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Deep Learning for Text Style Transfer: A Survey

Di Jin, Zhijing Jin, Zhiting Hu, Olga Vechtomova, Rada Mihalcea
2021 Computational Linguistics  
We also provide discussions on a variety of important topics regarding the future development of this task.  ...  We discuss the task formulation, existing datasets and subtasks, evaluation, as well as the rich methodologies in the presence of parallel and non-parallel data.  ...  Language Processing, ACL/IJCNLP 2021, Lee, Joosung. 2020.  ... 
doi:10.1162/coli_a_00426 fatcat:v7vmb62ckfcu5k5mpu2pydnrxy

Few-Shot Table-to-Text Generation with Prototype Memory

Yixuan Su, Zaiqiao Meng, Simon Baker, Nigel Collier
2021 Findings of the Association for Computational Linguistics: EMNLP 2021   unpublished
In Findings of the Association for Com- two-stage model for low resource table-to-text gen- putational Linguistics: ACL/IJCNLP 2021, Online eration.  ...  In Proceedings of the 57th Conference of Event, August 1-6, 2021, pages 560–569.  ... 
doi:10.18653/v1/2021.findings-emnlp.77 fatcat:2cctb4aqnzfslgw7rtn73cxr2u

Keyphrase Generation with Fine-Grained Evaluation-Guided Reinforcement Learning

Yichao Luo, Yige Xu, Jiacheng Ye, Xipeng Qiu, Qi Zhang
2021 Findings of the Association for Computational Linguistics: EMNLP 2021   unpublished
1: Long Papers), Vir- tual Event, August 1-6, 2021, pages 4598–4608.  ...  In Proceedings of the 59th Annual Meeting of the Association for Com- putational Linguistics and the 11th International Joint Conference on Natural Language Processing, ACL/IJCNLP 2021, (Volume  ... 
doi:10.18653/v1/2021.findings-emnlp.45 fatcat:5s7tdmq5cnh5bkey45jaysgyhy

DoCoGen: Domain Counterfactual Generation for Low Resource Domain Adaptation [article]

Nitay Calderon and Eyal Ben-David and Amir Feder and Roi Reichart
2022 arXiv   pre-print
Our model outperforms strong baselines and improves the accuracy of a state-of-the-art unsupervised DA algorithm.  ...  Given an input text example, our DoCoGen algorithm generates a domain-counterfactual textual example (D-con) - that is similar to the original in all aspects, including the task label, but its domain is  ...  Acknowledgements We would like to thank the action editor and the reviewers, as well as the members of the IE@Technion NLP group for their valuable feedback and advice.  ... 
arXiv:2202.12350v2 fatcat:7uomvkwjuvcctpghiy5kxbcnpe

Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little [article]

Koustuv Sinha, Robin Jia, Dieuwke Hupkes, Joelle Pineau, Adina Williams, Douwe Kiela
2021 arXiv   pre-print
A possible explanation for the impressive performance of masked language model (MLM) pre-training is that such models have learned to represent the syntactic structures prevalent in classical NLP pipelines  ...  linguistic knowledge.  ...  We also thank the anonymous reviewers for their constructive feedback during the reviewing phase, which helped polish the paper to its current state.  ... 
arXiv:2104.06644v2 fatcat:6arq2lp37zbctln637ommaiqvu

Deep Learning for Text Style Transfer: A Survey [article]

Di Jin, Zhijing Jin, Zhiting Hu, Olga Vechtomova, Rada Mihalcea
2021 arXiv   pre-print
We discuss the task formulation, existing datasets and subtasks, evaluation, as well as the rich methodologies in the presence of parallel and non-parallel data.  ...  We also provide discussions on a variety of important topics regarding the future development of this task. Our curated paper list is at https://github.com/zhijing-jin/Text_Style_Transfer_Survey  ...  Language Processing, ACL/IJCNLP 2021, Lee, Joosung. 2020.  ... 
arXiv:2011.00416v5 fatcat:wfw3jfh2mjfupbzrmnztsqy4ny

Contrastive Learning of Sociopragmatic Meaning in Social Media [article]

Chiyu Zhang, Muhammad Abdul-Mageed, Ganesh Jawahar
2022 arXiv   pre-print
Our framework outperforms other contrastive learning frameworks for both in-domain and out-of-domain data, across both the general and few-shot settings.  ...  Recent progress in representation and contrastive learning in NLP has not widely considered the class of sociopragmatic meaning (i.e., meaning in interaction within different language communities).  ...  Canada (SSHRC; 435-2018-0576; 895-2020-1004; 895-2021-1008), Canadian Foundation for Innovation (CFI; 37771), Compute Canada (CC), 12 and UBC ARC-Sockeye. 13 Any opinions, conclusions or recommendations  ... 
arXiv:2203.07648v2 fatcat:6zmhiogvirdlznoaqonyuesc54

UNKs Everywhere: Adapting Multilingual Language Models to New Scripts [article]

Jonas Pfeiffer, Ivan Vulić, Iryna Gurevych, Sebastian Ruder
2021 arXiv   pre-print
Furthermore, we show that learning of the new dedicated embedding matrix in the target language can be improved by leveraging a small number of vocabulary items (i.e., the so-called lexically overlapping  ...  We also demonstrate that they can yield improvements for low-resource languages written in scripts covered by the pretrained model.  ...  We thank Laura Rimell, Nils Reimers, Michael Bugert and the anonymous reviewers for insightful feedback and suggestions on a draft of this paper.  ... 
arXiv:2012.15562v3 fatcat:4zrgue5xyfbu5ft4fun5jaspx4

A Primer on Pretrained Multilingual Language Models [article]

