wanyu/IteraTeR_v2 huggingface dataset:
Original:  The present work provides an integrated scheme for understanding the mechanisms by which morphogenetic processes of each individual cell collectively lead to the development of a large tissue with its correct shape and size .
Revised:  The present work provides an integrated scheme for the understanding of the mechanisms that are involved in orchestrating the morphogenetic processes in individual cells, in order to achieve epithelial tissue morphogenesis .
Edit intent: clarity
Original: Despite the recent great success of deep neural networks in various applications, designing and training a deep neural network is still among the greatest challenges in the field.
Revised: Despite the recent success of deep neural networks in various applications, designing and training a deep neural network is still among the greatest challenges in the field.
Edit intent: fluency
Original: Despite the recent great success of deep neural networks in various applications, designing and training a deep neural network is still among the greatest challenges in the field.
Revised: Despite the recent great success of deep neural networks in various applications, designing and training deep neural networks is still among the greatest challenges in the field.
Edit intent: fluency
Original:  In this work, we present a smooth optimisation perspective on designing and training multilayer Feedforward Neural Networks (FNNs) in the supervised learning setting .
Revised:  In this work, we address the challenge of designing and training multilayer Feedforward Neural Networks (FNNs) in the supervised learning setting .
Edit intent: clarity
Original:  In this work, we present a smooth optimisation perspective on designing and training multilayer Feedforward Neural Networks (FNNs) in the supervised learning setting .
Revised:  In this work, we present a smooth optimisation perspective on designing and training feedforward Multilayer Perceptrons (MLPs) from a smooth optimisation perspective .
Edit intent: clarity
Original:  By characterising the critical point conditions of an FNN based optimisation problem , we identify the conditions to eliminate local optima of the corresponding cost function.
Revised:  By characterising the critical point conditions of an MLP based loss function , we identify the conditions to eliminate local optima of the corresponding cost function.
Edit intent: clarity
Original:  By characterising the critical point conditions of an FNN based optimisation problem , we identify the conditions to eliminate local optima of the corresponding cost function.
Revised:  By characterising the critical point conditions of an FNN based optimisation problem , we identify conditions to eliminate local optima of the corresponding cost function.
Edit intent: fluency
Original:  Moreover, by studying the Hessian structure of the cost function at the global minima, we develop an approximate Newton FNN algorithm, which is capable of alleviating the vanishing gradient problem.
Revised:  By studying the Hessian structure of the cost function at the global minima, we develop an approximate Newton FNN algorithm, which is capable of alleviating the vanishing gradient problem.
Edit intent: coherence
Original:  Finally, our results are numerically verified on two classic benchmarks, i.e., the XOR problem and the four region classification problem .
Revised:  Finally, our results are numerically verified on two classic benchmarks, i.e., the XOR problem and the four region classification .
Edit intent: fluency
Original: Despite the recent success of deep neural networks in various applications, designing and training deep neural networks is still among the greatest challenges in the field .
Revised: Training deep neural networks in various applications, designing and training deep neural networks is still among the greatest challenges in the field .
Edit intent: clarity
Original: Despite the recent success of deep neural networks in various applications, designing and training deep neural networks is still among the greatest challenges in the field .
Revised: Despite the recent success of deep neural networks for solving machine learning problems is one great challenge in the field .
Edit intent: clarity
Original: P4 is an emergent packet-processing language where the user can describe how the packets are to be processed in a switching element.
Revised: P4 is an emergent packet-processing language with which the user can describe how the packets are to be processed in a switching element.
Edit intent: clarity
Original:  This paper presents a way to implement advanced operations that are not directly supported in P4.
Revised:  This paper presents a way to implement complex operations that are not directly supported in P4.
Edit intent: clarity
Original:  This paper presents a way to implement advanced operations that are not directly supported in P4.
Revised:  This paper presents a way to implement advanced operations that are not natively supported in P4.
Edit intent: clarity
Original:  In this work, two different ways to add extensions to P4 are presented : i) using new native primitives and ii) using extern instances.
