wanyu/IteraTeR_v2 huggingface dataset:
Original:  Initial work onlearned indexes has repeatedly shown that by learning the distribution of the data, index structures such as the B-Tree , can boost their performance by an order of magnitude while using a smaller memory footprint.
Revised:  Initial work onlearned indexes has repeatedly shown that by learning the distribution of the data, index structures such as the B-Tree , can boost their performance by an order of magnitude while having a smaller memory footprint.
Edit intent: clarity
Original:  In this work we propose a new class of learned indexes for multidimensional data that  instead of learning only from distribution of keys, learns from correlations between columns of the dataset.
Revised:  In this work we propose a new class of learned indexes for multidimensional data that , instead of learning only from distribution of keys, learns from correlations between columns of the dataset.
Edit intent: fluency
Original:  In this work we propose a new class of learned indexes for multidimensional data that  instead of learning only from distribution of keys, learns from correlations between columns of the dataset.
Revised:  In this work we propose a new class of learned indexes for multidimensional data that instead of learning the distribution of keys, learns from correlations between columns of the dataset.
Edit intent: clarity
Original:  In this work we propose a new class of learned indexes for multidimensional data that  instead of learning only from distribution of keys, learns from correlations between columns of the dataset.
Revised:  In this work we propose a new class of learned indexes for multidimensional data that instead of learning only from distribution of keys, learns the correlations between attributes of the dataset.
Edit intent: clarity
Original:  Our approach is motivated by the observation that in real datasets, correlation between two or more attributes of the data is a common occurrence.
Revised:  Our approach is driven by the observation that in real datasets, correlation between two or more attributes of the data is a common occurrence.
Edit intent: clarity
Original:  This method reduces the dimensionality of the index and thus makes it more efficient.
Revised:  This method reduces the dimensionality and hence makes the index smaller and more efficient.
Edit intent: clarity
Original:  We  show experimentally that by predicting correlated attributes in the data, rather than indexing them, we can improve the query execution time and reduce the memory overhead of the index at the same time .
Revised:  We show experimentally that by predicting correlated attributes in the data, we can improve the query execution time and reduce the memory overhead of the index at the same time .
Edit intent: clarity
Original: Bayesian regularization-backpropagation neural network (BR-BPNN) , a machine learning algorithm, is employed to predict some aspects of the gecko spatula peeling such as the variation of the maximum normal and tangential pull-off forces and the resultant force angle at detachment with the peeling angle.
Revised: Bayesian regularization-backpropagation neural network (BR-BPNN) model is employed to predict some aspects of the gecko spatula peeling such as the variation of the maximum normal and tangential pull-off forces and the resultant force angle at detachment with the peeling angle.
Edit intent: clarity
Original: Bayesian regularization-backpropagation neural network (BR-BPNN) , a machine learning algorithm, is employed to predict some aspects of the gecko spatula peeling such as the variation of the maximum normal and tangential pull-off forces and the resultant force angle at detachment with the peeling angle.
Revised: Bayesian regularization-backpropagation neural network (BR-BPNN) , a machine learning algorithm, is employed to predict some aspects of the gecko spatula peeling viz. the variation of the maximum normal and tangential pull-off forces and the resultant force angle at detachment with the peeling angle.
Edit intent: clarity
Original:  It is observed that BR-BPNN models have significant potential to estimate the peeling behavior.
Revised:  It is shown that the BR-BPNN models have significant potential to estimate the peeling behavior.
Edit intent: clarity
Original:  It is also an improvement over the contour-path effective permittivity algorithm by including some extra terms in the formulas.
Revised:  It is also an improvement over the contour-path effective-permittivity algorithm by including some extra terms in the formulas.
Edit intent: fluency
Original:  The numerical results demonstrate that the new algorithm has achieved significant improvement in accuracy over  other methods.
Revised:  The numerical results demonstrate that the new algorithm has achieved significant improvement in accuracy over the other methods.
Edit intent: fluency
Original: Conventional algorithms for finding low-rank canonical polyadic (CP) tensor decompositions are unwieldy for large sparse tensors.
Revised: The low-rank canonical polyadic (CP) tensor decompositions are unwieldy for large sparse tensors.
