A Survey on Dialogue Systems: Recent Advances and New Frontiers

Long Short-Term Memory

Hochreiter, S., & Schmidhuber, J. (1997) · Neural Computation · doi:10.1162/neco.1997.9.8.1735 · Cited by 102,318

Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation

Cho, K., van Merrienboer, B., Gulcehre, C., Bahdanau, D., Bougares, F., Schwenk, H., & Bengio, Y. (2014) · Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.3115/v1/d14-1179 · Cited by 25,545

Distributed Representations of Words and Phrases and their Compositionality

Mikolov, T., Sutskever, I., Chen, K., Corrado, G., & Dean, J. (2013) · arXiv · doi:10.48550/arxiv.1310.4546 · Cited by 24,533

Generative Adversarial Nets

Labaca-Castro, R. (2023) · Springer eBooks · doi:10.1007/978-3-658-40442-0_9 · Cited by 21,119

Auto-Encoding Variational Bayes

Kingma, D. P., & Welling, M. (2013) · arXiv · doi:10.48550/arxiv.1312.6114 · Cited by 20,067

Neural Machine Translation by Jointly Learning to Align and Translate

Bahdanau, D., Cho, K., & Bengio, Y. (2014) · arXiv · doi:10.48550/arxiv.1409.0473 · Cited by 16,213

Advances in Neural Information Processing Systems 25

Zhang, Y., Sutton, C. A., Storkey, A., & Zoubin Ghahramani, A. (2012) · Cited by 12,653

Term-Weighting Approaches in Automatic Text Retrieval

Salton, G., & Buckley, C. (1988) · Information Processing & Management · doi:10.1016/0306-4573(88)90021-0 · Cited by 11,421

Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning

Williams, R. J. (1992) · Machine Learning · doi:10.1007/bf00992696 · Cited by 8,608

Recurrent neural network based language model

Mikolov, T., Karafiát, M., Burget, L., Černocký, J., & Khudanpur, S. (2010) · Interspeech 2010 · doi:10.21437/interspeech.2010-343 · Cited by 5,390

Chatbot-mediated Learning: Conceptual Framework for the Design of Chatbot Use Cases in Education

Sonderegger, S., & Seufert, S. (2022) · Proceedings of the 14th International Conference on Computer Supported Education · doi:10.5220/0010999200003182 · Cited by 29

Investigating meta-intents: user interaction preferences in conversational recommender systems

Ma, Y., & Ziegler, J. (2024) · User Modeling and User-Adapted Interaction · doi:10.1007/s11257-024-09411-3 · Cited by 28

From Process Models to Chatbots

López, A., Sànchez-Ferreres, J., Carmona, J., & Padró, L. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-21290-2_24 · Cited by 28

CAEVR: Biosignals-Driven Context-Aware Empathy in Virtual Reality

Gupta, K., Zhang, Y., Gunasekaran, T. S., Krishna, N., Pai, Y. S., & Billinghurst, M. (2024) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2024.3372130 · Cited by 29

Summaries, Highlights, and Action Items: Design, Implementation and Evaluation of an LLM-powered Meeting Recap System

Asthana, S., Hilleli, S., He, P., & Halfaker, A. (2025) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3711074 · Cited by 38

Latent Diffusion Model for Social Recommendation

He, Q., Zhang, Y., Li, K., Li, X., & Zhou, W. (2026) · IEEE Transactions on Systems Man and Cybernetics Systems · doi:10.1109/tsmc.2026.3657816 · Cited by 31

Conditional Text Generation for Harmonious Human-Machine Interaction

Guo, B., Wang, H., Ding, Y., Wu, W., Hao, S., Sun, Y., & Yu, Z. (2021) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3439816 · Cited by 35

User Simulation for Evaluating Information Access Systems

Balog, K., & Zhai, C. (2024) · Foundations and Trends® in Information Retrieval · doi:10.1561/1500000098 · Cited by 52

Smooth Talking: Generative Versus Scripted Coaching Chatbot Adoption and Efficacy Comparison

Terblanche, N. H. D. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2423125 · Cited by 27

