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

Neural Encoder-Decoder based Urdu Conversational Agent

Alam, M. (2018) · IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) · doi:10.1109/uemcon.2018.8796688 · Cited by 3

Memory Attention Neural Network for Multi-domain Dialogue State Tracking

Xu, Z., Chen, Z., Chen, L., Zhu, S., & Yu, K. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-60450-9_4 · Cited by 3

THINK: A novel conversation model for generating grammatically correct and coherent responses

Sun, B., Feng, S., Li, Y., Liu, J., & Li, K. (2022) · Knowledge-Based Systems · doi:10.1016/j.knosys.2022.108376 · Cited by 2

Generating Predictable and Adaptive Dialog Policies in Single- and Multi-domain Goal-oriented Dialog Systems

Le, N. X. T., Siddique, A. B., Jamour, F., Oymak, S., & Hristidis, V. (2021) · International Journal of Semantic Computing · doi:10.1142/s1793351x21400109 · Cited by 3

On selection of topics that users are interested in but are not familiar with

Sakai, Y., & Matsumoto, M. (2022) · International Power Electronics Conference (IPEC) · doi:10.23919/ipec-himeji2022-ecce53331.2022.9807252 · Cited by 2

DuIVRS: A Telephonic Interactive Voice Response System for Large-Scale POI Attribute Acquisition at Baidu Maps

Huang, J., Wang, H., & Wang, S. (2022) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3511808.3557131 · Cited by 2

Enhancing Mental Health Support through Artificial Intelligence: Advances in Speech and Text Analysis within Online Therapy PlatformsPreprint

Jelassi, M., Matteli, K., Khalfallah, H. B., & Jacques Demongeot, A. (2024) · Preprints.org · doi:10.20944/preprints202402.1585.v1 · Cited by 1

FCM: A Fine-grained Comparison Model for Multi-turn Dialogue Reasoning

Wang, X., Zhang, H., Zhao, S., Zou, Y., Chen, H., Ding, Z., Cheng, B., & Lan, Y. (2021) · Findings of the Association for Computational Linguistics: EMNLP 2021 · doi:10.18653/v1/2021.findings-emnlp.362 · Cited by 4

Open Questions for Next Generation Chatbots

Ye, W., & Li, Q. (2020) · IEEE/ACM Symposium on Edge Computing (SEC) · doi:10.1109/sec50012.2020.00050 · Cited by 1

Designing rule-based conversational agents with behavioral programming: a study of human subjects

Rosenfeld, A., & Haimovich, N. (2022) · EuroMed Journal of Business · doi:10.1108/emjb-09-2021-0144 · Cited by 1

Historical Information-Based Intent Detection for Multiturn Dialogue

Sun, X., Zheng, H., & Tang, Z. (2022) · International Conference on Computing and Artificial Intelligence (ICCAI) · doi:10.1145/3532213.3532299 · Cited by 1

Enhancing Designer Knowledge to Dialogue Management: A Comparison between Supervised and Reinforcement Learning Approaches

Nishimoto, B. E., Cristo, R., Mansano, A. F., Hruschka, E. R., Caridá, V. F., & Costa, A. H. R. (2022) · doi:10.5753/eniac.2022.227625 · Cited by 1

Improving the Categorization of Intent of a Chatbot in Portuguese with Data Augmentation Obtained by Reverse Translation

Soares, J. D. N., & Maia, J. E. B. (2023) · Lecture notes in networks and systems · doi:10.1007/978-3-031-35507-3_40 · Cited by 1

Improved conversational recommender system based on dialog context

Wang, X., Liu, J., & Duan, J. (2023) · Natural Language Engineering · doi:10.1017/s1351324923000451 · Cited by 1

ERDL: Efficient Retrieval Framework Based on Distillation from Large Language Models

Yu, H., Li, R., Zhang, Z., Ye, S., Liu, Q., Huang, Z., & Chen, E. (2024) · International Conference on Computational Linguistics and Natural Language Processing (CLNLP) · doi:10.1109/clnlp64123.2024.00023 · Cited by 1

