wanyu/IteraTeR_v2 huggingface dataset:
Original:   In this paper, we are also dealing with this problem, but present a different approach.
Revised:  In this paper, we deal with this problem, but present a different approach.
Edit intent: clarity
Original:  We use the boundary conditions in our investigation in the sense that so called simultaneous approximation terms (SATs) are applied which are frequently used in the finite difference community.
Revised:  We use the boundary conditions to stabilize the scheme following a procedure that are frequently used in the finite difference community.
Edit intent: clarity
Original:  Specific boundary operators are constructed which guarantee stability.
Revised:  Specific boundary operators are constructed such that they guarantee stability.
Edit intent: clarity
Original:  The SAT approach has already been used in the discontinuous Galerkin framework, but here we apply it -- up to our knowledge -- for the first time together with a continuous Galerkin scheme.
Revised:  This approach has already been used in the discontinuous Galerkin framework, but here we apply it -- up to our knowledge -- for the first time together with a continuous Galerkin scheme.
Edit intent: coherence
Original:  The SAT approach has already been used in the discontinuous Galerkin framework, but here we apply it -- up to our knowledge -- for the first time together with a continuous Galerkin scheme.
Revised:  The SAT approach has already been used in the discontinuous Galerkin framework, but here we apply it with a continuous Galerkin scheme.
Edit intent: coherence
Original:  This contradicts the general perception of stability problems for pure Galerkin schemes .
Revised:  This contradicts the general perception of stability problems for pure Galerkin scheme exist .
Edit intent: clarity
Original: In the hyperbolic community, discontinuous Galerkin (DG) approaches are mainly applied when finite element methods are considered.
Revised: In the hyperbolic community, discontinuous Galerkin approaches are mainly applied when finite element methods are considered.
Edit intent: clarity
Original:  On the contrary, continuous Galerkin (CG) methods appear to be unsuitable for hyperbolic problems and there exists still the perception that continuous Galerkin methods are notoriously unstable .
Revised:  On the contrary, continuous Galerkin (CG) methods appear to be unsuitable for hyperbolic problems .
Edit intent: coherence
Original:   However, this perception is not true and the stabilization terms are unnecessary , in general  .
Revised:  However, this perception is not true and the stabilization terms can be removed , in general .
Edit intent: clarity
Original:  In this paper, we deal with this problem, but present a different approach.
Revised:  In this paper, we deal with this problem, and present a different approach.
Edit intent: coherence
Original:  Further, we point out that we do not need exact integration, it suffices if the quadrature rule and the norm in the differential operator are the same, such that the summation-by-parts (SBP) property is fulfilled meaning that a discrete Gauss Theorem is valid.
Revised:  Further, we point out that we do not need exact integration, it suffices if the quadrature rule and the norm in the differential operator are the same, such that the summation-by-parts (SBP) property is fulfilled meaning that a discrete Gauss Th. is valid.
Edit intent: clarity
Original: The next frontier for 5G and post-5G networks towards truly ubiquitous connectivity is the use of Low Earth Orbit (LEO) small-satellite constellations to support the three 5G use cases: enhanced mobile broadband (eMBB) , massive machine-type communications (mMTC), and ultra-reliable low-latency communications (URLLC) .
Revised: The next frontier for 5G and post-5G networks towards truly ubiquitous connectivity is the use of Low Earth Orbit (LEO) small-satellite constellations to support 5G use cases: enhanced mobile broadband (eMBB) , massive machine-type communications (mMTC), and ultra-reliable low-latency communications (URLLC) .
Edit intent: clarity
Original: The next frontier for 5G and post-5G networks towards truly ubiquitous connectivity is the use of Low Earth Orbit (LEO) small-satellite constellations to support the three 5G use cases: enhanced mobile broadband (eMBB) , massive machine-type communications (mMTC), and ultra-reliable low-latency communications (URLLC) .