Few-shot Named Entity Recognition: Definition, Taxonomy and Research Directions

Moscato, V., Postiglione, M., & Sperlí, G. (2023) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3609483 · Cited by 33

A review of dialogue systems: current trends and future directions

Algherairy, A. S., & Ahmed, M. (2023) · Neural Computing and Applications · doi:10.1007/s00521-023-09322-1 · Cited by 25

An Optimal Approach to Enhance Context Aware Description Administration Service for Cloud Robots in a Deep Learning Environment

Subha, R., Haldorai, A., & Ramu, A. (2021) · Wireless Personal Communications · doi:10.1007/s11277-021-08073-3 · Cited by 25

DialTest: automated testing for recurrent-neural-network-driven dialogue systems

Liu, Z., Feng, Y., & Chen, Z. (2021) · ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA) · doi:10.1145/3460319.3464829 · Cited by 31

Task-Optimized Adapters for an End-to-End Task-Oriented Dialogue System

Bang, N., Lee, J., & Koo, M. (2023) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2023.findings-acl.464 · Cited by 25

PROTOTYPE-TO-STYLE: Dialogue Generation With Style-Aware Editing on Retrieval Memory

Su, Y., Wang, Y., Cai, D., Baker, S., Korhonen, A., & Collier, N. (2021) · IEEE/ACM Transactions on Audio Speech and Language Processing · doi:10.1109/taslp.2021.3087948 · Cited by 27

User Satisfaction Estimation with Sequential Dialogue Act Modeling in Goal-oriented Conversational Systems

Deng, Y., Zhang, W., Lam, W. P., Cheng, H., & Meng, H. M. L. (2022) · International World Wide Web Conference (WWW) · doi:10.1145/3485447.3512020 · Cited by 24

Dialogue intent classification with character-CNN-BGRU networks

Wang, Y., Huang, J., He, T., & Tu, X. (2019) · Multimedia Tools and Applications · doi:10.1007/s11042-019-7678-1 · Cited by 27

Human Annotated Dialogues Dataset for Natural Conversational Agents

Merdivan, E., Singh, D., Hanke, S., Kropf, J., Holzinger, A., & Geist, M. (2020) · Applied Sciences · doi:10.3390/app10030762 · Cited by 29

Enhancements to the Sequence-to-Sequence-Based Natural Answer Generation Models

Palasundram, K., Sharef, N. M., Kasmiran, K. A., & Azman, A. (2020) · IEEE Access · doi:10.1109/access.2020.2978551 · Cited by 25

ChatGPT and the AI revolution: a comprehensive investigation of its multidimensional impact and potential

Afjal, M. (2023) · Library Hi Tech · doi:10.1108/lht-07-2023-0322 · Cited by 34

Multi-Turn Dialogue Reading Comprehension With Pivot Turns and Knowledge

Zhang, Z., Li, J., & Zhao, H. (2021) · IEEE/ACM Transactions on Audio Speech and Language Processing · doi:10.1109/taslp.2021.3058616 · Cited by 24

Privacy-Enabled Smart Home Framework with Voice Assistant

Singh, D., Psychoula, I., Merdivan, E., Kropf, J., Hanke, S., Sandner, E., Chen, L., & Holzinger, A. (2019) · Computer communications and networks · doi:10.1007/978-3-030-25590-9_16 · Cited by 22

A comprehensive survey on automatic text summarization with exploration of LLM-based methods

Zhang, Y., Jin, H., Meng, D., Wang, J., & Tan, J. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.131928 · Cited by 293

End-to-end Task-oriented Dialogue: A Survey of Tasks, Methods, and Future Directions

Qin, L., Pan, W., Chen, Q., Liao, L., Zhou, Y., Zhang, Y., Che, W., & Li, M. (2023) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2023.emnlp-main.363 · Cited by 39

LexRAG: Benchmarking Retrieval-Augmented Generation in Multi-Turn Legal Consultation Conversation

