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Latest papers without code

"TL;DR:" Out-of-Context Adversarial Text Summarization and Hashtag Recommendation

1 Apr 2021

This paper presents Out-of-Context Summarizer, a tool that takes arbitrary public news articles out of context by summarizing them to coherently fit either a liberal- or conservative-leaning agenda.

ADVERSARIAL TEXT TEXT GENERATION TEXT SUMMARIZATION

Adversarial Text-to-Image Synthesis: A Review

25 Jan 2021

With the advent of generative adversarial networks, synthesizing images from textual descriptions has recently become an active research area.

ADVERSARIAL TEXT CONDITIONAL IMAGE GENERATION

Persistent Anti-Muslim Bias in Large Language Models

14 Jan 2021

It has been observed that large-scale language models capture undesirable societal biases, e. g. relating to race and gender; yet religious bias has been relatively unexplored.

ADVERSARIAL TEXT LANGUAGE MODELLING

From Unsupervised Machine Translation To Adversarial Text Generation

10 Nov 2020

B-GAN is able to generate a distributed latent space representation which can be paired with an attention based decoder to generate fluent sentences.

ADVERSARIAL TEXT TEXT GENERATION UNSUPERVISED MACHINE TRANSLATION

CAT-Gen: Improving Robustness in NLP Models via Controlled Adversarial Text Generation

EMNLP 2020

Experiments on real-world NLP datasets demonstrate that our method can generate more diverse and fluent adversarial texts, compared to many existing adversarial text generation approaches.

ADVERSARIAL TEXT SENTIMENT ANALYSIS TEXT GENERATION

What Machines See Is Not What They Get: Fooling Scene Text Recognition Models With Adversarial Text Images

CVPR 2020

Specifically, we propose a novel and efficient optimization-based method that can be naturally integrated to different sequential prediction schemes, i. e., connectionist temporal classification (CTC) and attention mechanism.

ADVERSARIAL ATTACK ADVERSARIAL TEXT CLASSIFICATION OPTICAL CHARACTER RECOGNITION SCENE TEXT SCENE TEXT RECOGNITION

Improving Adversarial Text Generation by Modeling the Distant Future

ACL 2020

Auto-regressive text generation models usually focus on local fluency, and may cause inconsistent semantic meaning in long text generation.

ADVERSARIAL TEXT IMITATION LEARNING TEXT GENERATION

Meta-CoTGAN: A Meta Cooperative Training Paradigm for Improving Adversarial Text Generation

12 Mar 2020

To this end, we introduce a cooperative training paradigm, where a language model is cooperatively trained with the generator and we utilize the language model to efficiently shape the data distribution of the generator against mode collapse.

ADVERSARIAL TEXT LANGUAGE MODELLING META-LEARNING TEXT GENERATION

Generating Natural Language Adversarial Examples on a Large Scale with Generative Models

10 Mar 2020

It can attack text classification models with a higher success rate than existing methods, and provide acceptable quality for humans in the meantime.

ADVERSARIAL TEXT CLASSIFICATION SENTIMENT ANALYSIS TEXT CLASSIFICATION TEXT GENERATION

Playing to Learn Better: Repeated Games for Adversarial Learning with Multiple Classifiers

10 Feb 2020

The objective of the adversary is to evade the learner's prediction mechanism by sending adversarial queries that result in erroneous class prediction by the learner, while the learner's objective is to reduce the incorrect prediction of these adversarial queries without degrading the prediction quality of clean queries.

ADVERSARIAL TEXT