---
title: "Text generation — papers, page 2"
description: "Text generation: 115 papers of the Elamur Research library · page 2 of 2 · 26–115, the most cited first."
canonical: "https://research.elamur.ai/free/en/topics/text-generation/page/2/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/topics/text-generation/page/2/)

[home](https://md.research.elamur.ai/free/en/) / [topics](https://md.research.elamur.ai/free/en/topics/) / [Text generation](https://md.research.elamur.ai/free/en/topics/text-generation/) / page 2

# ✍️ Text generation

115 papers · page 2 of 2 · 26–115 · the most cited first · [all topics](https://md.research.elamur.ai/free/en/topics/)

Programs that write: from data to text, stories, paraphrases and the choices of a generator.

[← prev](https://md.research.elamur.ai/free/en/topics/text-generation/) [1](https://md.research.elamur.ai/free/en/topics/text-generation/) **2**

26. [**Paraphrase Generation with Deep Reinforcement Learning**Zichao Li, Xin Jiang, Lifeng Shang, et al.*2018 · 298 citations*](https://md.research.elamur.ai/free/en/papers/li-2018-paraphrase-generation-deep-reinforcement-learning/)
27. [**Why We Need New Evaluation Metrics for NLG**Jekaterina Novikova, Ondřej Dušek, Amanda Cercas Curry, et al.*2017 · 287 citations*](https://md.research.elamur.ai/free/en/papers/novikova-2017-why-we-need-new-evaluation/)
28. [**Text Generation from Knowledge Graphs with Graph Transformers**Rik Koncel-Kedziorski, Dhanush Bekal, Yi Luan, et al.*2019 · 284 citations*](https://md.research.elamur.ai/free/en/papers/kedziorski-2019-text-generation-knowledge-graphs-graph/)
29. [**Is ChatGPT a Good NLG Evaluator? A Preliminary Study**Jiaan Wang, Yunlong Liang, Fandong Meng, et al.*2023 · 281 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-chatgpt-good-nlg-evaluator-preliminary/)
30. [**Learning Neural Templates for Text Generation**Sam Wiseman, Stuart Shieber, Alexander Rush*2018 · 279 citations*](https://md.research.elamur.ai/free/en/papers/wiseman-2018-learning-neural-templates-text-generation/)
31. [**Handling Divergent Reference Texts when Evaluating Table-to-Text Generation**Bhuwan Dhingra, Manaal Faruqui, Ankur Parikh, et al.*2019 · 266 citations*](https://md.research.elamur.ai/free/en/papers/dhingra-2019-handling-divergent-reference-texts-when/)
32. [**Few-shot Natural Language Generation for Task-Oriented Dialog**Baolin Peng, Chenguang Zhu, Chunyuan Li, et al.*2020 · 253 citations*](https://md.research.elamur.ai/free/en/papers/peng-2020-few-shot-natural-language-generation/)
33. [**Societal Biases in Language Generation: Progress and Challenges**Emily Sheng, Kai-Wei Chang, Prem Natarajan, et al.*2021 · 252 citations*](https://md.research.elamur.ai/free/en/papers/sheng-2021-societal-biases-language-generation-progress/)
34. [**A Fast and Portable Realizer for Text Generation Systems**Benoit Lavoie, Owen Rainbow*1997 · 247 citations*](https://md.research.elamur.ai/free/en/papers/lavoie-1997-fast-portable-realizer-text-generation/)
35. [**Contrastive Decoding: Open-ended Text Generation as Optimization**Xiang Lisa Li, Ari Holtzman, Daniel Fried, et al.*2022 · 246 citations*](https://md.research.elamur.ai/free/en/papers/li-2022-contrastive-decoding-open-ended-text/)
36. [**FUDGE: Controlled Text Generation With Future Discriminators**Kevin Yang, Dan Klein*2021 · 234 citations*](https://md.research.elamur.ai/free/en/papers/yang-2021-fudge-controlled-text-generation-future/)
37. [**A Deep Generative Framework for Paraphrase Generation**Ankush Gupta, Arvind Agarwal, Prawaan Singh, et al.*2017 · 231 citations*](https://md.research.elamur.ai/free/en/papers/gupta-2017-deep-generative-framework-paraphrase-generation/)
