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Positioning yourself in the maze of Neural Text Generation: A Task-Agnostic Survey [article]

Khyathi Raghavi Chandu, Alan W Black
2021 arXiv   pre-print
Thereby, we deliver a one-stop destination for researchers in the field to facilitate a perspective on where to situate their work and how it impacts other closely related generation tasks.  ...  In order to progress research in text generation, it is critical to absorb the existing research works and position ourselves in this massively growing field.  ...  In Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL 2019, Florence, Italy, July 28-August 2, 2019, Volume 1: Long Papers, pages 2650-2660.  ... 
arXiv:2010.07279v2 fatcat:jp76n5vk7zbvnhfexhwa3rludu

The Expression of Moral Values in the Twitter Debate: a Corpus of Conversations

Marco Stranisci, Michele De Leonardis, Cristina Bosco, Viviana Patti
2021 Italian Journal of Computational Linguistics  
In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 2819–2829, Florence, Italy, July-August. Core, Mark G. and James Allen. 1997.  ...  In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 720–730, Melbourne, Australia, July.  ... 
doi:10.4000/ijcol.880 fatcat:7rwvh6qe2rhhrh2fozcxrctvfy

On the Robustness of Language Encoders against Grammatical Errors [article]

Fan Yin, Quanyu Long, Tao Meng, Kai-Wei Chang
2020 arXiv   pre-print
To interpret model behaviors, we further design a linguistic acceptability task to reveal their abilities in identifying ungrammatical sentences and the position of errors.  ...  Results confirm that the performance of all tested models is affected but the degree of impact varies.  ...  Acknowledgements We would like to thank the anonymous reviewers for their feedback. This work is supported by NSF Grant #IIS-1927554.  ... 
arXiv:2005.05683v1 fatcat:6lo24qidevhtjduvef466wq4pe

Reinforcement Learning-based Dialogue Guided Event Extraction to Exploit Argument Relations [article]

Qian Li, Hao Peng, Jianxin Li, Jia Wu, Yuanxing Ning, Lihong Wang, Philip S. Yu, Zheng Wang
2021 arXiv   pre-print
Event extraction is a fundamental task for natural language processing. Finding the roles of event arguments like event participants is essential for event extraction.  ...  Experimental results show that our approach consistently outperforms seven state-of-the-art event extraction methods for the classification of events and argument role and argument identification.  ...  Linguistics, ACL 2019, Florence, Italy, July 28- August 2, 2019, Volume Processing, ACL 2015, July 26-31, 2015, Beijing, China, Volume 1: 1: Long Papers, pp. 1340–1350, 2019.  ... 
arXiv:2106.12384v2 fatcat:blyylym77vdupbrolil2dtmrna

A Primer on Pretrained Multilingual Language Models [article]

Sumanth Doddapaneni, Gowtham Ramesh, Mitesh M. Khapra, Anoop Kunchukuttan, Pratyush Kumar
2021 arXiv   pre-print
In this survey, we review the existing literature covering the above broad areas of research pertaining to . Based on our survey, we recommend some promising directions of future research.  ...  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.  ...  , ACL 2019, Florence, Asahara, Luma Ateyah, Mohammed Attia, and Italy, July 28- August 2, 2019, Volume 1: Long Pa- et. al. 2018a.  ... 
arXiv:2107.00676v2 fatcat:jvvt6wwitvg2lc7bmttvv3aw6m

Logic2Text: High-Fidelity Natural Language Generation from Logical Forms [article]

Zhiyu Chen, Wenhu Chen, Hanwen Zha, Xiyou Zhou, Yunkai Zhang, Sairam Sundaresan, William Yang Wang
2020 arXiv   pre-print
We experiment on (1) Fully-supervised training with the full datasets, and (2) Few-shot setting, provided with hundreds of paired examples; We compare several popular generation models and analyze their  ...  We hope our dataset can encourage research towards building an advanced NLG system capable of natural, faithful, and human-like generation.  ...  The authors are solely responsible for the contents of the paper and the opinions expressed in this publication do not reflect those of the funding agencies.  ... 
arXiv:2004.14579v2 fatcat:q7hv27p3pjfmxkvtwz7en74hpa

A Survey of Deep Active Learning [article]

Pengzhen Ren, Yun Xiao, Xiaojun Chang, Po-Yao Huang, Zhihui Li, Brij B. Gupta, Xiaojiang Chen, Xin Wang
2021 arXiv   pre-print
Although the related research has been quite abundant, it lacks a comprehensive survey of DAL.  ...  In this way, DL has aroused strong interest of researchers and has been rapidly developed. Compared with DL, researchers have relatively low interest in AL.  ...  In Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL 2019, Florence, Italy, July 28- August 2, 2019, Volume 1: Long Papers.  ... 
arXiv:2009.00236v2 fatcat:zuk2doushzhlfaufcyhoktxj7e

What Have We Achieved on Text Summarization? [article]

