wanyu/IteraTeR_v2 huggingface dataset:
Original:  The decision problem existence of a M%DIFDELCMD < \PhiRF%%%\PhiRF asks to determine whether a given SLC loop admits a M\PhiRF, and the corresponding bounded decision problem restricts the search to M\PhiRFs of depth d, where the parameter d is part of the input.
Revised:  The decision problem existence of a M%DIFDELCMD < \PhiRF%%%\PhiRF asks to determine whether a given SLC loop admits a M\PhiRF, and the corresponding bounded decision problem restricts the search to M\PhiRFs of depth d, where the parameter d is part of the input.
Edit intent: fluency
Original:  Our research has led to a new representation for single-path loops, the difference polyhedron replacing the customary transition polyhedron .
Revised:  Our research has led to a new representation for single-path loops, the difference polyhedron replacing the customary transition polyhedron .
Edit intent: fluency
Original: In the study of the human connectome, the vertices and the edges of the network of the human brain is analyzed: the vertices of the graphs are the anatomically identified gray matter areas of the subjects;
Revised: In the study of the human connectome, the vertices and the edges of the network of the human brain are analyzed: the vertices of the graphs are the anatomically identified gray matter areas of the subjects;
Edit intent: fluency
Original: The increasing adoption of the Internet of Things (IoT) requires careful design and optimization of the next-generation mobile networks (a.k.a. 5G) in every aspect to efficiently cope with the diverse and wide range of IoT requirements.
Edit intent: coherence
Original:  In this paper, we propose a load aware initial cell search and selection scheme for 5G millimeter wave networks.
Revised:  In this paper, we propose a load-aware initial cell search and selection scheme for 5G millimeter wave networks.
Edit intent: fluency
Original:  In this paper, we propose a load aware initial cell search and selection scheme for 5G millimeter wave networks.
Revised:  In this paper, we propose a load aware initial cell search and selection scheme for 5G networks.
Edit intent: clarity
Original:  The results show that the proposed initial cell search and selection scheme is throughput optimal with a carefully optimized connection threshold.
Revised:  The results show that the proposed cell search and selection scheme is throughput optimal with a carefully optimized connection threshold.
Edit intent: clarity
Original: Much of human knowledge is encoded in the text, such as scientific publications, books, and the web.
Revised: Much of human knowledge is encoded in text, available in scientific publications, books, and the web.
Edit intent: clarity
Original:  Given the rapid growth of these resources, we need automated methods to extract such knowledge into formal, machine-processable structures, such as knowledge graphs.
Revised:  Given the rapid growth of these resources, we need automated methods to extract such knowledge into machine-processable structures, such as knowledge graphs.
Edit intent: clarity
Original:  An important task in this process is entity normalization (also called entity grounding, or resolution), which consists of mapping  entity mentions in text to canonical entities in well-known reference sets.
Revised:  An important task in this process is entity normalization , which consists of mapping entity mentions in text to canonical entities in well-known reference sets.
Edit intent: coherence
Original:  However, entity resolution is a challenging problem , since there often are many textual forms for a canonical entity  .
Revised:  However, entity resolution is a challenging problem ; there often are many textual forms for a canonical entity .
Edit intent: coherence
Original:  The problem is particularly acute in the scientific domain , such as biology .
Revised:  The problem is particularly acute in scientific domains , such as biology .
Edit intent: fluency
Original:  Yet an understanding of the dynamical mechanisms needed to generate a population code based on transient trajectories is still missing .
Revised:  Yet the dynamical mechanisms needed to generate a population code based on transient trajectories is still missing .
Edit intent: clarity
Original:  Yet an understanding of the dynamical mechanisms needed to generate a population code based on transient trajectories is still missing .
Revised:  Yet an understanding of the dynamical mechanisms needed to generate a population code based on transient trajectories have not been fully elucidated .
Edit intent: clarity
Original:  Here we show that a broad class of high-dimensional linear networks of recurrently connected units exhibits the properties needed for transient coding.
Revised:  Here we examine transient coding in a broad class of high-dimensional linear networks of recurrently connected units exhibits the properties needed for transient coding.