Revised:  In this work, we explored two different methods to add extensions to P4 are presented : i) using new native primitives and ii) using extern instances.
Edit intent: clarity
Original:  In this work, two different ways to add extensions to P4 are presented : i) using new native primitives and ii) using extern instances.
Revised:  In this work, two different ways to add extensions to P4 : i) using new native primitives and ii) using extern instances.
Edit intent: clarity
Original:  The tests show that both methods are effective, with similar performance in terms of average packet latency.
Revised:  The tests showed similar relative performance in both methods in terms of normalized packet latency.
Edit intent: clarity
Original:  However, extern instances utilization suggests being more suitable for target-specific switching applications, where the manufacturer/vendor can specify its own specific operations without changes in the P4 semantics, exporting them to P4 as a standard vendor-specific library .
Revised:  However, extern instances appear to be more suitable for target-specific switching applications, where the manufacturer/vendor can specify its own specific operations without changes in the P4 semantics, exporting them to P4 as a standard vendor-specific library .
Edit intent: clarity
Original: In this paper, based on a novel definition of the condition number , the expression of the relative condition number of  equality constrained indefinite least squares problem is first presented when the data space is measured by a general product norm.
Revised: In this paper, within a unified framework of the condition number , the expression of the relative condition number of equality constrained indefinite least squares problem is first presented when the data space is measured by a general product norm.
Edit intent: clarity
Original: In this paper, based on a novel definition of the condition number , the expression of the relative condition number of  equality constrained indefinite least squares problem is first presented when the data space is measured by a general product norm.
Revised: In this paper, based on a novel definition of the condition number , the expression of the relative condition number of the equality constrained indefinite least squares problem is first presented when the data space is measured by a general product norm.
Edit intent: fluency
Original:  Then, by setting the specific norms and parameters, we obtain the explicit expressions of the normwise, mixed and componentwise condition numbers , and we also present two equivalent but simpler expressions of the normwise condition number.
Revised:  Then, by setting the specific norms and parameters, some widely used condition numbers, like the normwise, mixed and componentwise condition numbers , and we also present two equivalent but simpler expressions of the normwise condition number.
Edit intent: clarity
Original:  The sparse component of a tensor is also recovered by the reweighted l _1 norm which enhances the accuracy of decomposition.
Revised:  The sparse component of the tensor is also recovered by the reweighted l _1 norm which enhances the accuracy of decomposition.
Edit intent: fluency
Original:  The sparse component of a tensor is also recovered by the reweighted l _1 norm which enhances the accuracy of decomposition.
Revised:  The sparse component of a tensor is also recovered by reweighted l 1 norm which enhances the accuracy of decomposition.
Edit intent: fluency
Original:  An efficient iterative decomposition scheme based on t-SVD is proposed which improves low-rank signal recovery significantly.
Edit intent: coherence
Original:  The effectiveness of the proposed method is established by applying to video denoising problem , and experimental results reveal that the  algorithm outperforms its counterparts.
Revised:  The effectiveness of the proposed method is established by applying it to the video denoising problem , and experimental results reveal that the algorithm outperforms its counterparts.
Edit intent: clarity
Original:  The effectiveness of the proposed method is established by applying to video denoising problem , and experimental results reveal that the  algorithm outperforms its counterparts.
Revised:  The effectiveness of the proposed method is established by applying to video denoising problem and the experimental results reveal that the algorithm outperforms its counterparts.
Edit intent: fluency
Original:  The effectiveness of the proposed method is established by applying to video denoising problem , and experimental results reveal that the  algorithm outperforms its counterparts.
Revised:  The effectiveness of the proposed method is established by applying to video denoising problem , and experimental results reveal that the proposed algorithm outperforms its counterparts.
Edit intent: fluency
Original:  There are two variants of protein complexes that act as mechanosensors of the 2nd kind: producing the one-off or a reversible action.
Revised:  There are two variants of protein complexes that act as mechanosensors of the 2nd kind: producing either a one-off or a reversible action.
Edit intent: clarity
Original: The susceptibility of millimeter waveform propagation to blockages may largely restrict the coverage of mmWave signals.