Enhancing Patient Intake Process in Mental Health Consultations Using RAG-Driven Chatbot

Shayaninasab, M., Zahoor, M., & Yalçın, Ö. N. (2024) · International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) · doi:10.1109/aciiw63320.2024.00053 · Cited by 2

Knowledge Discovery and Scientometric Analysis of Conversational Artificial Intelligence (CAI) for Mental Health

Hidayat, M. L., Ahmad, I., Assidiqi, M. H., Khanzada, T. J. S., & Meccawy, M. (2025) · International Conference on Innovation in Artificial Intelligence and Internet of Things (AIIT) · doi:10.1109/aiit63112.2025.11082869 · Cited by 1

AIML+: Enhancing AIML for the Educational Domain Through Frames and Large Language Models

Oliverio, M., Balestrucci, P. F., Luca Anselma, A., & Mazzei, A. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-98459-4_13 · Cited by 1

A Non-AI Homework Support Tool to Enhance Achievement and Interest in Science Education: BilgeCan Bot

Yılmaz, T., & Dökme, Ï. (2025) · El-Cezeri Fen ve Mühendislik Dergisi · doi:10.31202/ecjse.1726783 · Cited by 1

When Words Fall Short: The Case for Conversational Interfaces that Don’t Listen

Simpson, J., Stening, H., Patil, G., Nalepka, P., Dras, M., Kallen, R. W., Hosking, S. G., Richardson, M. J., & Richards, D. (2025) · INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION · doi:10.1145/3716553.3750799 · Cited by 1

A Hybrid Pipeline and Large Language Model System for Task-Oriented Dialogue

Zheng, Y., Tan, W., Li, Q., Liu, L., Yan, Z., & Dai, H. (2025) · IEEE International Conference on High Performance Computing and Communications; IEEE International Conference on Smart City; IEEE International Conference on Data Science and Systems (HPCC/SmartCity/DSS) · doi:10.1109/hpcc67675.2025.00069 · Cited by 1

Enhancing Chatbot Performance in a SaaS Platform Through Retrieval-Augmented Generation and Prompt Engineering: A Case Study in Behavioral Safety Analysis

Rivera, J., Zapata, S., Pizarro, R., & Keith, B. (2025) · Knowledge · doi:10.3390/knowledge5040025 · Cited by 1

Smarter Coaching Chatbots: Leveraging Hybrid Architectures for Deeper Context Awareness

Bauer, A., Mai, V., Neef, C., & Richert, A. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-13184-3_1 · Cited by 1

Multi-round self-optimization with large language models for conversational recommendation

He, Q., Zhang, Y., Li, K., Li, X., & Wang, X. (2026) · Applied Intelligence · doi:10.1007/s10489-026-07165-6 · Cited by 1

AI-assisted sales coaching framework: Empirically-derived models for B2B communication analysis

Mäntyvaara, J., Nevalainen, P., Glavatskiy, K. S., & Heikkonen, J. (2026) · Array · doi:10.1016/j.array.2026.100755 · Cited by 1

The Case For Language Model Approximated LIKE Predicate

Li, Y. X., Wang, D., Wang, Z., Zhou, Y., Yan, Y., Geng, J., Wang, X., Zeng, Z., & Wang, H. (2026) · Proceedings of the ACM on Management of Data · doi:10.1145/3786703 · Cited by 1

AFDM : an Analytical Framework of Dialogue Manager

Keyvanpour, M. R., Shirzad, M. B., & Rashidghalam, H. (2020) · Iranian Joint Congress on Fuzzy and Intelligent Systems · doi:10.1109/cfis49607.2020.9238732 · Cited by 1

Using BERT Model for Intent Classification in Human-Computer Dialogue Systems to Reduce Data Volume Requirement

Liu, H., & Peng, H. (2021) · Lecture notes in networks and systems · doi:10.1007/978-3-030-80285-1_59 · Cited by 1

Hierarchical Multi-turn Dialogue Generation Model Based on Double-layer Decoding

Gong, S., Zeng, B., Chen, X., Xu, M., & Luo, S. (2021) · International Conference on Computer Engineering and Application (ICCEA) · doi:10.1109/iccea53728.2021.00030 · Cited by 2

