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07/08/2023
Answering Ambiguous Questions via Iterative Prompting
In open-domain question answering, due to the ambiguity of questions, mu...
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06/07/2023
Embracing Uncertainty: Adaptive Vague Preference Policy Learning for Multi-round Conversational Recommendation
Conversational recommendation systems (CRS) effectively address informat...
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10/22/2021
Adaptive Bridge between Training and Inference for Dialogue
Although exposure bias has been widely studied in some NLP tasks, it fac...
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09/22/2021
FCM: A Fine-grained Comparison Model for Multi-turn Dialogue Reasoning
Despite the success of neural dialogue systems in achieving high perform...
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09/14/2021
Identifying Untrustworthy Samples: Data Filtering for Open-domain Dialogues with Bayesian Optimization
Being able to reply with a related, fluent, and informative response is ...
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09/10/2021
Topic-Aware Contrastive Learning for Abstractive Dialogue Summarization
Unlike well-structured text, such as news reports and encyclopedia artic...
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06/26/2021
Improving Sequential Recommendation Consistency with Self-Supervised Imitation
Most sequential recommendation models capture the features of consecutiv...
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03/02/2021
Probing Product Description Generation via Posterior Distillation
In product description generation (PDG), the user-cared aspect is critic...
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02/16/2021
User-Inspired Posterior Network for Recommendation Reason Generation
Recommendation reason generation, aiming at showing the selling points o...
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10/05/2020
Regularizing Dialogue Generation by Imitating Implicit Scenarios
Human dialogues are scenario-based and appropriate responses generally r...
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09/27/2020
Modeling Topical Relevance for Multi-Turn Dialogue Generation
Topic drift is a common phenomenon in multi-turn dialogue. Therefore, an...
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09/16/2020
Collaborative Group Learning
Collaborative learning has successfully applied knowledge transfer to gu...
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09/16/2020
Group-wise Contrastive Learning for Neural Dialogue Generation
Neural dialogue response generation has gained much popularity in recent...
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04/06/2020
Data Manipulation: Towards Effective Instance Learning for Neural Dialogue Generation via Learning to Augment and Reweight
Current state-of-the-art neural dialogue models learn from human convers...
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03/04/2020
Posterior-GAN: Towards Informative and Coherent Response Generation with Posterior Generative Adversarial Network
Neural conversational models learn to generate responses by taking into ...
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03/02/2020
Learning from Easy to Complex: Adaptive Multi-curricula Learning for Neural Dialogue Generation
Current state-of-the-art neural dialogue systems are mainly data-driven ...
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01/18/2020
Adaptive Parameterization for Neural Dialogue Generation
Neural conversation systems generate responses based on the sequence-to-...
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11/20/2019
EmpGAN: Multi-resolution Interactive Empathetic Dialogue Generation
Conventional emotional dialogue system focuses on generating emotion-ric...
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08/31/2018
Explicit State Tracking with Semi-Supervision for Neural Dialogue Generation
The task of dialogue generation aims to automatically provide responses ...
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11/06/2017