Edit intent: clarity
Original:   ZI is an attempt to provide a simple and accessible and multimodal open source platform for FEM based forward and inverse computations . Zeffiro is Italian for a 'gentle breeze'.
Revised:  Zeffiro is Italian for a 'gentle breeze'. ZI is an attempt to provide a simple and accessible and multimodal open source platform for FEM based forward and inverse computations . Zeffiro is Italian for a 'gentle breeze'.
Edit intent: coherence
Original:   ZI is an attempt to provide a simple and accessible and multimodal open source platform for FEM based forward and inverse computations . Zeffiro is Italian for a 'gentle breeze'.
Revised:  ZI is an attempt to provide a simple and accessible and multimodal open source platform for Finite Element Method based forward and inverse computations . Zeffiro is Italian for a 'gentle breeze'.
Edit intent: clarity
Original:   It allows one to (1) generate the FE mesh for a given multi-layer head model, (2) form a basis for computing a LF matrix and inverting a given set of measurements, and (3) to visualize the reconstructions on the FE mesh.
Revised:  Methods It allows one to (1) generate the FE mesh for a given multi-layer head model, (2) form a basis for computing a LF matrix and inverting a given set of measurements, and (3) to visualize the reconstructions on the FE mesh.
Edit intent: fluency
Original:   It allows one to (1) generate the FE mesh for a given multi-layer head model, (2) form a basis for computing a LF matrix and inverting a given set of measurements, and (3) to visualize the reconstructions on the FE mesh.
Revised:  It allows one to (1) generate the finite element mesh for a given multi-layer head model, (2) form a basis for computing a LF matrix and inverting a given set of measurements, and (3) to visualize the reconstructions on the FE mesh.
Edit intent: clarity
Original:  To tackle the issue of the high computational cost, ZI uses graphics processing unit (GPU) acceleration for each of the processing stages (1)-(3)  . In its current configuration, ZI includes forward solvers for E / MEG and linearized EIT LF matrices and and a set of inverse solvers utilizing the hierarchical Bayesian model (HBM).
Revised:  To tackle the issue of the high computational cost, ZI uses graphics processing unit acceleration for each of the processing stages (1)-(3) . In its current configuration, ZI includes forward solvers for E / MEG and linearized EIT LF matrices and and a set of inverse solvers utilizing the hierarchical Bayesian model (HBM).
Edit intent: clarity
Original:  To tackle the issue of the high computational cost, ZI uses graphics processing unit (GPU) acceleration for each of the processing stages (1)-(3)  . In its current configuration, ZI includes forward solvers for E / MEG and linearized EIT LF matrices and and a set of inverse solvers utilizing the hierarchical Bayesian model (HBM).
Revised:  To tackle the issue of the high computational cost, ZI uses graphics processing unit (GPU) acceleration for each of the processing stages (1)-(3) to tackle the issue of the high computational cost . In its current configuration, ZI includes forward solvers for E / MEG and linearized EIT LF matrices and and a set of inverse solvers utilizing the hierarchical Bayesian model (HBM).
Edit intent: coherence
Original:  To tackle the issue of the high computational cost, ZI uses graphics processing unit (GPU) acceleration for each of the processing stages (1)-(3)  . In its current configuration, ZI includes forward solvers for E / MEG and linearized EIT LF matrices and and a set of inverse solvers utilizing the hierarchical Bayesian model (HBM).
Revised:  To tackle the issue of the high computational cost, ZI uses graphics processing unit (GPU) acceleration for each of the processing stages (1)-(3) . In its current configuration, ZI includes forward solvers for electro- / MEG and linearized EIT LF matrices and and a set of inverse solvers utilizing the hierarchical Bayesian model (HBM).
Edit intent: fluency
Original:   In this paper, we describe the mathematics behind the ZI, describe the principle operations and usage of ZI, concentrating especially on EEG/MEG, and introduce some central points for the developer perspective.
Revised:  In this paper, we describe the mathematics behind the ZI, describe the principal operations and usage of ZI, concentrating especially on EEG/MEG, and introduce some central points for the developer perspective.
Edit intent: fluency
Original:   In this paper, we describe the mathematics behind the ZI, describe the principle operations and usage of ZI, concentrating especially on EEG/MEG, and introduce some central points for the developer perspective.
