반응형 자연어처리572 [2023-02-26] 오늘의 자연어처리 Coarse-to-Fine Knowledge Selection for Document Grounded Dialogs Multi-document grounded dialogue systems (DGDS) belong to a class of conversational agents that answer users' requests by finding supporting knowledge from a collection of documents. Most previous studies aim to improve the knowledge retrieval model or propose more effective ways to incorporate external knowledge into a parametric .. 2023. 2. 26. [2023-02-25] 오늘의 자연어처리 Empathetic Response Generation via Emotion Cause Transition Graph Empathetic dialogue is a human-like behavior that requires the perception of both affective factors (e.g., emotion status) and cognitive factors (e.g., cause of the emotion). Besides concerning emotion status in early work, the latest approaches study emotion causes in empathetic dialogue. These approaches focus on understanding a.. 2023. 2. 25. [2023-02-24] 오늘의 자연어처리 Open-domain Visual Entity Recognition: Towards Recognizing Millions of Wikipedia Entities Large-scale multi-modal pre-training models such as CLIP and PaLI exhibit strong generalization on various visual domains and tasks. However, existing image classification benchmarks often evaluate recognition on a specific domain (e.g., outdoor images) or a specific task (e.g., classifying plant species), .. 2023. 2. 24. [2023-02-23] 오늘의 자연어처리 UML: A Universal Monolingual Output Layer for Multilingual ASR Word-piece models (WPMs) are commonly used subword units in state-of-the-art end-to-end automatic speech recognition (ASR) systems. For multilingual ASR, due to the differences in written scripts across languages, multilingual WPMs bring the challenges of having overly large output layers and scaling to more languages. In this work, .. 2023. 2. 23. 이전 1 ··· 81 82 83 84 85 86 87 ··· 143 다음 반응형