Edit intent: clarity
Original: This study exploits the advancements in information and communication technology (ICT), connected and automated vehicles (CAVs), and sensing, to develop anticipatory multi-objective eco-routing strategies.
Revised: This study exploits the advancements in information and communication technology (ICT), connected and automated vehicles (CAVs), and sensing, to develop proactive multi-objective eco-routing strategies.
Edit intent: clarity
Original:  It is found that anticipatory routing strategies outperformed the myopic strategies, regardless of the routing objective.
Revised:  It is found that proactive routing strategies outperformed the myopic strategies, regardless of the routing objective.
Edit intent: clarity
Original:  Whether myopic or anticipatory , the multi-objective routing, with travel time and GHG minimization as objectives, outperformed the single objective routing strategies, causing a reduction in the average travel time (TT), average vehicle kilometre travelled (VKT), total GHG and total NOx by 17\%, 21\%, 18\%, and 20\%, respectively.
Revised:  Whether myopic or proactive , the multi-objective routing, with travel time and GHG minimization as objectives, outperformed the single objective routing strategies, causing a reduction in the average travel time (TT), average vehicle kilometre travelled (VKT), total GHG and total NOx by 17\%, 21\%, 18\%, and 20\%, respectively.
Edit intent: clarity
Original:  In this paper, we model network formation as a ``choice'' that is made by nodes in a network to connect to other nodes.
Revised:  In this paper, we model network formation as a "choice" that is made by nodes in a network to connect to other nodes.
Edit intent: fluency
Original:  We study these ``choices'' using discrete-choice models, in which an agent chooses between two or more discrete alternatives.
Revised:  We study these "choices" using discrete-choice models, in which an agent chooses between two or more discrete alternatives.
Edit intent: fluency
Original:  We employ the ``repeated choice'' (RC) model to study network formation TrainRevelt97mixedlogit.
Revised:  We employ the "repeated choice" (RC) model to study network formation TrainRevelt97mixedlogit.
Edit intent: fluency
Original:  In addition, it is also challenging to predict the future consuming workloads .
Revised:  In addition, it is also challenging to predict the future workloads that may utilize the partitionings .
Edit intent: clarity
Original: Persistent partitioning is effective in improving the performance by avoiding the expensive shuffling operation, while incurring relatively small overhead .
Revised: Persistent partitioning is effective in avoiding expensive shuffling operations .
Edit intent: clarity
Original:  We propose the Lachesis system, which allows UDFs to be decomposed into analyzable and reusable sub-computations and relies on a deep reinforcement learning model that infers which sub-computations should be used to partition the underlying data.
Revised:  We propose the Lachesis system, which represents UDF-centric workloads as workflows of analyzable and reusable sub-computations and relies on a deep reinforcement learning model that infers which sub-computations should be used to partition the underlying data.
Edit intent: clarity
Original:  We propose the Lachesis system, which allows UDFs to be decomposed into analyzable and reusable sub-computations and relies on a deep reinforcement learning model that infers which sub-computations should be used to partition the underlying data.
Revised:  We propose the Lachesis system, which allows UDFs to be decomposed into analyzable and reusable sub-computations and relies on a deep reinforcement learning model to infer which sub-computations should be used to partition the underlying data.
Edit intent: fluency
Original:  This analysis is then used to automatically optimize the storage of the data across applications  .
Revised:  This analysis is then applied to automatically optimize the storage of the data across applications .
Edit intent: fluency
Original:  The key problem solved by the paper is the first demonstration of a reversible cache coherence protocol that naturally rollbacks the effects of squashed speculative execution.
Revised:  The key problem solved by the paper is the first coherence protocol that naturally rollbacks the effects of squashed speculative execution.
Edit intent: clarity
Original:  It reveals a key advantage of RCP: the coherence actions triggered by the merge and purge operations are not in the critical path of the execution and can be performed in the cache hierarchy concurrently with processor execution .
Revised:  It reveals a key advantage of RCP: the coherence actions triggered by the merge and purge operations are not in the critical path of the execution and can be performed in the cache hierarchy concurrently with processor execution 
Edit intent: fluency
Original:  To solve the dual task, we develop an open source mobile app.
Revised:  To solve the dual task, we developed an open source mobile app.