Revised: The next frontier for 5G and post-5G networks towards truly ubiquitous connectivity is the use of Low Earth Orbit (LEO) small-satellite constellations to support the three 5G connectivity. Besides enhanced mobile broadband (eMBB) , massive machine-type communications (mMTC), and ultra-reliable low-latency communications (URLLC) .
Edit intent: clarity
Original: The next frontier for 5G and post-5G networks towards truly ubiquitous connectivity is the use of Low Earth Orbit (LEO) small-satellite constellations to support the three 5G use cases: enhanced mobile broadband (eMBB) , massive machine-type communications (mMTC), and ultra-reliable low-latency communications (URLLC) .
Revised: The next frontier for 5G and post-5G networks towards truly ubiquitous connectivity is the use of Low Earth Orbit (LEO) small-satellite constellations to support the three 5G use cases: enhanced mobile broadband (eMBB) and massive machine type communications (mMTC), and ultra-reliable low-latency communications (URLLC) .
Edit intent: fluency
Original: The next frontier for 5G and post-5G networks towards truly ubiquitous connectivity is the use of Low Earth Orbit (LEO) small-satellite constellations to support the three 5G use cases: enhanced mobile broadband (eMBB) , massive machine-type communications (mMTC), and ultra-reliable low-latency communications (URLLC) .
Revised: The next frontier for 5G and post-5G networks towards truly ubiquitous connectivity is the use of Low Earth Orbit (LEO) small-satellite constellations to support the three 5G use cases: enhanced mobile broadband (eMBB) , massive machine-type communications (mMTC), LEO constellations can support ultra-reliable low-latency communications (URLLC) .
Edit intent: clarity
Original: The next frontier for 5G and Beyond-5G (B5G) networks towards truly ubiquitous connectivity is the use of Low Earth Orbit (LEO) small-satellite constellations to support 5G connectivity .
Revised: The next frontier towards truly ubiquitous connectivity is the use of Low Earth Orbit (LEO) small-satellite constellations to support 5G connectivity .
Edit intent: clarity
Original: The next frontier for 5G and Beyond-5G (B5G) networks towards truly ubiquitous connectivity is the use of Low Earth Orbit (LEO) small-satellite constellations to support 5G connectivity .
Revised: The next frontier for 5G and Beyond-5G (B5G) networks towards truly ubiquitous connectivity is the use of Low Earth Orbit (LEO) small-satellite constellations to support 5G and Beyond-5G (B5G) networks .
Edit intent: fluency
Original:  Besides enhanced mobile broadband (eMBB) and massive machine type communications (mMTC), LEO constellations can support ultra-reliable communications (URC) with relaxed latency requirements in the order of a few tens of milliseconds.
Revised:  Besides enhanced mobile broadband (eMBB) and massive machine-type communications (mMTC), LEO constellations can support ultra-reliable communications (URC) with relaxed latency requirements in the order of a few tens of milliseconds.
Edit intent: fluency
Original:  Besides enhanced mobile broadband (eMBB) and massive machine type communications (mMTC), LEO constellations can support ultra-reliable communications (URC) with relaxed latency requirements in the order of a few tens of milliseconds.
Revised:  Besides enhanced mobile broadband (eMBB) and massive machine type communications (mMTC), LEO constellations can support ultra-reliable communications (URC) with relaxed latency requirements of a few tens of milliseconds.
Edit intent: clarity
Original:  This paper provides a comprehensive overview of the physical and logical links, along with the essential architectural and technological components that enable the full integration of LEO constellations into 5G and Beyond-5G systems.
Revised:  This paper provides a comprehensive overview of the physical and logical links, along with the essential architectural and technological components that enable the full integration of LEO constellations into 5G and B5G systems.
Edit intent: clarity
Original:  Furthermore, we characterize and compare each physical link category (ground-to-satellite and inter-satellite) in terms of achievable rates, propagation delays, and Doppler shift.
Revised:  Furthermore, we characterize and compare each physical link category in terms of achievable rates, propagation delays, and Doppler shift.