38. [**Step-by-Step: Separating Planning from Realization in Neural Data-to-Text Generation**Amit Moryossef, Yoav Goldberg, Ido Dagan*2019 · 230 citations*](https://md.research.elamur.ai/free/en/papers/moryossef-2019-step-step-separating-planning-realization/)
39. [**Computational Interpretations of the Gricean Maxims in the Generation of Referring Expressions**Robert Dale, Ehud Reiter*1995 · 225 citations*](https://md.research.elamur.ai/free/en/papers/dale-1995-computational-interpretations-gricean-maxims-generation/)
40. [**Stochastic Language Generation in Dialogue using Recurrent Neural Networks with Convolutional Sentence Reranking**Tsung-Hsien Wen, Milica Gašić, Dongho Kim, et al.*2015 · 212 citations*](https://md.research.elamur.ai/free/en/papers/wen-2015-stochastic-language-generation-dialogue-recurrent/)
41. [**Logical Natural Language Generation from Open-Domain Tables**Wenhu Chen, Jianshu Chen, Yu Su, et al.*2020 · 209 citations*](https://md.research.elamur.ai/free/en/papers/chen-2020-logical-natural-language-generation-open/)
42. [**Towards a Unified Multi-Dimensional Evaluator for Text Generation**Ming Zhong, Yang Liu, Da Yin, et al.*2022 · 204 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2022-unified-multi-dimensional-evaluator-text/)
43. [**AraT5: Text-to-Text Transformers for Arabic Language Generation**El Moatez Billah Nagoudi, AbdelRahim Elmadany, Muhammad Abdul-Mageed*2022 · 201 citations*](https://md.research.elamur.ai/free/en/papers/nagoudi-2022-arat5-text-text-transformers-arabic/)
44. [**Measuring Attribution in Natural Language Generation Models**Hannah Rashkin, Vitaly Nikolaev, Matthew Lamm, et al.*2023 · 198 citations*](https://md.research.elamur.ai/free/en/papers/rashkin-2023-measuring-attribution-natural-language-generation/)
45. [**Authorship Attribution for Neural Text Generation**Adaku Uchendu, Thai Le, Kai Shu, et al.*2020 · 195 citations*](https://md.research.elamur.ai/free/en/papers/uchendu-2020-authorship-attribution-neural-text-generation/)
46. [**Application-driven Statistical Paraphrase Generation**Shiqi Zhao, Xiang Lan, Ting Liu, et al.*2009 · 186 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2009-application-driven-statistical-paraphrase-generation/)
47. [**compare-mt: A Tool for Holistic Comparison of Language Generation Systems**Graham Neubig, Zi-Yi Dou, Junjie Hu, et al.*2019 · 185 citations*](https://md.research.elamur.ai/free/en/papers/neubig-2019-compare-mt-tool-holistic-comparison/)
48. [**Representation Degeneration Problem in Training Natural Language Generation Models**Jun Gao, Di He, Xu Tan, et al.*2019 · 179 citations*](https://md.research.elamur.ai/free/en/papers/gao-2019-representation-degeneration-problem-training-natural/)
49. [**Controllable Paraphrase Generation with a Syntactic Exemplar**Mingda Chen, Qingming Tang, Sam Wiseman, et al.*2019 · 173 citations*](https://md.research.elamur.ai/free/en/papers/chen-2019-controllable-paraphrase-generation-syntactic-exemplar/)
50. [**The First Surface Realisation Shared Task: Overview and Evaluation Results**Anja Belz, Michael White, Dominic Espinosa, et al.*2011 · 172 citations*](https://md.research.elamur.ai/free/en/papers/belz-2011-first-surface-realisation-shared-task/)
51. [**Neural Syntactic Preordering for Controlled Paraphrase Generation**Tanya Goyal, Greg Durrett*2020 · 167 citations*](https://md.research.elamur.ai/free/en/papers/goyal-2020-neural-syntactic-preordering-controlled-paraphrase/)
52. [**Towards Controllable Biases in Language Generation**Emily Sheng, Kai-Wei Chang, Prem Natarajan, et al.*2020 · 166 citations*](https://md.research.elamur.ai/free/en/papers/sheng-2020-controllable-biases-language-generation/)
53. [**Quark: Controllable Text Generation with Reinforced Unlearning**Ximing Lu, Sean Welleck, Jack Hessel, et al.*2022 · 164 citations*](https://md.research.elamur.ai/free/en/papers/lu-2022-quark-controllable-text-generation-reinforced/)
