Who cites «Optimizing Statistical Machine Translation for Text Simplification» · page 3
431 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. ← the card
- Exploring Variation of Results from Different Experimental Conditions — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
- Flesch or Fumble? Evaluating Readability Standard Alignment of Instruction-Tuned Language Models — 2023 · Proceedings of the Third Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)
- G-SPEED: General SParse Efficient Editing MoDel — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
- Gauging the Gap Between Human and Machine Text Simplification Through Analytical Evaluation of Simplification Strategies and Errors — 2023 · Findings of the Association for Computational Linguistics: EACL 2023
- LENS: A Learnable Evaluation Metric for Text Simplification — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Learning to Paraphrase Sentences to Different Complexity Levels — 2023 · Transactions of the Association for Computational Linguistics
- Leveraging Prefix Transfer for Multi-Intent Text Revision — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
- MVP: Multi-task Supervised Pre-training for Natural Language Generation — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
- Med-EASi: Finely Annotated Dataset and Models for Controllable Simplification of Medical Texts — 2023 · arXiv:2302.09155
- Medical Text Simplification: Optimizing for Readability with Unlikelihood Training and Reranked Beam Search Decoding — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
- Metric-Based In-context Learning: A Case Study in Text Simplification — 2023 · Proceedings of the 16th International Natural Language Generation Conference
- MuLER: Detailed and Scalable Reference-based Evaluation — 2023 · Proceedings of the 27th Conference on Computational Natural Language Learning (CoNLL)
- Multilingual Simplification of Medical Texts — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
- NapSS: Paragraph-level Medical Text Simplification via Narrative Prompting and Sentence-matching Summarization — 2023 · Findings of the Association for Computational Linguistics: EACL 2023
- Non-autoregressive Text Editing with Copy-aware Latent Alignments — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
- On Operations in Automatic Text Simplification — 2023 · Proceedings of the Second Workshop on Text Simplification, Accessibility and Readability
- PivotFEC: Enhancing Few-shot Factual Error Correction with a Pivot Task Approach using Large Language Models — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
- Reducing Sequence Length by Predicting Edit Spans with Large Language Models — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
- Reference Matters: Benchmarking Factual Error Correction for Dialogue Summarization with Fine-grained Evaluation Framework — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Revisiting non-English Text Simplification: A Unified Multilingual Benchmark — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- RewriteLM: An Instruction-Tuned Large Language Model for Text Rewriting — 2023 · arXiv:2305.15685 · AAAI 2024
- SIMSUM: Document-level Text Simplification via Simultaneous Summarization — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- SWiPE: A Dataset for Document-Level Simplification of Wikipedia Pages — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Sentence Simplification Using Paraphrase Corpus for Initialization — 2023 · arXiv:2305.19754
- SimpLex: a lexical text simplification architecture — 2023 · arXiv:2304.07002 · Neural Computing and Applications, 35(8):6265-6280, 2023
- Simplification by Lexical Deletion — 2023 · Proceedings of the Second Workshop on Text Simplification, Accessibility and Readability
- Simplifying Administrative Texts for Italian L2 Readers with Controllable Transformers Models: A Data-driven Approach — 2023 · Proceedings of the Ninth Italian Conference on Computational Linguistics (CLiC-it 2023)
- The student becomes the master: Outperforming GPT3 on Scientific Factual Error Correction — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
- Thresh: A Unified, Customizable and Deployable Platform for Fine-Grained Text Evaluation — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
- Towards Reference-free Text Simplification Evaluation with a BERT Siamese Network Architecture — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
- Traditional Readability Formulas Compared for English — 2023 · arXiv:2301.02975
- Uniform Complexity for Text Generation — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
- Using ChatGPT as a CAT tool in Easy Language translation — 2023 · Proceedings of the Second Workshop on Text Simplification, Accessibility and Readability
- What Comes Next? Evaluating Uncertainty in Neural Text Generators Against Human Production Variability — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
- Zero-shot Faithful Factual Error Correction — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- huPWKP: A Hungarian Text Simplification Corpus — 2023 · Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing
- (Psycho-)Linguistic Features Meet Transformer Models for Improved Explainable and Controllable Text Simplification — 2022 · Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022)
- A Benchmark Dataset for Multi-Level Complexity-Controllable Machine Translation — 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference
- An Imitation Learning Curriculum for Text Editing with Non-Autoregressive Models — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- An Investigation into the Effect of Control Tokens on Text Simplification — 2022 · Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022)
- Automatic Text Simplification of News Articles in the Context of Public Broadcasting — 2022 · arXiv:2212.13317
- Benchmarking Automated Clinical Language Simplification: Dataset, Algorithm, and Evaluation — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
- CoditT5: Pretraining for Source Code and Natural Language Editing — 2022 · arXiv:2208.05446
- Cognitive Simplification Operations Improve Text Simplification — 2022 · Proceedings of the 26th Conference on Computational Natural Language Learning (CoNLL)
- Complex Word Identification in Vietnamese: Towards Vietnamese Text Simplification — 2022 · Proceedings of the Workshop on Multilingual Information Access (MIA)
- Control Prefixes for Parameter-Efficient Text Generation — 2022 · Proceedings of the Second Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)
- Controllable Text Simplification with Deep Reinforcement Learning — 2022 · Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)
- Divide-and-Conquer Text Simplification by Scalable Data Enhancement — 2022 · Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022)
- Explain to me like I am five -- Sentence Simplification Using Transformers — 2022 · arXiv:2212.04595