Edit intent: clarity
Original: The goal of eXtreme Multi-label Learning (XML) is to design and learn a model that can automatically annotate a given data point with the most relevant subset of labels from an extremely large label set.
Revised: The goal of eXtreme Multi-label Learning (XML) is to automatically annotate a given data point with the most relevant subset of labels from an extremely large label set.
Edit intent: clarity
Original:  Motivated by the complexities of these methods and their subsequent training requirements, in this paperwe propose a simple baseline technique for this task.
Revised:  In this paper, rather than coming-up with an altogether new method, our objective is to present and validate a simple baseline technique for this task.
Edit intent: coherence
Original:  Motivated by the complexities of these methods and their subsequent training requirements, in this paperwe propose a simple baseline technique for this task.
Revised:  Motivated by the complexities of these methods and their subsequent training requirements, in this paperwe propose a simple baseline for this task.
Edit intent: clarity
Original:  Next we show how an ensemble of such global embeddings can be used to achieve further boost in prediction accuracies with only linear increase in training and prediction time.
Revised:  Next we show how an ensemble of multiple such learners can be used to achieve further boost in prediction accuracies with only linear increase in training and prediction time.
Edit intent: clarity
Original:  Next we show how an ensemble of such global embeddings can be used to achieve further boost in prediction accuracies with only linear increase in training and prediction time.
Revised:  Next we show how an ensemble of such global embeddings can be used to achieve further boost in prediction accuracy with only linear increase in training and prediction time.
Edit intent: clarity
Original:  This theoretical upper bound depends only on the noise associated with sample labels in a dataset as well as the label variance.
Revised:  This theoretical upper bound depends only on the noise associated with the response variable in a dataset as well as the label variance.
Edit intent: clarity
Original:  This theoretical upper bound depends only on the noise associated with sample labels in a dataset as well as the label variance.
Revised:  This theoretical upper bound depends only on the noise associated with sample labels in a dataset as well as its variance.
Edit intent: clarity
Original:  Although we study biological datasets in this work, the new upper bound estimates will hold true for regression models from any research field or application area where sample labels are associated with noise.
Revised:  Although we study biological datasets in this work, the new upper bound estimates will hold true for regression models from any research field or application area where response variables have associated noise.
Edit intent: clarity
Original:  The optimality of the inequality with respect to the subsampled length scale is demonstrated.
Revised:  We discuss and demonstrate the optimality of the inequality with respect to the subsampled length scale is demonstrated.
Edit intent: clarity
Original:  The error bound blows up as the subsampled length scale approaches 0 if the underlying function is not regular enough .
Revised:  We observe that the error bound blows up as the subsampled length scale approaches 0 if the underlying function is not regular enough .
Edit intent: clarity
Original:  The error bound blows up as the subsampled length scale approaches 0 if the underlying function is not regular enough .
Revised:  The error bound blows up as the subsampled lengthscale approaches zero, due to the fact that the underlying function is not regular enough .
Edit intent: clarity
Original:  One of the most popular methods for achieving this is to use domain randomisation, which involves randomly perturbing various aspects of a simulated environment in order to make trained agents robust to the reality gap between the simulator and the real world .
Revised:  One popular method for achieving transferability is to use domain randomisation, which involves randomly perturbing various aspects of a simulated environment in order to make trained agents robust to the reality gap between the simulator and the real world .
Edit intent: clarity
Original:  One of the most popular methods for achieving this is to use domain randomisation, which involves randomly perturbing various aspects of a simulated environment in order to make trained agents robust to the reality gap between the simulator and the real world .
Revised:  One of the most popular methods for achieving this is to use domain randomisation, which involves randomly perturbing various aspects of a simulated environment in order to make trained agents robust to the reality gap .
Edit intent: clarity
Original:  However, less work has gone into understanding such agents-which are deployed in the real world-beyond task performance.
Revised:  However, less work has gone into understanding such agents - which are deployed in the real world-beyond task performance.