Li, H., Chen, Y., Hu, Y., Ai, Q., Chen, J., Yang, X., Yang, J., Wu, Y., Liu, Z., & Liu, Y. (2025) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3726302.3730340 · Cited by 27

A Neural Question Answering System for Basic Questions about Subroutines

Bansal, A., Eberhart, Z., Wu, L., & McMillan, C. (2021) · IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER) · doi:10.1109/saner50967.2021.00015 · Cited by 21

Intent Classification for a Management Conversational Assistant

Hefny, A. H., Dafoulas, G. A., & Ismail, M. A. (2020) · International Conference on Computer Engineering & Systems (ICCES) · doi:10.1109/icces51560.2020.9334685 · Cited by 21

PIN: A Novel Parallel Interactive Network for Spoken Language Understanding

Zhou, P., Huang, Z., Liu, F., & Zou, Y. (2021) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr48806.2021.9411948 · Cited by 21

Improving the Applicability of Knowledge-Enhanced Dialogue Generation Systems by Using Heterogeneous Knowledge from Multiple Sources

Wu, S., Wang, M., Li, Y., Zhang, D., & Wu, Z. (2022) · ACM International Conference on Web Search and Data Mining (WSDM) · doi:10.1145/3488560.3498393 · Cited by 21

Taking Search to Task

Shah, C. S., White, R. W., Thomas, P., Mitra, B., Sarkar, S., & Belkin, N. J. (2023) · Conference on Human Information Interaction and Retrieval · doi:10.1145/3576840.3578288 · Cited by 21

An Intelligent Conversational Agent for the Legal Domain

Amato, F., Fonisto, M., Giacalone, M., & Sansone, C. (2023) · Information · doi:10.3390/info14060307 · Cited by 23

A Hierarchical Attention Based Seq2Seq Model for Chinese Lyrics Generation

Fan, H., Wang, J., Zhuang, B., Wang, S., & Xiao, J. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-29894-4_23 · Cited by 21

Conversational Recommender System Chatbot Based on Functional Requirement

Theosaksomo, D., & Widyantoro, D. H. (2019) · International Conference on Telecommunication Systems, Services, and Applications · doi:10.1109/tssa48701.2019.8985467 · Cited by 21

Unstructured Text Enhanced Open-Domain Dialogue System: A Systematic Survey

Ma, L., Li, M., Zhang, W., Li, J., & Liu, T. (2021) · ACM Transactions on Information Systems · doi:10.1145/3464377 · Cited by 24

State-of-the-Art in Open-Domain Conversational AI: A Survey

Adewumi, T., Liwicki, F., & Liwicki, M. (2022) · Information · doi:10.3390/info13060298 · Cited by 24

Towards personalized persuasive dialogue generation for adversarial task oriented dialogue setting

Tiwari, A., Khandwe, A., Saha, S., Ramnani, R., Maitra, A., & Sengupta, S. (2022) · Expert Systems with Applications · doi:10.1016/j.eswa.2022.118775 · Cited by 20

Chatbots as Part of Digital Government Service Provision – A User Perspective

Abbas, N., Følstad, A., & Bjørkli, C. A. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-25581-6_5 · Cited by 23

Sohbet Robotları (Chatbots) ve Yabancı Dil Eğitimi

Akkaya, N., & ŞENGÜL, L. (2023) · Buca eğitim fakültesi dergisi (Online)/Buca Eğitim Fakültesi dergisi · doi:10.53444/deubefd.1340781 · Cited by 24

Explaining the Wait: How Justifying Chatbot Response Delays Impact User Trust

Zhang, Z., Tsiakas, K., & Schneegass, C. (2024) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3640794.3665550 · Cited by 28

ChatGPT en Educación Superior: explorando sus potencialidades y sus limitaciones

Galli, M. G., & Kanobel, M. C. (2023) · Revista Educación Superior y Sociedad (ESS) · doi:10.54674/ess.v35i2.815 · Cited by 37

Survey on dialogue systems including slavic languages

Wołk, K., Wołk, A., Wnuk, D. C., Grześ, T., & Skubis, I. (2021) · Neurocomputing · doi:10.1016/j.neucom.2021.11.076 · Cited by 21

