wanyu/IteraTeR_v2 huggingface dataset:
Original:  We formulate a multiagent system as a coupled non-linear network with a generic ordinary differential equation (ODE) based state evolution  and develop a neural network-based realization of its time-discretized model.
Revised:  We formulate a multi-agent system as a coupled non-linear network with a generic ordinary differential equation (ODE) based state evolution and develop a neural network-based realization of its time-discretized model.
Edit intent: fluency
Original:  We formulate a multiagent system as a coupled non-linear network with a generic ordinary differential equation (ODE) based state evolution  and develop a neural network-based realization of its time-discretized model.
Revised:  We formulate a multiagent system as a coupled non-linear network with a generic ordinary differential equation (ODE) based state evolution , and develop a neural network-based realization of its time-discretized model.
Edit intent: fluency
Original:  MagNet is trained to discover the core dynamics of a multi-agent system from observations  and tuned on-line to learn agent-specific parameters of the dynamics to ensure accurate prediction even when physical or relational attributes of agents, or number of agents change.
Revised:  MagNet is trained to discover the core dynamics of a multi-agent system from observations , and tuned on-line to learn agent-specific parameters of the dynamics to ensure accurate prediction even when physical or relational attributes of agents, or number of agents change.
Edit intent: fluency
Original: The aim of this paper is to understand if Distributed Ledger Technologies (DLTs) are ready to support complex services, such as those related to smart transportation systems .
Revised: The aim of this paper is to understand whether Distributed Ledger Technologies (DLTs) are ready to support complex services, such as those related to smart transportation systems .
Edit intent: fluency
Original: The aim of this paper is to understand if Distributed Ledger Technologies (DLTs) are ready to support complex services, such as those related to smart transportation systems .
Revised: The aim of this paper is to understand if Distributed Ledger Technologies (DLTs) are ready to support complex services, such as those related to Intelligent Transportation Systems (ITS) .
Edit intent: clarity
Original:  We propose an architecture for smart transportation systems that resorts to DLT features.
Revised:  We propose an architecture for ITS that resorts to DLT features.
Edit intent: clarity
Original: Ontology-Based Data Access (OBDA) has traditionally focused on providing a unified view of heterogeneous datasets (e.g., relational database, CSV, JSON), either by materializing integrated data into RDF or by performing on-the-fly integration via SPARQL-to-SQL query translation.
Revised: Ontology-Based Data Access (OBDA) has traditionally focused on providing a unified view of heterogeneous datasets , either by materializing integrated data into RDF or by performing on-the-fly integration via SPARQL-to-SQL query translation.
Edit intent: coherence
Original: Ontology-Based Data Access (OBDA) has traditionally focused on providing a unified view of heterogeneous datasets (e.g., relational database, CSV, JSON), either by materializing integrated data into RDF or by performing on-the-fly integration via SPARQL-to-SQL query translation.
Revised: Ontology-Based Data Access (OBDA) has traditionally focused on providing a unified view of heterogeneous datasets (e.g., relational database, CSV, JSON), either by materializing integrated data into RDF or by performing on-the fly querying via SPARQL query translation.
Edit intent: clarity
Original:  In the specific case of tabular datasets comprised of several CSV or Excel files, query translation approaches have been applied taking as input a lightweight schema with table and column names, and considering each source as a single table that can be loaded into a relational database system (RDB).
Revised:  In the specific case of tabular datasets represented as several CSV or Excel files, query translation approaches have been applied taking as input a lightweight schema with table and column names, and considering each source as a single table that can be loaded into a relational database system (RDB).
Edit intent: clarity
Original:  In the specific case of tabular datasets comprised of several CSV or Excel files, query translation approaches have been applied taking as input a lightweight schema with table and column names, and considering each source as a single table that can be loaded into a relational database system (RDB).
Revised:  In the specific case of tabular datasets comprised of several CSV or Excel files, query translation approaches have been applied by considering each source as a single table that can be loaded into a relational database system (RDB).
Edit intent: coherence
Original:  We propose Morph-CSV, a framework  that enforces constraints and can be used together with any SPARQL-to-SQL OBDA engine.
Revised:  We propose Morph-CSV, a framework that can be used together with any SPARQL-to-SQL OBDA engine.