Incorporating Social Practices in Dialogue Systems

Yildiz, E., Bensch, S., & Dignum, F. P. M. (2022) · Lecture notes in computer science · doi:10.1007/978-3-030-94890-0_7 · Cited by 1

Dynamic Network Model for Multi-Domain End-to-end Task-Oriented Dialogue System

Zhao, F., Qiu, M. L., Li, X., & Guo, D. (2022) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros47612.2022.9981938 · Cited by 1

Learning Dialogue Policy Efficiently Through Dyna Proximal Policy Optimization

Huang, C., & Cao, B. (2022) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-031-24383-7_22 · Cited by 1

Reward estimation with scheduled knowledge distillation for dialogue policy learning

Qiu, J., Zhang, H., & Yang, Y. (2023) · Connection Science · doi:10.1080/09540091.2023.2174078 · Cited by 2

Dynalogue: A Transformer-Based Dialogue System with Dynamic Attention

Zhang, R., Wu, T., Chen, X., Wen, S., Nepal‬, ‪., Paris, C. L., & Xiang, Y. (2023) · International World Wide Web Conference (WWW) · doi:10.1145/3543507.3583330 · Cited by 1

Research on Empathetic Dialogue Generation Based on Emotional Cognition and Empathetic Response

Cao, Y., Yu, H., & Wan, F. (2023) · Advances in Social Science, Education and Humanities Research/Advances in social science, education and humanities research · doi:10.2991/978-2-38476-094-7_9 · Cited by 1

Efficient Dialogue State Tracking based on Dialogue-level State Prediction and Historical Dialogue State Deletion

Hu, J., & Tan, L. (2023) · International Conference on Communications, Computing and Artificial Intelligence (CCCAI) · doi:10.1109/cccai59026.2023.00034 · Cited by 1

Scientific Reading Comprehension with Sentences Selection and Ranking

Chen, J., Wang, W., & Shao, S. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-44699-3_9 · Cited by 1

U-CORE: A Unified Deep Cluster-wise Contrastive Framework for Open Relation Extraction

Zhou, J., Dong, S., Huang, Y., Wu, M., Li, H., Wang, J., Tu, H., & Wang, X. (2023) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00604 · Cited by 1

Skill Check: Some Considerations on the Evaluation of Gamemastering Models for Role-Playing Games

Góngora, S., Chiruzzo, L., Méndez, G., & Gervás, P. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-49065-1_27 · Cited by 3

Fine-grained Conversational Decoding via Isotropic and Proximal Search

Yao, Y., Wu, H., Xu, Q., & Song, L. (2023) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2023.emnlp-main.5 · Cited by 1

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

An Optimized Ranking Based Technique towards Conversational Recommendation Models

Dhawan, S., Singh, K., Batra, A., Choi, A., & Choi, E. (2024) · International Journal of Computing and Digital Systems · doi:10.12785/ijcds/150185 · Cited by 1

A Survey of Conversational Styles and Systems

Nagpal, R., Fatty, S., & Brizan, D. G. (2024) · Conference on Human System Interactions · doi:10.1109/hsi61632.2024.10613569 · Cited by 1

Deep Contrastive Active Learning for Out-of-domain Filtering in Dialog Systems

Oruche, R., Zampieri, M., & Calyam, P. P. (2024) · IEEE International Conference on Data Science and Advanced Analytics (DSAA) · doi:10.1109/dsaa61799.2024.10722769 · Cited by 1

Multi-Head Encoder Shared Model Integrating Intent and Emotion for Dialogue Summarization

Xing, X., Zhang, X., Zhou, S., Zhang, R., & Chen, J. (2024) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2024.056877 · Cited by 1

Intent-calibrated Self-training for Answer Selection in Open-domain Dialogues

Deng, W., Pei, J., Ren, Z., Chen, Z., & Ren, P. (2023) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00599 · Cited by 3