Prompting large language models for user simulation in task-oriented dialogue systems

Algherairy, A. S., & Ahmed, M. (2024) · Computer Speech & Language · doi:10.1016/j.csl.2024.101697 · Cited by 25

A Weighted Composite Metric for Evaluating User Experience in Educational Chatbots: Balancing Usability, Engagement, and Effectiveness

Alabbas, A., & Alomar, K. (2025) · Future Internet · doi:10.3390/fi17020064 · Cited by 25

Towards an open-domain chatbot for language practice

Tyen, G., Brenchley, M., Caines, A., & Buttery, P. J. (2022) · Workshop on Innovative Use of NLP for Building Educational Applications · doi:10.18653/v1/2022.bea-1.28 · Cited by 23

Improving BERT with local context comprehension for multi-turn response selection in retrieval-based dialogue systems

Chen, Z., Liu, L., Wan, Y., Chen, Y., Chen, D., Li, W., & Lin, Y. (2023) · Computer Speech & Language · doi:10.1016/j.csl.2023.101525 · Cited by 18

Improving Conversational Recommendation Systems via Counterfactual Data Simulation

Wang, X., Zhou, K., Tang, X., Zhao, W. X., Pan, F., Cao, Z., & Wen, J.-R. (2023) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3580305.3599387 · Cited by 21

State Machine Based Human-Bot Conversation Model and Services

Zamanirad, S., Benatallah, B., Rodríguez, C., Yaghoub-Zadeh-Fard, M.-A., Bouguelia, S., & Brabra, H. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-49435-3_13 · Cited by 17

A memory network based end-to-end personalized task-oriented dialogue generation

Zhang, B., Xu, X., Li, X., Ye, Y., Chen, X., & Wang, Z. (2020) · Knowledge-Based Systems · doi:10.1016/j.knosys.2020.106398 · Cited by 17

A Linguistic Study on Relevance Modeling in Information Retrieval

Fan, Y., Guo, J., Ma, X., Zhang, R., Lan, Y., & Cheng, X. (2021) · International World Wide Web Conference (WWW) · doi:10.1145/3442381.3450009 · Cited by 21

Coarse-grained decomposition and fine-grained interaction for multi-hop question answering

Cao, X., & Liu, Y. (2021) · Journal of Intelligent Information Systems · doi:10.1007/s10844-021-00645-w · Cited by 21

Social robotic application to support active and healthy ageing

Cooper, S., Fava, A. D., Villacañas, Ó., Silva, T., Fernández-Carbajales, V., Unzueta, L., Serras, M., Marchionni, L., & Ferro, F. (2021) · IEEE RO-MAN · doi:10.1109/ro-man50785.2021.9515432 · Cited by 17

Assistive Technologies for Supporting the Wellbeing of Older Adults

Dratsiou, I., Varella, A., Romanopoulou, E. D., Villacañas, Ó., Cooper, S., Isaris, P., Serras, M., Unzueta, L., Silva, T., Zurkuhlen, A., et al. (2022) · Technologies · doi:10.3390/technologies10010008 · Cited by 17

Empathy Level Alignment via Reinforcement Learning for Empathetic Response Generation

Ma, H., Zhang, B., Xu, B., Wang, J., Lin, H., & Sun, X. N. (2025) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2025.3544594 · Cited by 16

The Evolution of Search: Three Computing Paradigms

Wu, X., Xingquan Zhu, A., & Wu, M. (2022) · ACM Transactions on Management Information Systems · doi:10.1145/3495214 · Cited by 16

ReMeDi

Yan, G., Pei, J., Ren, P., Ren, Z., Xin, X., Liang, H., de Rijke, M., & Chen, Z. (2022) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3477495.3531809 · Cited by 17

Taxonomy of Abstractive Dialogue Summarization: Scenarios, Approaches, and Future Directions

Jia, Q., Liu, Y., Ren, S., & Zhu, K. Q. (2023) · ACM Computing Surveys · doi:10.1145/3622933 · Cited by 20

