Paper-Conference

CorefDiffs: Co-referential and Differential Knowledge Flow in Document Grounded Conversations
Knowledge-grounded dialog systems need to incorporate smooth transitions among knowledge selected for generating responses, to ensure …
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Lightweight Contextual Logical Structure Recovery
Logical structure recovery in scientific articles associates text with a semantic section of the article. Although previous work has …
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Comparative Snippet Generation
We model products′ reviews to generate comparative responses consisting of positive and negative experiences regarding the product. …
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GL-CLeF: A Global--Local Contrastive Learning Framework for Cross-lingual Spoken Language Understanding
Due to high data demands of current methods, attention to zero-shot cross-lingual spoken language understanding (SLU) has grown, as …
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Interpreting the Robustness of Neural NLP Models to Textual Perturbations
Modern Natural Language Processing (NLP) models are known to be sensitive to input perturbations and their performance can decrease …
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N-Shot Learning for Augmenting Task-Oriented Dialogue State Tracking
Augmentation of task-oriented dialogues has followed standard methods used for plain-text such as back-translation, word-level …
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So Different Yet So Alike! Constrained Unsupervised Text Style Transfer
Automatic transfer of text between domains has become popular in recent times. One of its aims is to preserve the semantic content …
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Reliability Testing for Natural Language Processing Systems
Questions of fairness, robustness, and transparency are paramount to address before deploying NLP systems. Central to these concerns is …
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Zero-shot Fact Verification by Claim Generation
Neural models for automated fact verification have achieved promising results thanks to the availability of large, human-annotated …
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Velocidapter: Task-oriented Dialogue Comprehension Modeling Pairing Synthetic Text Generation with Domain Adaptation
We introduce a synthetic dialogue generation framework, Velocidapter, which addresses the corpus availability problem for dialogue …
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