[PDF][PDF] A Survey on Response Selection for Retrieval-based Dialogues.
Building an intelligent dialogue system capable of naturally and coherently conversing with
humans has been a long-standing goal of artificial intelligence. In the past decade, with the …
humans has been a long-standing goal of artificial intelligence. In the past decade, with the …
Deep learning for code generation: a survey
In the past decade, thanks to the powerfulness of deep-learning techniques, we have
witnessed a whole new era of automated code generation. To sort out developments, we …
witnessed a whole new era of automated code generation. To sort out developments, we …
Evaluating and Enhancing the Robustness of Sustainable Neural Relationship Classifiers Using Query-Efficient Black-Box Adversarial Attacks
Neural relation extraction (NRE) models are the backbone of various machine learning
tasks, including knowledge base enrichment, information extraction, and document …
tasks, including knowledge base enrichment, information extraction, and document …
Audio steganography with speech recognition system
H Tan, C Liu, Y Lyu, X Zhang… - 2021 IEEE Sixth …, 2021 - ieeexplore.ieee.org
Deep neural networks (DNNs) are vulnerable to adversarial examples that are intentionally
crafted by adding small perturbations to the original input. Most works focus on generating …
crafted by adding small perturbations to the original input. Most works focus on generating …
Generating Adversarial Texts by the Universal Tail Word Addition Attack
Deep neural networks (DNNs) are vulnerable to adversarial examples, which can mislead
models without affecting normal judgment of humans. In the image field, such adversarial …
models without affecting normal judgment of humans. In the image field, such adversarial …
Misleading Sentiment Analysis: Generating Adversarial Texts by the Ensemble Word Addition Algorithm
Deep neural networks are vulnerable to the adversarial examples that are generated by
adding small perturbations to the original inputs. Similarly, traditional machine learning …
adding small perturbations to the original inputs. Similarly, traditional machine learning …