SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization

Attention Is All You Need

Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., & Polosukhin, I. (2017) · arXiv · doi:10.48550/arxiv.1706.03762 · Cited by 120,404

MizAR 60 for Mizar 50

Jakubův, J., Chvalovský, K., Goertzel, Z., et al. (2023) · DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) · doi:10.4230/lipics.itp.2023.19 · Cited by 76,648

Interrater reliability: The kappa statistic

McHugh, M. L. (2012) · Biochemia Medica · doi:10.11613/bm.2012.031 · Cited by 19,877

Untitled work

(2004) · Cited by 9,718

Get To The Point: Summarization with Pointer-Generator Networks

See, A., Liu, P. J., & Manning, C. D. (2017) · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · doi:10.18653/v1/p17-1099 · Cited by 3,775

A Neural Attention Model for Abstractive Sentence Summarization

Rush, A. M., Chopra, S., & Weston, J. (2015) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d15-1044 · Cited by 2,932

Teaching Machines to Read and ComprehendPreprint

Hermann, K. M., Kočiský, T., Grefenstette, E., Espeholt, L., Kay, W., Suleyman, M., & Blunsom, P. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1506.03340 · Cited by 2,855

fairseq: A Fast, Extensible Toolkit for Sequence Modeling

Ott, M., Edunov, S., Baevski, A., Fan, A., Gross, S., Ng, N., Grangier, D., & Auli, M. (2019) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/n19-4009 · Cited by 2,475

Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond

Nallapati, R., Zhou, B., dos Santos, C., Gulcehre, C., & Xiang, B. (2016) · Proceedings of The 20th SIGNLL Conference on Computational Natural Language Learning · doi:10.18653/v1/k16-1028 · Cited by 2,361

Abstractive Sentence Summarization with Attentive Recurrent Neural Networks

Chopra, S., Auli, M., & Rush, A. M. (2016) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/n16-1012 · Cited by 896

Assessing Inter-metric Correlation for Multi-document Summarization Evaluation

Ridenour, M., Agrawal, A., & Olabisi, O. (2022) · Workshop on Generation, Evaluation and Metrics (GEM) · doi:10.18653/v1/2022.gem-1.40 · Cited by 1

Hiding in Plain Sight: Insights into Abstractive Text Summarization

Srivastava, V. P., Bhat, S., & Pedanekar, N. (2023) · Workshop on Insights from Negative Results in NLP (Insights) · doi:10.18653/v1/2023.insights-1.8 · Cited by 1

Summarization of Dialogues and Conversations At Scale

Yang, D., & Zhu, C. (2023) · doi:10.18653/v1/2023.eacl-tutorials.3 · Cited by 2

Beyond Quantity

Sudmann, A., Echterhölter, A., Ramsauer, M., Retkowski, F., Schröter, J., & Waibel, A. (2023) · AI critique · doi:10.1515/9783839467664 · Cited by 5

Multi-User MultiWOZ: Task-Oriented Dialogues among Multiple Users

Jo, Y., Zhao, X., Biswas, A., Bassiou, N., Auvray, V., Malandrakis, N., Metallinou, A., & Potamianos, A. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.213 · Cited by 1

Lexical Repetitions Lead to Rote Learning: Unveiling the Impact of Lexical Overlap in Train and Test Reference Summaries

Choubey, P. K., Fabbri, A. R., Xiong, C., & Wu, C.-S. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.484 · Cited by 1

Multi-Stage Pre-training Enhanced by ChatGPT for Multi-Scenario Multi-Domain Dialogue Summarization

Zhou, W., Li, G., Cheng, X., Liang, X., Zhu, J., Zhai, F., & Li, Z. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.460 · Cited by 6

Meeting Summarization: A Survey

Bidkar, M. (2024) · International Journal for Research in Applied Science and Engineering Technology · doi:10.22214/ijraset.2024.58145 · Cited by 1

