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Found 5 papers, 4 papers with code
Jointly Encoding Word Confusion Network and Dialogue Context with BERT for Spoken Language Understanding
In this paper, a novel BERT based SLU model (WCN-BERT SLU) is proposed to encode WCNs and the dialogue context jointly.
Prior Knowledge Driven Label Embedding for Slot Filling in Natural Language Understanding
The proposed approaches are evaluated on three datasets.
Data Augmentation with Atomic Templates for Spoken Language Understanding
The atomic templates produce exemplars for fine-grained constituents of semantic representations.
A Hierarchical Decoding Model For Spoken Language Understanding From Unaligned Data
In the paper, we focus on spoken language understanding from unaligned data whose annotation is a set of act-slot-value triples.
CrowdHuman: A Benchmark for Detecting Human in a Crowd
There are a total of $470K$ human instances from the train and validation subsets, and $~22. 6$ persons per image, with various kinds of occlusions in the dataset.
Ranked #7 on
Pedestrian Detection
on Caltech
(using extra training data)