Revised: The susceptibility of millimeter waveform propagation to blockages limits the coverage of mmWave signals.
Edit intent: clarity
Original: The susceptibility of millimeter waveform propagation to blockages may largely restrict the coverage of mmWave signals.
Revised: The susceptibility of millimeter waveform propagation to blockages may largely restrict the coverage of millimeter-wave (mmWave) signals.
Edit intent: clarity
Original:  Using stochastic geometry, we derive expressions for the downlink coverage probability of a relay-assisted mmWave cellular network when the D2D links (from relays to destinations) are implemented in either the mmWave or microwave band.
Revised:  Using stochastic geometry, we derive expressions for the downlink coverage probability of relay-assisted mmWave cellular network when the D2D links (from relays to destinations) are implemented in either the mmWave or microwave band.
Edit intent: fluency
Original:  Using stochastic geometry, we derive expressions for the downlink coverage probability of a relay-assisted mmWave cellular network when the D2D links (from relays to destinations) are implemented in either the mmWave or microwave band.
Revised:  Using stochastic geometry, we derive expressions for the downlink coverage probability of a relay-assisted mmWave cellular networks when the D2D links (from relays to destinations) are implemented in either the mmWave or microwave band.
Edit intent: fluency
Original:  Using stochastic geometry, we derive expressions for the downlink coverage probability of a relay-assisted mmWave cellular network when the D2D links (from relays to destinations) are implemented in either the mmWave or microwave band.
Revised:  Using stochastic geometry, we derive expressions for the downlink coverage probability of a relay-assisted mmWave cellular network when the D2D links are implemented in either the mmWave or microwave band.
Edit intent: clarity
Original:  For microwave D2D links, with the Rayleigh fading assumption, we derive the coverage probability considering different path loss models for line-of-sight (LOS) and non-line-of-sight (NLOS) links .
Revised:  For microwave D2D links, we derive the coverage probability considering different path loss models for line-of-sight (LOS) and non-line-of-sight (NLOS) links .
Edit intent: clarity
Original:  For microwave D2D links, with the Rayleigh fading assumption, we derive the coverage probability considering different path loss models for line-of-sight (LOS) and non-line-of-sight (NLOS) links .
Revised:  For microwave D2D links, with the Rayleigh fading assumption, we derive the coverage probability considering both line-of-sight (LOS) and non-line-of-sight (NLOS) links .
Edit intent: clarity
Original:  For microwave D2D links, with the Rayleigh fading assumption, we derive the coverage probability considering different path loss models for line-of-sight (LOS) and non-line-of-sight (NLOS) links .
Revised:  For microwave D2D links, with the Rayleigh fading assumption, we derive the coverage probability considering different path loss models for line-of-sight (LOS) and non-line-of-sight (NLOS) propagation .
Edit intent: clarity
Original:  Numerical results suggest that the downlink coverage of a mmWave cellular network can be improved by enabling two-hop D2D relay transmissions.
Revised:  Numerical results show that downlink coverage and SE can be improved by enabling two-hop D2D relay transmissions.
Edit intent: clarity
Original:  Numerical results suggest that the downlink coverage of a mmWave cellular network can be improved by enabling two-hop D2D relay transmissions.
Revised:  Numerical results suggest that the downlink coverage of a mmWave cellular network can be improved using two-hop D2D relay transmissions.
Edit intent: clarity
Original:  In most situations , microwave D2D relays achieve better coverage than mmWave D2D relays because microwave D2D links can be established under NLOS conditions ;
Revised:  In most situations , microwave D2D relays achieve better coverage because D2D relays because microwave D2D links can be established under NLOS conditions ;
Edit intent: clarity
Original:  In most situations , microwave D2D relays achieve better coverage than mmWave D2D relays because microwave D2D links can be established under NLOS conditions ;
Revised:  In most situations , microwave D2D relays achieve better coverage than mmWave D2D connections can be established under NLOS conditions ;
Edit intent: clarity
Original:  however , mmWave D2D relays achieve better coverage when the density of interferers is large because their antenna arrays reject interference from off-boresight directions and blockages eliminate interference from NLOS interferers  .
