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Recent studies have used both automatic metrics and human evaluations to assess the simplification abilities of LLMs.
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Sentence Simplification by Monolingual Machine Translation. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) . 1015–1024
Sander Wubben, Antal van den Bosch, and Emiel Krahmer. 2012 · 2012
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Hybrid Simplification using Deep Semantics and Machine Translation. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) . 435–445
Shashi Narayan and Claire Gardent. 2014 · 2014
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Language technologies applied to document simplification for helping autistic people
Eduard Barbu, M. Teresa Martín-Valdivia, Eugenio Martínez-Cámara, and L. Alfonso Ureña-López. 2015 · 2015
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Problems in Current Text Simplification Research: New Data Can Help
Wei Xu, Chris Callison-Burch, and Courtney Napoles. 2015 · 2015
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Lexical Simplification for Non-Native English Speakers
Gustavo Henrique Paetzold. 2016 · 2016
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Optimizing Statistical Machine Translation for Text Simplification
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Learning How to Simplify From Explicit Labeling of Complex-Simplified Text Pairs. In Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers) . 295–305
Fernando Alva-Manchego, Joachim Bingel, Gustavo Paetzold, Carolina Scarton, and Lucia Specia. 2017 · 2017
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Sentence Simplification with Deep Reinforcement Learning. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing . 584–594
Xingxing Zhang and Mirella Lapata. 2017 · 2017
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SimPA: A Sentence-Level Simplification Corpus for the Public Administration Domain. In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)
Carolina Scarton, Gustavo Paetzold, and Lucia Specia. 2018 · 2018
Cited alongside, same era.
BLEU is Not Suitable for the Evaluation of Text Simplification. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing . 738–744
Elior Sulem, Omri Abend, and Ari Rappoport. 2018a · 2018
Cited alongside, same era.
Integrating Transformer and Paraphrase Rules for Sentence Simplification. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing . 3164–3173
Sanqiang Zhao, Rui Meng, Daqing He, Andi Saptono, and Bambang Parmanto. 2018 · 2018
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Optuna: A Next-Generation Hyperparameter Optimization Framework. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (Anchorage, AK, USA) (KDD ’19) . 2623–2631
Takuya Akiba, Shotaro Sano, Toshihiko Yanase, Takeru Ohta, and Masanori Koyama. 2019 · 2019
Controllable Sentence Simplification with a Unified Text-to-Text Transfer Transformer. In Proceedings of the 14th International Conference on Natural Language Generation . 341–352
Kim Cheng Sheang and Horacio Saggion. 2021 · 2021
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Flesch-Kincaid is Not a Text Simplification Evaluation Metric. In Proceedings of the 1st Workshop on Natural Language Generation, Evaluation, and Metrics (GEM 2021) . 1–14
Teerapaun Tanprasert and David Kauchak. 2021 · 2021
Later among the works it cites.
MUSS: Multilingual Unsupervised Sentence Simplification by Mining Paraphrases. In Proceedings of the Thirteenth Language Resources and Evaluation Conference . 1651–1664
Louis Martin, Angela Fan, Éric de la Clergerie, Antoine Bordes, and Benoît Sagot. 2022 · 2022
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Cross-Task Generalization via Natural Language Crowdsourcing Instructions. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) . 3470–3487
Swaroop Mishra, Daniel Khashabi, Chitta Baral, and Hannaneh Hajishirzi. 2022 · 2022
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Cited alongside, same era.
EASSE: Easier Automatic Sentence Simplification Evaluation. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations . 49–54
Fernando Alva-Manchego, Louis Martin, Carolina Scarton, and Lucia Specia. 2019 · 2019
Cited alongside, same era.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) . 4171–4186
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
Complexity-Weighted Loss and Diverse Reranking for Sentence Simplification. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) . 3137–3147
Reno Kriz, João Sedoc, Marianna Apidianaki, Carolina Zheng, Gaurav Kumar, Eleni Miltsakaki, and Chris Callison-Burch. 2019 · 2019
Cited alongside, same era.