Mitigating Knowledge Conflicts in Data-to-Text Generation via the Internalization of Fact Extraction

Mo, X., Xiang, Y., Pan, Y., Hou, Y., & Luo, P. (2024) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn60899.2024.10651167 · Cited by 2

Improving Abstractive Summarization with Unsupervised Dynamic LoRA Mixtures

Chernyshev, D. (2024) · Lobachevskii Journal of Mathematics · doi:10.1134/s1995080224603710 · Cited by 1

UniMPC: Towards a Unified Framework for Multi-Party Conversations

Xie, Y., Sun, C., Liu, Y., Ji, Z., & Liu, B. (2024) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3627673.3679864 · Cited by 1

Beyond Words: Multi-modal Chat Summarization using Text with Emoji and GIF Emotion Analysis

Herur, S. V., Shalini, M., Bhuvan, A. J., Jain, V., & Preethi, P. (2024) · International Conference on Intelligent Systems and Advanced Applications (ICISAA) · doi:10.1109/icisaa62385.2024.10829282 · Cited by 1

Analysis of Multidomain Abstractive Summarization Using Salience Allocation

Rehman, T., Bose, R., Dey, S., & Chattopadhyay, S. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-81339-9_16 · Cited by 2

Improving the Summarization Effectiveness of Abstractive Datasets through Contrastive Learning

Shin, J., & Lee, Y. (2025) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3716851 · Cited by 1

Sentop: sentence-level prefix prompt for controllable abstractive summarization

Zhao, S. G., Sun, Y., Chen, J., Duan, Z. Y., Zou, C., Cheng, Y., & He, F. (2025) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-025-02669-y · Cited by 1

Identifying Synchronous and Asynchronous Communications in IMA Traffic

Thirumurugan, S., Weber, J., Alshammari, R., Zincir-Heywood, N., Nandy, B., & Seddigh, N. (2025) · IEEE/IFIP Network Operations and Management Symposium · doi:10.1109/noms57970.2025.11073614 · Cited by 1

ALSA: Context-Sensitive Prompt Privacy Preservation in Large Language Models

Ma, H., Lü, W., Liang, Y., Wang, T., Zhang, Q., Zhu, Y., & Si, J. (2025) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3711896.3736840 · Cited by 3

Context or No Context? A preliminary exploration of human-in-the-loop approach for Incremental Temporal Summarization in meetings

Beckage, N., Kumar, S. H., Sahay, S., & Manuvinakurike, R. (2021) · Workshop on New Frontiers in Summarization (NewSum) · doi:10.18653/v1/2021.newsum-1.11 · Cited by 1

Seri: Sketching-Reasoning-Integrating Progressive Workflow for Empathetic Response Generation

Bi, G., Cao, Y., Li, P., Xie, Y., Fang, F., & Lin, Z. (2023) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49357.2023.10094672 · Cited by 1

Picking the Underused Heads: A Network Pruning Perspective of Attention Head Selection for Fusing Dialogue Coreference Information

Liu, Z., & Chen, N. F. (2023) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49357.2023.10096717 · Cited by 1

Guiding Abstractive Dialogue Summarization with Content Planning

Wang, Y., Wan, X., & Cai, Z. (2022) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2022.findings-emnlp.248 · Cited by 1

A Lite Hierarchical Model for Dialogue Summarization with Multi-Granularity Decoder

Zheng, T., & Saga, R. (2023) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2023.270 · Cited by 1

EmailSum: Abstractive Email Thread SummarizationPreprint

Zhang, S., Çelikyılmaz, A., Gao, J., & Bansal, M. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2107.14691 · Cited by 8

Prompt scoring system for dialogue summarization using GPT-3Preprint

Prodan, G., & Pelican, E. (2021) · doi:10.36227/techrxiv.16652392.v1 · Cited by 1

Who says like a style of Vitamin: Towards Syntax-Aware DialogueSummarization using Multi-task LearningPreprint