Revised:  however , mmWave D2D relays achieve better coverage when the density of interferers is large because blockages eliminate interference from NLOS interferers .
Edit intent: clarity
Original:  Specifically, for every n, d = 2 ^{o %DIFDELCMD < \left(%%% \frac{\log n{\log \log n}}%DIFDELCMD < \right)%%%  }, and every d-dimensional symmetric norm \|\cdot\|, there exists a data structure for poly(\log \log n)-approximate nearest neighbor search over \|\cdot\| for n-point datasets achieving n^{o(1)} query time and n^{1+o(1)} space.
Revised:  Specifically, for every n, d = 2 ^{o %DIFDELCMD < \left(%%% {\log \log n}}%DIFDELCMD < \right)%%% }, and every d-dimensional symmetric norm \|\cdot\|, there exists a data structure for poly(\log \log n)-approximate nearest neighbor search over \|\cdot\| for n-point datasets achieving n^{o(1)} query time and n^{1+o(1)} space.
Edit intent: clarity
Original:  Specifically, for every n, d = 2 ^{o %DIFDELCMD < \left(%%% \frac{\log n{\log \log n}}%DIFDELCMD < \right)%%%  }, and every d-dimensional symmetric norm \|\cdot\|, there exists a data structure for poly(\log \log n)-approximate nearest neighbor search over \|\cdot\| for n-point datasets achieving n^{o(1)} query time and n^{1+o(1)} space.
Revised:  Specifically, for every n, d = 2 ^{o %DIFDELCMD < \left(%%% \frac{\log n{\log \log n}}%DIFDELCMD < \right)%%% (1) }, and every d-dimensional symmetric norm \|\cdot\|, there exists a data structure for poly(\log \log n)-approximate nearest neighbor search over \|\cdot\| for n-point datasets achieving n^{o(1)} query time and n^{1+o(1)} space.
Edit intent: coherence
Original:  Even in this special case, which is theoretically the least beneficial for our fast algorithm, we observe a 5 to 25-fold improvement in throughput compared to previous state-of-the-art .
Revised:  Even in this special case, which is theoretically the least beneficial ) case of our approach, we demonstrate a 5 to 25-fold improvement in throughput compared to previous state-of-the-art .
Edit intent: clarity
Original: In this note , we show that while almost all functions require exponential size branching programs to compute, for all functions f there is a branching program computing a large number of copies of f which has linear size per copy of f.
Revised: In this paper , we show that while almost all functions require exponential size branching programs to compute, for all functions f there is a branching program computing a large number of copies of f which has linear size per copy of f.
Edit intent: clarity
Original: Network representation learning (NRL) aims to build low-dimensional vectors for vertices in a network.
Revised: Network representation learning (NRL) aims to learn low-dimensional vectors for vertices in a network.
Edit intent: clarity
Original:  It's a common sense that vertices in the same community tend to connect densely , and usually share common attributes.
Revised:  It's intuitive that vertices in the same community tend to connect densely , and usually share common attributes.
Edit intent: clarity
Original:  It's a common sense that vertices in the same community tend to connect densely , and usually share common attributes.
Revised:  It's a common sense that vertices in the same community tend to connect densely and share common attributes.
Edit intent: coherence
Original:  In this work , we propose a novel NRL model by introducing community information of vertices to learn more discriminative network representations , named as Community-enhanced Network Representation Learning (CNRL).
Revised:  In this work , we propose a novel NRL model by introducing community information of vertices , named as Community-enhanced Network Representation Learning (CNRL).
Edit intent: clarity
Original:  In this way, we can obtain more informative representation of a vertex accompanying with its community information .
Revised:  Moreover, the proposed community enhancement mechanism can be applied to various existing NRL models .
Edit intent: coherence
Original:  In experiments, we evaluate the proposed CNRL model on vertex classification, link prediction, and community detection using several real-world datasets.