Revised:  In this paper, we describe the mathematics behind the ZI, describe the principle operations and usage and introduce some central points for the developer perspective.
Edit intent: coherence
Original: Background and Objectives This article introduces the Zeffiro interface (ZI)  for brain imaging.
Revised:  This article introduces the Zeffiro interface (ZI) for brain imaging.
Edit intent: coherence
Original:  ZI is an attempt to provide a simple and accessible and multimodal open source platform for Finite Element Method based forward and inverse computations in the Matlab environment.
Revised:  ZI is an attempt to provide a simple , accessible and multimodal open source platform for Finite Element Method based forward and inverse computations in the Matlab environment.
Edit intent: fluency
Original:  Methods It allows one to (1) generate the finite element mesh for a given multi-layer head model, (2) form a basis for computing a lead field matrix and inverting a given set of measurements , and (3) to visualize the reconstructions on the finite element mesh.
Revised:  It allows one to (1) generate the finite element mesh for a given multi-layer head model, (2) form a basis for computing a lead field matrix and inverting a given set of measurements , and (3) to visualize the reconstructions on the finite element mesh.
Edit intent: fluency
Original:  Methods It allows one to (1) generate the finite element mesh for a given multi-layer head model, (2) form a basis for computing a lead field matrix and inverting a given set of measurements , and (3) to visualize the reconstructions on the finite element mesh.
Revised:  Methods It allows one to (1) generate a given multi-compartment head model, (2) form a basis for computing a lead field matrix and inverting a given set of measurements , and (3) to visualize the reconstructions on the finite element mesh.
Edit intent: clarity
Original:  Methods It allows one to (1) generate the finite element mesh for a given multi-layer head model, (2) form a basis for computing a lead field matrix and inverting a given set of measurements , and (3) to visualize the reconstructions on the finite element mesh.
Revised:  Methods It allows one to (1) generate the finite element mesh for a given multi-layer head model, (2) to evaluate a lead field matrix and inverting a given set of measurements , and (3) to visualize the reconstructions on the finite element mesh.
Edit intent: clarity
Original:  ZI uses graphics processing unit acceleration for each of the processing stages (1)-(3) to tackle the issue of the high computational cost .
Revised:  ZI uses graphics processing unit acceleration for each of the processing stages (1)-(3) .
Edit intent: coherence
Original:  In its current configuration, ZI includes forward solvers for electro-/magnetoencephalography  and linearized electrical impedance tomography  as well as a set of inverse solvers utilizing the hierarchical Bayesian model (HBM).
Revised:  In its current configuration, ZI includes forward solvers for electro-/magnetoencephalography and linearized electrical impedance tomography as well as a set of inverse solvers based on the hierarchical Bayesian model (HBM).
Edit intent: clarity
Original:  Results GPU acceleration was found to be necessary, specifically, in the generation of the FE mesh and the evaluation of the LF matrix in order to achieve a feasibly short computation time.
Revised:  Results GPU acceleration was found to be essential in the generation of the FE mesh and the evaluation of the LF matrix in order to achieve a feasibly short computation time.
Edit intent: clarity
Original:  Results GPU acceleration was found to be necessary, specifically, in the generation of the FE mesh and the evaluation of the LF matrix in order to achieve a feasibly short computation time.
Revised:  Results GPU acceleration was found to be necessary, specifically, in the generation of the FE mesh and the LF matrix in order to achieve a feasibly short computation time.
Edit intent: clarity
Original: In this paper, we consider the subset selection problem for function f with constraint bound B which changes over time.
Revised: We consider the subset selection problem for function f with constraint bound B which changes over time.
Edit intent: clarity
Original: In this paper, we consider the subset selection problem for function f with constraint bound B which changes over time.
Revised: In this paper, we consider the subset selection problem for function f with constraint bound B that changes over time.
Edit intent: fluency
Original:  The new algorithm achieves the query complexity of O(N^{(2^{l-1}-1) / (2^{l}-1)}) . Moreover, it finds multiclaws\ge \left(_N N^{2^{l-1-1}{ 2^{l}-1}}}\right) \colon \to \le  for random functions, which are harder to find than multicollisions .