Lee, S., Yang, K., Park, C., Sedoc, J., & Lim, H. (2021) · arXiv (Cornell University) · Cited by 1

Prompt scoring system for dialogue summarization using GPT-3Preprint

Prodan, G., & Pelican, E. (2021) · doi:10.36227/techrxiv.16652392 · Cited by 1

Abstractive Dialogue Summarization Based on Dynamic Pattern Exploiting Training

Chen, Z., Li, C., Wang, L., & He, L. (2022) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn55064.2022.9892323 · Cited by 1

Abstractive Text Summary with Transformer on Youtube Video Subtitle

Atipa, J. L., Javin, J., Bryan, F., Yesmaya, V., & Wongso, R. (2023) · International Journal of Emerging Technology and Advanced Engineering · doi:10.46338/ijetae0223_01 · Cited by 1

Abstractive Dialog Summarization using Two Stage Framework with Contrastive Learning

Halder, S. D., Paul, M. K., & Islam, B. (2022) · International Conference on Computer and Information Technology (ICCIT) · doi:10.1109/iccit57492.2022.10055286 · Cited by 1

Gated Delta Networks: Improving Mamba2 with Delta Rule

Yang, S., Kautz, J., & Hatamizadeh, A. (2024) · arXiv · doi:10.48550/arxiv.2412.06464 · Cited by 1

Hierarchical Summarization for Longform Spoken DialogPreprint

Li, D., Chen, T., Tung, A., & Chilton, L. B. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2108.09597

SummerTime: Text Summarization Toolkit for Non-expertsPreprint

Ni, A., Azerbayev, Z., Mutuma, M., Feng, T., Zhang, Y., Yu, T., Awadallah, A. H., & Radev, D. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2108.12738

An Exploratory Study on Long Dialogue Summarization: What Works and What's NextPreprint

Zhang, Y., Ni, A., Yu, T., Zhang, R., Zhu, C., Deb, B., Çelikyılmaz, A., Awadallah, A. H., & Radev, D. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2109.04609 · Cited by 10

Are we summarizing the right way? : a survey of dialogue summarization data sets

Tuggener, D., Mieskes, M., Deriu, J., & Cieliebak, M. (2021) · Zürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences) · doi:10.21256/zhaw-23506

Low-Resource Dialogue Summarization with Domain-Agnostic Multi-Source PretrainingPreprint

Zou, Y., Zhu, B., Hu, X., Gui, T., & Zhang, Q. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2109.04080

Does Pretraining for Summarization Require Knowledge Transfer?Preprint

Krishna, K., Bigham, J. P., & Lipton, Z. C. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2109.04953 · Cited by 12

TWEETSUMM -- A Dialog Summarization Dataset for Customer ServicePreprint

Feigenblat, G., Gunasekara, C., Sznajder, B., Joshi, S., Konopnicki, D., & Aharonov, R. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2111.11894 · Cited by 8

Report on the SIGDial 2021 special session on summarization of dialogues and multi-party meetings (SummDial)

Ghosal, T., Singh, M., Nedoluzhko, A., & Bojar, O. (2021) · ACM SIGIR Forum · doi:10.1145/3527546.3527561

A Coarse-to-Fine Training Paradigm for Dialogue Summarization

Liu, Z., Wang, Z., & Wang, J. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-15919-0_35

Topic-Features for Dialogue Summarization

Zhang, Z., & Li, J. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-17120-8_26

NEWSFARM: A Large-Scale Chinese Corpus of Long News Summarization

Zang, S., Zhang, C., Liu, X., Chen, X., Zhang, P., & Liu, J. (2022) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr56361.2022.9956691

A Relation Enhanced Model For Abstractive Dialogue Summarization

Yi, P., & Liu, R. (2022) · International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC) · doi:10.1109/cyberc55534.2022.00047

