wanyu/IteraTeR_v2 huggingface dataset:
Original:  Our system first splits the documents into topical segments, "visualizes" the matching between the query and the segments, and then feeds the interaction matrix into a Neu-IR model, DeepTileBars, to obtain the final ranking score .
Revised:  Our system first splits the documents into topical segments, "visualizes" the matching between the query and the segments, and then feeds an interaction matrix into a Neu-IR model, DeepTileBars, to obtain the final ranking score .
Edit intent: fluency
Original:  Our system first splits the documents into topical segments, "visualizes" the matching between the query and the segments, and then feeds the interaction matrix into a Neu-IR model, DeepTileBars, to obtain the final ranking score .
Revised:  Our system first splits the documents into topical segments, "visualizes" the matching between the query and the segments, and then feeds the interaction matrix into a Neu-IR model, DeepTileBars, to obtain the final ranking scores .
Edit intent: fluency
Original:  DeepTileBars models the relevance signals happening at different granularities in a document's topic hierarchy.
Revised:  DeepTileBars models the relevance signals occurring at different granularities in a document's topic hierarchy.
Edit intent: fluency
Original:  It thus better captures the discourse structure of the document and the matching patterns.
Revised:  It better captures the discourse structure of the document and the matching patterns.
Edit intent: coherence
Original:  It thus better captures the discourse structure of the document and the matching patterns.
Revised:  It thus better captures the discourse structure of a document and thus the matching patterns.
Edit intent: coherence
Original: In this paper, we propose a new hybridizable discontinuous Galerkin (HDG) method for steady-state diffusion problems .
Revised: In this paper, hybridizable discontinuous Galerkin (HDG) method for steady-state diffusion problems .
Edit intent: clarity
Original:  Numerical results are present to validate our theoretical results.
Revised:  Numerical results are presented to validate our theoretical results.
Edit intent: fluency
Original: Identification of high affinity drug-target interactions (DTI) is a major research question in drug discovery.
Revised: Identification of high affinity drug-target interactions is a major research question in drug discovery.
Edit intent: clarity
Original:  Such a benchmark set should contain hard instances in particular, but so far, the standard approach to produce instances has been to sample values randomly uniformly .
Revised:  Such a benchmark set should contain hard instances in particular, but so far, the standard approach to produce instances has been to sample values randomly from a uniform distribution .
Edit intent: clarity
Original: In this paper, we address the scheduling and resource allocation problem for uplink OFDMA in IEEE 802.11ax WLANs.
Revised: In this paper, we study the scheduling and resource allocation problem for uplink OFDMA in IEEE 802.11ax WLANs.
Edit intent: clarity
Original:  The OFDMA resource allocation problem for 802.11ax is inherently difficult to solve because consecutive subcarriers are grouped into resource units, and each user is assigned to one resource unit at most.
Revised:  The OFDMA resource allocation problem for 802.11ax is inherently difficult to solve because consecutive subcarriers are grouped into resource units, and every user is assigned to one resource unit at most.
Edit intent: fluency
Original:  In order to provide long-term performance guarantees, we propose stochastic utility maximisation subject to both peak and average power constraints  and solve the problem using Lyapunov optimisation .
Revised:  In order to provide long-term performance guarantees, we focus on maximizing the utility of average user rates subject to both peak and average power constraints and solve the problem using Lyapunov optimisation .
Edit intent: clarity
Original:  In order to provide long-term performance guarantees, we propose stochastic utility maximisation subject to both peak and average power constraints  and solve the problem using Lyapunov optimisation .
Revised:  In order to provide long-term performance guarantees, we propose stochastic utility maximisation subject to both peak and average power constraints , and solve the problem using Lyapunov optimisation .
Edit intent: fluency
Original:  In order to provide long-term performance guarantees, we propose stochastic utility maximisation subject to both peak and average power constraints  and solve the problem using Lyapunov optimisation .
Revised:  In order to provide long-term performance guarantees, we propose stochastic utility maximisation subject to both peak and average power constraints and solve the problem using Lyapunov optimization .