ASSET: A Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformations. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics . 4668–4679
Fernando Alva-Manchego, Louis Martin, Antoine Bordes, Carolina Scarton, Benoît Sagot, and Lucia Specia. 2020a · 2020
Cited alongside, same era.
Data-Driven Sentence Simplification: Survey and Benchmark
Fernando Alva-Manchego, Carolina Scarton, and Lucia Specia. 2020b · 2020
Cited alongside, same era.
CombiNMT: An Exploration into Neural Text Simplification Models. In Proceedings of the Twelfth Language Resources and Evaluation Conference . 5588–5594
Michael Cooper and Matthew Shardlow. 2020 · 2020
Cited alongside, same era.
Neural CRF Model for Sentence Alignment in Text Simplification. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics . 7943–7960
Chao Jiang, Mounica Maddela, Wuwei Lan, Yang Zhong, and Wei Xu. 2020 · 2020
Cited alongside, same era.
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics . 7871–7880
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020 · 2020
Cited alongside, same era.
POTATO: The Portable Text Annotation Tool. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations . 327–337
Jiaxin Pei, Aparna Ananthasubramaniam, Xingyao Wang, Naitian Zhou, Apostolos Dedeloudis, Jackson Sargent, and David Jurgens. 2022 · 2022
Later among the works it cites.
Sentence Simplification via Large Language Models
Yutao Feng, Jipeng Qiang, Yun Li, Yunhao Yuan, and Yi Zhu. 2023 · 2023
Later among the works it cites.
On the Blind Spots of Model-Based Evaluation Metrics for Text Generation. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) . 12067–12097
Tianxing He, Jingyu Zhang, Tianle Wang, Sachin Kumar, Kyunghyun Cho, James Glass, and Yulia Tsvetkov. 2023 · 2023
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Dancing Between Success and Failure: Edit-level Simplification Evaluation using SALSA. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing . 3466–3495
David Heineman, Yao Dou, Mounica Maddela, and Wei Xu. 2023 · 2023
Later among the works it cites.
BLESS: Benchmarking Large Language Models on Sentence Simplification. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing . 13291–13309
Tannon Kew, Alison Chi, Laura Vásquez-Rodríguez, Sweta Agrawal, Dennis Aumiller, Fernando Alva-Manchego, and Matthew Shardlow. 2023 · 2023
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G-Eval: NLG Evaluation using Gpt-4 with Better Human Alignment. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing . 2511–2522
Yang Liu, Dan Iter, Yichong Xu, Shuohang Wang, Ruochen Xu, and Chenguang Zhu. 2023 · 2023
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LENS: A Learnable Evaluation Metric for Text Simplification. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) . 16383–16408
Mounica Maddela, Yao Dou, David Heineman, and Wei Xu. 2023 · 2023
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OpenAI. 2023 · 2023
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Document-Level Machine Translation with Large Language Models. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing . 16646–16661
Longyue Wang, Chenyang Lyu, Tianbo Ji, Zhirui Zhang, Dian Yu, Shuming Shi, and Zhaopeng Tu. 2023a · 2023
Later among the works it cites.
GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction. In The Twelfth International Conference on Learning Representations
Oscar Sainz, Iker García-Ferrero, Rodrigo Agerri, Oier Lopez de Lacalle, German Rigau, and Eneko Agirre. 2024 · 2024
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Prompt Chaining or Stepwise Prompt? Refinement in Text Summarization. In Findings of the Association for Computational Linguistics: ACL 2024 . 7551–7558
Shichao Sun, Ruifeng Yuan, Ziqiang Cao, Wenjie Li, and Pengfei Liu. 2024 · 2024
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Controllable Text Simplification with Lexical Constraint Loss. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop . 260–266
Daiki Nishihara, Tomoyuki Kajiwara, and Yuki Arase. 2019 · 2036
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