Estimating Subjective Crowd Evaluations as an Additional Objective to Improve Natural Language Generation

Human ratings are one of the most prevalent methods to evaluate the performance of natural language processing algorithms . It is commonto measure the quality of sentences generated by a natural language generationmodel using human raters . In this paper, we argue for exploring the use ofsubjective evaluations within the process of training language generationmodels in a multi-task learning setting .…

A Scalable Algorithm for Decentralized Actor Termination Detection

Automatic garbage collection (GC) prevents certain kinds of bugs and reducesprogramming overhead . GC techniques for sequential programs are based onreachability analysis . However, testing reachability from a root set is inadequate for determining whether an actor is garbage . We present a low-overhead reference listing technique (called DRL) fortermination detection in actor systems .…

Action Conditioned 3D Human Motion Synthesis with Transformer VAE

We tackle the problem of action-conditioned generation of realistic and diverse human motion sequences . In contrast to methods that complete, orextend, motion sequences, this task does not require an initial pose orsequence . We learn an action-aware latent representation for human motionsby training a generative variational autoencoder (VAE) We evaluate our approach on NTU RGB+D, HumanAct12 and UESTC datasets and show improvements over the state of the art .…

SchedGuard Protecting against Schedule Leaks Using Linux Containers

Real-time systems have recently been shown to be vulnerable to timinginference attacks . SchedGuard is integrated into the Linux kernel using cgroups, making it amenable to use with container frameworks . Not only is SchedGuard able to protect against the attacks mentioned above, but it also ensures that the real-timetasks/containers meet their temporal requirements .…

Cross Partisan Discussions on YouTube Conservatives Talk to Liberals but Liberals Don t Talk to Conservatives

Most users with at least 10 comments posted at least once on both left-leaning and right-leaning YouTube channels . We present the first large-scale measurement study of cross-partisandiscussions between liberals and conservatives on YouTube, based on a dataset of 274,241 political videos from 973 channels of US partisan media and 134Mcomments from 9.3M users over eight months in 2020 .…

MIPROT A Medical Image Processing Toolbox for MATLAB

This paper presents a Matlab toolbox to perform basic image processing and visualization tasks, particularly designed for medical image processing . The toolbox is entirely written in native Matlab code, but is fast and flexible . Main use cases for the toolbox are illustrated here, including image input/output, pre-processing, filtering, image registration and visualisation .…

Channel Modeling for Drug Carrier Matrices

Molecular communications is a promising framework for the design of controlled-release drug delivery systems . In a matrix carrier, drug molecules are dispersed inthe matrix and diffuse from the inner to the outer layers of the carrier onceimmersed in a dissolution medium .…

Accelerating science with human versus alien artificial intelligences

Data-driven artificial intelligence models fed with published scientific findings have been used to create powerful prediction engines for scientific and technological advance . These models succeed by predicting human predictions and the scientists who will make them . By tuning AI to avoid the crowd, however, itgenerates scientifically promising “alien” hypotheses unlikely to be imagined or pursued without intervention, not only accelerating but punctuatingscientific advance .…

Interpretable Methods for Identifying Product Variants

For e-commerce companies, organization andgrouping of products in meaningful ways is important for creating great customer shopping experiences . One important way of grouping products is to identify a family of product variants,where the variants are mostly the same with slight and yet distinct differences(e.g.…

StylePTB A Compositional Benchmark for Fine grained Controllable Text Style Transfer

Text style transfer aims to controllably generate text with targetedstylistic changes while maintaining core meaning from the source sentenceconstant . Many existing style transfer benchmarks do not offer fine-grained control on sentence structure, emphasis, and content of the sentence . We introduce a large-scale benchmark, StylePTB, with pairedsentences undergoing 21 stylistic changes spanning atomic lexical,syntactic, semantic, and thematic transfers of text .…

MIMO OFDM Based Massive Connectivity With Frequency Selectivity Compensation

In this paper, we study how to efficiently and reliably detect active devicesand estimate their channels in a multiple- input multiple-input multiple-output (MIMO)orthogonal frequency-division multiplexing (OFDM) system . We propose a block-wise linear channel model and an efficient turbo message passing (Turbo-MP) algorithm to resolve the Bayesian inference problem with near-linearcomplexity .…

Polar Precoding A Unitary Finite Feedback Transmit Precoder for Polar Coded MIMO Systems