Revised:  The new algorithm achieves the query complexity of O(N^{(2^{l-1}-1) / (2^{l}-1)}) . Moreover, it finds multiclaws\ge \left(_N N^{2^{l-1-1}{ 2^{l}-1}}}\right) \colon \to \le for random functions, which is harder to find than multicollisions .
Edit intent: fluency
Original:  The new algorithm achieves the query complexity of O(N^{(2^{l-1}-1) / (2^{l}-1)}) . Moreover, it finds multiclaws\ge \left(_N N^{2^{l-1-1}{ 2^{l}-1}}}\right) \colon \to \le  for random functions, which are harder to find than multicollisions .
Revised:  The new algorithm achieves the query complexity of O(N^{(2^{l-1}-1) / (2^{l}-1)}) . Moreover, it finds multiclaws\ge \left(_N N^{2^{l-1-1}{ 2^{l}-1}}}\right) \colon \to \le for random functions, which are harder to find than a multicollision .
Edit intent: clarity
Original: Research in computer graphics has been in pursuit of realistic image generation for a long time.
Edit intent: clarity
Original:  Recent advances in machine learning with deep generative models have shown increasing success of closing the realism gap by using data-driven and learned components.
Revised:  Recent advances in Generative Adversarial Networks (GANs) have shown increasing success of closing the realism gap by using data-driven and learned components.
Edit intent: clarity
Original:  But they also raise challenges to visual forensics and model authentication .
Revised:  But they also raise challenges to visual forensics and model attribution .
Edit intent: clarity
Original:  We present the first study of learning GAN fingerprints towards image attribution : we systematically investigate the performance of classifying an image as real or GAN-generated.
Revised:  We present the first study of learning GAN fingerprints towards image attribution and using them to classify an image as real or GAN-generated.
Edit intent: clarity
Original:  Our experiments validate that GANs carry distinct model fingerprints and leave stable fingerprints to their generated images, which support image attribution .
Revised:  Our experiments validate that GANs carry distinct model fingerprints and leave stable fingerprints in their generated images, which support image attribution .
Edit intent: clarity
Original:  Even a single difference in GAN training initialization can result in different fingerprints, which enables fine-grained model authentication .
Revised:  Even a single difference in GAN training can result in different fingerprints, which enables fine-grained model authentication .
Edit intent: clarity
Original:  Fingerprint finetuning is effective in immunizing  five types of adversarial image perturbations . Comparisons also show our learned fingerprints consistently outperform several baselines in a variety of setups.
Revised:  Fingerprint finetuning is effective in immunizing against five types of adversarial image perturbations . Comparisons also show our learned fingerprints consistently outperform several baselines in a variety of setups.
Edit intent: fluency
Original: In the framework of abstract linear inverse problems in infinite-dimensional Hilbert space we discuss generic convergence behaviours of approximate solutions determined by means of general projection methods, namely outside the standard assumptions of Petrov-Galerkin truncation schemes.
Revised: In the framework of abstract linear inverse problems in infinitedimensional Hilbert space we discuss generic convergence behaviours of approximate solutions determined by means of general projection methods, namely outside the standard assumptions of Petrov-Galerkin truncation schemes.
Edit intent: fluency
Original:  The presentation is based on theoretical results together with a series of model examples , and it is corroborated by specific numerical experiments.
Revised:  The presentation is based on theoretical results together with a series of model examples and numerical experiments.
Edit intent: clarity
Original: Applications that exploit the architectural details of high performance computing (HPC) systems have become increasingly invaluable in academia and industry over the past two decades.
Revised: Applications that exploit the architectural details of high-performance computing (HPC) systems have become increasingly invaluable in academia and industry over the past two decades.
Edit intent: fluency
Original:  As these systems grow  small costs such as latency---the fixed cost of memory accesses---accumulate over the numerous iterations in a large simulation and become a significant barrier to performance.
Revised:  As these systems grow , small costs such as latency---the fixed cost of memory accesses---accumulate over the numerous iterations in a large simulation and become a significant barrier to performance.
