wanyu/IteraTeR_v2 huggingface dataset:
Original:  We provide statistical analysis on the performance of the considered system by deriving analytical expressions for the outage probability, average bit-error-rate (BER), average signal-to-noise ratio (SNR), and a lower bound on the ergodic capacity over independent and identical (i.i.d) \alpha-\mu fading model and statistical pointing errors.
Revised:  We provide statistical analysis on the performance of the considered system by deriving analytical expressions for the outage probability, average bit-error-rate (BER), average signal-to-noise ratio (SNR), and a lower bound on the ergodic capacity over independent and identical (i.i.d) \alpha-\mu fading combined with the statistical effect of pointing errors.
Edit intent: clarity
Original:  We  demonstrate the effect of the system parameters on outage probability and average BER with the help of diversity order.
Revised:  We also demonstrate the effect of the system parameters on outage probability and average BER with the help of diversity order.
Edit intent: coherence
Original:  This is a threat to the integrity of the platform, as such activity has the potential to affect entire results of democratic processes.
Revised:  These interactions are a threat to the integrity of the platform, as such activity has the potential to affect entire results of democratic processes.
Edit intent: clarity
Original:  These features are designed to bring out communities amongst the users that work to boost the content of particular accounts.
Revised:  Our proposed features are designed to bring out communities amongst the users that work to boost the content of particular accounts.
Edit intent: clarity
Original: Knowledge distillation is a widely used general technique to transfer knowledge from a teacher network to a student network.
Edit intent: coherence
Original:  Our method uses a contrastive objective to simultaneously estimate and maximize a lower bound on the mutual information between intermediate and global feature representations from the teacher and the student networks.
Revised:  Our method uses a contrastive objective to simultaneously estimate and maximize a lower bound on the mutual information of local and global feature representations from the teacher and the student networks.
Edit intent: clarity
Original:  Our empirical results show that our method outperforms competing approaches across a wide range of student-teacher pairs with different capacities, with different architectures, and when student networks are with extremely low capacity.
Revised:  Our empirical results show that MIMKD outperforms competing approaches across a wide range of student-teacher pairs with different capacities, with different architectures, and when student networks are with extremely low capacity.
Edit intent: clarity
Original:  A manifestations of this is in social agreements, often described in texts, such as contracts.
Revised:  A manifestation of this is in social agreements, often described in texts, such as contracts.
Edit intent: fluency
Original:  We details improvements that can be made in the methodology to incorporate the projection of sentence embedding on to a subspace representation of fairness.
Revised:  We detail improvements that can be made in the methodology to incorporate the projection of sentence embedding on to a subspace representation of fairness.
Edit intent: fluency
Original: To treat others as one would wish to be treated is a common formulation of the Golden Rule (GR).
Revised: To treat others as one would wish to be treated is a common formulation of the golden rule (GR).
Edit intent: fluency
Original:  Yet, despite its prevalence as an axiom throughout history, no digitisation of the moral philosophy exists.
Revised:  Yet, despite its prevalence as an axiom throughout history, no transfer of this moral philosophy into computational systems exists.
Edit intent: clarity
Original:  In this paper we consider how to digitise it so that it may be used to measure sentences such as : the boy harmed the girl, and categorise them as fair or unfair.
Revised:  In this paper we consider how to algorithmically operationalise this rule so that it may be used to measure sentences such as : the boy harmed the girl, and categorise them as fair or unfair.
Edit intent: clarity
Original:  In this paper we consider how to digitise it so that it may be used to measure sentences such as : the boy harmed the girl, and categorise them as fair or unfair.
Revised:  In this paper we consider how to digitise it so that it may be used to measure sentences such as the boy harmed the girl, and categorise them as fair or unfair.
Edit intent: fluency
Original:  Implementing two approaches, one using the USE, and a second using ALBERT.
Revised:  Implementing it within two language models, the USE, and a second using ALBERT.
Edit intent: clarity
Original: Feature reassembly is an essential component in modern CNNs-based segmentation approaches, which includes feature downsampling and upsampling operators.
Revised: Feature reassembly is an essential component in modern CNN-based segmentation approaches, which includes feature downsampling and upsampling operators.