Dandan Huang, Leyang Cui, Sen Yang, Guangsheng Bao, Kun Wang, Jun Xie, Yue Zhang
2020 arXiv   pre-print
Aiming to gain more understanding of summarization systems with respect to their strengths and limits on a fine-grained syntactic and semantic level, we consult the Multidimensional Quality Metric(MQM)  ...  and quantify 8 major sources of errors on 10 representative summarization models manually.  ...  Acknowledge We thank all anonymous reviewers for their constructive comments. This work is supported by NSFC 61976180 and a research grant from Tencent Inc.  ... 
arXiv:2010.04529v1 fatcat:tsvkgiqi7vbxpivw2qgrta2y54

A Tutorial on Evaluation Metrics used in Natural Language Generation

Mitesh M. Khapra, Ananya B. Sai
2021 Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Tutorials   unpublished
(v) What are the possible future directions of research?  ...  Especially in the last few years, there has been an increasing focus on evaluation metrics, with several criticisms of existing metrics and proposals for several new metrics.  ...  In Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL 2019, Florence, Italy, July 28-August 2, 2019, Volume 1: Long Papers, pages 2799-2808.  ... 
doi:10.18653/v1/2021.naacl-tutorials.4 fatcat:nju2lewr35fyvlf72uwqqigpd4

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  ...  , ACL 2019, Florence, cal Lamblin, Utku Evci, Kelvin Xu, Ross Goroshin, Italy, July 28- August 2, 2019, Volume 1: Long Pa- Carles Gelada, Kevin Swersky, Pierre-Antoine Man- pers,  ... 
arXiv:2112.10668v1 fatcat:ehexgbyr5jfetimihdd66sxdtm

Algorithmic Fairness Datasets: the Story so Far [article]

Alessandro Fabris, Stefano Messina, Gianmaria Silvello, Gian Antonio Susto
2022 arXiv   pre-print
As a result, a growing community of researchers has been investigating the equity of existing algorithms and proposing novel ones, advancing the understanding of risks and opportunities of automated decision-making  ...  Secondly, we document and summarize hundreds of available alternatives, annotating their domain and supported fairness tasks, along with additional properties of interest for fairness researchers.  ...  Acknowledgements The authors would like to thank the following researchers and dataset creators for the useful feedback on the data briefs: Alain Barrat, Luc Behaghel, Asia Biega, Marko Bohanec, Chris  ... 
arXiv:2202.01711v2 fatcat:5hf4a42pubc5vnt7tw3al4m5bq

Towards Explainable Fact Checking [article]

Isabelle Augenstein
2021 arXiv   pre-print
This development has spurred research in the area of automatic fact checking, from approaches to detect check-worthy claims and determining the stance of tweets towards claims, to methods to determine  ...  Despite this, current solutions for explainability are still lacking in the area of fact checking.  ...  In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics.  ... 
arXiv:2108.10274v2 fatcat:5s4an6irezcjfmvvhmiaeqarh4

Bag of Tricks for Optimizing Transformer Efficiency

Ye Lin, Yanyang Li, Tong Xiao, Jingbo Zhu
2021 Findings of the Association for Computational Linguistics: EMNLP 2021   unpublished
In Proceedings of the 57th Confer- ence of the Association for Computational Linguis- tics, ACL 2019, Florence, Italy, July 28- August 2, 2019, Volume 1: Long Papers, pages 1810–1822.  ...  CoRR, abs/2006.10369. 57th Conference of the Association for Computa- tional Linguistics, ACL 2019, Florence, Italy, July Young  ... 
doi:10.18653/v1/2021.findings-emnlp.357 fatcat:abneqepygnbupondrn4wk3qaam

Transferrable Framework Based on Knowledge Graphs for Generating Explainable Results in Domain-Specific, Intelligent, Information Retrieval

Hasan Abu-Rasheed, Christian Weber, Johannes Zenkert, Mareike Dornhöfer, Madjid Fathi
2022 Informatics  
This is due to the high costs, which are associated with intensive customization and required knowledge modelling, when developing new explainable solutions for each industrial domain.  ...  The use of the KG resulted in minimum-to-zero adjustments when creating explanations for multiple intelligent IR algorithms in multiple domains.  ...  In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, Florence, Italy, 28 July2 August 2019; pp. 845–854. 12. Ribeiro, M.T.; Singh, S.; Guestrin, C.  ... 
doi:10.3390/informatics9010006 fatcat:kazl7m3egzbrpkx763wuqyxdei

Virtual Data Augmentation: A Robust and General Framework for Fine-tuning Pre-trained Models

Kun Zhou, Wayne Xin Zhao, Sirui Wang, Fuzheng Zhang, Wei Wu, Ji-Rong Wen
2021 Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing   unpublished
Florence, Italy, July 28- August 2, 2019, Volume 1: Long Papers, pages 1085–1097. Qizhe Xie, Zihang Dai, Eduard H.  ...  Bowman. 2019. guistics, ACL 2019, Florence, Italy, July 28- August GLUE: A multi-task benchmark and analysis plat- 2, 2019, Volume 1: Long Papers, pages 5564–5569.  ... 
doi:10.18653/v1/2021.emnlp-main.315 fatcat:hnbvwxrf5rbqdfp6aan5zjfi4q
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