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87 papers · 1 filter
Likelihood Ratios and Generative Classifiers for Unsupervised Out-of-Domain Detection In Task Oriented Dialog
Varun Gangal, Abhinav Arora, Arash Einolghozati +1
The task of identifying out-of-domain (OOD) input examples directly at test-time has seen renewed interest recently due to increased real world deployment of models. In this work,…
From Patches to Pictures (PaQ-2-PiQ): Mapping the Perceptual Space of Picture Quality
Zhenqiang Ying, Haoran Niu, Praful Gupta +3
Blind or no-reference (NR) perceptual picture quality prediction is a difficult, unsolved problem of great consequence to the social and streaming media industries that impacts bil…
Pretrained Encyclopedia: Weakly Supervised Knowledge-Pretrained Language Model
Wenhan Xiong, Jingfei Du, William Yang Wang +1
Recent breakthroughs of pretrained language models have shown the effectiveness of self-supervised learning for a wide range of natural language processing (NLP) tasks. In addition…
ClusterFit: Improving Generalization of Visual Representations
Xueting Yan, Ishan Misra, Abhinav Gupta +2
Pre-training convolutional neural networks with weakly-supervised and self-supervised strategies is becoming increasingly popular for several computer vision tasks. However, due to…
Generating Interactive Worlds with Text
Angela Fan, Jack Urbanek, Pratik Ringshia +8
Procedurally generating cohesive and interesting game environments is challenging and time-consuming. In order for the relationships between the game elements to be natural, common…
Deep Learning for Symbolic Mathematics
Guillaume Lample, François Charton
Neural networks have a reputation for being better at solving statistical or approximate problems than at performing calculations or working with symbolic data. In this paper, we s…