Sparse Dropout: a dropout layer specialized for attention mechanismPreprint

Liu, P., Deng, G., Zhao, S., Shi, Y., & Liu, X. (2023) · Research Square · doi:10.21203/rs.3.rs-2840311/v1

PSentScore: Evaluating Sentiment Polarity in Dialogue SummarizationPreprint

Zhou, Y., Ringeval, F., & Portet, F. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2307.12371

CoMix: Guide Transformers to Code-Mix using POS structure and Phonetics

Arora, G. S., Merugu, S., & Sembium, V. (2023) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2023.findings-acl.506

AdapterShare: Task Correlation Modeling with Adapter Differentiation

Chen, Z., Chen, B., Lü, C., Yu, K., & Lou, J. (2022) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2022.emnlp-main.728

The Fourth Workshop on Insights from Negative Results in NLP

Tafreshi, S., Akula, A., Sedoc, J., Валентинович, Д. А., Rogers, A., & Rumshisky, A. (2023) · doi:10.18653/v1/2023.insights-1

Improving Dialogue Summarization with Mixup Label Smoothing

Cheng, S., & Song, D. (2023) · Lecture notes in electrical engineering · doi:10.1007/978-981-99-6187-0_46

SAMDIT: Systematic Study of Adding Memory to Divided Input in the Transformer to Process Long Documents

Adel, A. A. (2023) · Studies in computational intelligence · doi:10.1007/978-3-031-44865-2_10

Unsupervised Domain Adaptation on Question-Answering System with Conversation Data

Adiba, A. I., Homma, T., & Sogawa, Y. (2022) · Annual Meeting of the Special Interest Group on Discourse and Dialogue · doi:10.18653/v1/2022.sigdial-1.42

ICM : Intent and Conversational Mining from Conversation Logs

Mitra, S., Ramnani, R., Ranjan, S., & Sengupta, S. (2022) · Annual Meeting of the Special Interest Group on Discourse and Dialogue · doi:10.18653/v1/2022.sigdial-1.39

Investigating the Representation of Open Domain Dialogue Context for Transformer Models

Padmakumar, V., Hedayatnia, B., Jin, D., Lange, P. L., Kim, S., Peng, N., Liu, Y., & Hakkani-Tur, D. Z. (2023) · Annual Meeting of the Special Interest Group on Discourse and Dialogue · doi:10.18653/v1/2023.sigdial-1.50

LMGQS: A Large-scale Dataset for Query-focused Summarization

Xu, R., Wang, S., Liu, Y., Wang, S., Yi‐chong, X., Iter, D., He, P., Zhu, C., & Zeng, M. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.984 · Cited by 2

Dynamic Low-rank Estimation for Transformer-based Language Models

Hua, T., Li, X., Gao, S., Hsu, Y.-C., Shen, Y., & Jin, H. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.621 · Cited by 1

Boosting Summarization with Normalizing Flows and Aggressive Training

Yu, Y. F., & Shen, X. (2023) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2023.emnlp-main.165 · Cited by 1

Beyond Detection: A Defend-and-Summarize Strategy for Robust and Interpretable Rumor Analysis on Social Media

Chang, Y.-T., Song, Y.-Z., Chen, Y.-S., & Shuai, H.-H. (2023) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2023.emnlp-main.707 · Cited by 1

EntSUMv2: Dataset, Models and Evaluation for More Abstractive Entity-Centric Summarization

Mehra, D., Xie, L., Hofmann-Coyle, E., Kulkarni, M., & Preoțiuc-Pietro, D. (2023) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2023.emnlp-main.337

Query-Based Dialogue Summarization Using BART

Du, L. (2024) · Applied and Computational Engineering · doi:10.54254/2755-2721/29/20231149 · Cited by 1

DiscSumm: A Discourse Based Saliency Model to Generate Abstract Summaries for Conversation

Srivastava, S., & Tripathi, A. (2023) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc53992.2023.10394053