We propose a unitary precoding scheme to improve polar-coded MIMO systems . The proposed polar-precoding scheme relies on the polarization criterion . Our simulation results show that the proposal outperforms the state-of-the-art DFT pre-code scheme . In contrast to the traditional design of MIMo precoding criteria, we design a matrix for maximizing polarization among data streams without degrading the capacity .…

Iterative Access Point Selection MMSE Precoding and Power Allocation for Cell Free Networks

In this work, we propose iterative access point (AP) selection (APS), linearminimum mean-square error (MMSE) precoding and power allocation techniques forCell-Free Massive multiple-input multiple- input multiple-output (MIMO) systems . Simulations show that the proposed approach outperforms existing conjugatebeamforming (CB) and zero-forcing (ZF) schemes and that performance remains excellent with APS, in the presence of perfect and imperfect channel stateinformation (CSI)…

WEC Deriving a Large scale Cross document Event Coreference dataset from Wikipedia

Cross-document event coreference resolution is a foundational task for NLP applications involving multi-text processing . Existing corpora for this task are scarce and relatively small, while annotating only modest-size clusters of documents belonging to the same topic . We present an efficient methodology for gathering a large-scale dataset for cross-document coreference from Wikipedia, where coreference links are restricted within predefined topics .…

Innovative Bert based Reranking Language Models for Speech Recognition

Bidirectional Encoder Representations from Transformers (BERT) has achieved impressive success on many natural languageprocessing tasks such as question answering and language understanding . In view of the above, this paperpresents a novel instantiation of the BERT-based contextualized language models(LMs) for use in reranking of N-best hypotheses produced by automatic speechrecognition .…

Classical quantum network coding a story about tensor

Kobayashi et al. showed how to convert any network coding protocol into a quantum coding protocol . They left open whether existence of quantum network coding protocols implied the existence of a classical one . We characterize the set of distribution tasks achievable with non zeroprobability for both classical and quantum networks.…

NeMo Inverse Text Normalization From Development To Production

Inverse text normalization (ITN) converts spoken-domain automatic speechrecognition (ASR) output into written-domain text . Many state-of-the-art ITN systems use hand-written weightedfinite-state transducer(WFST) grammars since this task has extremely low tolerance to unrecoverable errors . We introduce an open-source PythonWFST-based library for ITN .…

Unsupervised Learning of Explainable Parse Trees for Improved Generalisation

Recent RvNN-based models fail to learn simple grammar and meaningful semantics in their intermediate treerepresentation . In this work, we propose an attention mechanism over Tree-LSTMsto learn more meaningful and explainable parse tree structures . We alsodemonstrate the superior performance of our proposed model on natural languageinference, semantic relatedness, and sentiment analysis tasks .…

Compressive Neural Representations of Volumetric Scalar Fields

We present an approach for compressing volumetric scalar fields usingimplicit neural representations . Our approach represents a scalar field as alearned function, wherein a neural network maps a point in the domain to an output scalar value . By setting the number of weights of the neural network to be smaller than the input size, we achieve compressed representations of scalarfields .…

Velocity Skinning for Real time Stylized Skeletal Animation

We propose asimple, real-time solution for adding secondary animation effects on top of standard skinning . Our method takes a standard skeleton animation as input, along with skin mesh and rig weights . It then derives per-vertex deformations from the different linear and angularvelocities along the skeletal hierarchy .…

Fine tuning Encoders for Improved Monolingual and Zero shot Polylingual Neural Topic Modeling

Neural topic models can augment or replace bag-of-words inputs with the learned representations of deep pre-trained transformer-based word prediction models . One added benefit when using representations from multilingual models is that they facilitate zero-shot polylingual topic modeling . We find that fine-tuning encoder representations on topic classification and integrating the topic classification task directly into topic modeling improves topic quality .…

How Should Network Slice Instances be Provided to Multiple Use Cases of a Single Vertical Industry

There are a large number of vertical industries implementing multiple usecases, each use case characterized by diverging service, network, andconnectivity requirements such as automobile, manufacturing, power grid, etc. Such heterogeneity cannot be effectively managed and efficiently mapped onto asingle type of network slice instance (NSI) Both approaches tackle the same technical issue ofprovisioning, management, and orchestration of per vertical per use case NSIs in order to improve resource allocation and enhance network performance .…