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Bridging the Gap between Prior and Posterior Knowledge Selection for Knowledge-Grounded Dialogue Generation
AbstractKnowledge selection plays an important role in knowledge-grounded dialogue, which is a challenging task to generate more informative responses by leveraging external knowledge. Recently, latent variable models have been proposed …...
The Dialogue Dodecathlon: Open-Domain Knowledge and Image Grounded Conversational Agents
AbstractWe introduce dodecaDialogue: a set of 12 tasks that measures if a conversational agent can communicate engagingly with personality and empathy, ask questions, answer questions by utilizing knowledge resources, discuss …...
Generating Relevant and Coherent Dialogue Responses using Self-Separated Conditional Variational AutoEncoders
AbstractConditional Variational AutoEncoder (CVAE) effectively increases the diversity and informativeness of responses in open-ended dialogue generation tasks through enriching the context vector with sampled latent variables. However, due to the …...
Counterfactual Data Augmentation via Perspective Transition for Open-Domain Dialogues
AbstractThe construction of open-domain dialogue systems requires high-quality dialogue datasets. The dialogue data admits a wide variety of responses for a given dialogue history, especially responses with different semantics. However, …...
Dial2vec: Self-Guided Contrastive Learning of Unsupervised Dialogue Embeddings
AbstractIn this paper, we introduce the task of learning unsupervised dialogue embeddings.Trivial approaches such as combining pre-trained word or sentence embeddings and encoding through pre-trained language models (PLMs) have been …...
DialAug: Mixing up Dialogue Contexts in Contrastive Learning for Robust Conversational Modeling
AbstractRetrieval-based conversational systems learn to rank response candidates for a given dialogue context by computing the similarity between their vector representations. However, training on a single textual form of the …...
Q-TOD: A Query-driven Task-oriented Dialogue System
AbstractExisting pipelined task-oriented dialogue systems usually have difficulties adapting to unseen domains, whereas end-to-end systems are plagued by large-scale knowledge bases in practice. In this paper, we introduce a novel …...
Modeling User Satisfaction Dynamics in Dialogue via Hawkes Process
AbstractDialogue systems have received increasing attention while automatically evaluating their performance remains challenging. User satisfaction estimation (USE) has been proposed as an alternative. It assumes that the performance of a …...