- Fine-tuned Language Models are Continual Learners — 2022 · arXiv:2205.12393
- GEMv2: Multilingual NLG Benchmarking in a Single Line of Code — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
- GRS: Combining Generation and Revision in Unsupervised Sentence Simplification — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
- Generation of Patient After-Visit Summaries to Support Physicians — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
- Improving Iterative Text Revision by Learning Where to Edit from Other Revision Tasks — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
- Improving Text Simplification with Factuality Error Detection — 2022 · Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022)
- Inducing Positive Perspectives with Text Reframing — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- IrekiaLFes: a New Open Benchmark and Baseline Systems for Spanish Automatic Text Simplification — 2022 · Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022)
- JADES: New Text Simplification Dataset in Japanese Targeted at Non-Native Speakers — 2022 · Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022)
- Klexikon: A German Dataset for Joint Summarization and Simplification — 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference
- Lexically Constrained Decoding with Edit Operation Prediction for Controllable Text Simplification — 2022 · Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022)
- Linguistic Corpus Annotation for Automatic Text Simplification Evaluation — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
- MUSS: Multilingual Unsupervised Sentence Simplification by Mining Paraphrases — 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference
- Multitasking Framework for Unsupervised Simple Definition Generation — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Noisy Channel for Automatic Text Simplification — 2022 · arXiv:2211.03152
- Novelty Controlled Paraphrase Generation with Retrieval Augmented Conditional Prompt Tuning — 2022 · arXiv:2202.00535
- PEER: A Collaborative Language Model — 2022 · arXiv:2208.11663
- Patient-friendly Clinical Notes: Towards a new Text Simplification Dataset — 2022 · Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022)
- Predicting Sentence Deletions for Text Simplification Using a Functional Discourse Structure — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
- Quantified Reproducibility Assessment of NLP Results — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- RCML at TSAR-2022 Shared Task: Lexical Simplification With Modular Substitution Candidate Ranking — 2022 · Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022)
- Reproducing a Manual Evaluation of the Simplicity of Text Simplification System Outputs — 2022 · Proceedings of the 15th International Conference on Natural Language Generation: Generation Challenges
- Revision for Concision: A Constrained Paraphrase Generation Task — 2022 · Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022)
- Same Author or Just Same Topic? Towards Content-Independent Style Representations — 2022 · Proceedings of the 7th Workshop on Representation Learning for NLP
- Simple TICO-19: A Dataset for Joint Translation and Simplification of COVID-19 Texts — 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference
- SimpleStyle: An Adaptable Style Transfer Approach — 2022 · arXiv:2212.10498
- Sous-titrage automatique : étude de stratégies d''adaptation aux genres télévisuels [Automatic closed captioning: a study of strategies for televisual genre adaptation] — 2022
- TS-ANNO: An Annotation Tool to Build, Annotate and Evaluate Text Simplification Corpora — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
- Text Revision by On-the-Fly Representation Optimization — 2022 · Proceedings of the First Workshop on Intelligent and Interactive Writing Assistants (In2Writing 2022)
- Text Simplification of College Admissions Instructions: A Professionally Simplified and Verified Corpus — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
- Towards Arabic Sentence Simplification via Classification and Generative Approaches — 2022 · Proceedings of the Seventh Arabic Natural Language Processing Workshop (WANLP)
- Understanding Iterative Revision from Human-Written Text — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Updated Headline Generation: Creating Updated Summaries for Evolving News Stories — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- A New Dataset and Efficient Baselines for Document-level Text Simplification in German — 2021 · Proceedings of the Third Workshop on New Frontiers in Summarization
- A Non-Autoregressive Edit-Based Approach to Controllable Text Simplification — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
- A Review of Text Style Transfer using Deep Learning — 2021 · arXiv:2109.15144 · IEEE Transactions on Artificial Intelligence (TAI), (2021)
- A Syntax-Aware Edit-based System for Text Simplification — 2021 · Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)
- An Unsupervised Method for Building Sentence Simplification Corpora in Multiple Languages — 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021
- Automatic Text Simplification for Social Good: Progress and Challenges — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
- BiSECT: Learning to Split and Rephrase Sentences with Bitexts — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
- Controllable Sentence Simplification with a Unified Text-to-Text Transfer Transformer — 2021 · Proceedings of the 14th International Conference on Natural Language Generation
- Controllable Text Simplification with Explicit Paraphrasing — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
- Decontextualization: Making Sentences Stand-Alone — 2021 · Transactions of the Association for Computational Linguistics
- Document-Level Text Simplification: Dataset, Criteria and Baseline — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
- Does It Capture STEL? A Modular, Similarity-based Linguistic Style Evaluation Framework — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
- Elaborative Simplification: Content Addition and Explanation Generation in Text Simplification — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
- Evaluating and Explaining Natural Language Generation with GenX — 2021 · Proceedings of the Second Workshop on Data Science with Human in the Loop: Language Advances
- Evidence-based Factual Error Correction — 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
- ExT5: Towards Extreme Multi-Task Scaling for Transfer Learning — 2021 · arXiv:2111.10952
- Explainable Prediction of Text Complexity: The Missing Preliminaries for Text Simplification — 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
- Exploring German Multi-Level Text Simplification — 2021 · Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)