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Found 32 papers, 12 papers with code
Generalization of Brady-Yong Algorithm for Fast Hough Transform to Arbitrary Image Size
Herewith, the paper provides a theoretical analysis of the computational complexity and accuracy of the proposed algorithm.
Classifier identification in Ancient Egyptian as a low-resource sequence-labelling task
The complex Ancient Egyptian (AE) writing system was characterised by widespread use of graphemic classifiers (determinatives): silent (unpronounced) hieroglyphic signs clarifying the meaning or indicating the pronunciation of the host word.
Beyond prompt brittleness: Evaluating the reliability and consistency of political worldviews in LLMs
Due to the widespread use of large language models (LLMs), we need to understand whether they embed a specific "worldview" and what these views reflect.
Approximate Attributions for Off-the-Shelf Siamese Transformers
In this work, we reassess these restrictions and propose (i) a model with exact attribution ability that retains the original model's predictive performance and (ii) a way to compute approximate attributions for off-the-shelf models.
Improving Cross-Lingual Transfer through Subtree-Aware Word Reordering
Despite the impressive growth of the abilities of multilingual language models, such as XLM-R and mT5, it has been shown that they still face difficulties when tackling typologically-distant languages, particularly in the low-resource setting.
Multilingual estimation of political-party positioning: From label aggregation to long-input Transformers
We carry out the analysis of the Comparative Manifestos Project dataset across 41 countries and 27 languages and find that the task can be efficiently solved by state-of-the-art models, with label aggregation producing the best results.
Investigating semantic subspaces of Transformer sentence embeddings through linear structural probing
The question of what kinds of linguistic information are encoded in different layers of Transformer-based language models is of considerable interest for the NLP community.
An Attribution Method for Siamese Encoders
Despite the success of Siamese encoder models such as sentence transformers (ST), little is known about the aspects of inputs they pay attention to.
Adverbs, Surprisingly
This paper begins with the premise that adverbs are neglected in computational linguistics.
Additive manifesto decomposition: A policy domain aware method for understanding party positioning
The workflow covers (a) definition of suitable policy domains; (b) automatic labeling of domains, if no manual labels are available; (c) computation of domain-level similarities and aggregation at a global level; (d) extraction of interpretable party positions on major policy axes via multidimensional scaling.
Representation biases in sentence transformers
Variants of the BERT architecture specialised for producing full-sentence representations often achieve better performance on downstream tasks than sentence embeddings extracted from vanilla BERT.
Word-order typology in Multilingual BERT: A case study in subordinate-clause detection
The capabilities and limitations of BERT and similar models are still unclear when it comes to learning syntactic abstractions, in particular across languages.
Fast matrix multiplication for binary and ternary CNNs on ARM CPU
In this paper, we propose novel fast algorithms of ternary, ternary-binary, and binary matrix multiplication for mobile devices with ARM architecture.
On the properties of some low-parameter models for color reproduction in terms of spectrum transformations and coverage of a color triangle
One of the classical approaches to solving color reproduction problems, such as color adaptation or color space transform, is the use of low-parameter spectral models.
On the Relation between Syntactic Divergence and Zero-Shot Performance
We explore the link between the extent to which syntactic relations are preserved in translation and the ease of correctly constructing a parse tree in a zero-shot setting.
Part of Speech and Universal Dependency effects on English Arabic Machine Translation
In this research paper, I will elaborate on a method to evaluate machine translation models based on their performance on underlying syntactical phenomena between English and Arabic languages.
SERRANT: a syntactic classifier for English Grammatical Error Types
SERRANT is a system and code for automatic classification of English grammatical errors that combines SErCl and ERRANT.
Illumination Estimation Challenge: experience of past two years
The main advantage of testing a method on a challenge over testing in on some of the known datasets is the fact that the ground-truth illuminations for the challenge test images are unknown up until the results have been submitted, which prevents any potential hyperparameter tuning that may be biased.
Classifying Syntactic Errors in Learner Language
We present a method for classifying syntactic errors in learner language, namely errors whose correction alters the morphosyntactic structure of a sentence.
ResNet-like Architecture with Low Hardware Requirements
In the paper, we introduce a bipolar morphological ResNet (BM-ResNet) model obtained from a much more complex ResNet architecture by converting its layers to bipolar morphological ones.
Fast Implementation of 4-bit Convolutional Neural Networks for Mobile Devices
We introduce an efficient implementation of 4-bit matrix multiplication for quantized neural networks and perform time measurements on a mobile ARM processor.
Line detection via a lightweight CNN with a Hough Layer
Line detection is an important computer vision task traditionally solved by Hough Transform.
Accelerated FBP for computed tomography image reconstruction
The classical direct implementations of this algorithm require the execution of $\Theta(N^3)$ operations, where $N$ is the linear size of the 2D slice.
Fine-Grained Analysis of Cross-Linguistic Syntactic Divergences
The patterns in which the syntax of different languages converges and diverges are often used to inform work on cross-lingual transfer.
SegBo: A Database of Borrowed Sounds in the World's Languages
Phonological segment borrowing is a process through which languages acquire new contrastive speech sounds as the result of borrowing new words from other languages.
Fast Implementation of Morphological Filtering Using ARM NEON Extension
Experiments showed 3 times efficiency increase for final implementation of erosion and dilation compared to van Herk/Gil-Werman algorithm without SIMD, 5. 7 times speedup for 8x8 matrix transpose and 12 times speedup for 16x16 matrix transpose compared to transpose without SIMD.
Computational optimization of convolutional neural networks using separated filters architecture
This paper considers a convolutional neural network transformation that reduces computation complexity and thus speedups neural network processing.
A Document Skew Detection Method Using Fast Hough Transform
The majority of document image analysis systems use a document skew detection algorithm to simplify all its further processing stages.
A Method of Detecting End-To-End Curves of Limited Curvature
In this paper we consider a method for detecting end-to-end curves of limited curvature like the k-link polylines with bending angle between adjacent segments in a given range.
Bipolar Morphological Neural Networks: Convolution Without Multiplication
To demonstrate efficiency of the proposed model we consider classical convolutional neural networks and convert the pre-trained convolutional layers to the bipolar morphological layers.
HoughNet: neural network architecture for vanishing points detection
We demonstrate its potential by solving the problem of vanishing points detection in the images of documents.
Linear colour segmentation revisited
In this work we discuss the known algorithms for linear colour segmentation based on a physical approach and propose a new modification of segmentation algorithm.