Edit intent: fluency
Original:  As these systems grow  small costs such as latency---the fixed cost of memory accesses---accumulate over the numerous iterations in a large simulation and become a significant barrier to performance.
Revised:  As these systems grow small costs such as latency---due to the fixed cost of memory accesses---accumulate over the numerous iterations in a large simulation and become a significant barrier to performance.
Edit intent: clarity
Original:  The swept time-space decomposition rule is a communication-avoiding technique for time-stepping stencil update formulas that attempts to sidestep a portion of the latency costs.
Revised:  The swept time-space decomposition rule is a communication-avoiding technique for time-stepping stencil update formulas that attempts to reduce latency costs.
Edit intent: clarity
Original:  This work extends the swept rule by targeting heterogeneous, CPU/GPU architectures representative of current and future HPC systems.
Revised:  This work extends the swept rule by targeting heterogeneous, CPU/GPU architectures representing current and future HPC systems.
Edit intent: fluency
Original:  We show that the swept rule produces a 4--18x speedup with the heat equation and a 1.5-3x speedup with the Euler equations  using the same processors and work distribution  .
Revised:  The swept rule produces a 4--18x speedup with the heat equation and a 1.5-3x speedup with the Euler equations using the same processors and work distribution .
Edit intent: coherence
Original:  We show that the swept rule produces a 4--18x speedup with the heat equation and a 1.5-3x speedup with the Euler equations  using the same processors and work distribution  .
Revised:  We show that the swept rule produces a 4--18x speedup with the heat equation and a 1.5-3x speedup with the Euler equations , using the same processors and work distribution .
Edit intent: fluency
Original:  These results demonstrate the potential effectiveness of the swept rule for different equations and numerical schemes on massively parallel compute systems that incur substantial latency costs.
Revised:  These results show the potential effectiveness of the swept rule for different equations and numerical schemes on massively parallel compute systems that incur substantial latency costs.
Edit intent: fluency
Original:  These results demonstrate the potential effectiveness of the swept rule for different equations and numerical schemes on massively parallel compute systems that incur substantial latency costs.
Revised:  These results demonstrate the potential effectiveness of the swept rule for different equations and numerical schemes on massively parallel computing systems that incur substantial latency costs.
Edit intent: fluency
Original:  By exploiting the bilinearity structure of the expected adjacency matrix of the network , we separate its null eigenspace, and reduce the exact description of the  model to a smaller vector space.
Revised:  By exploiting the bilinear structure of the expected adjacency matrix of the network , we separate its null eigenspace, and reduce the exact description of the model to a smaller vector space.
Edit intent: fluency
Original:  By exploiting the bilinearity structure of the expected adjacency matrix of the network , we separate its null eigenspace, and reduce the exact description of the  model to a smaller vector space.
Revised:  By exploiting the bilinearity structure of the matrix representation of the generative model , we separate its null eigenspace, and reduce the exact description of the model to a smaller vector space.
Edit intent: clarity
Original:  By exploiting the bilinearity structure of the expected adjacency matrix of the network , we separate its null eigenspace, and reduce the exact description of the  model to a smaller vector space.
Revised:  By exploiting the bilinearity structure of the expected adjacency matrix of the network , we separate its null eigenspace, and reduce the exact description of the generative model to a smaller vector space.
Edit intent: clarity
Original:  The proposed scheme  will be very useful in the study of dynamical processes on networks, as well as in the understanding of  models to come, according to the provided universal classification.
Revised:  The proposed scheme will be very useful in the study of dynamical processes on networks, as well as in the understanding of models to come, according to the provided classification.
Edit intent: clarity
Original:  The NVIDIA Tesla V100 GPU introduced a specialized functional unit called the Tensor Core to meet growing demand for higher performance on this workload.
Revised:  The NVIDIA Tesla V100 GPU introduced a specialized functional unit , the "tensor core", that helps meet the growing demand for higher performance on this workload.
Edit intent: clarity
Original:  In this paper , we comprehensively investigate NVIDIA's Tensor Core implementation found in Volta and Turing architectures and propose an architectural model for it.
Revised:  In this paper , we comprehensively investigate NVIDIA's Volta and Turing architectures and propose an architectural model for it.
Edit intent: coherence