Unsupervised Multi-task Learning Dialogue Management

Sushravya, G. M., & Sengupta, S. (2019) · Joint International Conference on Data Science & Management of Data (CODS-COMAD) · doi:10.1145/3297001.3297026 · Cited by 1

Dialogue System for Service Desk of Complex Software Systems Based on Relational Concept Analysis

Beresnev, A., Zhdankin, A., Lobantsev, A., Vasiliev, A., Vedernikov, N., & Gusarova, N. (2019) · International Conference on Geoinformatics and Data Analysis (ICGDA) · doi:10.1145/3318236.3318258 · Cited by 1

History and Development Tendency of Human - Computer Dialogue System

Lin, X., Yuan, T., & Lei, G. (2019) · International Conference on Artificial Intelligence and Big Data (ICAIBD) · doi:10.1109/icaibd.2019.8836978 · Cited by 1

Training Set Expansion Using Word Embeddings for Korean Medical Information Extraction

Kim, Y.-M. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-33752-0_19 · Cited by 1

Topic Judgment Helps Question Similarity Prediction in Medical FAQ Dialogue Systems

Zhu, L., Dai, X., Huang, Q., Xiang, H., & Zheng, J. (2019) · IEEE ... International Conference on Data Mining workshops · doi:10.1109/icdmw.2019.00140 · Cited by 1

HDGS: A Hybrid Dialogue Generation System using Adversarial Learning

Yu, H., Li, A., Jiang, R., Jia, Y., Zhao, X., & Han, W. (2019) · IEEE International Conference on Data Science in Cyberspace · doi:10.1109/dsc.2019.00028 · Cited by 1

AIIS: The SIGIR 2020 Workshop on Applied Interactive Information Systems

Chen, H., Ren, Z., Ren, P., Yin, D., & He, X. (2020) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3397271.3401461 · Cited by 1

Visualization for Analyzing Usage Status from Dialogue Systems

Seki, Y. (2020) · IEEE Annual International Computer Software and Applications Conference (COMPSAC) · doi:10.1109/compsac48688.2020.00-10 · Cited by 1

Weighted User Goal Sampling for Dialog Policy Learning

Yin, K., & Wang, Z. (2021) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1757/1/012078 · Cited by 1

Phrase-Level Action Reinforcement Learning for Neural Dialog Response Generation

Yamazaki, T., & Aizawa, A. (2021) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2021.findings-acl.446 · Cited by 1

Overview of the NLPCC 2021 Shared Task: AutoIE2

Guo, W., Yang, X., Bai, X., Wu, T., Liu, W., Zhao, Z., Ju, Q., & Yang, Y. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-88483-3_42 · Cited by 1

Building Conversational Agents for Military Training: Towards a Virtual Wingman

van Oijen, J., & Claessen, O. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-77772-2_34 · Cited by 1

An Evaluation of Chinese Human-Computer Dialogue Technology

Feng, Z., Zhu, C., Zhang, W., Chen, Z., Che, W., Huang, M., & Li, L. (2021) · Data Intelligence · doi:10.1162/dint_a_00090 · Cited by 1

Process-Aware Dialogue System With Clinical Guideline Knowledge

Wang, M., Gao, F., & Gu, J. (2022) · International Journal of Web Services Research · doi:10.4018/ijwsr.304392 · Cited by 1

Exploratory Analysis of Usage Statistics of Dialogue Systems by Visualization

Seki, Y. (2022) · Information and Technology in Education and Learning · doi:10.12937/itel.2.1.dev.p001 · Cited by 1

Generic Concept for Integrating Voice Assistance Into Smart Therapeutic Interventions

Scheible, J., Hofmann, F., Reichert, M., Pryss, R. C., & Schickler, M. (2022) · Proceedings - IEEE Symposium on Computer-Based Medical Systems · doi:10.1109/cbms55023.2022.00017 · Cited by 1

Estimating the conceptual distance between unknown words using machine learning

Sakai, Y., & Matsumoto, M. (2022) · Joint International Conference on Soft Computing and Intelligent Systems and International Symposium on Advanced Intelligent Systems (SCIS&ISIS) · doi:10.1109/scisisis55246.2022.10002049 · Cited by 1

