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168,738 papers · 148 categories

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97195292389 · Jun 202019922001200920172026
48 results for fake features

Improves estimation under model misspecification with fake features.

problem Model misspecification with fake features.
method Proposes a framework to decompose output error into underlying, fake, and missing features.
result Fake features can significantly improve estimation performance, even when not correlated with underlying features.

In this paper we show strategies to easily identify fake samples generated with the Generative Adversarial Network framework. One strategy is based on the statistical analysis and comparison of raw pixel values and features extracted from them. The other strategy learns formal specifications from the real data and show…

2018-07-13abs ↗pdf ↗

In this work, we study abstractive text summarization by exploring different models such as LSTM-encoder-decoder with attention, pointer-generator networks, coverage mechanisms, and transformers. Upon extensive and careful hyperparameter tuning we compare the proposed architectures against each other for the abstractiv…

2019-03-24abs ↗pdf ↗

Social media are nowadays one of the main news sources for millions of people around the globe due to their low cost, easy access and rapid dissemination. This however comes at the cost of dubious trustworthiness and significant risk of exposure to 'fake news', intentionally written to mislead the readers. Automaticall…

2019-02-10abs ↗pdf ↗

Generative Adversarial Networks (GANs) were intuitively and attractively explained under the perspective of game theory, wherein two involving parties are a discriminator and a generator. In this game, the task of the discriminator is to discriminate the real and generated (i.e., fake) data, whilst the task of the gene…

2017-11-06abs ↗pdf ↗

Fake engagement is one of the significant problems in Online Social Networks (OSNs) which is used to increase the popularity of an account in an inorganic manner. The detection of fake engagement is crucial because it leads to loss of money for businesses, wrong audience targeting in advertising, wrong product predicti…

2019-09-13abs ↗pdf ↗

MALCOM generates fake comments to fool fake news detectors.

problem Adversaries can manipulate fake news detection models with malicious comments.
method Proposes a novel threat model and develops an adversarial comment generation framework (MALCOM).
result MALCOM can fool fake news detectors 90-94% of the time, depending on the model and dataset.

A fake quadric is a smooth projective surface that has the same rational cohomology as a smooth quadric surface but is not biholomorphic to one. We provide an explicit classification of all irreducible fake quadrics according to the commensurability class of their fundamental group. To accomplish this task, we develop …

2015-04-17abs ↗pdf ↗

RealStats detects fake images rigorously, combining multiple detectors for robustness.

problem Detecting AI-generated images remains challenging due to evolving generative models.
method Combines training-free statistics to compute p-values and aggregate them for a unified real-image distribution.
result Framework produces interpretable probability scores for robust fake image detection.

We study quotients Γ\HnΓ\backslash \mathbb H^n of the nn-fold product of the upper half plane H\mathbb H by irreducible and torsion-free lattices Γ<PSL2(R)nΓ< PSL_2(\mathbb R)^n with the same Betti numbers as the nn-fold product (P1)n(\mathbb P^1)^n of projective lines. Such varieties are called fake products of projective lines…

2014-11-12abs ↗pdf ↗

Framework detects fake news using weak social signals from multiple sources.

problem Lack of annotated data for early fake news detection.
method Jointly uses weak social signals and clean data to train deep neural networks in a meta-learning framework.
result Framework outperforms state-of-the-art baselines for early fake news detection.

Deep generative models have recently achieved impressive results for many real-world applications, successfully generating high-resolution and diverse samples from complex datasets. Due to this improvement, fake digital contents have proliferated growing concern and spreading distrust in image content, leading to an ur…

2019-11-02abs ↗pdf ↗

While the purpose of most fake news is misinformation and political propaganda, our team sees it as a new type of myth that is created by people in the age of internet identities and artificial intelligence. Seeking insights on the fear and desire hidden underneath these modified or generated stories, we use machine le…

2019-08-05abs ↗pdf ↗

We give a criterion for a projective surface to become a quotient of a fake projective plane. We also give a detailed information on the elliptic fibration of a (2,3)(2,3)-elliptic surface that is the minimal resolution of a quotient of a fake projective plane. As a consequence, we give a classification of Q{\mathbb Q}-h…

2010-10-02abs ↗pdf ↗

A fake wedge is a diagram of spaces K <- A -> C whose double mapping cylinder is contractible. The terminology stems from the special case A = K v C with maps given by the projections. In this paper, we study the homotopy type of the moduli space D(K,C) of fake wedges on K and C. We formulate two conjectures concerning…

2012-08-10abs ↗pdf ↗

Can machine learning models for recommendation be easily fooled? While the question has been answered for hand-engineered fake user profiles, it has not been explored for machine learned adversarial attacks. This paper attempts to close this gap. We propose a framework for generating fake user profiles which, when inco…

2018-09-21abs ↗pdf ↗

This article presents a preliminary approach towards characterizing political fake news on Twitter through the analysis of their meta-data. In particular, we focus on more than 1.5M tweets collected on the day of the election of Donald Trump as 45th president of the United States of America. We use the meta-data embedd…

2017-12-16abs ↗pdf ↗

Recently the GAN generated face images are more and more realistic with high-quality, even hard for human eyes to detect. On the other hand, the forensics community keeps on developing methods to detect these generated fake images and try to guarantee the credibility of visual contents. Although researchers have develo…

2019-02-27abs ↗pdf ↗