wanyu/IteraTeR_v2 huggingface dataset:
Original:  Furthermore, this survey provides a starting point for valuable pedagogic baseline data  in the context of substantial computer science curriculum reform in UK schools, as well as increasingly scrutiny of teaching excellence and graduate employability for UK universities.
Revised:  Furthermore, this survey provides a starting point for valuable pedagogic baseline data in the context of substantial computer science curriculum reform in UK schools, as well as increasing scrutiny of teaching excellence and graduate employability for UK universities.
Edit intent: fluency
Original:  In this paper a lower bound of the problem is presented and a formula is proposed which yields a no-hole \lambda-L(k, k-1, \ldots, 2, 1)-labeling of square grid with at most 9{8} approximation ratio .
Revised:  In this paper a lower bound of the problem is presented and a formula is proposed which yields a \lambda-L(k, k-1, \ldots, 2, 1)-labeling of square grid with at most 9{8} approximation ratio .
Edit intent: clarity
Original:  In this paper a lower bound of the problem is presented and a formula is proposed which yields a no-hole \lambda-L(k, k-1, \ldots, 2, 1)-labeling of square grid with at most 9{8} approximation ratio .
Revised:  In this paper a lower bound of the problem is presented and a formula is proposed which yields a no-hole \lambda-L(k, k-1, \ldots, 2, 1)-labeling of square grid , with approximation ratio at most 9{8} approximation ratio .
Edit intent: fluency
Original:  To this end  we examine the trade-off between accuracy and speed for different architectures and additionally propose to use an L1 penalty on the filter activations to further encourage sparsity in the intermediate representations.
Revised:  To this end , we examine the trade-off between accuracy and speed for different architectures and additionally propose to use an L1 penalty on the filter activations to further encourage sparsity in the intermediate representations.
Edit intent: fluency
Original:  We demonstrate the efficacy of our approach on the KITTI object detection benchmark and show that Vote3Deep models with as few as three layers outperform the previous state of the art in both laser and laser-vision based approaches across the board by margins of up to 40\% while remaining highly competitive in terms of processing time.
Revised:  We demonstrate the efficacy of our approach on the KITTI object detection benchmark and show that Vote3Deep models with as few as three layers outperform the previous state of the art in both laser and laser-vision based approaches by margins of up to 40\% while remaining highly competitive in terms of processing time.
Edit intent: clarity
Original:  We also construct a simplified description in terms of stochastic differential equations to approximate the individual-based model.
Revised:  We also propose a simplified description in terms of stochastic differential equations to approximate the individual-based model.
Edit intent: clarity
Original:  This includes a proof of the fact that every very well-covered graph is localizable and characterizations of localizable graphs within the classes of line graphs, triangle-free graphs, C4-free graphs, and cubic graphs, each leading to a polynomial time recognition algorithm for localizable graphs in the class .
Revised:  Our results include a proof of the fact that every very well-covered graph is localizable and characterizations of localizable graphs within the classes of line graphs, triangle-free graphs, C4-free graphs, and cubic graphs, each leading to a polynomial time recognition algorithm for localizable graphs in the class .
Edit intent: clarity
Original:  This includes a proof of the fact that every very well-covered graph is localizable and characterizations of localizable graphs within the classes of line graphs, triangle-free graphs, C4-free graphs, and cubic graphs, each leading to a polynomial time recognition algorithm for localizable graphs in the class .
Revised:  This includes a proof of the fact that every very well-covered graph is localizable and characterizations of localizable graphs within the classes of line graphs, triangle-free graphs, C_4-free graphs, and cubic graphs, each leading to a polynomial time recognition algorithm for localizable graphs in the class .
Edit intent: clarity
Original:  This includes a proof of the fact that every very well-covered graph is localizable and characterizations of localizable graphs within the classes of line graphs, triangle-free graphs, C4-free graphs, and cubic graphs, each leading to a polynomial time recognition algorithm for localizable graphs in the class .