Edit intent: coherence
Original:  Morph-CSV resorts to both a Constraints component and a set of operators that apply each type of constraint to the input with the aim of enhancing query completeness and performance.
Revised:  Morph-CSV relies on both a constraint component and a set of operators that apply each type of constraint to the input with the aim of enhancing query completeness and performance.
Edit intent: clarity
Original:  Morph-CSV resorts to both a Constraints component and a set of operators that apply each type of constraint to the input with the aim of enhancing query completeness and performance.
Revised:  Morph-CSV resorts to both a Constraints component and a set of constraint operators. For a given set of constraints, the operators are applied to each type of constraint to the input with the aim of enhancing query completeness and performance.
Edit intent: clarity
Original:  Morph-CSV resorts to both a Constraints component and a set of operators that apply each type of constraint to the input with the aim of enhancing query completeness and performance.
Revised:  Morph-CSV resorts to both a Constraints component and a set of operators that apply each type of constraint with the aim of enhancing query completeness and performance.
Edit intent: clarity
Original:  Morph-CSV is compared with existing approaches in terms of query result completeness and performance .
Revised:  Morph-CSV is able to speed up the total query execution time by up to two orders of magnitude, while it is able to produce all the query answers .
Edit intent: clarity
Original: We introduce a new multimodal retrieval task - TV show Retrieval (TVR), in which a short video moment has to be localized from a large video (with subtitle) corpus, given a natural language query.
Revised: We introduce TV show Retrieval (TVR), in which a short video moment has to be localized from a large video (with subtitle) corpus, given a natural language query.
Edit intent: clarity
Original:  We present several baselines and a novel Cross-modal Moment Localization (XML ) modular network for this new dataset and task .
Revised:  Further, we present several baselines and a novel Cross-modal Moment Localization (XML ) modular network for this new dataset and task .
Edit intent: coherence
Original:  We present several baselines and a novel Cross-modal Moment Localization (XML ) modular network for this new dataset and task .
Revised:  We present several baselines and a novel Cross-modal Moment Localization (XML ) network for multimodal moment retrieval tasks .
Edit intent: clarity
Original:  Here models need to jointly use the video and subtitle to generate a caption description.
Edit intent: coherence
Original: Blockchains are typically managed by peer-to-peer (P2P) networks providing the support and substrate to the socalled distributed ledger (DLT), a replicated, shared, and synchronized data structure, geographically spread across multiple nodes.
Revised: Blockchains are typically managed by peer-to-peer (P2P) networks providing the support and substrate to the so-called distributed ledger (DLT), a replicated, shared, and synchronized data structure, geographically spread across multiple nodes.
Edit intent: fluency
Original:  In this paper  we focus on the network side of the BTC P2P network, analyzing its nodes from a purely network measurements-based approach.
Revised:  In this paper , we focus on the network side of the BTC P2P network, analyzing its nodes from a purely network measurements-based approach.
Edit intent: fluency
Original: Passive acoustics provides a powerful tool for monitoring the endangered North Atlantic right whale ( NARW ), but improved detection algorithms are needed to handle diverse and variable acoustic conditions and differences in recording techniques and equipment.
Revised: Passive acoustics provides a powerful tool for monitoring the endangered North Atlantic right whale ( NARW ), but robust detection algorithms are needed to handle diverse and variable acoustic conditions and differences in recording techniques and equipment.
Edit intent: clarity
Original:  Here, we investigate the potential of Deep Neural Networks for addressing this need.
Revised:  Here, we investigate the potential of deep neural networks for addressing this need.
Edit intent: fluency
Original:  ResNet, an architecture commonly used for image recognition, is trained to recognize the time-frequency representation of the characteristic NARW upcall.
Revised:  ResNet, an architecture commonly used for image recognition, is trained to recognize the time-frequency representation of the characteristic North Atlantic right whale upcall.
Edit intent: clarity
Original:  The network is trained on several thousand examples recorded at various locations in the Gulf of St.  Lawrence in 2018 and 2019, using different equipment and deployment techniques.
Revised:  The network is trained on several thousand examples recorded at various locations in the Gulf of St. \ Lawrence in 2018 and 2019, using different equipment and deployment techniques.
