research
∙
09/12/2023
Minimum Bayes' Risk Decoding for System Combination of Grammatical Error Correction Systems
For sequence-to-sequence tasks it is challenging to combine individual s...
share
research
∙
06/21/2023
Sample Attackability in Natural Language Adversarial Attacks
Adversarial attack research in natural language processing (NLP) has mad...
research
∙
06/08/2023
CUED at ProbSum 2023: Hierarchical Ensemble of Summarization Models
In this paper, we consider the challenge of summarizing patients' medica...
research
∙
05/02/2023
Sentiment Perception Adversarial Attacks on Neural Machine Translation Systems
With the advent of deep learning methods, Neural Machine Translation (NM...
research
∙
03/10/2023
Rewarding Chatbots for Real-World Engagement with Millions of Users
The emergence of pretrained large language models has led to the deploym...
research
∙
01/30/2023
Identifying Adversarially Attackable and Robust Samples
This work proposes a novel perspective on adversarial attacks by introdu...
research
∙
11/16/2022
L2 proficiency assessment using self-supervised speech representations
There has been a growing demand for automated spoken language assessment...
research
∙
08/19/2022
Gender Bias and Universal Substitution Adversarial Attacks on Grammatical Error Correction Systems for Automated Assessment
Grammatical Error Correction (GEC) systems perform a sequence-to-sequenc...
research
∙
04/17/2022
Residue-Based Natural Language Adversarial Attack Detection
Deep learning based systems are susceptible to adversarial attacks, wher...
research
∙
07/15/2021