54. [**Semantic Noise Matters for Neural Natural Language Generation**Ondřej Dušek, David M. Howcroft, Verena Rieser*2019 · 164 citations*](https://md.research.elamur.ai/free/en/papers/dusek-2019-semantic-noise-matters-neural-natural/)
55. [**On Hallucination and Predictive Uncertainty in Conditional Language Generation**Yijun Xiao, William Yang Wang*2021 · 155 citations*](https://md.research.elamur.ai/free/en/papers/xiao-2021-hallucination-predictive-uncertainty-conditional-language/)
56. [**DART: Open-Domain Structured Data Record to Text Generation**Linyong Nan, Dragomir Radev, Rui Zhang, et al.*2020 · 154 citations*](https://md.research.elamur.ai/free/en/papers/nan-2020-dart-open-domain-structured-data/)
57. [**Investigating Pretrained Language Models for Graph-to-Text Generation**Leonardo F. R. Ribeiro, Martin Schmitt, Hinrich Schütze, et al.*2021 · 149 citations*](https://md.research.elamur.ai/free/en/papers/ribeiro-2021-investigating-pretrained-language-models-graph/)
58. [**A Token-level Reference-free Hallucination Detection Benchmark for Free-form Text Generation**Tianyu Liu, Yizhe Zhang, Chris Brockett, et al.*2022 · 140 citations*](https://md.research.elamur.ai/free/en/papers/liu-2022-token-level-reference-free-hallucination/)
59. [**NeuroLogic A*esque Decoding: Constrained Text Generation with Lookahead Heuristics**Ximing Lu, Sean Welleck, Peter West, et al.*2022 · 136 citations*](https://md.research.elamur.ai/free/en/papers/lu-2022-neurologic-esque-decoding-constrained-text/)
60. [**INSTRUCTSCORE: Towards Explainable Text Generation Evaluation with Automatic Feedback**Wenda Xu, Danqing Wang, Liangming Pan, et al.*2023 · 122 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-instructscore-explainable-text-generation-evaluation/)
61. [**AMR-To-Text Generation with Graph Transformer**Tianming Wang, Xiaojun Wan, Hanqi Jin*2020 · 108 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-amr-text-generation-graph-transformer/)
62. [**AMR-to-text Generation with Synchronous Node Replacement Grammar**Linfeng Song, Xiaochang Peng, Yue Zhang, et al.*2017 · 108 citations*](https://md.research.elamur.ai/free/en/papers/song-2017-amr-text-generation-synchronous-node/)
63. [**Broad Coverage Multilingual Deep Sentence Generation with a Stochastic Multi-Level Realizer**Bernd Bohnet, Leo Wanner, Simon Mille, et al.*2010 · 93 citations*](https://md.research.elamur.ai/free/en/papers/bohnet-2010-broad-coverage-multilingual-deep-sentence/)
64. [**The First Multilingual Surface Realisation Shared Task (SR'18): Overview and Evaluation Results**Simon Mille, Anja Belz, Bernd Bohnet, et al.*2018 · 86 citations*](https://md.research.elamur.ai/free/en/papers/mille-2018-first-multilingual-surface-realisation-shared/)
65. [**Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation**Patrick Fernandes, Aman Madaan, Emmy Liu, et al.*2023 · 84 citations*](https://md.research.elamur.ai/free/en/papers/fernandes-2023-bridging-gap-survey-integrating-human/)
66. [**DiMLex: A Lexicon of Discourse Markers for Text Generation and Understanding**Manfred Stede, Carla Umbach*1998 · 84 citations*](https://md.research.elamur.ai/free/en/papers/stede-1998-dimlex-lexicon-discourse-markers-text/)
67. [**Pragmatically Informative Text Generation**Sheng Shen, Daniel Fried, Jacob Andreas, et al.*2019 · 78 citations*](https://md.research.elamur.ai/free/en/papers/shen-2019-pragmatically-informative-text-generation/)
68. [**Towards broad coverage surface realization with CCG**Michael White, Rajakrishnan Rajkumar, Scott Martin*2007 · 73 citations*](https://md.research.elamur.ai/free/en/papers/white-2007-broad-coverage-surface-realization-ccg/)
