Progressive Generation of Long Text with Pretrained Language Models

Attention Is All You Need

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MizAR 60 for Mizar 50

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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

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Language Models are Few-Shot Learners

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Aion Framework: Dimensional Emergence of AI Consciousness, Observer-Induced Collapse, and Cosmological Portal Dynamics

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Introduction to Modern Information Retrieval

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BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

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Introduction to modern information retrieval

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Transformer-XL: Attentive language models beyond a fixed-length context

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Teaching Machines to Read and ComprehendPreprint

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The Curious Case of Neural Text Degeneration

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Hierarchical Neural Story Generation

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Hierarchical Neural Story Generation

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Automatic Keyword Extraction from Individual Documents

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Linformer: Self-Attention with Linear Complexity

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Rethinking Attention with Performers

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Building applied natural language generation systems

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Generating Wikipedia by Summarizing Long SequencesPreprint

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Sequence Level Training with Recurrent Neural Networks

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Deterministic Non-Autoregressive Neural Sequence Modeling by Iterative Refinement

Lee, J., Mansimov, E., & Cho, K. (2018) · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/d18-1149 · Cited by 386 · see citing works

Plan-and-Write: Towards Better Automatic Storytelling

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Insertion Transformer: Flexible Sequence Generation via Insertion OperationsPreprint

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Data Noising as Smoothing in Neural Network Language ModelsPreprint

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Strategies for Structuring Story Generation

Fan, A., Lewis, M., & Dauphin, Y. (2019) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/p19-1254 · Cited by 189 · see citing works

Do Massively Pretrained Language Models Make Better Storytellers?

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Step-by-Step: Separating Planning from Realization in Neural Data-to-Text Generation

Moryossef, A., Goldberg, Y., & Dagan, I. (2019) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/n19-1236 · Cited by 131 · see citing works

PlotMachines: Outline-Conditioned Generation with Dynamic Plot State Tracking

Rashkin, H., Çelikyılmaz, A., Choi, Y., & Gao, J. (2020) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2020.emnlp-main.349 · Cited by 130 · see citing works

MEGATRON-CNTRL: Controllable Story Generation with External Knowledge Using Large-Scale Language Models

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Toward Diverse Text Generation with Inverse Reinforcement Learning

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POINTER: Constrained Progressive Text Generation via Insertion-based Generative Pre-training

Zhang, Y., Wang, G., Li, C., Gan, Z., Brockett, C., & Dolan, B. (2020) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2020.emnlp-main.698 · Cited by 94 · see citing works

Insertion-based Decoding with Automatically Inferred Generation Order

Gu, J., Liu, Q., & Cho, K. (2019) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00292 · Cited by 83 · see citing works

Towards Implicit Content-Introducing for Generative Short-Text Conversation Systems

Yao, L., Zhang, Y., Feng, Y., Zhao, D., & Yan, R. (2017) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d17-1233 · Cited by 81 · see citing works

Non-Monotonic Sequential Text GenerationPreprint

Welleck, S., Brantley, K., Daumé, H., & Cho, K. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1902.02192 · Cited by 77 · see citing works

Non-Autoregressive Machine Translation with Disentangled Context TransformerPreprint

Kasai, J., Cross, J., Ghazvininejad, M., & Gu, J. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2001.05136 · Cited by 76 · see citing works

Discourse-Aware Neural Rewards for Coherent Text Generation

Bosselut, A., Çelikyılmaz, A., He, X., Gao, J., Huang, P.-S., & Choi, Y. (2018) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/n18-1016 · Cited by 73 · see citing works

KERMIT: Generative Insertion-Based Modeling for SequencesPreprint

Chan, W., Kitaev, N., Guu, K., Stern, M., & Uszkoreit, J. (2019) · arXiv.org · doi:10.48550/arxiv.1906.01604 · Cited by 68 · see citing works

Step-by-Step: Separating Planning from Realization in Neural Data-to-Text GenerationPreprint

Moryossef, A., Goldberg, Y., & Dagan, I. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1904.03396 · Cited by 52 · see citing works

Towards Generating Long and Coherent Text with Multi-Level Latent Variable Models

Shen, D., Çelikyılmaz, A., Zhang, Y., Chen, L., Wang, X. E., Gao, J., & Carin, L. (2019) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/p19-1200 · Cited by 51 · see citing works