Sumanth Doddapaneni, Gowtham Ramesh, Mitesh M. Khapra, Anoop Kunchukuttan, Pratyush Kumar
2021 arXiv   pre-print
Multilingual Language Models () such as mBERT, XLM, XLM-R, etc. have emerged as a viable option for bringing the power of pretraining to a large number of languages.  ...  variety of tasks and languages for evaluating (iii) analysing the performance of on monolingual, zero-shot cross-lingual and bilingual tasks (iv) understanding the universal language patterns (if any)  ...  CoRR, ACL/IJCNLP 2021, (Volume 1: Long Papers), Vir- abs/2004.14327. tual Event, August 1-6, 2021, pages 3118–3135. As- Aaron van den Oord, Yazhe Li, and Oriol Vinyals.  ... 
arXiv:2107.00676v2 fatcat:jvvt6wwitvg2lc7bmttvv3aw6m

Paradigm Shift in Natural Language Processing [article]

Tianxiang Sun, Xiangyang Liu, Xipeng Qiu, Xuanjing Huang
2021 arXiv   pre-print
In the era of deep learning, modeling for most NLP tasks has converged to several mainstream paradigms.  ...  For example, we usually adopt the sequence labeling paradigm to solve a bundle of tasks such as POS-tagging, NER, Chunking, and adopt the classification paradigm to solve tasks like sentiment analysis.  ...  ), Virtual Event, August 1-6, 2021, pages 7183-7195.  ... 
arXiv:2109.12575v1 fatcat:vckeva3u3va3vjr6okhuztox4y

Few-shot Learning with Multilingual Language Models [article]

Xi Victoria Lin, Todor Mihaylov, Mikel Artetxe, Tianlu Wang, Shuohui Chen, Daniel Simig, Myle Ott, Naman Goyal, Shruti Bhosale, Jingfei Du, Ramakanth Pasunuru, Sam Shleifer (+9 others)
2021 arXiv   pre-print
We present a detailed analysis of where the model succeeds and fails, showing in particular that it enables cross-lingual in-context learning on some tasks, while there is still room for improvement on  ...  On the FLORES-101 machine translation benchmark, our model outperforms GPT-3 on 171 out of 182 translation directions with 32 training examples, while surpassing the official supervised baseline in 45  ...  guistics: ACL/IJCNLP 2021, Online Event, August 1-6, 2021, volume ACL/IJCNLP 2021 of Findings Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali of ACL, pages 3534–3546.  ... 
arXiv:2112.10668v1 fatcat:ehexgbyr5jfetimihdd66sxdtm

ElitePLM: An Empirical Study on General Language Ability Evaluation of Pretrained Language Models [article]

Junyi Li, Tianyi Tang, Zheng Gong, Lixin Yang, Zhuohao Yu, Zhipeng Chen, Jingyuan Wang, Wayne Xin Zhao, Ji-Rong Wen
2022 arXiv   pre-print
Moreover, the prediction results of PLMs in our experiments are released as an open resource for more deep and detailed analysis on the language abilities of PLMs.  ...  This paper can guide the future work to select, apply, and design PLMs for specific tasks. We have made all the details of experiments publicly available at https://github.com/RUCAIBox/ElitePLM.  ...  Association for Computational Linguistics. sented in Table 10. 2021, Online Event, August 1-6, 2021, volume ACL/IJCNLP 2021 of Findings of ACL, pages 1558- Reasoning Tests.  ... 
arXiv:2205.01523v1 fatcat:d2qusgoj75aefa32btqgtkybdi

Evaluating Explanations: How much do explanations from the teacher aid students? [article]

Danish Pruthi, Rachit Bansal, Bhuwan Dhingra, Livio Baldini Soares, Michael Collins, Zachary C. Lipton, Graham Neubig, William W. Cohen
2021 arXiv   pre-print
In this work, we introduce a framework to quantify the value of explanations via the accuracy gains that they confer on a student model trained to simulate a teacher model.  ...  Crucially, the explanations are available to the student during training, but are not available at test time.  ...  Findings Kayo Yin, Patrick Fernandes, Danish Pruthi, Aditi of the Association for Computational Linguistics: Chaudhary, André F. T.  ... 
arXiv:2012.00893v2 fatcat:czmvmj4525fcdffimhaxqxtgdu

DoCoGen: Domain Counterfactual Generation for Low Resource Domain Adaptation

Nitay Calderon, Eyal Ben-David, Amir Feder, Roi Reichart
2022 Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)   unpublished
Our model outperforms strong baselines and improves the accuracy of a state-of-the-art unsupervised DA algorithm. 1  ...  Given an input text example, our DoCoGen algorithm generates a domain-counterfactual textual example (D-CON) -that is similar to the original in all aspects, including the task label, but its domain is  ...  Acknowledgements We would like to thank the action editor and the reviewers, as well as the members of the IE@Technion NLP group for their valuable feedback and advice.  ... 
doi:10.18653/v1/2022.acl-long.533 fatcat:lkukck3wn5d4hdcbn6xidk7smm

Theoretical and Practical Issues in the Semantic Annotation of Four Indigenous Languages

Jens E. L. Van Gysel, Meagan Vigus, Lukas Denk, Andrew Cowell, Rosa Vallejos, Tim O'Gorman, William Croft
2021 Proceedings of The Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop   unpublished
In Findings of the Association for Com- putational Linguistics: ACL-IJCNLP 2021, pages Deng Cai and Wai Lam. 2020.  ...  In Proceedings of the Linguistics. 58th Annual Meeting of the Association for Compu- tational Linguistics, pages 1290–1301, Online.  ... 
doi:10.18653/v1/2021.law-1.2 fatcat:k5zsmrpu7rbdldjc2qleaxuhmi
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