69. [**Automatic Story Generation: Challenges and Attempts**Amal Alabdulkarim, Siyan Li, Xiangyu Peng*2021 · 61 citations*](https://md.research.elamur.ai/free/en/papers/alabdulkarim-2021-automatic-story-generation-challenges-attempts/)
70. [**Bidirectional Grammars and the Design of Natural Language Generation Systems**Douglas E. Appelt*1987 · 59 citations*](https://md.research.elamur.ai/free/en/papers/appelt-1987-bidirectional-grammars-design-natural-language/)
71. [**Paraphrase Generation as Zero-Shot Multilingual Translation: Disentangling Semantic Similarity from Lexical and Syntactic Diversity**Brian Thompson, Matt Post*2020 · 55 citations*](https://md.research.elamur.ai/free/en/papers/thompson-2020-paraphrase-generation-as-zero-shot/)
72. [**DiscoScore: Evaluating Text Generation with BERT and Discourse Coherence**Wei Zhao, Michael Strube, Steffen Eger*2023 · 53 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-discoscore-evaluating-text-generation-bert/)
73. [**Towards a Decomposable Metric for Explainable Evaluation of Text Generation from AMR**Juri Opitz, Anette Frank*2021 · 50 citations*](https://md.research.elamur.ai/free/en/papers/opitz-2021-decomposable-metric-explainable-evaluation-text/)
74. [**Linguistic realisation as machine translation: Comparing different MT models for AMR-to-text generation**Thiago Castro Ferreira, Iacer Calixto, Sander Wubben, et al.*2017 · 46 citations*](https://md.research.elamur.ai/free/en/papers/ferreira-2017-linguistic-realisation-as-machine-translation/)
75. [**Assessing Discourse Relations in Language Generation from GPT-2**Wei-Jen Ko, Junyi Jessy Li*2020 · 30 citations*](https://md.research.elamur.ai/free/en/papers/ko-2020-assessing-discourse-relations-language-generation/)
76. [**Underspecified Universal Dependency Structures as Inputs for Multilingual Surface Realisation**Simon Mille, Anja Belz, Bernd Bohnet, et al.*2018 · 26 citations*](https://md.research.elamur.ai/free/en/papers/mille-2018-underspecified-universal-dependency-structures-as/)
77. [**A More Precise Analysis of Punctuation for Broad-Coverage Surface Realization with CCG**Michael White, Rajakrishnan Rajkumar*2008 · 25 citations*](https://md.research.elamur.ai/free/en/papers/white-2008-more-precise-analysis-punctuation-broad/)
78. [**Designing a Symbolic Intermediate Representation for Neural Surface Realization**Henry Elder, Jennifer Foster, James Barry, et al.*2019 · 20 citations*](https://md.research.elamur.ai/free/en/papers/elder-2019-designing-symbolic-intermediate-representation-neural/)
79. [**Multi-lingual Sentence Generation from the PIVOT interlingua**Akitoshi Okumura, Kazunori Muraki, Susumu Akamine*1991 · 19 citations*](https://md.research.elamur.ai/free/en/papers/okumura-1991-multi-lingual-sentence-generation-pivot/)
80. [**Can Diffusion Model Achieve Better Performance in Text Generation ? Bridging the Gap between Training and Inference !**Zecheng Tang, Pinzheng Wang, Keyan Zhou, et al.*2023 · 18 citations*](https://md.research.elamur.ai/free/en/papers/tang-2023-can-diffusion-model-achieve-better/)
81. [**The Third Multilingual Surface Realisation Shared Task (SR'20): Overview and Evaluation Results**Simon Mille, Anya Belz, Bernd Bohnet, et al.*2020 · 18 citations*](https://md.research.elamur.ai/free/en/papers/mille-2020-third-multilingual-surface-realisation-shared/)
82. [**Unsupervised Syntactically Controlled Paraphrase Generation with Abstract Meaning Representations**Kuan-Hao Huang, Varun Iyer, Anoop Kumar, et al.*2022 · 15 citations*](https://md.research.elamur.ai/free/en/papers/huang-2022-unsupervised-syntactically-controlled-paraphrase-generation/)
83. [**Evaluating Text Generation from Discourse Representation Structures**Chunliu Wang, Rik van Noord, Arianna Bisazza, et al.*2021 · 14 citations*](https://md.research.elamur.ai/free/en/papers/wang-2021-evaluating-text-generation-discourse-representation/)