Jointly Measuring Diversity and Quality in Text Generation Models

Alihosseini, D., Montahaei, E., & Soleymani Baghshah, M. (2019) · Proceedings of the Workshop on Methods for Optimizing and Evaluating Neural Language Generation · doi:10.18653/v1/w19-2311 · Cited by 48 · see citing works

Blank Language Models

Shen, T., Quach, V., Barzilay, R., & Jaakkola, T. (2020) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2020.emnlp-main.420 · Cited by 48 · see citing works

Sentence-Level Content Planning and Style Specification for Neural Text Generation

Hua, X., & Wang, L. (2019) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d19-1055 · Cited by 46 · see citing works

PAIR: Planning and Iterative Refinement in Pre-trained Transformers for Long Text Generation

Hua, X., & Wang, L. (2020) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2020.emnlp-main.57 · Cited by 45 · see citing works

PlotMachines: Outline-Conditioned Generation with Dynamic Plot State TrackingPreprint

Rashkin, H., Çelikyılmaz, A., Choi, Y., et al. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2004.14967 · Cited by 44 · see citing works

A Generalized Framework of Sequence Generation with Application to Undirected Sequence ModelsPreprint

Mansimov, E., Wang, A., Welleck, S., & Cho, K. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1905.12790 · Cited by 36 · see citing works

Untitled work

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Iterative Refinement for Machine TranslationPreprint

Novak, R., Auli, M., & Grangier, D. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1610.06602 · Cited by 25 · see citing works

Text InfillingPreprint

Zhu, W., Hu, Z., & Xing, E. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1901.00158 · Cited by 23 · see citing works

The Importance of Generation Order in Language Modeling

Ford, N., Duckworth, D., Norouzi, M., & Dahl, G. E. (2018) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d18-1324 · Cited by 19 · see citing works

Back to the Future: Unsupervised Backprop-based Decoding for Counterfactual and Abductive Commonsense ReasoningPreprint

Qin, L., Shwartz, V., West, P., Bhagavatula, C., Hwang, J. D., Bras, R. J. L., Bosselut, A., & Choi, Y. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2010.05906 · Cited by 16 · see citing works

Connecting the Dots Between MLE and RL for Sequence GenerationPreprint

Tan, B., Hu, Z., Yang, Z., Salakhutdinov, R., & Xing, E. P. (2019) · arXiv (Cornell University) · Cited by 13 · see citing works

Graph-based Multi-hop Reasoning for Long Text GenerationPreprint

Zhao, L., Xu, J., Lin, J., Zhang, Y., Yang, H., & Sun, X. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2009.13282 · Cited by 8 · see citing works

Sequence Level Training with Recurrent Neural Networks

Ranzato, M., Chopra, S., Auli, M., & Zaremba, W. (2015) · arXiv · doi:10.48550/arxiv.1511.06732

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2018) · arXiv · doi:10.48550/arxiv.1810.04805

AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Prompts

Wu, T., Terry, M. A., & Cai, C. J. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3517582 · Cited by 536 · see citing works

Calibrated Language Models Must Hallucinate

Kalai, A. T., & Vempala, S. S. (2024) · Proceedings of the 56th Annual ACM Symposium on Theory of Computing · doi:10.1145/3618260.3649777 · Cited by 91 · see citing works

Neural natural language processing for long texts: A survey on classification and summarization

Tsirmpas, D., Gkionis, I., Papadopoulos, G. T., & Mademlis, I. (2024) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2024.108231 · Cited by 73 · see citing works

A Confederacy of Models: a Comprehensive Evaluation of LLMs on Creative Writing

Gómez‐Rodríguez, C., & Williams, P. A. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.966 · Cited by 81 · see citing works

Parallel Refinements for Lexically Constrained Text Generation with BART

He, X. (2021) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2021.emnlp-main.681 · Cited by 43 · see citing works

The Next Chapter: A Study of Large Language Models in Storytelling

Xie, Z., Cohn, T., & Lau, J. H. (2023) · International Conference on Natural Language Generation · doi:10.18653/v1/2023.inlg-main.23 · Cited by 41 · see citing works