Edit intent: fluency
Original:  Existing feature reassembly operators reassemble multiple features from a small predefined region into one for each target location independently.
Revised:  Existing operators reassemble multiple features from a small predefined region into one for each target location independently.
Edit intent: clarity
Original:  This may result in loss of spatial information, which could vanish activations of tiny lesions particularly when they cluster together.
Revised:  This may result in loss of spatial information, which could vanish activations caused by tiny lesions particularly when they cluster together.
Edit intent: clarity
Original:  In this way, long range spatial dependencies are captured to maintain activations on tiny lesions , particularly when multiple lesions coexist . Experimental results on two lesion segmentation benchmarks, i.e. DDR and IDRiD, show that  our M2MRF outperforms existing feature reassembly operators .
Revised:  In this way, long range spatial dependencies are captured to maintain activations on tiny lesions . Experimental results on two lesion segmentation benchmarks, i.e. DDR and IDRiD, show that our M2MRF outperforms existing feature reassembly operators .
Edit intent: clarity
Original:  Be it a planned smart city or even a wreckage site affected by natural calamity, we may imagine the buildings, any surface-erected structure or other blockage as obstacles for the drone to fly in a direct line-of-sight path.
Revised:  Be it a planned smart city or even a wreckage site affected by natural calamity, we may imagine the buildings, any surface-erected structure or other blockage as obstacles for the drone to fly in a straight line-of-sight path.
Edit intent: clarity
Original:  So, the whole bird's eye-view of the landscape can be transformed to a graph of grid-cells, where some are occupied to indicate the obstacles and some are free to indicate the free path.
Revised:  So, the whole bird's eye-view of the whole landscape is first transformed to a graph of grid-cells, where some are occupied to indicate the obstacles and some are free to indicate the free path.
Edit intent: clarity
Original:   The autonomous drone (AutoDrone) will  be able to find out the shortest hindrance-free pathwhile travelling in two-dimensional space and move from one place to another.
Revised:  The autonomous drone (AutoDrone) will thus be able to find out the shortest hindrance-free pathwhile travelling in two-dimensional space and move from one place to another.
Edit intent: coherence
Original:   The autonomous drone (AutoDrone) will  be able to find out the shortest hindrance-free pathwhile travelling in two-dimensional space and move from one place to another.
Revised:  The autonomous drone (AutoDrone) will be able to move from one place to another along the shortest path, without colliding into hindrances, while traveling in a two-dimensional space and move from one place to another.
Edit intent: clarity
Original:  Our work shows different scenarios to path-tracing, through the shortest feasible path computed by the autonomous drone.
Revised:  Experiments are done on different scenarios of map layouts and obstacle positions to understand the shortest feasible path computed by the autonomous drone.
Edit intent: clarity
Original:  Our work shows different scenarios to path-tracing, through the shortest feasible path computed by the autonomous drone.
Revised:  Our work shows different scenarios to path-tracing, through the shortest feasible route, computed by the autonomous drone.
Edit intent: clarity
Original: The 3D vision community is witnesses a modeling shift from CNNs to Transformers, where pure Transformer architectures have attained top accuracy on the major 3D learning benchmarks.
Revised: The 3D vision community is witnesses a modeling shift from CNNs to Transformers, where pure Transformer architectures have achieved top accuracy on the major 3D learning benchmarks.
Edit intent: fluency
Original: The 3D vision community is witnesses a modeling shift from CNNs to Transformers, where pure Transformer architectures have attained top accuracy on the major 3D learning benchmarks.
Revised: The 3D vision community is witnesses a modeling shift from CNNs to Transformers, where pure Transformer architectures have attained top accuracy on the major learning benchmarks.
Edit intent: clarity
Original:  To solve this shortcoming, we introduce patch-attention to adaptively learn a much smaller set of bases upon which the attention maps are computed.
Revised:  To solve this shortcoming, we introduce Patch attention (PAT) to adaptively learn a much smaller set of bases upon which the attention maps are computed.
Edit intent: clarity
Original:  By a weighted summation upon these bases, patch-attention not only captures the global shape context but also achieves linear complexity to input size.
Revised:  By a weighted summation upon these bases, PAT not only captures the global shape context but also achieves linear complexity to input size.
