Constructing Datasets for Multi-hop Reading Comprehension Across Documents

Most Reading Comprehension methods limit themselves to queries which can be answered using a single sentence, paragraph, or document. Enabling models to combine disjoint pieces of textual evidence would extend the scope of machine comprehension methods, but currently there exist no resources to train and test this capability. We propose a novel task to encourage the development of models for text understanding across multiple documents and to investigate the limits of existing methods. In our task, a model learns to seek and combine evidence - effectively performing multi-hop (alias multi-step) inference. We devise a methodology to produce datasets for this task, given a collection of query-answer pairs and thematically linked documents. Two datasets from different domains are induced, and we identify potential pitfalls and devise circumvention strategies. We evaluate two previously proposed competitive models and find that one can integrate information across documents. However, both models struggle to select relevant information, as providing documents guaranteed to be relevant greatly improves their performance. While the models outperform several strong baselines, their best accuracy reaches 42.9% compared to human performance at 74.0% - leaving ample room for improvement.Comment: This paper directly corresponds to the TACL version (https://transacl.org/ojs/index.php/tacl/article/view/1325) apart from minor changes in wording, additional footnotes, and appendice

A Factorization Machine Framework for Testing Bigram Embeddings in Knowledgebase Completion

Embedding-based Knowledge Base Completion models have so far mostly combined distributed representations of individual entities or relations to compute truth scores of missing links. Facts can however also be represented using pairwise embeddings, i.e. embeddings for pairs of entities and relations. In this paper we explore such bigram embeddings with a flexible Factorization Machine model and several ablations from it. We investigate the relevance of various bigram types on the fb15k237 dataset and find relative improvements compared to a compositional model.Comment: accepted for AKBC 2016 workshop, 6page

Multiple-line inference of selection on quantitative traits

Trait differences between species may be attributable to natural selection. However, quantifying the strength of evidence for selection acting on a particular trait is a difficult task. Here we develop a population-genetic test for selection acting on a quantitative trait which is based on multiple-line crosses. We show that using multiple lines increases both the power and the scope of selection inference. First, a test based on three or more lines detects selection with strongly increased statistical significance, and we show explicitly how the sensitivity of the test depends on the number of lines. Second, a multiple-line test allows to distinguish different lineage-specific selection scenarios. Our analytical results are complemented by extensive numerical simulations. We then apply the multiple-line test to QTL data on floral character traits in plant species of the Mimulus genus and on photoperiodic traits in different maize strains, where we find a signatures of lineage-specific selection not seen in a two-line test.Comment: 21 pages, 11 figures; to appear in Genetic

Complex Embeddings for Simple Link Prediction

In statistical relational learning, the link prediction problem is key to automatically understand the structure of large knowledge bases. As in previous studies, we propose to solve this problem through latent factorization. However, here we make use of complex valued embeddings. The composition of complex embeddings can handle a large variety of binary relations, among them symmetric and antisymmetric relations. Compared to state-of-the-art models such as Neural Tensor Network and Holographic Embeddings, our approach based on complex embeddings is arguably simpler, as it only uses the Hermitian dot product, the complex counterpart of the standard dot product between real vectors. Our approach is scalable to large datasets as it remains linear in both space and time, while consistently outperforming alternative approaches on standard link prediction benchmarks.Comment: 10+2 pages, accepted at ICML 201

Cross-Border Tax Effects on Affiliate Investment - Evidence from European Multinationals

Several recent papers show that increases in the capital stock at one multinational affiliate tend to raise the capital stock at other locations, rather than to reduce it. In this paper, we theoretically and empirically explore the consequences of these findings for national corporate tax policy. Our main hypothesis is that domestic corporate taxation not only reduces domestic capital investment but also lowers capital stocks at foreign affiliates within a multinational group. The paper identifies several channels through which domestic taxation may exert such a cross-border effect on foreign capital. Using micro data on European multinational firms, we confirm the hypothesis showing that a ten percentage point increase in corporate tax rates is associated with a 5.5 percent decrease in the affiliate’s capital stock. From a welfare point of view, this cross-border tax effect on capital investment gives rise to a negative fiscal externality of corporate taxation which is empirically shown to compensate a substantial fraction of the well-known positive profit shifting externality

Multinational Firms Mitigate Tax Competition

In a recent study, Becker & Riedel (EER, 2012), we show that an increase in foreign taxes is associated with a decrease in domestic investment. In this paper, we explore the implications of this finding for tax competition. If foreign taxes decrease domestic investment instead of increasing it, the welfare properties of tax competition may fundamentally change. We build a model which demonstrates that an increase in the share of multinationals may mitigate tax competition in the sense that equilibrium taxes are higher. This finding contradicts the popular belief that multinational firms aggravate tax competition

Requirements for, and Cytoplasmic Concentrations of, Sulphate and Chloride, and Cytoplasmic Volume Spaces in the Halophilic Bacterium Ectothiorhodospira mobilis

Ectothiorhodospira mobilis is a halophilic phototrophic bacterium that has been isolated from soda lakes containing high concentrations of sulphate, chloride and carbonates. It utilizes reduced sulphur compounds as photosynthetic electron donors and oxidizes them to sulphate, but can also grow photoheterotrophically with sulphate as sole sulphur source. The requirements for, and the cytoplasmic concentrations of, sulphate and chloride have been determined. High concentrations of sulphate are neither required for nor inhibit growth. Although chloride is by far the dominant anion of the environment, growth of E. mobilis occurs in the absence of added chloride. Sodium chloride can be replaced by sodium sulphate and sodium carbonate. Chloride is excluded from the cytoplasm with decreasing ratios of cytoplasmic/external chloride at increasing external chloride concentrations (under iso-osmotic conditions)

Corporate tax effects on the quality and quantity of FDI

This paper measures the relative importance of quality and quantity effects of corporate taxation on foreign direct investment. Quantity is affected if corporate taxes reduce the equilibrium stock of foreign capital in a given country. Quality effects arise if taxes decrease the extent to which investment contributes to the corporate tax base and the capital intensity of production. Depending on the sign of the quality effects, the detrimental welfare effects of corporate taxation are either mitigated or aggravated. We derive a number of hypotheses how corporate tax changes may affect the quality of investment. Our hypotheses are then tested using data from a large sample of European multinationals. With regard to corporate tax effects on the corporate tax base, we find that quality effects account for up to fourty per cent of the total effect. With regard to corporate tax effects on labour income, our results suggest that quality effects mitigate the negative quantity effect by nearly sixty percent (as corporate taxes strongly increase the labor intensity of production). An important implication is that governments should not exclusively care about the size of inbound FDI flows but also about their specific characteristics, i.e. their quality