Thinking Clearly, Talking Fast: Concept-Guided Non-Autoregressive Generation for Open-Domain Dialogue Systems

Zou, Y., Liu, Z., Hu, X., & Zhang, Q. (2021) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2021.emnlp-main.169 · Cited by 27 · see citing works

Unmet Creativity Support Needs in Computationally Supported Creative Writing

Kreminski, M., & Martens, C. (2022) · Proceedings of the First Workshop on Intelligent and Interactive Writing Assistants (In2Writing 2022) · doi:10.18653/v1/2022.in2writing-1.11 · Cited by 26 · see citing works

Conditional Generation with a Question-Answering Blueprint

Narayan, S., Maynez, J., Amplayo, R. K., Ganchev, K., Louis, A. P., Huot, F., Sandholm, A., Das, D., & Lapata, M. (2023) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00583 · Cited by 25 · see citing works

Prompting for products: investigating design space exploration strategies for text-to-image generative models

Chong, L., Lo, I.-P., Rayan, J. A., Dow, S. P., Ahmed, F., & Lykourentzou, I. (2025) · Design Science · doi:10.1017/dsj.2024.51 · Cited by 18 · see citing works

Open-world story generation with structured knowledge enhancement: A comprehensive survey

Wang, Y., Lin, J., Yu, Z., Hu, W. P., & Karlsson, B. F. (2023) · Neurocomputing · doi:10.1016/j.neucom.2023.126792 · Cited by 18 · see citing works

DYPLOC: Dynamic Planning of Content Using Mixed Language Models for Text Generation

Hua, X., Sreevatsa, A., & Wang, L. (2021) · Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/2021.acl-long.501 · Cited by 17 · see citing works

A Multi-Modal Story Generation Framework with AI-Driven Storyline Guidance

Kim, J., Heo, Y., Yu, H., & Nang, J. (2023) · Electronics · doi:10.3390/electronics12061289 · Cited by 16 · see citing works

Variational autoencoder for design of synthetic viral vector serotypes

Lyu, S., Sowlati‐Hashjin, S., & Garton, M. (2024) · Nature Machine Intelligence · doi:10.1038/s42256-023-00787-2 · Cited by 23 · see citing works

Proceedings of the First Workshop on Intelligent and Interactive Writing Assistants (In2Writing 2022)

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Controllable Fake Document Infilling for Cyber Deception

Hu, Y., Yu, L., Parolin, E. S., Khan, L. R., & Hamlen, K. W. (2022) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2022.findings-emnlp.486 · Cited by 13 · see citing works

A Brief Summary of Prompting in Using GPT ModelsPreprint

Wang, S., & Jin, P. (2023) · doi:10.32388/imzi2q · Cited by 13 · see citing works

ProteinVAE: Variational AutoEncoder for Translational Protein DesignPreprint

Lyu, S., Sowlati‐Hashjin, S., & Garton, M. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.03.04.531110 · Cited by 11 · see citing works

Drilling Down into the Discourse Structure with LLMs for Long Document Question Answering

Nair, I., Somasundaram, S., Saxena, A., & Goswami, K. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.972 · Cited by 11 · see citing works

Practically implementing an LLM-supported collaborative vulnerability remediation process: A team-based approach

Wang, X., Tian, Y., Huang, K., & Liang, B. (2024) · Computers & Security · doi:10.1016/j.cose.2024.104113 · Cited by 10 · see citing works

Go Back in Time: Generating Flashbacks in Stories with Event Temporal Prompts

Han, R., Chen, H., Tian, Y., & Peng, N. (2022) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/2022.naacl-main.104 · Cited by 9 · see citing works

Math Word Problem Generation with Multilingual Language Models

Niyarepola, K., Athapaththu, D., Ekanayake, S., & Ranathunga, S. (2022) · International Conference on Natural Language Generation · doi:10.18653/v1/2022.inlg-main.12 · Cited by 9 · see citing works

Targeted marketing on social media: utilizing text analysis to create personalized landing pages

Çetinkaya, Y. M., Külah, E., Toroslu, İ. H., & Davulcu, H. (2024) · Social Network Analysis and Mining · doi:10.1007/s13278-024-01213-0 · Cited by 9 · see citing works