Edit intent: fluency
Original: In this paper, we study the scheduling and resource allocation problem for uplink OFDMA in  IEEE 802.11ax WLANs.
Revised: We consider the scheduling and resource allocation problem for uplink OFDMA in IEEE 802.11ax WLANs.
Edit intent: clarity
Original: In this paper, we study the scheduling and resource allocation problem for uplink OFDMA in  IEEE 802.11ax WLANs.
Revised: In this paper, we study the scheduling and resource allocation problem in IEEE 802.11ax WLANs.
Edit intent: coherence
Original:  The OFDMA resource allocation problem for 802.11ax is inherently difficult to solve because consecutive subcarriers are grouped into resource units, and every user is assigned to one resource unit at most .
Revised:  The OFDMA resource allocation problem is non-convex and difficult to solve because consecutive subcarriers are grouped into resource units, and every user is assigned to one resource unit at most .
Edit intent: clarity
Original:  The OFDMA resource allocation problem for 802.11ax is inherently difficult to solve because consecutive subcarriers are grouped into resource units, and every user is assigned to one resource unit at most .
Revised:  The OFDMA resource allocation problem for 802.11ax is inherently difficult to solve .
Edit intent: coherence
Original:  However, since power in the uplink is allocated to each user individually, the instantaneous utility maximisation problem can be formulated as an assignment problem , andhence, solved in polynomial time by the Hungarian algorithm.
Revised:  However, because users have independent uplink power budgets, the problem of maximizing the utility of instantaneous user rates can be formulated as an assignment problem , andhence, solved in polynomial time by the Hungarian algorithm.
Edit intent: clarity
Original:  However, since power in the uplink is allocated to each user individually, the instantaneous utility maximisation problem can be formulated as an assignment problem , andhence, solved in polynomial time by the Hungarian algorithm.
Revised:  However, since power in the uplink is allocated to each user individually, the instantaneous utility maximisation problem can be formulated as an assignment problem and, hence, can be efficiently solved by the Hungarian algorithm.
Edit intent: clarity
Original:  In order to provide long-term performance guarantees, we focus on maximizing the utility of  average user rates subject to both peak and average power constraints, and solve the problem using Lyapunov optimization .
Revised:  In order to provide long-term performance guarantees, we focus on maximizing the utility of average user rates subject to average rate and power constraints using Lyapunov optimization .
Edit intent: clarity
Original:  Due to the peculiar subcarrier allocation model of IEEE 802.11ax, the OFDMA resource allocation problem is  non-convex and difficult to solve  .
Revised:  Due to the peculiar subcarrier allocation model of IEEE 802.11ax, the OFDMA resource allocation problem is known to be non-convex and difficult to solve .
Edit intent: coherence
Original:  However, because users have independent uplink power budgets, the problem of maximizing the utility of instantaneous user rates can be formulated as an assignment problem and, hence, can be efficiently solved by the Hungarian algorithm .
Revised:  However, because users have independent uplink power budgets, the problem of maximizing the utility of instantaneous user rates can be formulated as an assignment problem , and hence can be solved using the Hungarian method .
Edit intent: clarity
Original:  Because many of these system identification algorithms were developed in other disciplines, they seem very different superficially and bear little obvious relationship with each other.
Revised:  Because many of these system identification algorithms were developed in other disciplines, they seem very different superficially and bear little relationship with each other.
Edit intent: clarity
Original:  However, accurately classifying skin lesions  , especially in the early stage  , is extremely challenging via dermatologists' observation .
Revised:  However, accurately classifying skin lesions , especially in the early stage , is extremely challenging for the dermatologists .
Edit intent: clarity
Original:  Hence, the discovery of reliable biomarkers for melanoma diagnosis will be meaningful  .
Revised:  Hence, the discovery of reliable biomarkers will be meaningful .
Edit intent: clarity
Original:  Hence, the discovery of reliable biomarkers for melanoma diagnosis will be meaningful  .
Revised:  Hence, the discovery of reliable biomarkers for melanoma diagnosis will be meaningful for melanoma diagnosis .