Edit intent: fluency
Original:  The algorithm to update vertex guards after any modification to the polygon takes O(k \lg{(n+ n') time.
Revised:  For the special case of the initial orthogonal polygon being hole-free and each update resulting in a hole-free orthogonal polygon, our guard updation algorithm takes O(k \lg{(n+ n') time.
Edit intent: clarity
Original:  The algorithm to update vertex guards after any modification to the polygon takes O(k \lg{(n+ n') time.
Revised:  The algorithm to update vertex guards after any modification to the polygon takes O(k \lg{(n+n') time.
Edit intent: fluency
Original: We devise an algorithm for surveying a dynamic orthogonal polygonal domain %DIFDELCMD < \cal %%% P by placing one guard at each vertex in a subset of vertices of%DIFDELCMD < \cal %DIFDELCMD < %%% P , i.e., whenever an orthogonal polygon domain \cal P'
Revised: We devise an algorithm for surveying a dynamic orthogonal polygonal domain %DIFDELCMD < \cal %%% by placing one guard at each vertex in a subset of vertices of%DIFDELCMD < \cal %DIFDELCMD < %%% P , i.e., whenever an orthogonal polygon domain \cal P'
Edit intent: fluency
Original: We devise an algorithm for surveying a dynamic orthogonal polygonal domain %DIFDELCMD < \cal %%% P by placing one guard at each vertex in a subset of vertices of%DIFDELCMD < \cal %DIFDELCMD < %%% P , i.e., whenever an orthogonal polygon domain \cal P'
Revised: We devise an algorithm for surveying a dynamic orthogonal polygonal domain %DIFDELCMD < \cal %%% P by placing one guard at each vertex in a subset of %DIFDELCMD < \cal %DIFDELCMD < %%% P , i.e., whenever an orthogonal polygon domain \cal P'
Edit intent: clarity
Original: We devise an algorithm for surveying a dynamic orthogonal polygonal domain %DIFDELCMD < \cal %%% P by placing one guard at each vertex in a subset of vertices of%DIFDELCMD < \cal %DIFDELCMD < %%% P , i.e., whenever an orthogonal polygon domain \cal P'
Revised: We devise an algorithm for surveying a dynamic orthogonal polygonal domain %DIFDELCMD < \cal %%% P by placing one guard at each vertex in a subset of vertices of%DIFDELCMD < \cal %DIFDELCMD < %%% its vertices , i.e., whenever an orthogonal polygon domain \cal P'
Edit intent: clarity
Original: We devise an algorithm for surveying a dynamic orthogonal polygonal domain %DIFDELCMD < \cal %%% P by placing one guard at each vertex in a subset of vertices of%DIFDELCMD < \cal %DIFDELCMD < %%% P , i.e., whenever an orthogonal polygon domain \cal P'
Revised: We devise an algorithm for surveying a dynamic orthogonal polygonal domain %DIFDELCMD < \cal %%% P by placing one guard at each vertex in a subset of vertices of%DIFDELCMD < \cal %DIFDELCMD < %%% P , i.e., whenever an orthogonal polygonal domain \cal P'
Edit intent: fluency
Original:  is modified to result in another orthogonal polygonal domain \cal P , our algorithm updates the set of (vertex ) guards surveying \cal P' so that the updated guard set surveys \cal P . Our algorithm modifies the guard placement in O(k (n+n')) amortized time , while ensuring the updated orthogonal polygon with h holes and n vertices is guarded using at most \lfloor (n+2h)/4 \rfloor vertex guards.
Revised:  is modified to result in another orthogonal polygonal domain \cal P , our algorithm updates the set of vertex guards surveying \cal P' so that the updated guard set surveys \cal P . Our algorithm modifies the guard placement in O(k (n+n')) amortized time , while ensuring the updated orthogonal polygon with h holes and n vertices is guarded using at most \lfloor (n+2h)/4 \rfloor vertex guards.
Edit intent: fluency
Original:  is modified to result in another orthogonal polygonal domain \cal P , our algorithm updates the set of (vertex ) guards surveying \cal P' so that the updated guard set surveys \cal P . Our algorithm modifies the guard placement in O(k (n+n')) amortized time , while ensuring the updated orthogonal polygon with h holes and n vertices is guarded using at most \lfloor (n+2h)/4 \rfloor vertex guards.