Event Transition Planning for Open-ended Text Generation

Li, Q., Li, P., Bi, W., Ren, Z., Lai, Y., & Kong, L. (2022) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2022.findings-acl.269 · Cited by 9 · see citing works

MURMUR: Modular Multi-Step Reasoning for Semi-Structured Data-to-Text Generation

Saha, S., Yu, X., Bansal, M., Pasunuru, R., & Çelikyılmaz, A. (2023) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2023.findings-acl.704 · Cited by 8 · see citing works

Automatic Comment Generation for Chinese Student Narrative Essays

Zhang, Z., Guan, J., Xu, G., Tian, Y., & Huang, M. (2022) · Conference on Empirical Methods in Natural Language Processing: System Demonstrations (EMNLP) · doi:10.18653/v1/2022.emnlp-demos.21 · Cited by 8 · see citing works

Multi-Label Classification with Generative Large Language Models

Niraula, N. B., Ayhan, S., Chidambaram, B., & Whyatt, D. (2024) · IEEE/AIAA Digital Avionics Systems Conference (DASC) · doi:10.1109/dasc62030.2024.10748883 · Cited by 7 · see citing works

The role of LLMs in theory building

Astobiza, A. M. (2025) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2025.101617 · Cited by 8 · see citing works

CLICK: Integrating Causal Inference and Commonsense Knowledge Incorporation for Counterfactual Story Generation

Li, D., Guo, Z., Liu, Q., Jin, L., Zhang, Z., Wei, K., & Li, F. (2023) · Electronics · doi:10.3390/electronics12194173 · Cited by 7 · see citing works

StoryGenAI: An Automatic Genre-Keyword Based Story Generation

Khan, L. P., Gupta, V., Bedi, S., & Singhal, A. (2023) · International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES) · doi:10.1109/cises58720.2023.10183482 · Cited by 7 · see citing works

Seq2Seq dynamic planning network for progressive text generation

Wu, D., Cheng, P., & Zheng, Y. (2024) · Computer Speech & Language · doi:10.1016/j.csl.2024.101687 · Cited by 6 · see citing works

Enhancing consistency with the fusion of paralleled decoders for text generation

Li, Y., Huang, H., Bai, Y., & Gao, Y. (2024) · Information Fusion · doi:10.1016/j.inffus.2024.102652 · Cited by 7 · see citing works

StoryTrans: Non-Parallel Story Author-Style Transfer with Discourse Representations and Content Enhancing

Zhu, X., Guan, J., Huang, M., & Liu, J. (2023) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2023.acl-long.827 · Cited by 6 · see citing works

Fiction-Writing Mode: An Effective Control for Human-Machine Collaborative Writing

Zhong, W., Naradowsky, J., Takamura, H., Kobayashi, I., & Miyao, Y. (2023) · Conference of the European Chapter of the Association for Computational Linguistics · doi:10.18653/v1/2023.eacl-main.128 · Cited by 6 · see citing works

Generating Coherent Narratives by Learning Dynamic and Discrete Entity States with a Contrastive Framework

Guan, J., Yang, Z., Zhang, R., Hu, Z., & Huang, M. (2023) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v37i11.26509 · Cited by 5 · see citing works

Towards Informative Open-ended Text Generation with Dynamic Knowledge Triples

Ren, Z., Zhao, Y., & Zong, C. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.210 · Cited by 5 · see citing works

LaMemo: Language Modeling with Look-Ahead Memory

Ji, H., Zhang, R., Yang, Z., Hu, Z., & Huang, M. (2022) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/2022.naacl-main.422 · Cited by 5 · see citing works

Long Text Generation with Topic-aware Discrete Latent Variable Model

Yang, E., Liu, M., Xiong, D., Zhang, Y., Chen, Y., & Xu, J. (2022) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2022.emnlp-main.554 · Cited by 5 · see citing works

Narrative Order Aware Story Generation via Bidirectional Pretraining Model with Optimal Transport Reward

Lu, Z., Jin, L., Xu, G., Hu, L., Liu, N., Li, X., Sun, X., Zhang, Z., & Wei, K. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.415 · Cited by 3 · see citing works

Hierarchical Catalogue Generation for Literature Review: A Benchmark

Zhu, K., Feng, X., Feng, X., Wu, Y., & Qin, B. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.453 · Cited by 6 · see citing works