Content Selection in Abstractive Summarization with Biased Encoder Mixtures

Chernyshev, D., & Dobrov, B. V. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-54534-4_5

SCAINs Presenter: Preventing Miscommunication by Detecting Context-Dependent Utterances in Spoken Dialogue

Tsuchiya, A., Maekawa, T., & Imai, M. (2024) · ACM International Conference on Intelligent User Interfaces (IUI) · doi:10.1145/3640543.3645147

Tasks for LLMs and Their Evaluation

Ostapuk, N., & Audiffren, J. (2024) · Springer eBooks · doi:10.1007/978-3-031-54827-7_6 · Cited by 2

Guiding ChatGPT to Generate Salient Domain Summaries

Gao, J. H., Cao, Z., Huang, S., Qin, L., & Ai, C. (2024) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn60899.2024.10650616 · Cited by 2

Utterance-Aware Adaptive Data Labeling and Summarization: Exploiting Large Language Models for Unbiased Dialog Annotation

Glazkov, N., & Makarov, I. (2024) · IEEE Access · doi:10.1109/access.2024.3476981 · Cited by 1

Sparse Mixture of Experts Language Models Excel in Knowledge Distillation

Xu, H., Liu, H., Gong, W., Deng, X., & Wang, H. (2024) · Lecture notes in computer science · doi:10.1007/978-981-97-9437-9_7

SimLayerKV: A Simple Framework for Layer-Level KV Cache ReductionPreprint

Zhang, X., Du, C., Du, C., Pang, T., Gao, W., & Lin, M. C. (2024) · Qeios · doi:10.32388/epai4t · Cited by 2

BRAIN: Blockchain-Based Inference and Training Platform for Large-Scale Models

Park, S.-H., Lee, J.-M., & Moon, S. (2024) · IEEE Access · doi:10.1109/access.2024.3503573 · Cited by 1

ConMix: Contrastive Learning with Mixup Augmentation for Dialogue Summarization

Chen, Z., & Xiao, J. (2024) · Lecture notes in computer science · doi:10.1007/978-981-96-0847-8_18

Dynamic Layer-Wise Token Pruning for Sequence-to-Sequence Transformer Inference

Keom, J. H., Kim, Y., Lee, S. J., & Lee, S. K. (2025) · Lecture notes in computer science · doi:10.1007/978-981-97-8705-0_23

An adaptive fusion-based data augmentation method for abstract dialogue summarization

Li, W., Jiang, D., Zhang, H., Xiao, K., & Cao, S. (2025) · PeerJ Computer Science · doi:10.7717/peerj-cs.2845

Role-Based Personalized Dialogue Summarization

Ren, Z. (2025) · IEEE Information Technology and Mechatronics Engineering Conference (ITOEC) · doi:10.1109/itoec63606.2025.10968536

APG: Automatic Prompt Generation for Improved Document Summarization

Parnell, J., Unanue, I. J., Matthews, S. L., & Piccardi, M. (2025) · IEEE Transactions on Audio Speech and Language Processing · doi:10.1109/taslpro.2025.3577363

Paired-Prompts: Guiding LLM to Make Better Dialogue Summarization in Parameter-Efficient Fine-Tuning

Fan, K., Wang, J., Feng, Y., Liu, F., & Zhou, X. (2025) · International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) · doi:10.1109/ainit65432.2025.11035988

Automatic Summarization of Parental Chats on WhatsApp

Dmitrieva, K., & Zholus, M. R. (2025) · Vestnik NSU Series Linguistics and Intercultural Communication · doi:10.25205/1818-7935-2025-23-1-80-92

Pegasus-CNN/dailymail fine-tuning for domain-specific summarization: performance evaluation and hyperparameter optimization

Mayil, V. V., & Swarnakar, S. (2025) · Iran Journal of Computer Science · doi:10.1007/s42044-025-00299-9 · Cited by 1

