Identifying the Importance of Content Overlap for Better Cross-lingual Embedding Mappings

In this work, we analyze the performance and properties of cross-lingual word embedding models created by mapping-based alignment methods. We use several measures of corpus and embedding similarity to predict BLI scores of cross-lingual embedding mappings over three types of corpora, three embedding methods and 55 language pairs. Our experimental results corroborate that instead of mere size, the amount of common content in the training corpora is essential. This phenomenon manifests in that i) despite of the smaller corpus sizes, using only the comparable parts of Wikipedia for training the monolingual embedding spaces to be mapped is often more efficient than relying on all the contents of Wikipedia, ii) the smaller, in return less diversified Spanish Wikipedia works almost always much better as a training corpus for bilingual mappings than the ubiquitously used English Wikipedia.

Can Question Generation Debias Question Answering Models? A Case Study on Question--Context Lexical Overlap

Question answering (QA) models for reading comprehension have been demonstrated to exploit unintended dataset biases such as question--context lexical overlap. This hinders QA models from generalizing to under-represented samples such as questions with low lexical overlap. Question generation (QG), a method for augmenting QA datasets, can be a solution for such performance degradation if QG can properly debias QA datasets. However, we discover that recent neural QG models are biased towards generating questions with high lexical overlap, which can amplify the dataset bias. Moreover, our analysis reveals that data augmentation with these QG models frequently impairs the performance on questions with low lexical overlap, while improving that on questions with high lexical overlap. To address this problem, we use a synonym replacement-based approach to augment questions with low lexical overlap. We demonstrate that the proposed data augmentation approach is simple yet effective to mitigate the degradation problem with only 70k synthetic examples.

The Overlap of Poetry and Prose in the Prose of the Umayyad Period

The study deals with the aesthetics of poetic language as the most prominent object of the literary interplay in the prose text of the writers, preachers and apostles of the Umayyad period.

Increasing the Effectiveness of Deleting the Negative Overlap in Radars That use Linear Frequency Modulation LFM

This paper presents a study of the possibility of improving the performance of the radar stations that use Linear Frequency Modulation (LFM) using signals pairs, uplink and downlink, to get rid of the negative interference signals, with the use of packet filters opposite narrow area dedicated to measuring the goal. The output of these packet filters is connected to subtractor circuit, so the reflected signals from fixed objects (negative interference) excite filters have the same arrangement leading to subtracting it, and the reflected signals from a moving target will vary its frequency value of the offset Doppler "fd" and thus excite different filters arranged to pass through the subtraction circuit without being deleted.