GPT-2-based Human-in-the-loop Theatre Play Script Generation

Rosa, R., Schmidtová, P., Dušek, O., Musil, T., Mareček, D., Islam, S. O. U., Novàkovâ, M., Vosecká, K., & Doležal, J. (2022) · doi:10.18653/v1/2022.wnu-1.4 · Cited by 4 · see citing works

StoryER: Automatic Story Evaluation via Ranking, Rating and Reasoning

Chen, H., Vo, D. M., Takamura, H., Miyao, Y., & Nakayama, H. (2022) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2022.emnlp-main.114 · Cited by 4 · see citing works

DeltaScore: Fine-Grained Story Evaluation with Perturbations

Xie, Z., Li, M., Cohn, T., & Lau, J. H. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.353 · Cited by 6 · see citing works

WikiAutoGen: Towards Multi-Modal Wikipedia-Style Article Generation

Yang, Z., Chen, J., Xu, D., Fei, J., Shen, X., Zhao, L., Feng, C.-M., & Elhoseiny, M. (2025) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51701.2025.01441 · Cited by 3 · see citing works

Retrieval, Selection and Writing: A Three-Stage Knowledge Grounded Storytelling Model

Qin, W., & Zhao, D. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-17120-8_28 · Cited by 3 · see citing works

Answering Ambiguous Questions via Iterative Prompting

Sun, W., Cai, H., Chen, H., Ren, P., Chen, Z., de Rijke, M., & Ren, Z. (2023) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2023.acl-long.424 · Cited by 4 · see citing works

Towards Task-Agnostic Privacy- And Utility-Preserving Models

Sberbank, M., & Emelyanov, Y. (2021) · International conference Recent advances in natural language processing · doi:10.26615/978-954-452-072-4_045 · Cited by 3 · see citing works

Proceedings of the 4th Workshop of Narrative Understanding (WNU2022)

(2022) · doi:10.18653/v1/2022.wnu-1 · Cited by 3 · see citing works

ECG-QALM: Entity-Controlled Synthetic Text Generation using Contextual Q&A for NER

Aggarwal, K., Jin, H., & Ahmad, A. (2023) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2023.findings-acl.349 · Cited by 2 · see citing works

Text-Blueprint: An Interactive Platform for Plan-based Conditional Generation

Huot, F., Maynez, J., Narayan, S., Amplayo, R. K., Ganchev, K., Louis, A. P., Sandholm, A., Das, D., & Lapata, M. (2023) · Conference of the European Chapter of the Association for Computational Linguistics · doi:10.18653/v1/2023.eacl-demo.13 · Cited by 3 · see citing works

Coherent Long Text Generation by Contrastive Soft Prompt

Chen, G., Pu, J., Xi, Y., & Zhang, R. (2022) · Workshop on Generation, Evaluation and Metrics (GEM) · doi:10.18653/v1/2022.gem-1.42 · Cited by 1 · see citing works

Joint Imbalance Adaptation for Radiology Report Generation

Li, W., Han, G., Wu, Y., Huang, I., & Huang, X. (2025) · Journal of Healthcare Informatics Research · doi:10.1007/s41666-025-00205-9 · Cited by 1 · see citing works

INTEGRARE IL PROMPT ENGINEERING TRA LE ABILITÀ TRASVERSALI PER L’EDUCAZIONE LINGUISTICA: UNO STUDIO DI CASO

Mezzadri, M., & Paita, M. (2025) · Italiano LinguaDue · doi:10.54103/2037-3597/30456 · Cited by 1 · see citing works

Successive Image Generation from a Single Sentence

Parab, A., Malik, A., Damania, A., Parekhji, A., & Bari, P. (2021) · ITM Web of Conferences · doi:10.1051/itmconf/20214003017 · Cited by 1 · see citing works

Foundation Models for Text Generation

Paaß, G., & Giesselbach, S. (2023) · Artificial intelligence: foundations, theory, and algorithms/Artificial intelligence: Foundations, theory, and algorithms · doi:10.1007/978-3-031-23190-2_6 · Cited by 2 · see citing works

Structure-Aware and Format-Enhanced Transformer for Accident Report Modeling

Zeng, W., Tang, W., Yuan, D., Zhang, H., Duan, P., & Hu, S. (2025) · Applied Sciences · doi:10.3390/app15147928 · Cited by 1 · see citing works