Chatbots and Health: General

Krahmer, E., Bosse, T., & de Bruijn, G. (2022) · Wiley eBooks · doi:10.1002/9781119678816.iehc0724 · Cited by 1

Bayesian Deep Multi-Agent Multimodal Reinforcement Learning for Embedded Systems in Games, Natural Language Processing and RoboticsPreprint

Kourouklides, I. (2022) · OSF Preprints (OSF Preprints) · doi:10.31219/osf.io/sjrkh_v1 · Cited by 1

Reinforcement learning for dialogue systems optimization with user adaptation

Carrara, N. (2019) · theses.fr (ABES) · doi:10.70675/84c4f883z5773z48d6zba77z4c53329fb3e4 · Cited by 1

A Survey of Agent Memory in the Second Half: Towards Self-Evolving and Long-Horizon Agents

Huang, W.-C., Zhang, W., Liang, Y., Bei, Y., Chen, Y., Feng, T., Pan, X., Tan, Z., Wang, Y., Wei, T., et al. (2026) · arXiv · doi:10.48550/arxiv.2602.06052 · Cited by 70

DLCEncDec : A Fully Character-Level Encoder-Decoder Model for Neural Responding Conversation

Wu, S., Li, Y., Zhang, X., & Wu, Z. (2018) · IEEE Annual International Computer Software and Applications Conference (COMPSAC) · doi:10.1109/compsac.2018.00079

Interpretation of Implicit Conditions in Database Search Dialogues

Fukunaga, S.-Y., Nishikawa, H., Tokunaga, T., Yokono, H., & Takahashi, T. (2019) · Journal of Natural Language Processing · doi:10.5715/jnlp.26.121

Multi-attending Memory Network for Modeling Multi-turn Dialogue

Ren, J., Li, Y., Zuo, C., Kong, W., & Ma, X. (2019) · High Performance Computing and Cluster Technologies Conference (HPCCT) · doi:10.1145/3341069.3342970

Towards Understanding Lifelong Learning for Dialogue Systems

Cieliebak, M., Galibert, O., & Deriu, J. (2021) · Lecture notes in electrical engineering · doi:10.1007/978-981-15-9323-9_33

Building End-to-End Task-oriented Dialogue Systems Via CNNs and Attention Mechanisms

Song, M., Chen, C., Niu, P., & Haihong, E. (2019) · International Conference on Electronics, Computers and Artificial Intelligence (ECAI) · doi:10.1109/ecai46879.2019.9041974

Expectation and Reaction as Intention for Conversation System

Zhang, Q. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-49062-1_19

MatDC: A Multi-turn Multi-domain Annotated Task-oriented Dialogue Dataset in Chinese

Tseng, Y.-H., Hsieh, S., Lian, R., Chiang, C.-Y., Chang, Y.-L., Chang, L.-P., & Hsieh, J.-L. (2020) · Conference on Technologies and Applications of Artificial Intelligence (TAAI) · doi:10.1109/taai51410.2020.00038

Generating Contextually Coherent Responses by Learning Structured Vectorized Semantics

Wang, Y., Zheng, Y., Jiang, S.-M., Dong, Y., Chen, J., & Wang, S. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-73197-7_5

Multi Path Training Framework for Data-Driven Open-Domain Conversation System

Wu, S., Zhang, D., Li, Y., & Wu, Z. (2021) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp39728.2021.9414273

Zero-shot Question Generation: Accelerate the Development of Domain-specific Dialogue System

Zhang, L., Ma, M., & Wang, P. (2021) · IEEE International Conference on Big Data Security on Cloud, IEEE International Conference on High Performance and Smart Computing, and IEEE International Conference on Intelligent Data and Security (BigDataSecurity/HPSC/IDS) · doi:10.1109/bigdatasecurityhpscids52275.2021.00032

Evaluation of Wizard-of-Oz and Self-Play Data Collection Techniques for Turkish Goal-Oriented Dialogue Agents

Arslan, D., & Eryiğit, G. (2021) · International Conference on Innovations in Intelligent Systems and Applications (INISTA) · doi:10.1109/inista52262.2021.9548636