A novel model on improving Chinese dialogue summarization with multi-perspective information enhancement

Wang, Z., Dong, K., Du, Z., Huang, J., Liu, H., & Wang, B. (2025) · Neural Networks · doi:10.1016/j.neunet.2025.107850

Empirical Evaluation on GPU, Overclocking, and LoRA for Deep Learning on Embedded Systems

Raphaloski, E., de Souza, M. C., & Matsubara, E. T. (2025) · IEEE Access · doi:10.1109/access.2025.3590316

Fine-Tuning a Large Language Model for Dialogue Summarization

Al-Juhani, O., Al-ahmadi, L., Alraimi, J. A., Alriyadh, A., & Chaffar, S. (2025) · Lecture notes in networks and systems · doi:10.1007/978-3-031-91235-1_3

Corm: Cache Optimization with Recent Message for Large Language Model InferencePreprint

Huang, Z., Jiang, H., & Dai, J. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5388897

Dialogue Summarization by Integrating Structural Features and Improving Factual Consistency Through Post-editing

He, Y., Li, G., Liu, F., & Yin, S. (2025) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-031-93251-9_21

DataSculpt: A Holistic Data Management Framework for Long-Context LLMs Training

Lu, K., Nie, X., Liang, Z., Pan, D., Zhang, S., Zhao, K., Chen, W., Zhou, Z., Dong, G., Cui, B., et al. (2025) · IEEE International Conference on Data Engineering (ICDE) · doi:10.1109/icde65448.2025.00316 · Cited by 8

General Quality Evaluation Metric Towards Demonstrations for In-Context Learning

Wang, H., Wu, J., Sun, H., Xia, Z., Cheng, D., Wang, J., Qi, Q., & Liao, J. (2025) · IEEE Transactions on Audio Speech and Language Processing · doi:10.1109/taslpro.2025.3606230

Enhancing Automatic Text Summarization: Extractive, Abstractive, and Hybrid Approaches

Thakar, H. A., Pradhan, V., & Thakar, D. (2025) · Lecture notes in networks and systems · doi:10.1007/978-981-96-4536-7_28

Performance Evaluation of Text Summarization Models on SAMSUM Chat Data

Bhatia, J., Patel, D., Patel, J., Kumhar, M., Chauhan, U., Trivedi, H., & Tanwar, S. (2025) · Lecture notes in networks and systems · doi:10.1007/978-981-96-4536-7_16

Leveraging RLHF and PEFT to Fine-Tune FLAN-T5 for Generating Non-toxic/Positive Summaries

Ahlawat, R., Singh, M., Tiwari, S., & Jindal, S. (2025) · Lecture notes in networks and systems · doi:10.1007/978-981-96-6883-0_35

From Conversations to Insights: A Multimodal Approach to Discussion Summarization

Singh, P. K., Kumar, N., Mehta, H. D., & Saha, S. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-04614-7_21

Generative Fuzzy System for Sequence-to-Sequence Learning via Rule-Based Inference

Yang, H., Deng, Z., Zhang, W., Zhao, Z., Wang, G., & Choi, K. (2025) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2025.3615650

On-Device AI for Chat Applications: Enhancing Privacy and Productivity Through Tonality-Driven Paraphrasing

Rao, S., Mahesh, A., Jaideep, N., Hegde, R., Rao, V. P., & Choudhuri, S. S. (2025) · Lecture notes in networks and systems · doi:10.1007/978-3-032-06694-7_35

DABART: Dynamic Semantic Optimization Framework for Dialogue Summarization via Adaptive Topic Analysis and Semantic Bridging

Jin, K., Wang, Y., Santos, L., Fang, T., Yang, X., & Im, S. (2025) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn64981.2025.11227739 · Cited by 1

Critical Analysis of Various Evaluation Techniques for Text Summarization

Parmar, J., & Singh, M. (2025) · Lecture notes in networks and systems · doi:10.1007/978-981-96-8750-3_9