Edit intent: clarity
Original:  Based on these proposed modules , we construct our neural architecture called PatchFormer  . Extensive experiments demonstrate that our network achieves strong accuracy on general 3D recognition tasks with 7.3 x speed-up than previous 3D Transformers.
Revised:  Based on these proposed modules , we construct our neural architecture called PatchFormer . Extensive experiments demonstrate that our network achieves strong accuracy on general 3D recognition tasks with 7.3 x speed-up than previous point Transformers.
Edit intent: clarity
Original: Linear power flow (LPF) models are important for the solution of large-scale problems in power system analysis.
Revised: Linear power flow (LPF) models are essential in power system analysis.
Edit intent: clarity
Original:  Defining the starting and ending points  in a single graph is difficult, and a tree cannot express the relationship among sibling nodes.
Revised:  Defining the starting and ending points of the path in a single graph is difficult, and a tree cannot express the relationship among sibling nodes.
Edit intent: clarity
Original:  However, a graph tree can be expressed using leaf and root nodes as its starting and ending points  and the relationship among sibling nodes.
Revised:  On the contrary, an AT can express leaf and root nodes as its starting and ending points and the relationship among sibling nodes.
Edit intent: clarity
Original:  However, a graph tree can be expressed using leaf and root nodes as its starting and ending points  and the relationship among sibling nodes.
Revised:  However, a graph tree can be expressed using leaf and root nodes as the starting and ending points and the relationship among sibling nodes.
Edit intent: clarity
Original:  Experiments on this platform demonstrate the effectiveness of the proposed methods for tracking the human neck and eye movement.
Revised:  Experimental tests, which are done based on a ROS platform, demonstrate the effectiveness of the proposed methods for tracking the human neck and eye movement.
Edit intent: clarity
Original:  To this end, we propose an adaptive and exponentially weighted pooling method named adaPool .
Revised:  To this end, we propose an adaptive and exponentially weighted pooling method named adaPool .
Edit intent: fluency
Original:  We term this method adaUnPool .
Revised:  We term this method adaUnPool .
Edit intent: fluency
Original:  For benchmarking, we introduce Inter4K , a novel high-quality, high frame-rate video dataset.
Revised:  For benchmarking, we introduce Inter4K , a novel high-quality, high frame-rate video dataset.
Edit intent: fluency
Original:  Locally, i.e. ~ in each mesh cell, we compute a principal coordinate system in which the hypersurface can be approximated as the graph of an osculating paraboloid.
Revised:  Locally, i.e. in each mesh cell, we compute a principal coordinate system in which the hypersurface can be approximated as the graph of an osculating paraboloid.
Edit intent: fluency
Original: The dynamics of a power grid are governed by a large number of nonlinear ordinary differential equations (ODEs).
Revised: The dynamics of power grids are governed by a large number of nonlinear ordinary differential equations (ODEs).
Edit intent: fluency
Original:  Limited by the size and stiffness of the ODEs, current numerical integration techniques are often too slow to be useful for real-time or large-scale resource allocation problems.
Revised:  Limited by the size and stiffness of the ODEs, current numerical integration techniques are often too slow to be useful in real-time or large-scale resource allocation problems.
Edit intent: fluency
Original:  In addition, the detailed system parameters are often not exactly known.
Revised:  In addition, detailed system parameters are often not exactly known.
Edit intent: fluency
Original:  Machine learning approaches have been proposed to reduce the computational efforts, but current methods generally suffer from overfitting and failures to predict unstable behaviors.
Revised:  Machine learning approaches have been proposed to reduce the computational efforts, but existing methods generally suffer from overfitting and failures to predict unstable behaviors.
Edit intent: clarity
Original:  The intuition is that although the system behavior is complex in the time domain, there are relatively few dominant modes in the frequency domain.
Revised:  The intuition is that although the system behavior is complex in the time domain, there are relatively few dominate modes in the frequency domain.
Edit intent: fluency
Original:  The literature contains spread information regarding security related solutions for microservices-based systems, but this spread makes difficult for practitionersto adopt novel security related solutions.
Revised:  The literature presents a plethora of security-related solutions for microservices-based systems, but this spread makes difficult for practitionersto adopt novel security related solutions.