Enhancing Personalized Mental Health Support Through Artificial Intelligence: Advances in Speech and Text Analysis Within Online Therapy Platforms

Jelassi, M., Matteli, K., Khalfallah, H. B., & Jacques Demongeot, A. (2024) · Information · doi:10.3390/info15120813 · Cited by 19

Continuous Melody Generation via Disentangled Short-Term Representations and Structural Conditions

Chen, K., Xia, G., & Dubnov, S. (2020) · IEEE International Conference on Semantic Computing (ICSC) · doi:10.1109/icsc.2020.00025 · Cited by 16

A Cooperative Memory Network for Personalized Task-oriented Dialogue Systems with Incomplete User Profiles

Pei, J., Ren, P., & de Rijke, M. (2021) · International World Wide Web Conference (WWW) · doi:10.1145/3442381.3449843 · Cited by 17

Deep Learning for Dialogue Systems: Chit-Chat and Beyond

Yan, R., Li, J., & Zhou, Y. (2022) · Foundations and Trends® in Information Retrieval · doi:10.1561/1500000083 · Cited by 17

Developing Context-Aware Dialoguing Services for a Cloud-Based Robotic System

Huang, J.-Y., Lee, W., & Lin, T.-A. (2019) · IEEE Access · doi:10.1109/access.2019.2905616 · Cited by 16

Attention-Based Response Generation Using Parallel Double Q-Learning for Dialog Policy Decision in a Conversational System

Su, M.-H., Wu, C., & Chen, L. (2019) · IEEE/ACM Transactions on Audio Speech and Language Processing · doi:10.1109/taslp.2019.2949687 · Cited by 18

A Multi-Attention Approach Using BERT and Stacked Bidirectional LSTM for Improved Dialogue State Tracking

Khan, M. A., Huang, Y., Feng, J., Prasad, B. K., Ali, Z., Ullah, I., & Kefalas, P. (2023) · Applied Sciences · doi:10.3390/app13031775 · Cited by 18

Conversational AI and Chatbots: Enhancing User Experience on Websites

Dobbala, M. K., & Lingolu, M. S. S. (2024) · American Journal of Computer Science and Technology · doi:10.11648/j.ajcst.20240703.11 · Cited by 17

Avoiding Echo-Responses in a Retrieval-Based Conversation System

Fedorenko, D., Smetanin, N., & Rodichev, A. (2018) · Communications in computer and information science · doi:10.1007/978-3-030-01204-5_9 · Cited by 15

EnsembleGAN

Zhang, J., Tao, C., Xu, Z., Xie, Q., Chen, W., & Yan, R. (2019) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3331184.3331193 · Cited by 14

A Hierarchical Structured Multi-Head Attention Network for Multi-Turn Response Generation

Lin, F., Zhang, C., Liu, S., & Ma, H. (2020) · IEEE Access · doi:10.1109/access.2020.2977471 · Cited by 15

Conversational AI over Military Scenarios Using Intent Detection and Response Generation

Chuang, H.-M., & Cheng, D.-W. (2022) · Applied Sciences · doi:10.3390/app12052494 · Cited by 15

Approximating stability for applied argument-based inquiry

Odekerken, D., Bex, F., Borg, A., & Testerink, B. (2022) · Intelligent Systems with Applications · doi:10.1016/j.iswa.2022.200110 · Cited by 15

Reinforcement Learning Over Knowledge Graphs for Explainable Dialogue Intent Mining

Yang, K., Kong, X., Wang, Y., Zhang, J., & de Melo, G. (2020) · IEEE Access · doi:10.1109/access.2020.2991257 · Cited by 18

Affective computing in the era of large language models: A survey from the NLP perspective

Zhang, Y., Yang, X., Xu, X., Gao, Z., Huang, Y., Mu, S., Feng, S., Wang, D., Zhang, Y., Song, K., et al. (2026) · Knowledge-Based Systems · doi:10.1016/j.knosys.2026.115411 · Cited by 28