Edit intent: fluency
Original:  Our work demonstrates that Deep Neural Networks can be trained to identify NARW upcalls under diverse and variable conditions with a performance that compares favorably to that of existing algorithms.
Revised:  Our work demonstrates that deep neural networks can be trained to identify NARW upcalls under diverse and variable conditions with a performance that compares favorably to that of existing algorithms.
Edit intent: fluency
Original:  Our work demonstrates that Deep Neural Networks can be trained to identify NARW upcalls under diverse and variable conditions with a performance that compares favorably to that of existing algorithms.
Revised:  Our work demonstrates that Deep Neural Networks can be trained to identify North Atlantic right whale upcalls under diverse and variable conditions with a performance that compares favorably to that of existing algorithms.
Edit intent: clarity
Original:  They are studied using various update modes: sequential (one node update at a time), asynchronous (any subset of nodes at a time) or synchronous (all nodes simultaneously).
Edit intent: clarity
Original:  For instance, it is known Cameron-Fairbairn-Gadouleau-2014%DIFDELCMD < ] %%% that for any alphabet Q and network size n (with finite exceptions) there is a universal automaton network f such that any permutation of Q^n is a composition of sequential updates of f.
Revised:  Cameron-Fairbairn-Gadouleau-2014%DIFDELCMD < ] %%% that for any alphabet Q and network size n (with finite exceptions) there is a universal automaton network f such that any permutation of Q^n is a composition of sequential updates of f.
Edit intent: coherence
Original:  For instance, it is known Cameron-Fairbairn-Gadouleau-2014%DIFDELCMD < ] %%% that for any alphabet Q and network size n (with finite exceptions) there is a universal automaton network f such that any permutation of Q^n is a composition of sequential updates of f.
Revised:  For instance, it is known %DIFDELCMD < ] %%% that for any alphabet Q and network size n (with finite exceptions) there is a universal automaton network f such that any permutation of Q^n is a composition of sequential updates of f.
Edit intent: coherence
Original:  For non-Boolean alphabets and for any network size, there are intrinsically non-sequential transformations (  that can not be obtained as composition of sequential updates of some network).
Revised:  For non-Boolean alphabets and for any network size, there are intrinsically non-sequential transformations ( i.e. that can not be obtained as composition of sequential updates of some network).
Edit intent: coherence
Original:  On the other hand, we show that there are universal automata networks for sequential updates if one allows to use a larger alphabet and then use either projection onto or restriction to the original alphabet.
Revised:  On the other hand, we show that there are universal automata networks for sequential updates if one is allowed to use a larger alphabet and then use either projection onto or restriction to the original alphabet.
Edit intent: fluency
Original: We present a novel modular object detection convolutional neural network that significantly improves the accuracy of computer vision object detection.
Revised: We present a novel modular object detection convolutional neural network that significantly improves the accuracy of object detection.
Edit intent: clarity
Original:  Compared to a state of the art object detection networks the classification error in the modular network is improved by approximately 3-5 times, from 12 percent to 2.5  -4.5 percent.
Revised:  Compared to a state of the art object detection networks the classification error in the modular network is improved by approximately 3-5 times, from 12 \% to 2.5 -4.5 percent.
Edit intent: fluency
Original:  The network is easy to implement, it can be a platform to improve the accuracy of widespread state of the art object detection networks and other kinds of deep learning networks  .
Revised:  The network architecture can be a platform to improve the accuracy of widespread state of the art object detection networks and other kinds of deep learning networks .
Edit intent: clarity
Original: An online resource scheduling framework is proposed for minimizing the sum of weighted task latency for all the mobile users, by optimizing offloading decision, transmission power , and resource allocation in the  mobile edge computing (MEC) system.
Revised: An online resource scheduling framework is proposed for minimizing the sum of weighted task latency for all the mobile users, by optimizing offloading decision, transmission power and resource allocation in the mobile edge computing (MEC) system.
Edit intent: fluency
Original:  Towards this end, a deep reinforcement learning (DRL) method is proposedto obtain an online resource scheduling policy .
Revised:  Towards this end, a deep reinforcement learning (DRL) based solution is proposed, which includes the following components .