Edit intent: clarity
Original:  The literature contains spread information regarding security related solutions for microservices-based systems, but this spread makes difficult for practitionersto adopt novel security related solutions.
Revised:  The literature contains spread information regarding security related solutions for microservices-based systems, but the spread of information difficult practitioners' adoption of novel security related solutions.
Edit intent: clarity
Original:  supporting principles or characteristics of information security, also considering the three possible states of data, according to the McCumber Cube.
Revised:  supporting principles or characteristics of information security, considering the three possible states of data, according to the McCumber Cube.
Edit intent: clarity
Original: Vision transformers (ViTs) have attracted much attention for their superior performance on computer vision tasks .
Revised: Vision Transformers (ViTs) have attracted much attention for their superior performance on computer vision tasks .
Edit intent: fluency
Original: Vision transformers (ViTs) have attracted much attention for their superior performance on computer vision tasks .
Revised: Vision transformers (ViTs) have emerged with superior performance on computer vision tasks .
Edit intent: clarity
Original:  To address their limitations of single-scale low-resolution representations, prior work adapts ViTs to high-resolution dense prediction tasks with hierarchical architectures to generate pyramid features.
Revised:  To address their limitations of single-scale low-resolution representations, which makes dense prediction tasks with hierarchical architectures to generate pyramid features.
Edit intent: clarity
Original:  To enhance ViTs with more capability to learn semantically-rich and spatially-precise multi-scale representations , in this work, we present an efficient integration of high-resolution multi-branch architectures with vision transformers, dubbed HRViT, pushing the Pareto front of dense prediction tasks to a new level.
Revised:  To enhance ViTs with more capability to learn semantically-rich and spatially-precise multi-scale representations by integrating high-resolution multi-branch architectures with vision transformers, dubbed HRViT, pushing the Pareto front of dense prediction tasks to a new level.
Edit intent: coherence
Original:  We explore heterogeneous branch design , reduce the redundancy in linear layers, and augment the model nonlinearity to balance the model performance and hardware efficiency .
Revised:  We explore heterogeneous branch designs , reduce the redundancy in linear layers, and augment the model nonlinearity to balance the model performance and hardware efficiency .
Edit intent: fluency
Original:  The proposed HRViT achieves 50.20\% mIoU on ADE20K and 83.16\% mIoU on Cityscapes for semantic segmentation tasks , surpassing state-of-the-art MiT and CSWin  with an average of +1.78 mIoU improvement, 28\% parameter reduction , and 21\% FLOPs reduction, demonstrating the potential of HRViT as strong vision backbones .
Revised:  The proposed HRViT achieves 50.20\% mIoU on ADE20K and 83.16\% mIoU on Cityscapes , surpassing state-of-the-art MiT and CSWin with an average of +1.78 mIoU improvement, 28\% parameter reduction , and 21\% FLOPs reduction, demonstrating the potential of HRViT as strong vision backbones .
Edit intent: clarity
Original:  The proposed HRViT achieves 50.20\% mIoU on ADE20K and 83.16\% mIoU on Cityscapes for semantic segmentation tasks , surpassing state-of-the-art MiT and CSWin  with an average of +1.78 mIoU improvement, 28\% parameter reduction , and 21\% FLOPs reduction, demonstrating the potential of HRViT as strong vision backbones .
Revised:  The proposed HRViT achieves 50.20\% mIoU on ADE20K and 83.16\% mIoU on Cityscapes for semantic segmentation tasks , surpassing state-of-the-art MiT and CSWin backbones with an average of +1.78 mIoU improvement, 28\% parameter reduction , and 21\% FLOPs reduction, demonstrating the potential of HRViT as strong vision backbones .
Edit intent: clarity
Original:  The proposed HRViT achieves 50.20\% mIoU on ADE20K and 83.16\% mIoU on Cityscapes for semantic segmentation tasks , surpassing state-of-the-art MiT and CSWin  with an average of +1.78 mIoU improvement, 28\% parameter reduction , and 21\% FLOPs reduction, demonstrating the potential of HRViT as strong vision backbones .