Edit intent: coherence
Original:  Recent years,  deep learning empowered computer-assisted diagnosis has been shown its value in medical imaging-based decision making.
Revised:  Recent years, the value of deep learning empowered computer-assisted diagnosis has been shown its value in medical imaging-based decision making.
Edit intent: clarity
Original:  Recent years,  deep learning empowered computer-assisted diagnosis has been shown its value in medical imaging-based decision making.
Revised:  Recent years, deep learning empowered computer-assisted diagnose has been shown its value in medical imaging-based decision making.
Edit intent: fluency
Original:  Recent years,  deep learning empowered computer-assisted diagnosis has been shown its value in medical imaging-based decision making.
Revised:  Recent years, deep learning empowered computer-assisted diagnosis has been shown in biomedical imaging based decision making.
Edit intent: clarity
Original:  However, lots of research focus on improving disease detection accuracy but not exploring the evidence of pathology.
Revised:  However, much research focuses on improving disease detection accuracy but not exploring the evidence of pathology.
Edit intent: clarity
Original:  Firstly, we propose an accurate neural network architecture to classify skin lesion .
Revised:  Firstly, we propose an accurate neural network architecture to classify skin lesions .
Edit intent: fluency
Original:  Secondly, we utilize a prediction difference analysis method that examining each patch on the image through patch wised corrupting for detecting the biomarkers.
Revised:  Secondly, we utilize a prediction difference analysis method that examines each patch on the image through patch wised corrupting for detecting the biomarkers.
Edit intent: fluency
Original:  Secondly, we utilize a prediction difference analysis method that examining each patch on the image through patch wised corrupting for detecting the biomarkers.
Revised:  Secondly, we utilize a prediction difference analysis method that examining each patch on the image through patch-wised corrupting to detect the biomarkers.
Edit intent: fluency
Original:  The findings might be significant to guide clinical diagnosis.
Revised:  The findings can be significant and useful to guide clinical diagnosis.
Edit intent: clarity
Original:  From aligning proteins in computational biology, to  de-anonymization of social networks, to recognition tasks in computer vision , this problem has applications in many diverse areas.
Revised:  From aligning proteins in computational biology, to the de-anonymization of social networks, to recognition tasks in computer vision , this problem has applications in many diverse areas.
Edit intent: fluency
Original:  From aligning proteins in computational biology, to  de-anonymization of social networks, to recognition tasks in computer vision , this problem has applications in many diverse areas.
Revised:  From aligning proteins in computational biology, to de-anonymization of social networks, as well as recognition tasks in computer vision , this problem has applications in many diverse areas.
Edit intent: coherence
Original:  Through extensive numerical experiments , we show that SPECTRE is able to recover high-accuracy alignments on both synthetic and real-world networks, and outperforms other algorithms in the seedless case .
Revised:  Through extensive numerical simulations , we show that SPECTRE is able to recover high-accuracy alignments on both synthetic and real-world networks, and outperforms other algorithms in the seedless case .
Edit intent: clarity
Original:  Through extensive numerical experiments , we show that SPECTRE is able to recover high-accuracy alignments on both synthetic and real-world networks, and outperforms other algorithms in the seedless case .
Revised:  Through extensive numerical experiments , we show that SPECTRE allows for fast run times and high accuracy on large synthetic and real-world networks, and outperforms other algorithms in the seedless case .
Edit intent: clarity
Original:  Two two-step symmetric methods are proposed and their long time behaviour is shown not only in a normal magnetic field but also in a strong magnetic field .
Revised:  A two-step symmetric methods are proposed and their long time behaviour is shown not only in a normal magnetic field but also in a strong magnetic field .
Edit intent: fluency
Original:  Two two-step symmetric methods are proposed and their long time behaviour is shown not only in a normal magnetic field but also in a strong magnetic field .
Revised:  Two two-step symmetric method is proposed and its long time behaviour is shown not only in a normal magnetic field but also in a strong magnetic field .
Edit intent: fluency
Original:  Two two-step symmetric methods are proposed and their long time behaviour is shown not only in a normal magnetic field but also in a strong magnetic field .