Out-of-distribution detection in text using statistical techniques

Raghavan, D., Bhandari, S., Banerjee, J., & Bandyopadhyay, S. (2025) · Discover Data · doi:10.1007/s44248-025-00091-x

Text summarization method of argumentative discourse by combining the BERT-transformer model

Altameemi, Y. M., Altamimi, M., Alkhalil, A., Uliyan, D. M., & Mansour, R. F. (2025) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2025.1654496 · Cited by 2

From Emojis to Emotions: Abstractive Dialogue Summarization with Emotional Supervision Signals

Wang, F., Zhu, Z., & Pei, H. (2025) · IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA) · doi:10.1109/ispa67752.2025.00127

AI-enhanced therapeutic alliance: bridging AI innovation and mental health care

Manimegalai, R., Vijay Raj Kumar, M., B., T., & Kumar, M. R. (2025) · Mental Health and Social Inclusion · doi:10.1108/mhsi-10-2025-0281

A Multi-Modal Fusion Strategy for Context-Aware and Scalable Abstractive Summarization of Heterogeneous Document Collections

Dheeravath, K., & Saritha, S. J. (2025) · International Conference on Emerging Techniques in Computational Intelligence (ICETCI) · doi:10.1109/icetci67340.2025.11258049

ProSan: Utility-Based Prompt Privacy Sanitizer

Shen, Z., Xi, Z., He, Y., Tong, W., Hua, J., & Zhong, S. (2026) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2026.3654397

Dispenser: Hierarchical KV Cache Management for Efficient LLM Generative Inference

Cao, B., Bian, K., Luo, G., & Kim, J. (2025) · IEEE International Conference on Parallel and Distributed Systems (ICPADS) · doi:10.1109/icpads67057.2025.11323033

Backdoor Complications: A Comprehensive Analysis and Mitigation of the Unforeseen Consequences of Backdoor Attacks

Zhang, R. Y., Shen, Y., Li, H., Jiang, W., Chen, H., Zhang, Y., Xu, G., & Zhang, Y. (2026) · IEEE Transactions on Dependable and Secure Computing · doi:10.1109/tdsc.2026.3658111

Knowledge-Injected Transformer (KIT): A Modular Encoder–Decoder Architecture for Efficient Knowledge Integration and Reliable Question Answering

Kirichenko, L., Maksymenko, D., Turuta, O., Yakovlev, S., & Turuta, O. (2026) · Applied Sciences · doi:10.3390/app16031601

Dialogue summarization with topic enhancement and factual consistency contrast

Zhanghui, L., Wentao, Z., Yuzhong, C., & Yixin, L. (2026) · Computer Speech & Language · doi:10.1016/j.csl.2026.101958

CorDial: Coarse-to-fine Abstractive Dialogue Summarization with Controllable Granularity

Wu, C.-S., Liu, L., Liu, W., Stenetorp, P., & Xiong, C. (2021) · Cited by 1

A Finer-grain Universal Dialogue Semantic Structures based Model For Abstractive Dialogue Summarization

Lei, Y., Zheng, F., Yan, Y., He, K., & Xu, W. (2021) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2021.findings-emnlp.117 · Cited by 11

DialSummEval: Revisiting Summarization Evaluation for Dialogues

Gao, M., & Wan, X. (2022) · Greater South Information System · doi:10.60692/q7htj-bxc48

Enhancing Abstractive Dialogue Summarization with Internal Knowledge

Wang, S., Ma, H., Zhang, Y., Ma, J., & He, L. J. (2024) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn60899.2024.10650220 · Cited by 4

Controllable Abstractive Dialogue Summarization with Sketch Supervision

Wu, C.-S., Liu, L., Liu, W., Stenetorp, P., & Xiong, C. (2021) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2021.findings-acl.454 · Cited by 52