Revised:  This includes a proof of the fact that every very well-covered graph is localizable and characterizations of localizable graphs within the classes of line graphs, triangle-free graphs, C4-free graphs, and cubic graphs, each leading to a polynomial time recognition algorithm .
Edit intent: clarity
Original:  On the negative side, we establish several hardness results, including NP-hardness of recognizing localizable graphs within  weakly chordal graphs, complements of line graphs, and graphs of independence number three.
Revised:  On the negative side, we prove NP-hardness of recognizing localizable graphs within weakly chordal graphs, complements of line graphs, and graphs of independence number three.
Edit intent: clarity
Original:  On the negative side, we establish several hardness results, including NP-hardness of recognizing localizable graphs within  weakly chordal graphs, complements of line graphs, and graphs of independence number three.
Revised:  On the negative side, we establish several hardness results, including NP-hardness of recognizing localizable graphs within the classes of weakly chordal graphs, complements of line graphs, and graphs of independence number three.
Edit intent: clarity
Original:  Furthermore, using localizable graphs we disprove a conjecture due to Zaare-Nahandi from 2015 about k-partite well-covered graphs having all maximal cliques of size k  .
Revised:  Furthermore, using localizable graphs we disprove a conjecture due to Zaare-Nahandi about k-partite well-covered graphs having all maximal cliques of size k .
Edit intent: clarity
Original:  For graphs with n vertices and average degree k, we show that on p processors, MFBC performs a factor of p^{1/3} less communication than known alternatives when k=n/p^{2/3}.
Revised:  For graphs with n vertices and average degree k, we show that on p processors, MFBC performs a factor of p^{1/3} less communication on p processors than the best known alternatives, for graphs with n vertices and average degree k=n/p^{2/3}.
Edit intent: clarity
Original:  The library automatically searches a space of distributed data decompositions and sparse matrix multiplication algorithms .
Revised:  It automatically searches a space of distributed data decompositions and sparse matrix multiplication algorithms .
Edit intent: clarity
Original:  The resulting code outperforms the well-known CombBLAS library by factors of up to 8 and shows more robust performance.
Revised:  The resulting code outperforms the well-known CombBLAS library by up to 8x and shows more robust performance.
Edit intent: clarity
Original:  Our design methodology is general and readily extensible to other graph problems.
Revised:  Our design methodology is readily extensible to other graph problems.
Edit intent: clarity
Original: Focal seizures are episodes of pathological brain activity that  arise from a localised area of the brain.
Revised: Focal seizures are episodes of pathological brain activity that appear to arise from a localised area of the brain.
Edit intent: clarity
Original:  The onset patterns of focal seizure activity have been studied intensively, and they can largely be distinguished into two types  .
Revised:  The onset patterns of focal seizure activity have been studied intensively, and they have largely been distinguished into two types .
Edit intent: clarity
Original:  Using a previously established computational model of neocortical tissue, we show that the two types of onset pattern can be distinguished based on the excitability of the "healthy" surrounding tissue, which by itself does not generate seizures, but can support seizure activity when incited.
Revised:  Here, we use a previously established computational model of neocortical tissue, we show that the two types of onset pattern can be distinguished based on the excitability of the "healthy" surrounding tissue, which by itself does not generate seizures, but can support seizure activity when incited.
Edit intent: coherence
Original:  The difference in surrounding tissue excitability also predicts a difference in surgical outcomes for the two patterns in the model, which appears to be confirmed by clinical literature .
Revised:  In our simulations, the difference in surrounding tissue excitability also predicts a difference in surgical outcomes for the two patterns in the model, which appears to be confirmed by clinical literature .
Edit intent: clarity
Original:  The difference in surrounding tissue excitability also predicts a difference in surgical outcomes for the two patterns in the model, which appears to be confirmed by clinical literature .
Revised:  The difference in surrounding tissue excitability also predicts a difference in surgical outcomes .