Edit intent: clarity
Original:  Firstly, a related and regularized stacked auto encoder (2r-SAE) with unsupervised learning is proposed to perform data compression and representation for high dimensional channel quality information (CQI) data, which can reduce the state space for DRL.
Revised:  Firstly, a related and regularized stacked auto encoder (2r-SAE) with unsupervised learning is applied to perform data compression and representation for high dimensional channel quality information (CQI) data, which can reduce the state space for DRL.
Edit intent: clarity
Original: %DIFDELCMD < \Millions %%%  of news articles are published online every day, which can be overwhelming for readers to follow.
Revised: %DIFDELCMD < \Millions %%% Millions of news articles are published online every day, which can be overwhelming for readers to follow.
Edit intent: fluency
Original: This paper proposes a new method for financial portfolio optimisation based on reducing simultaneous asset shocks across a portfolio of assets.
Revised: This paper proposes a new method for financial portfolio optimization based on reducing simultaneous asset shocks across a portfolio of assets.
Edit intent: fluency
Original: This paper proposes a new method for financial portfolio optimisation based on reducing simultaneous asset shocks across a portfolio of assets.
Revised: This paper proposes a new method for financial portfolio optimisation based on reducing simultaneous asset shocks across a collection of assets.
Edit intent: clarity
Original:  We adopt the new semi-metrics of \mbox{ James2019 to determine the distance between two time series' structural breaks.
Revised:  We adopt the new semi-metrics of \mbox{ James2019 to determine the distance between time series' structural breaks.
Edit intent: clarity
Original:  We build on the optimal portfolio theory of \mbox{ Markowitz1952 distance between asset structural breaks  , rather than portfolio variance , as our penalty function .
Revised:  Then, we build on the optimal portfolio theory of \mbox{ Markowitz1952 distance between asset structural breaks , rather than portfolio variance , as our penalty function .
Edit intent: fluency
Original:  We build on the optimal portfolio theory of \mbox{ Markowitz1952 distance between asset structural breaks  , rather than portfolio variance , as our penalty function .
Revised:  We build on the classical portfolio optimization theory of Markowitz and use this distance between asset structural breaks , rather than portfolio variance , as our penalty function .
Edit intent: clarity
Original:  We build on the optimal portfolio theory of \mbox{ Markowitz1952 distance between asset structural breaks  , rather than portfolio variance , as our penalty function .
Revised:  We build on the optimal portfolio theory of \mbox{ Markowitz1952 distance between asset structural breaks for our penalty function , rather than portfolio variance , as our penalty function .
Edit intent: clarity
Original:  We build on the optimal portfolio theory of \mbox{ Markowitz1952 distance between asset structural breaks  , rather than portfolio variance , as our penalty function .
Revised:  We build on the optimal portfolio theory of \mbox{ Markowitz1952 distance between asset structural breaks , rather than portfolio variance .
Edit intent: clarity
Original:  Our experiments are promising: on synthetic data, they indicate that our proposed method does indeed diversify among time series with highly similar structural breaks  .
Revised:  Our experiments are promising: on synthetic data, we show that our proposed method does indeed diversify among time series with highly similar structural breaks .
Edit intent: clarity
Original:  On real data, experiments illustrate that our proposed optimisation method produces higher risk-adjusted returns than mean variance portfolio optimisation.
Revised:  On real data, experiments illustrate that our proposed optimization method produces higher risk-adjusted returns than mean variance portfolio optimisation.
Edit intent: fluency
Original:  The predictive distribution is superior in every measure  , producing a higher mean, lower standard deviation and less kurtosis.
Revised:  The predictive distribution is superior in every measure analyzed , producing a higher mean, lower standard deviation and less kurtosis.
Edit intent: clarity
Original:  The predictive distribution is superior in every measure  , producing a higher mean, lower standard deviation and less kurtosis.
Revised:  The predictive distribution is superior in every measure , producing a higher mean, lower standard deviation and lower kurtosis.
Edit intent: fluency
Original:  The main implication for this method in portfolio management is reducing simultaneous asset shocks and potentially sharp associated drawdowns , during periods of highly similar structural breaks, such as a market crisis.
Revised:  The main implication for this method in portfolio management is reducing simultaneous asset shocks and potentially sharp associated drawdowns during periods of highly similar structural breaks, such as a market crisis.