Exploiting Explicit and Inferred Implicit Personas for Multi-turn Dialogue Generation

Wang, R., He, R., Wang, L., Si, Y., Liu, H., Wang, H., & Dang, J. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-88480-2_39

Text Generation in Dialogue System via Deep Neural Network

Shi, X., Sun, Y., Ding, Y., Han, D., & Li, J. (2021) · Journal of Physics Conference Series · doi:10.1088/1742-6596/2037/1/012047

A Tree-Based Approach for Building Efficient Task-Oriented Dialogue Systems

Gan, T., Li, C., Xi, Y., & He, Y. (2021) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-030-90196-7_45

Improved non-autoregressive dialog state tracking model

Li, B., Zhan, Y., Wei, Z., Huang, S. Z., & Sun, L. (2021) · International Conference on Control, Robotics and Intelligent System (CCRIS) · doi:10.1145/3483845.3483880

Intra-and-inter Sentence Attention Model for Enhanced Question Answering System

Liu, Y., & Hao, B. (2021) · International Conference on Intelligent Computing, Automation and Applications (ICAA) · doi:10.1109/icaa53760.2021.00029

AidIR: An Interactive Dialog System to Aid Disease Information Retrieval

Wang, D.-J., Chen, T.-Y., & Su, C. (2022) · Applied Sciences · doi:10.3390/app12041875

Intents4Bot - A Flexible Architecture to Capture User Intentions from Dialogue Systems

Silva, F. M., Franca, W. P. D., Palmeira, S. C., Bezerra, C. Q., Neto, G. M., Soares, T. S., Neto, A. P. A., Lins, D. A. S., Albuquerque, D. W., & Santos, D. F. S. (2022) · International Conference on Consumer Electronics · doi:10.1109/icce53296.2022.9730300

Leveraging knowledge graph embedding for effective conversational recommendation

Xia, Y. (2022) · doi:10.32657/10356/155658

UM AGENTE CONVERSACIONAL PERGUNTA-RESPOSTA COM RECOMENDAÇÕES BASEADAS EM UMA ONTOLOGIA DE DOMÍNIO

CARDOSO, J. P. S. (2020) · doi:10.17771/pucrio.acad.50180

An Ontology-Based Task-Oriented Dialogue to Create OutSystems Applications

Silva, J. Q., Melo, D., Rodrigues, I. P., Seco, J. C., Ferreira, C., & Parreira, J. (2022) · SN Computer Science · doi:10.1007/s42979-022-01418-0

Summarizing Developer Chat Conversations

Kumar, L. P. (2022) · doi:10.22215/etd/2022-15247

Response Sentence Modification Using a Sentence Vector for a Flexible Response Generation of Retrieval-based Dialogue Systems

Yahagi, R., Ito, A., Nose, T., & Chiba, Y. (2022) · Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) · doi:10.23919/apsipaasc55919.2022.9979841

Towards Sentiment and Emotion aided Intent Detection

Trivedi, A. K., Tiwari, A. S., Saha, S., Maitra, A., Ramnani, R., & Sengupta, S. (2022) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr56361.2022.9956278

Conversational Pattern Mining Using Motif Detection

Garber, N., & Marivate, V. N. (2023) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-031-25271-6_22

A Commonsense-Enhanced Document-Grounded Conversational Agent: A Case Study on Task-Based Dialogue

Strathearn, C., & Gkatzia, D. (2022) · Signals and communication technology · doi:10.1007/978-3-031-11035-1_6 · Cited by 1

ALGOBOT – MỘT HỆ THỐNG CHATBOT HỖ TRỢ GIẢI ĐÁP CÁC KIẾN THỨC CƠ BẢN VỀ CẤU TRÚC DỮ LIỆU VÀ GIẢI THUẬT

Nguyên, N. Đ. T. (2023) · Tạp chí Khoa học · doi:10.54607/hcmue.js.20.2.3613(2023

Dialogue System to Make Humor by Tatoe-Tsukkomi

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심층학습을 이용한 대화시스템의 연구방법 분석

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