Evaluating adversarial attacks against multiple fact verification systems

© 2019 Association for Computational Linguistics Automated fact verification has been progressing owing to advancements in modeling and availability of large datasets. Due to the nature of the task, it is critical to understand the vulnerabilities of these systems against adversarial instances designed to make them predict incorrectly. We introduce two novel scoring metrics, attack potency and system resilience which take into account the correctness of the adversarial instances, an aspect often ignored in adversarial evaluations. We consider six fact verification systems from the recent Fact Extraction and VERification (FEVER) challenge: the four best-scoring ones and two baselines. We evaluate adversarial instances generated by a recently proposed state-of-the-art method, a paraphrasing method, and rule-based attacks devised for fact verification. We find that our rule-based attacks have higher potency, and that while the rankings among the top systems changed, they exhibited higher resilience than the baselines

FEVER: A large-scale dataset for fact extraction and verification

In this paper we introduce a new publicly available dataset for verification against textual sources, FEVER: Fact Extraction and VERification. It consists of 185,445 claims generated by altering sentences extracted from Wikipedia and subsequently verified without knowledge of the sentence they were derived from. The claims are classified as Supported, Refuted or NotEnoughInfo by annotators achieving 0.6841 in Fleiss $\kappa$. For the first two classes, the annotators also recorded the sentence(s) forming the necessary evidence for their judgment. To characterize the challenge of the dataset presented, we develop a pipeline approach and compare it to suitably designed oracles. The best accuracy we achieve on labeling a claim accompanied by the correct evidence is 31.87%, while if we ignore the evidence we achieve 50.91%. Thus we believe that FEVER is a challenging testbed that will help stimulate progress on claim verification against textual sources.Comment: Updated version of NAACL2018 paper. Data is released on http://fever.a

Analyzing the EGEE production grid workload: application to jobs submission optimization

International audienceGrids reliability remains an order of magnitude below clusters on production infrastructures. This work is aims at improving grid application performances by improving the job submission system. A stochastic model, capturing the behavior of a complex grid workload management system is proposed. To instantiate the model, detailed statistics are extracted from dense grid activity traces. The model is exploited in a simple job resubmission strategy. It provides quantitative inputs to improve job submission performance and it enables quantifying the impact of faults and outliers on grid operations

Characterizing Workload of Web Applications on Virtualized Servers

With the ever increasing demands of cloud computing services, planning and management of cloud resources has become a more and more important issue which directed affects the resource utilization and SLA and customer satisfaction. But before any management strategy is made, a good understanding of applications' workload in virtualized environment is the basic fact and principle to the resource management methods. Unfortunately, little work has been focused on this area. Lack of raw data could be one reason; another reason is that people still use the traditional models or methods shared under non-virtualized environment. The study of applications' workload in virtualized environment should take on some of its peculiar features comparing to the non-virtualized environment. In this paper, we are open to analyze the workload demands that reflect applications' behavior and the impact of virtualization. The results are obtained from an experimental cloud testbed running web applications, specifically the RUBiS benchmark application. We profile the workload dynamics on both virtualized and non-virtualized environments and compare the findings. The experimental results are valuable for us to estimate the performance of applications on computer architectures, to predict SLA compliance or violation based on the projected application workload and to guide the decision making to support applications with the right hardware.Comment: 8 pages, 8 figures, The Fourth Workshop on Big Data Benchmarks, Performance Optimization, and Emerging Hardware in conjunction with the 19th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS-2014), Salt Lake City, Utah, USA, March 1-5, 201

Psoriasin, one of several new proteins identified in nasal lavage fluid from allergic and non-allergic individuals using 2-dimensional gel electrophoresis and mass spectrometry

BACKGROUND: Extravasation and luminal entry of plasma occurs continuously in the nose. This process is markedly facilitated in patients with symptomatic allergic rhinitis, resulting in an increased secretion of proteins. Identification of these proteins is an important step in the understanding of the pathological mechanisms in allergic diseases. DNA microarrays have recently made it possible to compare mRNA profiles of lavage fluids from healthy and diseased patients, whereas information on the protein level is still lacking. METHODS: Nasal lavage fluid was collected from 11 patients with symptomatic allergic rhinitis and 11 healthy volunteers. 2-dimensional gel electrophoresis was used to separate proteins in the lavage fluids. Protein spots were picked from the gels and identified using mass spectrometry and database search. Selected proteins were confirmed with western blot. RESULTS: 61 spots were identified, of which 21 were separate proteins. 6 of these proteins (psoriasin, galectin-3, alpha enolase, intersectin-2, Wnt-2B and hypothetical protein MGC33648) had not previously been described in nasal lavage fluids. The levels of psoriasin were markedly down-regulated in allergic individuals. Prolactin-inducible protein was also found to be down-regulated, whereas different fragments of albumin together with Ig gamma 2 chain c region, transthyretin and splice isoform 1 of Wnt-2B were up-regulated among the allergic patients. CONCLUSION: The identification of proteins in nasal lavage fluid with 2-dimensional gelelectrophoresis in combination with mass spectrometry is a novel tool to profile protein expression in allergic rhinitis and it might prove useful in the hunt for new therapeutic targets or diagnostic markers for allergic diseases. Psoriasin is a potent chemotactic factor and its down-regulation during inflammation might be of importance for the outcome of the disease

SLA Formulation for Squeezed Protection in Elastic Optical Networks Considering the Modulation Format

In spectrum-sliced elastic optical path networks (SLICE), the lightpath bandwidth is variable, and the virtual topology overlay on a physical topology shall be designed to optimize the spectrum utilization. Under static traffic, SLICE networks are typically designed through a mixed integer linear programming (MILP) with the aim of minimizing the spectrum utilization. In this paper, a new MILP formulation for protection in SLICE networks is proposed, which uses the concept of bandwidth squeezing and grooming to guarantee a minimum agreed bandwidth for each source–destination pair in the surviving bandwidth. The route for each demand on the physical topology is determined by balance equations together with physical layer constraints in the formulation, so that no pre-calculated routes are required and the modulation format of each established lightpath may be chosen with enough quality of transmission and to save network spectrum. Therefore, the proposed formulation jointly solves the virtual topology design and physical topology design problems. The first results evaluate the effectiveness of the MILP formulation for two small networks when connections are under different service-level agreement (SLA) requirements and are provisioned by an appropriate protection scheme and different modulation formats. Due to the NP-hard nature of the proposed MILP formulation, a heuristic algorithm for moderately large networks is also proposed. Case studies are carried out to analyze the basic properties of the formulation and the performance of the proposed heuristic. With the proposed formulation, it is possible to identify the configurations that ensure minimum spectrum occupation with different kinds of protection for each lightpath. Different kinds of modulation formats are considered and contrasted to the benchmark case of a single modulation format and using the same kind of protection for all lightpaths