Revised:  Two two-step symmetric methods are proposed and their long time behaviour is shown not only in a normal magnetic feld but also in a strong magnetic field .
Edit intent: fluency
Original:  Two two-step symmetric methods are proposed and their long time behaviour is shown not only in a normal magnetic field but also in a strong magnetic field .
Revised:  Two two-step symmetric methods are proposed and their long time behaviour is shown not only in a normal magnetic field but also in a strong magnetic feld .
Edit intent: fluency
Original:  It is obtained from the analysis that the first method has an additional superiority which the Boris method does not possess, and the second method has better long time conservations than the variational method which was researched recently in the literature.
Revised:  It is obtained from the analysis that the method has better long time conservations than the variational method which was researched recently in the literature.
Edit intent: clarity
Original:  GIGAQBX is a fast high-order scheme for evaluation of layer potentials based on Quadrature by Expansion (`QBX') using local expansions formed by Fast Multipole Method (FMM) for accurate near or on-surface evaluation .
Revised:  GIGAQBX is a fast high-order scheme for evaluation of layer potentials based on Quadrature by Expansion (`QBX') using local expansions formed via the Fast Multipole Method (FMM) for accurate near or on-surface evaluation .
Edit intent: clarity
Original:  GIGAQBX is a fast high-order scheme for evaluation of layer potentials based on Quadrature by Expansion (`QBX') using local expansions formed by Fast Multipole Method (FMM) for accurate near or on-surface evaluation .
Revised:  GIGAQBX is a fast high-order scheme for evaluation of layer potentials based on Quadrature by Expansion (`QBX') using local expansions formed by Fast Multipole Method (FMM) .
Edit intent: coherence
Original:  In our scheme, this single global expansion is decomposed into two parts that are evaluated separately: one  incorporating near-field contributions using target-specific expansions, and one conventionally using spherical harmonic expansions of far-field contributions, noting that convergence guarantees only exist for the sum of the two sub-expansions.
Revised:  In our scheme, this single global expansion is decomposed into two parts that are evaluated separately: one part incorporating near-field contributions using target-specific expansions, and one conventionally using spherical harmonic expansions of far-field contributions, noting that convergence guarantees only exist for the sum of the two sub-expansions.
Edit intent: clarity
Original:  In our scheme, this single global expansion is decomposed into two parts that are evaluated separately: one  incorporating near-field contributions using target-specific expansions, and one conventionally using spherical harmonic expansions of far-field contributions, noting that convergence guarantees only exist for the sum of the two sub-expansions.
Revised:  In our scheme, this single global expansion is decomposed into two parts that are evaluated separately: one incorporating near-field contributions using target-specific expansions, and one part using conventional spherical harmonic expansions of far-field contributions, noting that convergence guarantees only exist for the sum of the two sub-expansions.
Edit intent: fluency
Original:  By contrast, target-specific expansions were originally introduced as an acceleration mechanism for the `local' QBX schemes, in which the far-field does not contribute to the QBX expansion.
Revised:  By contrast, target-specific expansions were originally introduced as an acceleration mechanism for `local' QBX schemes, in which the far-field does not contribute to the QBX expansion.
Edit intent: fluency
Original:  GIGAQBX is a fast high-order scheme for evaluation of layer potentials based on Quadrature by Expansion (`QBX') using local expansions formed via the Fast Multipole Method (FMM). Target-specific expansions serve to lower the cost of local expansion evaluation , reducing the  computational effort from O((p+1) ^2 ) to O(p+1) in three dimensions, without any accuracy loss compared with conventional expansions, but with the loss of source/target separation in the expansion coefficients.
Revised:  GIGAQBX is a fast high-order scheme for evaluation of layer potentials based on Quadrature by Expansion (`QBX') using local expansions formed via the Fast Multipole Method (FMM). Target-specific expansions serve to lower the cost of the formation and evaluation of QBX local expansions , reducing the computational effort from O((p+1) ^2 ) to O(p+1) in three dimensions, without any accuracy loss compared with conventional expansions, but with the loss of source/target separation in the expansion coefficients.
