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ProtoInfoMax: Prototypical Networks with Mutual Information Maximization for Out-of-Domain Detection ...
Abstract: The ability to detect Out-of-Domain (OOD) inputs has been a critical requirement in many real-world NLP applications. For example, intent classification in dialogue systems. The reason is that the inclusion of unsupported OOD inputs may lead to catastrophic failure of systems. However, it remains an empirical question whether current methods can tackle such problems reliably in a realistic scenario where zero OOD training data is available. In this study, we propose ProtoInfoMax, a new architecture that extends Prototypical Networks to simultaneously process in-domain and OOD sentences via Mutual Information Maximization (InfoMax) objective. Experimental results show that our proposed method can substantially improve performance up to 20% for OOD detection in low resource settings of text classification. We also show that ProtoInfoMax is less prone to typical overconfidence errors of Neural Networks, leading to more reliable prediction results. ...
Keyword: Computational Linguistics; Conversational Agent; Machine Learning; Machine Learning and Data Mining; Natural Language Processing
URL: https://dx.doi.org/10.48448/z3pv-mw84
https://underline.io/lecture/39958-protoinfomax-prototypical-networks-with-mutual-information-maximization-for-out-of-domain-detection
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2
Towards the Early Detection of Child Predators in Chat Rooms: A BERT-based Approach ...
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3
Discourse-Driven Integrated Dialogue Development Environment for Open-Domain Dialogue Systems ...
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Distilling the Knowledge of Large-scale Generative Models into Retrieval Models for Efficient Open-domain Conversation ...
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5
Improving Dialogue State Tracking with Turn-based Loss Function and Sequential Data Augmentation ...
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Towards Realistic Single-Task Continuous Learning Research for NER ...
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Automated Template Paraphrasing for Conversational Assistants ...
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Elementary-Level Math Word Problem Generation using Pre-Trained Transformers ...
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MURAL: Multimodal, Multitask Representations Across Languages ...
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Challenges in Detoxifying Language Models ...
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Contextualize Knowledge Bases with Transformer for End-to-end Task-Oriented Dialogue Systems ...
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ConvAbuse: Data, Analysis, and Benchmarks for Nuanced Detection in Conversational AI ...
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An animated picture says at least a thousand words: Selecting Gif-based Replies in Multimodal Dialog ...
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SideControl: Controlled Open-domain Dialogue Generation via Additive Side Networks ...
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A Label-Aware BERT Attention Network for Zero-Shot Multi-Intent Detection in Spoken Language Understanding ...
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Coral: An Approach for Conversational Agents in Mental Health Applications ...
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MeLT: Message-Level Transformer with Masked Document Representations as Pre-Training for Stance Detection ...
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Iconary: A Pictionary-Based Game for Testing Multimodal Communication with Drawings and Text ...
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Mapping Language to Programs using Multiple Reward Components with Inverse Reinforcement Learning ...
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"I don't know who she is": Discourse and Knowledge Driven Coreference Resolution ...
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