An LSTM-based Intent Detector for Conversational Recommender Systems

Jbene, M., Tigani, S., Saadane, R., & Chehri, A. (2022) · IEEE Vehicular Technology Conference · doi:10.1109/vtc2022-spring54318.2022.9860839 · Cited by 16

RICE AlgebraBot: Lessons learned from designing and developing responsible conversational AI using induction, concretization, and exemplification to support algebra learning

Li, C., Xing, W., Song, Y., & Lyu, B. (2024) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2024.100338 · Cited by 22

DuIVA: An Intelligent Voice Assistant for Hands-free and Eyes-free Voice Interaction with the Baidu Maps App

Huang, J., Wang, H., Ding, S., & Wang, S. (2022) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3534678.3539030 · Cited by 14

Talk like me: Exploring the feedback speech rate regulation strategy of the voice user interface for elderly people

Wang, J., Yang, S., & Xu, Z. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1119355 · Cited by 12

Transfer Hierarchical Attention Network for Generative Dialog System

Zhang, X., & Yang, Q. (2019) · Machine Intelligence Research · doi:10.1007/s11633-019-1200-0 · Cited by 13

Personalizing Task-oriented Dialog Systems via Zero-shot Generalizable Reward Function

Siddique, A. B., Maqbool, M. H., Taywade, K., & Foroosh, H. (2022) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3511808.3557417 · Cited by 16

IRWoZ: Constructing an Industrial Robot Wizard-of-OZ Dialoguing Dataset

Li, C., Chrysostomou, D., Zhang, X., & Yang, H. (2023) · IEEE Access · doi:10.1109/access.2023.3259325 · Cited by 13

Conversational Interfaces in IoT Ecosystems: Where We Are, What Is Still Missing

Gallo, S., Paternò, F., & Malizia, A. (2023) · International Conference on Mobile and Ubiquitous Multimedia (MUM) · doi:10.1145/3626705.3627775 · Cited by 15

A Novel Approach for Ontology-Driven Information Retrieving Chatbot for Fashion Brands

Nazir, A., Yaseen, M., Ahmed, T., Imran, S., & Wasi, S. (2019) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2019.0100972 · Cited by 13

InstructTODS: Large Language Models for End-to-End Task-Oriented Dialogue Systems

Chung, W., Cahyawijaya, S., Wilie, B., Lovenia, H., & Fung, P. (2023) · doi:10.18653/v1/2023.nlint-1.1 · Cited by 36

Waiting Experience: Optimization of Feedback Mechanism of Voice User Interfaces Based on Time Perception

Wang, J., Li, Y., Yang, S., Dong, S.-Y., & Li, J. (2023) · IEEE Access · doi:10.1109/access.2023.3250278 · Cited by 12

Smart tourism chatbot system using Multi-domain Tourism Information DST

Kang, H.-C., Kang, K.-B., Kim, D., Jwa, M.-C., Ko, T.-S., & Jwa, J.-W. (2023) · International Conference on Ubiquitous and Future Networks · doi:10.1109/icufn57995.2023.10200288 · Cited by 12

Effective Utilization of External Knowledge and History Context in Multi-turn Spoken Language Understanding Model

Wang, Y., He, T., Fan, R., Zhou, W.-J., & Tu, X. (2019) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata47090.2019.9006162 · Cited by 12

Dialogue Act Classification for Virtual Agents for Software Engineers during Debugging

Wood, A., Eberhart, Z., & McMillan, C. (2020) · doi:10.1145/3387940.3391487 · Cited by 12

Semantic-aware conditional variational autoencoder for one-to-many dialogue generation

Wang, Y., Liao, J., Yu, H. Z., & Leng, J. (2022) · Neural Computing and Applications · doi:10.1007/s00521-022-07182-9 · Cited by 11

A Simple Meta-learning Paradigm for Zero-shot Intent Classification with Mixture Attention Mechanism

Liu, H., Zhao, S., Zhang, X., Zhang, F., Sun, J., Yu, H. Z., & Zhang, X. (2022) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3477495.3531803 · Cited by 15

Developing a Twitter bot that can join a discussion using state-of-the-art architectures