Revised:  In experiments, we evaluate our model on vertex classification, link prediction, and community detection using several real-world datasets.
Edit intent: clarity
Original:  The results demonstrate that CNRL significantly and consistently outperforms other state-of-the-art methods . Meanwhile, the detected meaningful communities verify our assumptions on the correlations among vertices , sequences, and communities.
Revised:  The results demonstrate that CNRL significantly and consistently outperforms other state-of-the-art methods while verifying our assumptions on the correlations among vertices , sequences, and communities.
Edit intent: coherence
Original:  The results demonstrate that CNRL significantly and consistently outperforms other state-of-the-art methods . Meanwhile, the detected meaningful communities verify our assumptions on the correlations among vertices , sequences, and communities.
Revised:  The results demonstrate that CNRL significantly and consistently outperforms other state-of-the-art methods . Meanwhile, the detected meaningful communities verify our assumptions on the correlations between vertices and communities.
Edit intent: clarity
Original: Sequential prediction is a fundamental task for Web applications.
Revised: Sequential recommendation is a fundamental task for Web applications.
Edit intent: clarity
Original:  However , they have  limitations.
Revised:  However , they have some limitations.
Edit intent: clarity
Original:  MF methods can merge additional information to address cold start but could not capture dynamic properties of user's interest , and MC based sequential methodshave difficulty in addressing cold start and has a strong Markov assumption that the next state only depends on the last state .
Revised:  MF based methods could not capture dynamic properties of user's interest , and MC based sequential methodshave difficulty in addressing cold start and has a strong Markov assumption that the next state only depends on the last state .
Edit intent: coherence
Original:  MF methods can merge additional information to address cold start but could not capture dynamic properties of user's interest , and MC based sequential methodshave difficulty in addressing cold start and has a strong Markov assumption that the next state only depends on the last state .
Revised:  MF methods can merge additional information to address cold start but could not capture dynamic user's interest , and MC based sequential methodshave difficulty in addressing cold start and has a strong Markov assumption that the next state only depends on the last state .
Edit intent: clarity
Original:  In this work, to  deal with the  cold start problem of sequential prediction , we propose a RNN modeladopting  visual and textual content of items, which is named as Visual and Textual \mathbf{Recurrent \mathbf{N}eural \mathbf{N}etwork (\mathbf{VT}-\mathbf{RNN}).
Revised:  In this work, to deal with the cold start problem , we propose a RNN modeladopting visual and textual content of items, which is named as Visual and Textual \mathbf{Recurrent \mathbf{N}eural \mathbf{N}etwork (\mathbf{VT}-\mathbf{RNN}).
Edit intent: clarity
Original:  In this work, to  deal with the  cold start problem of sequential prediction , we propose a RNN modeladopting  visual and textual content of items, which is named as Visual and Textual \mathbf{Recurrent \mathbf{N}eural \mathbf{N}etwork (\mathbf{VT}-\mathbf{RNN}).
Revised:  In this work, to deal with the cold start problem of sequential prediction , we propose a RNN modeladopting visual and textual ecurrent \mathbf{N}eural \mathbf{N}etwork (\mathbf{VT}-\mathbf{RNN}).
Edit intent: clarity
Original:  We can simultaneously learn the sequential latent vectors that }  dynamically capture the user's interest , as well as content-based representations that contribute to address the cold start . Experiments on two real-world datasets show that our proposed VT-RNN model can effectively generate the personalized ranking list  and significantly alleviate the  cold start problem.
Revised:  We can simultaneously learn the sequential latent vectors that } dynamically capture the user's interest , as well as content-based representations that contribute to address the cold start . Experiments on two real-world datasets show that MV-RNN can effectively generate the personalized ranking list and significantly alleviate the cold start problem.
Edit intent: clarity
Original: We propose a simple model of inter-bank lending and borrowing incorporating a game feature where the evolution of monetary reserve is described by a system of coupled Feller diffusions.
Revised: We propose a simple model of the banking system incorporating a game feature where the evolution of monetary reserve is described by a system of coupled Feller diffusions.
Edit intent: clarity