Revised:  is modified to result in another orthogonal polygonal domain \cal P , our algorithm updates the set of (vertex ) guards surveying \cal P' so that the updated guard set surveys \cal P . Our algorithm modifies the guard placement in O(k (n+n')) amortized time while ensuring the updated orthogonal polygon with h holes and n vertices is guarded using at most \lfloor (n+2h)/4 \rfloor vertex guards.
Edit intent: fluency
Original:  is modified to result in another orthogonal polygonal domain \cal P , our algorithm updates the set of (vertex ) guards surveying \cal P' so that the updated guard set surveys \cal P . Our algorithm modifies the guard placement in O(k (n+n')) amortized time , while ensuring the updated orthogonal polygon with h holes and n vertices is guarded using at most \lfloor (n+2h)/4 \rfloor vertex guards.
Revised:  is modified to result in another orthogonal polygonal domain \cal P , our algorithm updates the set of (vertex ) guards surveying \cal P' so that the updated guard set surveys \cal P . Our algorithm modifies the guard placement in O(k (n+n')) amortized time , while ensuring the updated orthogonal polygonal domain with h holes and n vertices is guarded using at most \lfloor (n+2h)/4 \rfloor vertex guards.
Edit intent: fluency
Original:  For the special case of the initial orthogonal polygon being hole-free and each update resulting in a hole-free orthogonal polygon, our guard updation algorithm takes O(k(n+n')) worst-case time.
Revised:  For the special case of the initial orthogonal polygon being hole-free and each update resulting in a hole-free orthogonal polygon, our guard update algorithm takes O(k(n+n')) worst-case time.
Edit intent: clarity
Original:  and, k is the sum of |n - n'| and the number of updates in a few structures maintained by our algorithm {\cal  {\cal   .
Revised:  and, k is the sum of |n - n'| and the number of updates to a few structures maintained by our algorithm {\cal {\cal .
Edit intent: fluency
Original: The theory of evolutionary computation for discrete search spaces has made a lot of progress during the last ten years.
Revised: The theory of evolutionary computation for discrete search spaces has made significant of progress in the last ten years.
Edit intent: clarity
Original:  This survey summarizes some of the most important recent results obtained in this research area.
Revised:  This survey summarizes some of the most important recent results in this research area.
Edit intent: clarity
Original:  It reviews important methods such as drift analysis , discusses theoretical insight on parameter tuning and parameter control, and summarizes the advances made for stochastic and dynamic problems.
Revised:  It reviews important methods such as drift analysis , discusses theoretical insight on parameter tuning and parameter control, and summarizes the latest advances for stochastic and dynamic problems.
Edit intent: clarity
Original: The theory of evolutionary computation for discrete search spaces has made significant of progress in the last ten years.
Revised: The theory of evolutionary computation for discrete search spaces has made significant progress in the last ten years.
Edit intent: fluency
Original:  The need to differentiate beyond accuracy is particularly pressing if two systems are at or near ceiling performance, like Convolutional Neural Networks (CNNs) and humans on visual object recognition.
Revised:  The need to differentiate beyond accuracy is particularly pressing if two systems are near ceiling performance, like Convolutional Neural Networks (CNNs) and humans on visual object recognition.
Edit intent: clarity
Original:  Making consistent errors on a trial-by-trial basis is a necessary condition if we want to ascertain similar processing strategies between decision makers.
Revised:  Making consistent errors on a trial-by-trial basis is a necessary condition for similar processing strategies between decision makers.
Edit intent: clarity
Original:  When applying error consistency to visual object recognition we obtain three main findings: (1.)
Revised:  When applying error consistency to object recognition we obtain three main findings: (1.)
Edit intent: clarity
Original:  Irrespective of architecture, CNNs are remarkably consistent with one another  (2.)
Revised:  Irrespective of architecture, CNNs are remarkably consistent with one another . (2.)
Edit intent: fluency
Original:  Most news recommendation methods model users' interests from their news click behaviors.
Revised:  Existing news recommendation models are usually learned from users' news click behaviors.
Edit intent: clarity
Original:  Usually the behaviors of users with the same sensitive attributes  have similar patterns , and existing news recommendation models can inherit these biases and encode them into news ranking results.