Edit intent: clarity
Original: In the present paper, we study the synchronization in a model of neural network which can be considered as a noisy version of the model of Mirollo and Strogatz (1990), namely, fully-connected and totally excitatory integrate and fire neural network with Gaussian white noises.
Revised: We study the synchronization in a model of neural network which can be considered as a noisy version of the model of Mirollo and Strogatz (1990), namely, fully-connected and totally excitatory integrate and fire neural network with Gaussian white noises.
Edit intent: clarity
Original: In the present paper, we study the synchronization in a model of neural network which can be considered as a noisy version of the model of Mirollo and Strogatz (1990), namely, fully-connected and totally excitatory integrate and fire neural network with Gaussian white noises.
Revised: In the present paper, we study the synchronization of fully-connected and totally excitatory integrate and fire neural network with Gaussian white noises.
Edit intent: clarity
Original: In the present paper, we study the synchronization in a model of neural network which can be considered as a noisy version of the model of Mirollo and Strogatz (1990), namely, fully-connected and totally excitatory integrate and fire neural network with Gaussian white noises.
Revised: In the present paper, we study the synchronization in a model of neural network which can be considered as a noisy version of the model of Mirollo and Strogatz (1990), namely, fully-connected and totally excitatory integrate and fire neural networks in presence of Gaussian white noises.
Edit intent: clarity
Original:  The Courant-Friedrichs-Lewy (CFL) limit of the final scheme is provided by the theory, and can be extended with a simple perturbation of the coefficients of the reduced models . Numerical tests confirm the stability of the proposed method, and its potential to accelerate multiscale FDTD simulations.
Revised:  The Courant-Friedrichs-Lewy (CFL) limit of the fine mesh. With a simple perturbation of the coefficients of the reduced models . Numerical tests confirm the stability of the proposed method, and its potential to accelerate multiscale FDTD simulations.
Edit intent: clarity
Original: In dense clusters of neurons  in nuclei, cells may interconnect via soma-to-soma interactions, in addition to conventional synaptic connections.
Revised: We assume that, within the dense clusters of neurons in nuclei, cells may interconnect via soma-to-soma interactions, in addition to conventional synaptic connections.
Edit intent: clarity
Original: In dense clusters of neurons  in nuclei, cells may interconnect via soma-to-soma interactions, in addition to conventional synaptic connections.
Revised: In dense clusters of neurons that can be found in nuclei, cells may interconnect via soma-to-soma interactions, in addition to conventional synaptic connections.
Edit intent: clarity
Original:  The inputs to the clusters are  normalised by adjusting the external arrival rates of spikes to each cluster , and then apply this architectures to learning from multi-channel datasets.
Revised:  The inputs to the clusters are first normalised by adjusting the external arrival rates of spikes to each cluster , and then apply this architectures to learning from multi-channel datasets.
Edit intent: fluency
Original:  The inputs to the clusters are  normalised by adjusting the external arrival rates of spikes to each cluster , and then apply this architectures to learning from multi-channel datasets.
Revised:  The inputs to the clusters are normalised by adjusting the external arrival rates of spikes to each cluster . Then we apply this architecture to learning from multi-channel datasets.
Edit intent: coherence
Original:  We present numerical results based on both images and sensor based data that show the value of this RNN-MLA for deep learning.
Revised:  Numerical results based on both images and sensor based data that show the value of this RNN-MLA for deep learning.
Edit intent: coherence
Original:  We present numerical results based on both images and sensor based data that show the value of this RNN-MLA for deep learning.
Revised:  We present numerical results based on both images and sensor based data , show the value of this RNN-MLA for deep learning.
Edit intent: fluency
Original:  We present numerical results based on both images and sensor based data that show the value of this RNN-MLA for deep learning.
Revised:  We present numerical results based on both images and sensor based data that show the value of this novel architecture for deep learning.
Edit intent: clarity
Original: A substring Q of a string S is called a shortest unique substring (SUS) for position p  in S, if Q occurs exactly once in S, this occurrence of Q contains position p, ] and every substring of S which contains position p  and is shorter than Q occurs at least twice in S.