84. [**DiscoFlan: Instruction Fine-tuning and Refined Text Generation for Discourse Relation Label Classification**Kaveri Anuranjana*2023 · 13 citations*](https://md.research.elamur.ai/free/en/papers/anuranjana-2023-discoflan-instruction-fine-tuning-refined/)
85. [**Text Generation from Discourse Representation Structures**Jiangming Liu, Shay B. Cohen, Mirella Lapata*2021 · 13 citations*](https://md.research.elamur.ai/free/en/papers/liu-2021-text-generation-discourse-representation-structures/)
86. [**Linguistically Motivated Complementizer Choice in Surface Realization**Rajakrishnan Rajkumar, Michael White*2011 · 13 citations*](https://md.research.elamur.ai/free/en/papers/rajkumar-2011-linguistically-motivated-complementizer-choice-surface/)
87. [**The Role of the Gricean Maxims in the Generation of Referring Expressions**Robert Dale, Ehud Reiter*1996 · 13 citations*](https://md.research.elamur.ai/free/en/papers/dale-1996-role-gricean-maxims-generation-referring/)
88. [**Towards Pragmatic Production Strategies for Natural Language Generation Tasks**Mario Giulianelli*2022 · 12 citations*](https://md.research.elamur.ai/free/en/papers/giulianelli-2022-pragmatic-production-strategies-natural-language/)
89. [**Underspecifying and Predicting Voice for Surface Realisation Ranking**Sina Zarrieß, Aoife Cahill, Jonas Kuhn*2011 · 11 citations*](https://md.research.elamur.ai/free/en/papers/zarriess-2011-underspecifying-predicting-voice-surface-realisation/)
90. [**Preventing False Temporal Implicatures: Interactive Defaults for Text Generation**Jon Oberlander, Alex Lascarides*1992 · 11 citations*](https://md.research.elamur.ai/free/en/papers/oberlander-1992-preventing-false-temporal-implicatures-interactive/)
91. [**Arabic Large Language Models for Medical Text Generation**Abdulrahman Allam, Seif Ahmed, Ali Hamdi, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/allam-2025-arabic-large-language-models-medical/)
92. [**The Gricean Maxims in NLP — A Survey**Lea Krause, Piek T.J.M. Vossen*2024 · 10 citations*](https://md.research.elamur.ai/free/en/papers/krause-2024-gricean-maxims-nlp-survey/)
93. [**Deterministic natural language generation from meaning representations for machine translation**Alastair Butler*2016 · 9 citations*](https://md.research.elamur.ai/free/en/papers/butler-2016-deterministic-natural-language-generation-meaning/)
94. [**An Error Analysis Framework for Shallow Surface Realization**Anastasia Shimorina, Yannick Parmentier, Claire Gardent*2021 · 8 citations*](https://md.research.elamur.ai/free/en/papers/shimorina-2021-error-analysis-framework-shallow-surface/)
95. [**RSA-Control: A Pragmatics-Grounded Lightweight Controllable Text Generation Framework**Yifan Wang, Vera Demberg*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-rsa-control-pragmatics-grounded-lightweight/)
96. [**Towards Fine-Grained Pedagogical Control over English Grammar Complexity in Educational Text Generation**Dominik Glandorf, Detmar Meurers*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/glandorf-2024-fine-grained-pedagogical-control-over/)
97. [**Annotating FrameNet via Structure-Conditioned Language Generation**Xinyue Cui, Swabha Swayamdipta*2024 · 6 citations*](https://md.research.elamur.ai/free/en/papers/cui-2024-annotating-framenet-structure-conditioned-language/)
98. [**Multilingual coreference resolution as text generation**Natalia Skachkova*2024 · 6 citations*](https://md.research.elamur.ai/free/en/papers/skachkova-2024-multilingual-coreference-resolution-as-text/)
99. [**Using Speech Acts in Logic-Based Rhetorical Structuring for Natural Language Generation in Human-Computer Dialogue**Vladimir Popescu, Jean Caelen, Corneliu Burileanu*2007 · 6 citations*](https://md.research.elamur.ai/free/en/papers/popescu-2007-speech-acts-logic-based-rhetorical/)