Edit intent: fluency
Original:  However, less work has gone into understanding such agents-which are deployed in the real world-beyond task performance.
Revised:  However, less work has gone into understanding such agents-which are deployed in the real world - beyond task performance.
Edit intent: fluency
Original:  In this work, we train agents for Fetch and Jaco robots on a visuomotor control task , and evaluate how well they generalise using different unit tests.
Revised:  In this work, we train agents for Fetch and Jaco robots on a visuomotor control task and evaluate how well they generalise using different unit tests.
Edit intent: fluency
Original:  Our results show that the primary outcome of domain randomisation is more redundant , entangled representations, accompanied with significant statistical/structural changes in the weights ;
Revised:  Our results show that the primary outcome of domain randomisation is more robust , entangled representations, accompanied with significant statistical/structural changes in the weights ;
Edit intent: clarity
Original:  Our results show that the primary outcome of domain randomisation is more redundant , entangled representations, accompanied with significant statistical/structural changes in the weights ;
Revised:  Our results show that the primary outcome of domain randomisation is more redundant , entangled representations, accompanied with larger weights with greater spatial structure ;
Edit intent: clarity
Original:   Furthermore, even with an improved saliency method introduced in this work, we show that qualitative studies may not always correspond with quantitative measures, necessitating the use of a wide suite of inspection tools in order to provide sufficient insights into the behaviour of trained agents.
Revised:  Furthermore, even with an improved saliency method introduced in this work, we show that qualitative studies may not always correspond with quantitative measures, necessitating the combination of inspection tools in order to provide sufficient insights into the behaviour of trained agents.
Edit intent: clarity
Original:  Presented with molecular simulation trajectories, networks learn to change temperature and chemical potential in order to promote the assembly of desired structures or choose between isoenergetic polymorphs.
Revised:  Presented with molecular simulation trajectories, networks learn to change temperature and chemical potential in order to promote the assembly of desired structures or choose between competing polymorphs.
Edit intent: clarity
Original:  In the first case, networks reproduce in a qualitative sense the results of previously-known protocols, but faster and with slightly higher fidelity;
Revised:  In the first case, networks reproduce in a qualitative sense the results of previously-known protocols, but faster and with higher fidelity;
Edit intent: clarity
Original:  The network architectures we have used can be straightforwardly adapted to handle a large number of input data and output control parameters, and so can be applied to a broad range of systems .
Revised:  The network architectures we have used is simple to implement and can be applied to a broad range of systems .
Edit intent: clarity
Original:  Different explanatory mechanisms, such as plant-plant interactions and plant-water feedback loops have been proposed to justify such a finding , yet a full understanding has not been reached.
Revised:  Different explanatory mechanisms, such as plant-plant interactions and plant-water feedback loops have been proposed to rationalize the emergence of such scale-free patterns , yet a full understanding has not been reached.
Edit intent: clarity
Original:  Furthermore, these are related to a percolation phenomenon that occurs in an intermittent or fluctuating way.
Revised:  Furthermore, this observation is related to a percolation phenomenon that occurs in an intermittent or fluctuating way.
Edit intent: clarity
Original:  From a theoretical side our study shed new light on intermittent percolation phenomena occurring under fluctuating conditions.
Revised:  From a theoretical side , our study sheds new light on intermittent percolation phenomena occurring under fluctuating conditions.
Edit intent: fluency
Original:  From a theoretical side our study shed new light on intermittent percolation phenomena occurring under fluctuating conditions.
Revised:  From a theoretical side our study shed new light on a novel type of percolation phenomenon occurring under temporally-varying external conditions.
Edit intent: clarity
Original: Understanding the causes and effects of spatial patterns of vegetation is a fundamental problem in ecology, especially because these can be used as early predictors of catastrophic shifts such as desertification processes.
Revised: Understanding the causes and effects of spatial vegetation patterns is a fundamental problem in ecology, especially because these can be used as early predictors of catastrophic shifts such as desertification processes.