Revised:  The proposed HRViT achieves 50.20\% mIoU on ADE20K and 83.16\% mIoU on Cityscapes for semantic segmentation tasks , surpassing state-of-the-art MiT and CSWin with an average of +1.78 mIoU improvement, 28\% parameter saving , and 21\% FLOPs reduction, demonstrating the potential of HRViT as strong vision backbones .
Edit intent: clarity
Original:  The proposed HRViT achieves 50.20\% mIoU on ADE20K and 83.16\% mIoU on Cityscapes for semantic segmentation tasks , surpassing state-of-the-art MiT and CSWin  with an average of +1.78 mIoU improvement, 28\% parameter reduction , and 21\% FLOPs reduction, demonstrating the potential of HRViT as strong vision backbones .
Revised:  The proposed HRViT achieves 50.20\% mIoU on ADE20K and 83.16\% mIoU on Cityscapes for semantic segmentation tasks , surpassing state-of-the-art MiT and CSWin with an average of +1.78 mIoU improvement, 28\% parameter reduction , and 21\% FLOPs reduction, demonstrating the potential of HRViT as a strong vision backbone for semantic segmentation .
Edit intent: fluency
Original:  We show the following: 1.
Revised:  We show the following: (1)
Edit intent: fluency
Original:  2. It is Unique Games-hard (UG-hard) to compute a (0.956+\varepsilon)-approximation to the value of the best product state, matching an existing approximation algorithm.
Revised:  (2) It is Unique Games-hard (UG-hard) to compute a (0.956+\varepsilon)-approximation to the value of the best product state, matching an existing approximation algorithm.
Edit intent: coherence
Original:  3. It is UG-hard to compute a (0.956+\varepsilon)-approximation to the value of the best (possibly entangled) state.
Revised:  (3) It is UG-hard to compute a (0.956+\varepsilon)-approximation to the value of the best (possibly entangled) state.
Edit intent: fluency
Original:  Their properties are characterized by a window function , and hence window design is a significant topic up to date .
Revised:  Their properties are characterized by a window function .
Edit intent: clarity
Original:  It is known to make time-frequency-domain processing robust to error , and therefore designing a better tight window is desired .
Revised:  It is known to make time-frequency-domain processing robust to error .
Edit intent: coherence
Original:  It is formulated as an optimization problemon an oblique manifold , and a Riemannian Newtonalgorithm on this manifold is derived to efficiently obtain a solution  .
Revised:  It is formulated as an optimization problemon an oblique manifold , and a Newton's method on an oblique manifold is derived to efficiently obtain a solution .
Edit intent: clarity
Original:  Examples include M/EEG inverse problems, neural encoding models for task-based fMRI analyses, and temperature monitoring of climate or CPU and GPU .
Revised:  Examples include M/EEG inverse problems, neural encoding models for task-based fMRI analyses, and climate science .
Edit intent: clarity
Original:  We prove that HLF-SZO achieves a  O(d/T^{2{3}}) convergence rate for Lipschitz and smooth objective functions (in both convex and nonconvex cases).
Revised:  We prove that HLF-SZO achieves a convergence rate of O(d/T^{2{3}}) convergence rate for Lipschitz and smooth objective functions (in both convex and nonconvex cases).
Edit intent: clarity
Original:  We prove that HLF-SZO achieves a  O(d/T^{2{3}}) convergence rate for Lipschitz and smooth objective functions (in both convex and nonconvex cases).
Revised:  We prove that HLF-SZO achieves a O(d/T^{2{3}}) for Lipschitz and smooth objective functions (in both convex and nonconvex cases).
Edit intent: clarity
Original:  In the first approach, we propose a rotation based ensemble of double random forest.
Revised:  In the first approach, we propose a rotation based double random forest.
Edit intent: clarity
Original:  In the second approach, we propose oblique ensembles of double random forest.
Revised:  In the second approach, we propose oblique double random forest.
Edit intent: clarity
Original:  To capture the geometric properties and to grow the decision trees of sufficient depth, we propose oblique ensembles of double random forest.
Revised:  To capture the geometric properties and to grow the decision trees of sufficient depth, we propose oblique double random forest.
Edit intent: clarity
Original:  The oblique ensembles of double random forest models are multivariate decision trees.
Revised:  The oblique double random forest models are multivariate decision trees.
Edit intent: clarity