100. [**Neural Surface Realization for Italian**Valerio Basile, Alessandro Mazzei*2018 · 4 citations*](https://md.research.elamur.ai/free/en/papers/basile-2018-neural-surface-realization-italian/)
101. [**A Human-in/on-the-Loop Framework for Accessible Text Generation**Lourdes Moreno, Paloma Martínez*2026 · 3 citations*](https://md.research.elamur.ai/free/en/papers/moreno-2026-human-loop-framework-accessible-text/)
102. [**Shape of Synth to Come: Why We Should Use Synthetic Data for English Surface Realization**Henry Elder, Robert Burke, Alexander O'Connor, et al.*2020 · 3 citations*](https://md.research.elamur.ai/free/en/papers/elder-2020-shape-synth-come-why-we/)
103. [**Children's English Reading Story Generation via Supervised Fine-Tuning of Compact LLMs with Controllable Difficulty and Safety**Qian Shen, Fanghua Cao, Min Yao, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/shen-2026-children-s-english-reading-story/)
104. [**pyrealb at the GEM'24 Data-to-text Task: Symbolic English Text Generation from RDF Triples**Guy Lapalme*2024 · 1 citation*](https://md.research.elamur.ai/free/en/papers/lapalme-2024-pyrealb-gem-24-data-text/)
105. [**Enhancing PTB Universal Dependencies for Grammar-Based Surface Realization**David L. King, Michael White*2016 · 1 citation*](https://md.research.elamur.ai/free/en/papers/king-2016-enhancing-ptb-universal-dependencies-grammar/)
106. [**Some apparently disjoint aims and requirements for grammar development environments” the case of natural language generation**John Bateman*1997 · 1 citation*](https://md.research.elamur.ai/free/en/papers/bateman-1997-some-apparently-disjoint-aims-requirements/)
107. [**A Severity-Based Curriculum Learning Strategy for Arabic Medical Text Generation**Ahmed Alansary, Molham Mohamed, Ali Hamdi*2026*](https://md.research.elamur.ai/free/en/papers/alansary-2026-severity-based-curriculum-learning-strategy/)
108. [**Bangla Key2Text: Text Generation from Keywords for a Low Resource Language**Tonmoy Talukder, G M Shahariar*2026*](https://md.research.elamur.ai/free/en/papers/talukder-2026-bangla-key2text-text-generation-keywords/)
109. [**Exploring Cognitively Informed Sentence Simplification with Gaze-Guided Text Generation**Andreas Säuberli, Diego Frassinelli, Barbara Plank*2026*](https://md.research.elamur.ai/free/en/papers/sauberli-2026-exploring-cognitively-informed-sentence-simplification/)
110. [**Logic-Level Evaluation of Logical Table-to-Text Generation**Lena Trigg, Dean F. Hougen, Ahsan Bilal*2026*](https://md.research.elamur.ai/free/en/papers/trigg-2026-logic-level-evaluation-logical-table/)
111. [**Severity-Aware Weighted Loss for Arabic Medical Text Generation**Ahmed Alansary, Molham Mohamed, Ali Hamdi*2026*](https://md.research.elamur.ai/free/en/papers/alansary-2026-severity-aware-weighted-loss-arabic/)
112. [**Rule-based Surface Realization of Romanian Weak Pronouns**Ciprian Gerstenberger*2025*](https://md.research.elamur.ai/free/en/papers/gerstenberger-2025-rule-based-surface-realization-romanian/)
113. [**The Role of PropBank Sense IDs in AMR-to-text Generation and Text-to-AMR Parsing**Thu Hoang, Mina Yang, Shira Wein*2025*](https://md.research.elamur.ai/free/en/papers/hoang-2025-role-propbank-sense-ids-amr/)
114. [**Survey on Controllable Text Generation (可控文本生成技术研究综述)**Jian Wang (王舰), Yuqing Sun (孙宇清)*2024*](https://md.research.elamur.ai/free/en/papers/wang-2024-controllable-text-generation/)
115. [**Toward Givenness Hierarchy Theoretic Natural Language Generation**Poulomi Pal, Tom Williams*2020*](https://md.research.elamur.ai/free/en/papers/pal-2020-toward-givenness-hierarchy-theoretic-natural/)

[← prev](https://md.research.elamur.ai/free/en/topics/text-generation/) [1](https://md.research.elamur.ai/free/en/topics/text-generation/) **2**