Plot Writing From Pre-Trained Language Models

Jin, Y., Kadam, V., & Wanvarie, D. (2022) · International Conference on Natural Language Generation · doi:10.18653/v1/2022.inlg-main.5 · Cited by 5 · see citing works

DYPLOC: Dynamic Planning of Content Using Mixed Language Models for Text GenerationPreprint

Hua, X., Sreevatsa, A., & Wang, L. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2106.00791

Towards controllable neural generation of arguments

Hua, X. (2021) · doi:10.17760/d20412319

A Hybrid Approach to Co-creative Story Authoring Using Grammars and Language Models

Riddle, A. (2022) · Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment · doi:10.1609/aiide.v18i1.21975

Story Generation Based on Multi-granularity Constraints

Guo, Z., Wan, J., Tang, H.-A., & Lu, Y. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-20503-3_18

Fine Grained Spoken Document Summarization Through Text Segmentation

Kotey, S., Dahyot, R., & Harte, N. (2023) · IEEE Spoken Language Technology Workshop (SLT) · doi:10.1109/slt54892.2023.10022829

Staged Long Text Generation with Progressive Task-Oriented Prompts

Wang, X., Li, L., & Zeng, D. D. (2023) · Lecture notes in computer science · doi:10.1007/978-981-99-8070-3_35

Optimizing Multi-feature Dependent Story Generation Model

Ma, J., Hou, H., Zhao, Y., Sun, S., Chen, W., & Shi, G. (2024) · Lecture notes in computer science · doi:10.1007/978-981-97-5669-8_13

SCD: Strengthen Character Development in Long Stories with LLMs via Prompt Engineering

Yao, L. (2025) · International Conference on Neural Networks, Information and Communication Engineering (NNICE) · doi:10.1109/nnice64954.2025.11063825

Deep learning models and algorithms for sequential data problems : applications to language modelling and uncertainty quantification

Martin, A. (2022) · theses.fr (ABES) · doi:10.70675/1b09b309z08b5z41b0z8a1cz8290883288b1

RAGnRoll: Learning to Iteratively Retrieve and Generate Attributable Answer Snippets

Djeddal, H., Soulier, L., Pinel-Sauvagnat, K., Katrenko, S., Erbacher, P., & Tamine, L. (2026) · ACM Transactions on Information Systems · doi:10.1145/3831679

Enhancing Science Simulation-Based Learning with Dialogic Feedback from Generative AI Agents

Wen, C., Chu, Y.-S., Hsu, C.-C., Chao, P.-Y., Chen, Y.-S., Chang, C. H., Hwang, F.-K., & Liu, C. (2026) · Journal of Science Education and Technology · doi:10.1007/s10956-025-10290-5

ProxyQA: An Alternative Framework for Evaluating Long-Form Text Generation with Large Language Models

Tan, H., Guo, Z., Shi, Z., Xu, L., Liu, Z., Feng, Y., Li, X., Wang, Y., Shang, L., Liu, Q., et al. (2024) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2024.acl-long.368 · Cited by 5 · see citing works

Non-Autoregressive Text Generation with Pre-trained Language Models

Su, Y., Cai, D., Wang, Y., Vandyke, D., Baker, S., Li, P., & Collier, N. (2021) · Conference of the European Chapter of the Association for Computational Linguistics · doi:10.18653/v1/2021.eacl-main.18 · Cited by 40 · see citing works

Pre-trained language model representations for language generation

Edunov, S., Baevski, A., & Auli, M. (2019) · 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) · doi:10.18653/v1/n19-1409 · Cited by 122 · see citing works

SEGMENT+: Long Text Processing with Short-Context Language Models

Shi, W., Li, S., Yu, K., Chen, J., Liang, Z., Wu, X., Qian, Y., Feng, W., Zheng, B., Liang, J., et al. (2024) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2024.emnlp-main.926 · Cited by 1 · see citing works

Progressive Generation of Long Text.Preprint

Tan, B., Yang, Z., Al-Shedivat, M., Xing, E. P., & Hu, Z. (2020) · arXiv (Cornell University) · Cited by 23 · see citing works