Edit intent: clarity
Original:  GIGAQBX is a fast high-order scheme for evaluation of layer potentials based on Quadrature by Expansion (`QBX') using local expansions formed via the Fast Multipole Method (FMM). Target-specific expansions serve to lower the cost of local expansion evaluation , reducing the  computational effort from O((p+1) ^2 ) to O(p+1) in three dimensions, without any accuracy loss compared with conventional expansions, but with the loss of source/target separation in the expansion coefficients.
Revised:  GIGAQBX is a fast high-order scheme for evaluation of layer potentials based on Quadrature by Expansion (`QBX') using local expansions formed via the Fast Multipole Method (FMM). Target-specific expansions serve to lower the cost of local expansion evaluation , reducing the associated computational effort from O((p+1) ^2 ) to O(p+1) in three dimensions, without any accuracy loss compared with conventional expansions, but with the loss of source/target separation in the expansion coefficients.
Edit intent: clarity
Original:  GIGAQBX is a fast high-order scheme for evaluation of layer potentials based on Quadrature by Expansion (`QBX') using local expansions formed via the Fast Multipole Method (FMM). Target-specific expansions serve to lower the cost of local expansion evaluation , reducing the  computational effort from O((p+1) ^2 ) to O(p+1) in three dimensions, without any accuracy loss compared with conventional expansions, but with the loss of source/target separation in the expansion coefficients.
Revised:  GIGAQBX is a fast high-order scheme for evaluation of layer potentials based on Quadrature by Expansion (`QBX') using local expansions formed via the Fast Multipole Method (FMM). Target-specific expansions serve to lower the cost of local expansion evaluation , reducing the computational effort from O((p+1) ^{2 ) to O(p+1) in three dimensions, without any accuracy loss compared with conventional expansions, but with the loss of source/target separation in the expansion coefficients.
Edit intent: fluency
Original:  By utilizing a large-scale scholarly dataset from the computer science field in the Microsoft Academic Graph (MAG-CS) dataset, we find that DCCPs exist universally in medium- and high-impact papers.
Revised:  By utilizing a large-scale scholarly dataset from the computer science field in the Microsoft Academic Graph (MAG-CS) dataset, we find that DCCPs exist universally in medium and highly cited papers.
Edit intent: clarity
Original:  higher-impact papers tend to contain more DCCPs than others.
Revised:  highly cited papers tend to contain more DCCPs than others.
Edit intent: clarity
Original:  This article provides a theoretical foundation for this algorithm in the general case of coupled FBSDEs.
Revised:  This article lays a theoretical foundation for this algorithm in the general case of coupled FBSDEs.
Edit intent: clarity
Original:  This article provides a theoretical foundation for this algorithm in the general case of coupled FBSDEs.
Revised:  This article provides a theoretical foundation for the deep BSDE method in the general case of coupled FBSDEs.
Edit intent: clarity
Original:  In particular, we provide a posteriori error estimation of the solution and prove the error can converge to zero given the universal approximation capability of neural networks.
Revised:  In particular, a posteriori error estimation of the solution and prove the error can converge to zero given the universal approximation capability of neural networks.
Edit intent: clarity
Original:  In particular, we provide a posteriori error estimation of the solution and prove the error can converge to zero given the universal approximation capability of neural networks.
Revised:  In particular, we provide a posteriori error estimation of the solution is provided and it is proved that the error converges to zero given the universal approximation capability of neural networks.
Edit intent: clarity
Original: Shopping basket data analysis is significant in understanding the shopping behaviors of customers.
Revised: Shopping transaction analysis is important for understanding the shopping behaviors of customers.
Edit intent: clarity
Original:  Existing models such as association rules are poor at modeling products which have short purchase histories and cannot be applied to new products (the cold-start problem).
Revised:  Existing models such as association rules are poor at modeling products that have short purchase histories and cannot be applied to new products (the cold-start problem).
Edit intent: fluency
Original:  The model's goal is to learn the product representations from the textual contents , that can capture the relationships between the products in the baskets.
Revised:  The model's goal is to learn the product representations from the textual contents to capture the relationships between the products in the baskets.
Edit intent: clarity