Revised: A substring Q of a string S is called a shortest unique substring (SUS) for position p in S, if Q occurs exactly once in S, this occurrence of Q contains position p, ], and every substring of S which contains position p and is shorter than Q occurs at least twice in S.
Edit intent: fluency
Original:   ]  ]  There exist optimal O(n)-time preprocessing scheme which answers queries in optimal O(k) time  , where n is the length of S and k is the number of SUSs for a query position .
Revised:  ] ] There exist optimal O(n)-time preprocessing scheme which answers queries in optimal O(k) time , where n is the length of S and k is the number of outputs for a given query .
Edit intent: clarity
Original:  In this paper, we reveal structural, combinatorial properties underlying this problem: Namely, we show that the number of intervals in S that correspond to  SUSs for all  positions in S is less than 1.5n .
Revised:  In this paper, we reveal structural, combinatorial properties underlying the SUS problem: Namely, we show that the number of intervals in S that correspond to SUSs for all positions in S is less than 1.5n .
Edit intent: coherence
Original:  We introduce a new invariant of strongly connected directed graphs - minimal number of vertices or edges necessary to remove to make remaining graphs not strongly connected.
Revised:  We discuss invariants of strongly connected directed graphs - minimal number of vertices or edges necessary to remove to make remaining graphs not strongly connected.
Edit intent: clarity
Original:   The main challenge in applying these schemes to large-scale problems is the computational complexity and memory demand resulting from a lifting of the image to a large structured matrix.
Revised:  The main challenge in applying these schemes to large-scale problems is the computational complexity and memory demand resulting from a lifting the image data to a large structured matrix.
Edit intent: clarity
Original:   The main challenge in applying these schemes to large-scale problems is the computational complexity and memory demand resulting from a lifting of the image to a large structured matrix.
Revised:  The main challenge in applying these schemes to large-scale problems is the computational complexity and memory demand resulting from a lifting of the image to a large scale matrix.
Edit intent: clarity
Original:  We introduce a fast and memory efficient  algorithm that exploits the convolution structure of the structured matrix to work in the original non-lifted domain, thus considerably reducing the complexity.
Revised:  We introduce a fast and memory efficient algorithm that exploits the convolutional structure of the structured matrix to work in the original non-lifted domain, thus considerably reducing the complexity.
Edit intent: clarity
Original:  We introduce a fast and memory efficient  algorithm that exploits the convolution structure of the structured matrix to work in the original non-lifted domain, thus considerably reducing the complexity.
Revised:  We introduce a fast and memory efficient algorithm that exploits the convolution structure of the lifted matrix to work in the original non-lifted domain, thus considerably reducing the complexity.
Edit intent: clarity
Original:  We introduce a fast and memory efficient  algorithm that exploits the convolution structure of the structured matrix to work in the original non-lifted domain, thus considerably reducing the complexity.
Revised:  We introduce a fast and memory efficient algorithm that exploits the convolution structure of the structured matrix to work in the original un-lifted domain, thus considerably reducing the complexity.
Edit intent: clarity
Original: Fourier domain structured low-rank matrix priors are emerging as powerful alternatives to traditional image recovery methods such as total variation (TV) and wavelet regularization.
Revised: Fourier domain structured low-rank matrix priors are emerging as powerful alternatives to traditional image recovery methods such as total variation and wavelet regularization.
Edit intent: clarity
Original:  The main challenge in applying these schemes to large-scale problems is the computational complexity and memory demand resulting from a lifting the image data to a large scale matrix.
Revised:  The main challenge in applying these schemes to large-scale problems is the computational complexity and memory demand resulting from lifting the image data to a large scale matrix.
Edit intent: fluency
Original: Birth defects such as cleft palate and craniosynostosisaffect the correct development of the skull , producing morphological malformations not specifically controlled by genetic or epigenetic factors.
