research
∙
08/17/2023
Is Argument Structure of Learner Chinese Understandable: A Corpus-Based Analysis
This paper presents a corpus-based analysis of argument structure errors...
share
research
∙
01/26/2023
Neural-Symbolic Inference for Robust Autoregressive Graph Parsing via Compositional Uncertainty Quantification
Pre-trained seq2seq models excel at graph semantic parsing with rich ann...
research
∙
05/01/2022
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness
Accurate uncertainty quantification is a major challenge in deep learnin...
research
∙
07/09/2021
Measuring and Improving Model-Moderator Collaboration using Uncertainty Estimation
Content moderation is often performed by a collaboration between humans ...
research
∙
12/10/2020
Large-Scale Generative Data-Free Distillation
Knowledge distillation is one of the most popular and effective techniqu...
research
∙
10/05/2020
Pruning Redundant Mappings in Transformer Models via Spectral-Normalized Identity Prior
Traditional (unstructured) pruning methods for a Transformer model focus...
research
∙
06/17/2020
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness
Bayesian neural networks (BNN) and deep ensembles are principled approac...
research
∙
10/25/2019
Fast Structured Decoding for Sequence Models
Autoregressive sequence models achieve state-of-the-art performance in d...
research
∙
09/15/2019
Hint-Based Training for Non-Autoregressive Machine Translation
Due to the unparallelizable nature of the autoregressive factorization, ...
research
∙
07/04/2019
A Comparative Analysis of Knowledge-Intensive and Data-Intensive Semantic Parsers
We present a phenomenon-oriented comparative analysis of the two dominan...
research
∙
11/26/2018
Implanting Rational Knowledge into Distributed Representation at Morpheme Level
Previously, researchers paid no attention to the creation of unambiguous...
research
∙
08/28/2018