Edit intent: fluency
Original:  The high performance of the recent FINUFFT library is in part due to its use of a new `` exponential of semicircle '' kernel \phi(z)=e^{\beta 1-z^2}, for z\in[-1,1], zero otherwise, whose Fourier transform \hat\phi is unknown analytically.
Revised:  The high performance of the recent FINUFFT library is in part due to its use of a new " exponential of semicircle '' kernel \phi(z)=e^{\beta 1-z^2}, for z\in[-1,1], zero otherwise, whose Fourier transform \hat\phi is unknown analytically.
Edit intent: fluency
Original:  The high performance of the recent FINUFFT library is in part due to its use of a new `` exponential of semicircle '' kernel \phi(z)=e^{\beta 1-z^2}, for z\in[-1,1], zero otherwise, whose Fourier transform \hat\phi is unknown analytically.
Revised:  The high performance of the recent FINUFFT library is in part due to its use of a new `` exponential of semicircle " kernel \phi(z)=e^{\beta 1-z^2}, for z\in[-1,1], zero otherwise, whose Fourier transform \hat\phi is unknown analytically.
Edit intent: fluency
Original:  A seasonal PMF model is also presented to handle dynamic networks.
Revised:  A seasonal PMF model is also presented to handle seasonal networks.
Edit intent: clarity
Original:  The results show an improved performance over the standard PMF model and other common link prediction techniques .
Revised:  The results show an improved performance over the standard PMF model and other statistical network models .
Edit intent: clarity
Original:   As an application we derive, under an uniformity assumption in \rho, the leading asymptotics of the density of the time average of the geometric Brownian motion as t\to 0.
Revised:  As an application we obtain the leading asymptotics of the density of the time average of the geometric Brownian motion as t\to 0.
Edit intent: clarity
Original: We propose a novel time discretization for the log-normal SABR model dS_t = \sigma_t S_t dW_t, d\sigma_t = \omega \sigma_t dZ_t, with corr(W_t,Z_t)=\varrho, which is a  variant of the Euler-Maruyama scheme , and study its asymptotic properties in the limit of a large number of time steps n%DIFDELCMD < \to %%% \infty at fixed \beta = \frac{1{2}\omega^2 n^2\tau, \rho = \sigma_0\tau}  .
Revised: We propose a novel time discretization for the log-normal SABR model which is a variant of the Euler-Maruyama scheme , and study its asymptotic properties in the limit of a large number of time steps n%DIFDELCMD < \to %%% \infty at fixed \beta = \frac{1{2}\omega^2 n^2\tau, \rho = \sigma_0\tau} .
Edit intent: coherence
Original: We propose a novel time discretization for the log-normal SABR model dS_t = \sigma_t S_t dW_t, d\sigma_t = \omega \sigma_t dZ_t, with corr(W_t,Z_t)=\varrho, which is a  variant of the Euler-Maruyama scheme , and study its asymptotic properties in the limit of a large number of time steps n%DIFDELCMD < \to %%% \infty at fixed \beta = \frac{1{2}\omega^2 n^2\tau, \rho = \sigma_0\tau}  .
Revised: We propose a novel time discretization for the log-normal SABR model dS_t = \sigma_t S_t dW_t, d\sigma_t = \omega \sigma_t dZ_t, with corr(W_t,Z_t)=\varrho, which is a variant of the Euler-Maruyama scheme . We study its asymptotic properties in the limit of a large number of time steps n%DIFDELCMD < \to %%% \infty at fixed \beta = \frac{1{2}\omega^2 n^2\tau, \rho = \sigma_0\tau} .
Edit intent: coherence
Original:  We derive an almost sure limit and a large deviations result for the log-asset price in the n%DIFDELCMD < \to %%% \infty limit .
Revised:  We derive an almost sure limit and a large deviations result for the log-asset price in the %DIFDELCMD < \to %%% \infty limit .
Edit intent: clarity
Original: Resting state functional MRI (rs-fMRI) is a widespread and powerful tool for investigating functional connectivity (FC) and brain disorders.
Revised: Resting state functional MRI (rs-fMRI) is a widespread and powerful tool for investigating functional connectivity and brain disorders.
Edit intent: clarity