Daniel Ortega, Dirk Väth, Gianna Weber, Lindsey Vanderlyn, Maximilian Schmidt, Moritz Völkel, Zorica Karacevic, Ngoc Thang Vu
| Challenge: | In this paper, we focus on task-oriented dialog systems, although our framework allows easy integration of non-task dialog systems and their combination. |
| Approach: | They propose an open source dialog system framework for education and research that supports multi-domain task-oriented conversations in two languages. |
| Outcome: | The proposed framework supports multi-domain task-oriented conversations in two languages and is open source for education and research. |
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Chia-Yu Li, Daniel Ortega, Dirk Väth, Florian Lux, Lindsey Vanderlyn, Maximilian Schmidt, Michael Neumann, Moritz Völkel, Pavel Denisov, Sabrina Jenne, Zorica Kacarevic, Ngoc Thang Vu
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| Challenge: | Dialog systems have gained attention as a convenient way for users to access information in a more personalized manner. |
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Shazia Afzal, Tejas Dhamecha, Nirmal Mukhi, Renuka Sindhgatta, Smit Marvaniya, Matthew Ventura, Jessica Yarbro
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End-to-End Learning of Task-Oriented Dialogs (N18-4)
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| Challenge: | Dissertation addresses the limitations of conventional task-oriented dialog systems . conventions of such systems include a complex pipeline and dialog state tracking . |
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| Challenge: | a prerequisite for the creation of a goal-oriented neural network dialogue system is a dataset that represents typical dialogue scenarios and includes various semantic annotations. |
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Are the Tools up to the Task? an Evaluation of Commercial Dialog Tools in Developing Conversational Enterprise-grade Dialog Systems (N19-2)
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| Challenge: | Existing toolsets are incomplete in meeting the goal of building effective dialog systems, authors say . |
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| Challenge: | Currently, most reinforcement learning methods for dialog policy learning train a centralized agent that selects a predefined joint action concatenating domain name, intent type, and slot name. |
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| Challenge: | Existing dialogue models may encounter scenarios which are not well-represented in the training data and produce unnatural, inappropriate, or unhelpful responses. |
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Conversation Learner - A Machine Teaching Tool for Building Dialog Managers for Task-Oriented Dialog Systems (2020.acl-demos)
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Swadheen Shukla, Lars Liden, Shahin Shayandeh, Eslam Kamal, Jinchao Li, Matt Mazzola, Thomas Park, Baolin Peng, Jianfeng Gao
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One Planner To Guide Them All ! Learning Adaptive Conversational Planners for Goal-oriented Dialogues (2025.emnlp-main)
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| Challenge: | Existing methods for goal-oriented dialogues involve training separate models for specific combinations of objectives, leading to computational and scalability issues. |
| Approach: | They propose a new dialogue policy method that can adapt to varying objective preferences at inference time without retraining. |
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