Revised: The premature fusion of cranial bones, craniosynostosis, affects the correct development of the skull , producing morphological malformations not specifically controlled by genetic or epigenetic factors.
Edit intent: clarity
Original: Birth defects such as cleft palate and craniosynostosisaffect the correct development of the skull , producing morphological malformations not specifically controlled by genetic or epigenetic factors.
Revised: Birth defects such as cleft palate and craniosynostosisaffect the correct development of the skull producing morphological malformations not specifically controlled by genetic or epigenetic factors.
Edit intent: fluency
Original:  To assess the susceptibility of each craniofacial suture to be lost , we used a network model of the skull to quantify the link reliability (an index based on stochastic block modeling and Bayesian inference) of each articulation.
Revised:  To assess the susceptibility of each craniofacial articulation to close prematurely , we used a network model of the skull to quantify the link reliability (an index based on stochastic block modeling and Bayesian inference) of each articulation.
Edit intent: clarity
Original:  Our findings indicate that skull bone arrangement might act as an epigenetic factor, predisposing some sutures to be lost both in normal and pathological development,  also affecting the long-term evolution of the skull.
Revised:  Our findings suggest that the topological arrangement of skull bones might act as an epigenetic factor, predisposing some sutures to be lost both in normal and pathological development, also affecting the long-term evolution of the skull.
Edit intent: clarity
Original:  Our findings indicate that skull bone arrangement might act as an epigenetic factor, predisposing some sutures to be lost both in normal and pathological development,  also affecting the long-term evolution of the skull.
Revised:  Our findings indicate that skull bone arrangement might act as an epigenetic factor, predisposing some sutures to be lost both in normal and pathological development, and also affecting the long-term evolution of the skull.
Edit intent: coherence
Original:  The vertices in R (similarly, in H) are called residents (resp., hospitals): each resident seeks to be matched to a hospital while each hospital h(a) }\ge  seeks cap( h ) \ge 1 many residents to be matched to it.
Revised:  The vertices in R (similarly, in H) are called residents (resp., hospitals): each resident seeks to be matched to \mathsf{cap(a) }\ge seeks cap( h ) \ge 1 many residents to be matched to it.
Edit intent: clarity
Original:  We consider the problem of computing a popular matching in G - a matching M is popular if M cannot lose an election to any other matching where vertices cast votes for one matching versus another.
Revised:  We consider the problem of computing a popular matching in G -- a matching M is popular if M cannot lose an election to any other matching where vertices cast votes for one matching versus another.
Edit intent: fluency
Original:  We consider the problem of computing a popular matching in G - a matching M is popular if M cannot lose an election to any other matching where vertices cast votes for one matching versus another.
Revised:  We consider the problem of computing a popular matching in G - a matching M is popular if M cannot lose an election to any matching where vertices cast votes for one matching versus another.
Edit intent: clarity
Original:  This is a simple extension of the classical Gale-Shapley algorithm and we prove its correctness via linear programming.
Revised:  This is an extension of the classical Gale-Shapley algorithm and we prove its correctness via linear programming.
Edit intent: clarity
Original: Using elementary cellular automata as an example, a novel, information-based classification of complex systems is proposed that circumvents the problems associated with isolating the complexity generated as a product of an initial state from that which is intrinsic to a dynamical rule  .
Revised: A novel, information-based classification of complex systems is proposed that circumvents the problems associated with isolating the complexity generated as a product of an initial state from that which is intrinsic to a dynamical rule .
Edit intent: clarity
Original: Using elementary cellular automata as an example, a novel, information-based classification of complex systems is proposed that circumvents the problems associated with isolating the complexity generated as a product of an initial state from that which is intrinsic to a dynamical rule  .
Revised: Using elementary cellular automata as an example, a novel, information-based classification of elementary cellular automata is proposed that circumvents the problems associated with isolating the complexity generated as a product of an initial state from that which is intrinsic to a dynamical rule .
Edit intent: clarity