Revised:  Usually the behaviors of users with the same sensitive attributes have similar patterns and news recommendation models can inherit these biases and encode them into news ranking results.
Edit intent: clarity
Original:  Thus, their recommendation results may be heavily influenced by the biases related to sensitive user attributes , which is unfair since users cannot receive sufficient news informationthat they are interested in .
Revised:  Thus, their recommendation results may be heavily influenced by the biases related to sensitive user attributes , which is unfair since users may not receive diverse news information .
Edit intent: clarity
Original:  For model training , we propose to  learn a bias-aware user embedding that captures the bias information on user attributes from click behaviors, and learn a bias-free user embedding that only encodes attribute-independent user interest information for fairness-aware news recommendation.
Revised:  In our approach , we propose to learn a bias-aware user embedding that captures the bias information on user attributes from click behaviors, and learn a bias-free user embedding that only encodes attribute-independent user interest information for fairness-aware news recommendation.
Edit intent: clarity
Original:  Moreover, we propose an orthogonality regularization method to encourage the bias-free user embeddings to be orthogonal to the bias-aware one to further purify the bias-free user embedding  .
Revised:  Moreover, we propose an orthogonality regularization method to encourage the bias-free user embeddings to be orthogonal to the bias-aware one to better distinguish the bias-free user embedding .
Edit intent: clarity
Original:  Moreover, we propose an orthogonality regularization method to encourage the bias-free user embeddings to be orthogonal to the bias-aware one to further purify the bias-free user embedding  .
Revised:  Moreover, we propose an orthogonality regularization method to encourage the bias-free user embeddings to be orthogonal to the bias-aware one to further purify the bias-free user embedding from the bias-aware one .
Edit intent: clarity
Original:  The key challenge is that depending on the sparsity levels, distribution of data, and compute platform, the optimal solution can vary, and a static solution does not suffice.
Revised:  The key challenge is that depending on the sparsity levels, distribution of data, and compute platform, the optimal solution can vary, and a static choice does not suffice.
Edit intent: clarity
Original:  These results are valid for most practically used (and sufficiently smooth ) activation functions.
Revised:  These results are valid for all sufficiently smooth activation functions.
Edit intent: clarity
Original:  Measurement noise and approximation errors therefore result in empirically determined graphs that in general violate  properties of BMGs.
Revised:  Measurement noise and approximation errors usually result in empirically determined graphs that in general violate properties of BMGs.
Edit intent: clarity
Original:  The arc modification problems for BMGs therefore provide a mean of correcting and improving the initial estimates of the best matches .
Revised:  The arc modification problems for BMGs aim at correcting such violations and thus provide a means to improve the initial estimates of the best matches .
Edit intent: clarity
Original:  The arc modification problems for BMGs therefore provide a mean of correcting and improving the initial estimates of the best matches .
Revised:  The arc modification problems for BMGs therefore provide a mean of correcting and improving the initial estimates of best match data .
Edit intent: clarity
Original:  We illustrate the interest of this platform through several use cases and we were able to find back conclusions that are known in the literature .
Revised:  We illustrate the interest of this platform through several use cases and we were able to find back conclusions that were initially found during meta-analyses .
Edit intent: clarity
Original:  We demonstrate the effectiveness of our algorithm through an extensive empirical evaluation and user study on reference tasks taken from the Hour of the Code: Classic Maze challenge by Code.org and the Intro to Programming with Karel course by CodeHS.com \emph{  \emph{  .
Revised:  We demonstrate the effectiveness of our algorithm through an extensive empirical evaluation and user study on reference tasks taken from the \emph{ \emph{ .
Edit intent: coherence
Original:  We demonstrate the effectiveness of our algorithm through an extensive empirical evaluation and user study on reference tasks taken from the Hour of the Code: Classic Maze challenge by Code.org and the Intro to Programming with Karel course by CodeHS.com \emph{  \emph{  .
Revised:  We demonstrate the effectiveness of our algorithm through an extensive empirical evaluation and user study on reference tasks taken from the Hour of the Code: Classic Maze challenge by Code.org and the Intro to Programming with Karel course by CodeHS.com \emph{Hour of the Code: Classic Maze \emph{ .
Edit intent: fluency