research
∙
08/29/2023
SpikeBERT: A Language Spikformer Trained with Two-Stage Knowledge Distillation from BERT
Spiking neural networks (SNNs) offer a promising avenue to implement dee...
share
research
∙
07/20/2023
Spinal nerve segmentation method and dataset construction in endoscopic surgical scenarios
Endoscopic surgery is currently an important treatment method in the fie...
research
∙
10/14/2022
Watermarking Pre-trained Language Models with Backdooring
Large pre-trained language models (PLMs) have proven to be a crucial com...
research
∙
06/11/2022
Improving the Adversarial Robustness of NLP Models by Information Bottleneck
Existing studies have demonstrated that adversarial examples can be dire...
research
∙
08/29/2021
Searching for an Effective Defender: Benchmarking Defense against Adversarial Word Substitution
Recent studies have shown that deep neural networks are vulnerable to in...
research
∙
05/31/2021
Exploration and Exploitation: Two Ways to Improve Chinese Spelling Correction Models
A sequence-to-sequence learning with neural networks has empirically pro...
research
∙
05/08/2021
Certified Robustness to Text Adversarial Attacks by Randomized [MASK]
Recently, few certified defense methods have been developed to provably ...
research
∙
03/22/2021
Alleviate Exposure Bias in Sequence Prediction with Recurrent Neural Networks
A popular strategy to train recurrent neural networks (RNNs), known as “...
research
∙
03/22/2021
SparseGAN: Sparse Generative Adversarial Network for Text Generation
It is still a challenging task to learn a neural text generation model u...
research
∙
03/21/2021
TextFlint: Unified Multilingual Robustness Evaluation Toolkit for Natural Language Processing
Various robustness evaluation methodologies from different perspectives ...
research
∙
03/02/2021
Unsupervised Word Segmentation with Bi-directional Neural Language Model
We present an unsupervised word segmentation model, in which the learnin...
research
∙
11/17/2020
Generating universal language adversarial examples by understanding and enhancing the transferability across neural models
Deep neural network models are vulnerable to adversarial attacks. In man...
research
∙
09/16/2020
Unsupervised Summarization by Jointly Extracting Sentences and Keywords
We present RepRank, an unsupervised graph-based ranking model for extrac...
research
∙
09/10/2020
Improving Coreference Resolution by Leveraging Entity-Centric Features with Graph Neural Networks and Second-order Inference
One of the major challenges in coreference resolution is how to make use...
research
∙
06/20/2020
Defense against Adversarial Attacks in NLP via Dirichlet Neighborhood Ensemble
Despite neural networks have achieved prominent performance on many natu...
research
∙
04/15/2020
Learning Structured Embeddings of Knowledge Graphs with Adversarial Learning Framework
Many large-scale knowledge graphs are now available and ready to provide...
research
∙
12/17/2019
