-based Fact-Checking of Health-related Claims](https://md.research.elamur.ai/free/en/papers/sarrouti-2021-evidence-based-fact-checking-health/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mourad Sarrouti, Asma Ben Abacha, Yassine Mrabet, et al.*2021 · 129 citations*
27. **[DocNLI: A Large-scale Dataset for Document-level Natural Language Inference](https://md.research.elamur.ai/free/en/papers/yin-2021-docnli-large-scale-dataset-document/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenpeng Yin, Dragomir Radev, Caiming Xiong*2021 · 121 citations*
28. **[CDLM: Cross-Document Language Modeling](https://md.research.elamur.ai/free/en/papers/caciularu-2021-cdlm-cross-document-language-modeling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Avi Caciularu, Arman Cohan, Iz Beltagy, et al.*2021 · 106 citations*
29. **[Probing Across Time: What Does RoBERTa Know and When?](https://md.research.elamur.ai/free/en/papers/liu-2021-probing-across-time-what-does/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Leo Z. Liu, Yizhong Wang, Jungo Kasai, et al.*2021 · 94 citations*
30. **[As Good as New. How to Successfully Recycle English GPT-2 to Make Models for Other Languages](https://md.research.elamur.ai/free/en/papers/vries-2021-as-good-as-new-how/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wietse de Vries, Malvina Nissim*2021 · 91 citations*
31. **[BERT Busters: Outlier Dimensions that Disrupt Transformers](https://md.research.elamur.ai/free/en/papers/kovaleva-2021-bert-busters-outlier-dimensions-that/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Olga Kovaleva, Saurabh Kulshreshtha, Anna Rogers, et al.*2021 · 90 citations*
32. **[AStitchInLanguageModels: Dataset and Methods for the Exploration of Idiomaticity in Pre-Trained Language Models](https://md.research.elamur.ai/free/en/papers/madabushi-2021-astitchinlanguagemodels-dataset-methods-exploration-idiomaticity/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Harish Tayyar Madabushi, Edward Gow-Smith, Carolina Scarton, et al.*2021 · 86 citations*
33. **[Collecting a Large-Scale Gender Bias Dataset for Coreference Resolution and Machine Translation](https://md.research.elamur.ai/free/en/papers/levy-2021-collecting-large-scale-gender-bias/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shahar Levy, Koren Lazar, Gabriel Stanovsky*2021 · 82 citations*
34. **[It's All in the Heads: Using Attention Heads as a Baseline for Cross-Lingual Transfer in Commonsense Reasoning](https://md.research.elamur.ai/free/en/papers/tikhonov-2021-it-s-all-heads-attention/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Alexey Tikhonov, Max Ryabinin*2021 · 69 citations*
35. **[Figurative Language in Recognizing Textual Entailment](https://md.research.elamur.ai/free/en/papers/chakrabarty-2021-figurative-language-recognizing-textual-entailment/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tuhin Chakrabarty, Debanjan Ghosh, Adam Poliak, et al.*2021 · 63 citations*
36. **[Cross-document Coreference Resolution over Predicted Mentions](https://md.research.elamur.ai/free/en/papers/cattan-2021-cross-document-coreference-resolution-over/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Arie Cattan, Alon Eirew, Gabriel Stanovsky, et al.*2021 · 62 citations*
37. [**TellMeWhy: A Dataset for Answering Why-Questions in Narratives**Yash Kumar Lal, Nathanael Chambers, Raymond Mooney, et al.*2021 · 53 citations*](https://md.research.elamur.ai/free/en/papers/lal-2021-tellmewhy-dataset-answering-why-questions/)
38. [**Speaker Turn Modeling for Dialogue Act Classification**Zihao He, Leili Tavabi, Kristina Lerman, et al.*2021 · 43 citations*](https://md.research.elamur.ai/free/en/papers/he-2021-speaker-turn-modeling-dialogue-act/)
39. **[What Does Your Smile Mean? Jointly Detecting Multi-Modal Sarcasm and Sentiment Using Quantum Probability](https://md.research.elamur.ai/free/en/papers/liu-2021-what-does-your-smile-mean/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yaochen Liu, Yazhou Zhang, Qiuchi Li, et al.*2021 · 43 citations*
40. [**GRICE: A Grammar-based Dataset for Recovering Implicature and Conversational rEasoning**Zilong Zheng, Shuwen Qiu, Lifeng Fan, et al.*2021 · 36 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2021-grice-grammar-based-dataset-recovering/)
41. **[A Multi-Task Learning Framework for Multi-Target Stance Detection](https://md.research.elamur.ai/free/en/papers/li-2021-multi-task-learning-framework-multi/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yingjie Li, Cornelia Caragea*2021 · 31 citations*
42. **[Scaling Within Document Coreference to Long Texts](https://md.research.elamur.ai/free/en/papers/thirukovalluru-2021-scaling-within-document-coreference-long/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Raghuveer Thirukovalluru, Nicholas Monath, Kumar Shridhar, et al.*2021 · 24 citations*
43. **[Perceived and Intended Sarcasm Detection with Graph Attention Networks](https://md.research.elamur.ai/free/en/papers/plepi-2021-perceived-intended-sarcasm-detection-graph-2021-findings-emnlp-408/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Joan Plepi, Lucie Flek*2021 · 18 citations*
44. **[CVAE-based Re-anchoring for Implicit Discourse Relation Classification](https://md.research.elamur.ai/free/en/papers/dou-2021-cvae-based-re-anchoring-implicit/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zujun Dou, Yu Hong, Yu Sun, et al.*2021 · 16 citations*
45. **[End-to-end Neural Information Status Classification](https://md.research.elamur.ai/free/en/papers/hou-2021-end-end-neural-information-status/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yufang Hou*2021 · 12 citations*
46. **[Marked Attribute Bias in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/dawkins-2021-marked-attribute-bias-natural-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hillary Dawkins*2021 · 10 citations*
47. [**A Closer Look into the Robustness of Neural Dependency Parsers Using Better Adversarial Examples**Yuxuan Wang, Wanxiang Che, Ivan Titov, et al.*2021 · 8 citations*](https://md.research.elamur.ai/free/en/papers/wang-2021-closer-look-into-robustness-neural/)
48. [**Domain-Aware Dependency Parsing for Questions**Aparna Garimella, Laura Chiticariu, Yunyao Li*2021 · 4 citations*](https://md.research.elamur.ai/free/en/papers/garimella-2021-domain-aware-dependency-parsing-questions/)
49. **[Calibrate your listeners! Robust communication-based training for pragmatic speakers](https://md.research.elamur.ai/free/en/papers/wang-2021-calibrate-your-listeners-robust-communication/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rose Wang, Julia White, Jesse Mu, et al.*2021 · 4 citations*
50. [**Do UD Trees Match Mention Spans in Coreference Annotations?**Martin Popel, Zdeněk Žabokrtský, Anna Nedoluzhko, et al.*2021 · 3 citations*](https://md.research.elamur.ai/free/en/papers/popel-2021-do-ud-trees-match-mention/)
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