Search Results for author:
Found 10 papers, 0 papers with code
Weakly Supervised Referring Image Segmentation with Intra-Chunk and Inter-Chunk Consistency
Referring image segmentation (RIS) aims to localize the object in an image referred by a natural language expression.
Scalable and Robust Self-Learning for Skill Routing in Large-Scale Conversational AI Systems
Skill routing is an important component in large-scale conversational systems.
Neural model robustness for skill routing in large-scale conversational AI systems: A design choice exploration
Ensuring model robustness or resilience in the skill routing component is an important problem since skills may dynamically change their subscription in the ontology after the skill routing model has been deployed to production.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Maximizing Subset Accuracy with Recurrent Neural Networks in Multi-label Classification
Multi-label classification is the task of predicting a set of labels for a given input instance.
What Makes Word-level Neural Machine Translation Hard: A Case Study on English-German Translation
Traditional machine translation systems often require heavy feature engineering and the combination of multiple techniques for solving different subproblems.
Medical Concept Embeddings via Labeled Background Corpora
In recent years, we have seen an increasing amount of interest in low-dimensional vector representations of words.
On Learning Vector Representations in Hierarchical Label Spaces
We present a novel method to learn vector representations of a label space given a hierarchy of labels and label co-occurrence patterns.
Large-scale Multi-label Text Classification - Revisiting Neural Networks
Neural networks have recently been proposed for multi-label classification because they are able to capture and model label dependencies in the output layer.