Edit intent: clarity
Original:  Furthermore, this observation is related to a percolation phenomenon that occurs in an intermittent or fluctuating way.
Revised:  Furthermore, this result is related to a percolation phenomenon that occurs in an intermittent or fluctuating way.
Edit intent: clarity
Original:  From a theoretical side, our study sheds new light on a novel type of percolation phenomenon occurring under temporally-varying external conditions  .
Revised:  From a theoretical side, our study sheds new light on a novel type of percolation phenomena occurring under temporally-varying external conditions .
Edit intent: fluency
Original: Many inferential and learning tasks can be accomplished efficiently by means of distributed optimization algorithms where the network topology  plays a critical role in driving the local interactions among neighboring agents .
Revised: Many optimization, inference and learning tasks can be accomplished efficiently by means of distributed optimization algorithms where the network topology plays a critical role in driving the local interactions among neighboring agents .
Edit intent: clarity
Original: Many inferential and learning tasks can be accomplished efficiently by means of distributed optimization algorithms where the network topology  plays a critical role in driving the local interactions among neighboring agents .
Revised: Many inferential and learning tasks can be accomplished efficiently by means of decentralized processing algorithms where the network topology plays a critical role in driving the local interactions among neighboring agents .
Edit intent: clarity
Original: Many inferential and learning tasks can be accomplished efficiently by means of distributed optimization algorithms where the network topology  plays a critical role in driving the local interactions among neighboring agents .
Revised: Many inferential and learning tasks can be accomplished efficiently by means of distributed optimization algorithms where the network topology plays a critical role in enabling the interactions among neighboring agents .
Edit intent: clarity
Original:  There is a large body of literature examining the effect of the graph structure on the performance of optimization strategies.
Revised:  There is a large body of literature examining the effect of the graph structure on the performance of decentralized processing strategies.
Edit intent: clarity
Original:  In this article, we examine the inverse problem and consider the reverse question: How much information does observing the behavior at the nodes  convey about the underlying network structure used for optimization?
Revised:  In this article, we examine the inverse problem and consider the reverse question: How much information does observing the behavior at the nodes of a graph convey about the underlying network structure used for optimization?
Edit intent: clarity
Original:  Over large-scale networks, the difficulty of addressing such inverse questions (or problems ) is compounded by the fact that usually only a limited portion of nodes can be probed, giving rise to a second important question: Despite the presence of several unobserved nodes, are partial and local observations still sufficient to discover the graph linking the probed nodes?
Revised:  Over large-scale networks, the difficulty in addressing such inverse questions (or problems ) is compounded by the fact that usually only a limited portion of nodes can be probed, giving rise to a second important question: Despite the presence of several unobserved nodes, are partial and local observations still sufficient to discover the graph linking the probed nodes?
Edit intent: fluency
Original:  Over large-scale networks, the difficulty of addressing such inverse questions (or problems ) is compounded by the fact that usually only a limited portion of nodes can be probed, giving rise to a second important question: Despite the presence of several unobserved nodes, are partial and local observations still sufficient to discover the graph linking the probed nodes?
Revised:  Over large-scale networks, the difficulty of addressing such inverse problems is compounded by the fact that usually only a limited portion of nodes can be probed, giving rise to a second important question: Despite the presence of several unobserved nodes, are partial and local observations still sufficient to discover the graph linking the probed nodes?
Edit intent: clarity
Original:  Over large-scale networks, the difficulty of addressing such inverse questions (or problems ) is compounded by the fact that usually only a limited portion of nodes can be probed, giving rise to a second important question: Despite the presence of several unobserved nodes, are partial and local observations still sufficient to discover the graph linking the probed nodes?
Revised:  Over large-scale networks, the difficulty of addressing such inverse questions (or problems ) is compounded by the fact that usually only a limited fraction of the nodes can be probed, giving rise to a second important question: Despite the presence of several unobserved nodes, are partial and local observations still sufficient to discover the graph linking the probed nodes?
Edit intent: clarity