Çetinkaya, Y. M., Toroslu, İ. H., & Davulcu, H. (2020) · Social Network Analysis and Mining · doi:10.1007/s13278-020-00665-4 · Cited by 14

A Review of Quality Assurance Research of Dialogue Systems

Li, X., Tao, C., Gao, J. Z., & Guo, H. (2022) · IEEE International Conference on Artificial Intelligence Testing (AITest) · doi:10.1109/aitest55621.2022.00021 · Cited by 13

Intelligent Customer Service System Optimization Based on Artificial Intelligence

Wu, Z. Y., She, Q., & Zhou, C. (2024) · Journal of Organizational and End User Computing · doi:10.4018/joeuc.336923 · Cited by 16

An Empathic GPT-Based Chatbot to Talk About Mental Disorders With Spanish Teenagers

Mármol-Romero, A. M., Garcı́a-Vega, M., Cumbreras, M. Á. G., & Montejo‐Ráez, A. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2344355 · Cited by 13

A Survey on Chatbot: Futuristic Conversational Agent for User Interaction

Goel, P., & Ganatra, A. P. (2021) · doi:10.1109/icspc51351.2021.9451763 · Cited by 11

Constructing novel datasets for intent detection and ner in a korean healthcare advice system: guidelines and empirical results

Kim, Y.-M., Lee, T., & Na, S.-O. (2022) · Applied Intelligence · doi:10.1007/s10489-022-03400-y · Cited by 11

Evaluating LLM-based Agents for Multi-turn Conversations: A Survey

Guan, S., Wang, J., 渡辺, 将., Zhu, B., Lou, J., & Xiong, H. (2026) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3793671 · Cited by 71

Human-in-the-Loop Interaction for continuously Improving Generative Model in Conversational Agent for Behavioral Intervention

Sun, X., Bosch, J. A., de Wit, J., & Krahmer, E. (2023) · ACM International Conference on Intelligent User Interfaces (IUI) · doi:10.1145/3581754.3584142 · Cited by 12

Deep Learning for Natural Language Processing

Wang, Y., Li, Z., Deng, Z., Song, H., & Yang, J. (2023) · Artificial intelligence · doi:10.5772/intechopen.112550 · Cited by 10

Deep adversarial reconstruction classification network for unsupervised domain adaptation

Lin, J.-W., Bian, Z., & Wang, S. (2023) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-023-02035-w · Cited by 10

Long-Term, in-the-Wild Study of Feedback about Speech Intelligibility for K-12 Students Attending Class via a Telepresence Robot

Rueben, M., Syed, M., London, E., Camarena, M., Shin, E., Zhang, Y., Wang, T. S., Groechel, T. R., Lee, R., & Matarić, M. J. (2021) · INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION · doi:10.1145/3462244.3479893 · Cited by 10

An approach to the classification of educational chatbots

Urquiza-Yllescas, J. F., Mendoza, S., Rodríguez, J., & Sánchez-Adame, L. M. (2022) · Journal of Intelligent & Fuzzy Systems · doi:10.3233/jifs-213275 · Cited by 11

Recent advances in deep learning based dialogue systems: a systematic survey

Ni, J., Young, T., Pandelea, V., Xue, F., & Cambria, E. (2022) · Artificial Intelligence Review · doi:10.1007/s10462-022-10248-8 · Cited by 313

Deep Learning for Dialogue Systems

Chen, Y.-N., Çelikyılmaz, A., & Hakkani-Tür, D. Z. (2018) · International Conference on Computational Linguistics · Cited by 8

A Study on the Dialogue System based on Deep Neural Network

교양학부, 한., Jhee, I.-Y., & Kim, H. (2018) · Lingua Humanitatis · doi:10.16945/2018202012

심층학습을 이용한 대화시스템의 연구방법 분석

지인영, & 김희동 (2018) · 인문언어

Recent Advances in Deep Learning-based Dialogue Systems

Ni, J., Young, T., Pandelea, V., Xue, F., Adiga, V. A. K., & Cambria, E. (2021) · Cited by 4