wanyu/IteraTeR_v2 huggingface dataset:
Original:  Many aspects of attentional modulation  , which were previously demonstrated in a laboratory setting  are reliably reproduced here in a classroom with portable low-cost electroencephalography (EEG) recorded simultaneously from multiple students .
Revised:  Many aspects of attentional modulation , which were previously established in a laboratory setting are reliably reproduced here in a classroom with portable low-cost electroencephalography (EEG) recorded simultaneously from multiple students .
Edit intent: clarity
Original:  Many aspects of attentional modulation  , which were previously demonstrated in a laboratory setting  are reliably reproduced here in a classroom with portable low-cost electroencephalography (EEG) recorded simultaneously from multiple students .
Revised:  Many aspects of attentional modulation , which were previously demonstrated in a laboratory setting , are reliably reproduced here in a classroom with portable low-cost electroencephalography (EEG) recorded simultaneously from multiple students .
Edit intent: fluency
Original:  Many aspects of attentional modulation  , which were previously demonstrated in a laboratory setting  are reliably reproduced here in a classroom with portable low-cost electroencephalography (EEG) recorded simultaneously from multiple students .
Revised:  Many aspects of attentional modulation , which were previously demonstrated in a laboratory setting are reliably reproduced here with portable low-cost electroencephalography (EEG) recorded simultaneously from multiple students .
Edit intent: clarity
Original:  Many aspects of attentional modulation  , which were previously demonstrated in a laboratory setting  are reliably reproduced here in a classroom with portable low-cost electroencephalography (EEG) recorded simultaneously from multiple students .
Revised:  Many aspects of attentional modulation , which were previously demonstrated in a laboratory setting are reliably reproduced here in a classroom with portable low-cost equipment .
Edit intent: clarity
Original:  The present data suggests that evoked neural responsesto video stimulus , known to be modulated by attention, can be used to assess the engagement of a group of students in real-time.
Revised:  The present data suggests that stimulus-evoked neural responses , known to be modulated by attention, can be used to assess the engagement of a group of students in real-time.
Edit intent: clarity
Original:  The present data suggests that stimulus-evoked neural responses, known to be modulated by attention, can be used to assess the engagement of a group of students in real-time  .
Revised:  The present data shows that stimulus-evoked neural responses, known to be modulated by attention, can be used to assess the engagement of a group of students in real-time .
Edit intent: clarity
Original:  We claim that for signal classification tasks , one may forgo the weight training step entirely and instead use a simple supervised clustering method  .
Revised:  We claim that for signal classification tasks one may forgo the weight training step entirely and instead use a simple supervised clustering method .
Edit intent: fluency
Original:  The proposed method is analyzed theoretically and explored through numerical experiments on real-world data.
Revised:  The proposed method is mathematically analyzed and explored through numerical experiments on real-world data.
Edit intent: clarity
Original:  The examples demonstrate that the proposed clustering method outperforms the traditional trained output weight approach in terms of speed, accuracy , and sensitivity to reservoir parameters.
Revised:  The examples demonstrate that the proposed may outperform the traditional trained output weight approach in terms of speed, accuracy , and sensitivity to reservoir parameters.
Edit intent: clarity
Original:  The examples demonstrate that the proposed clustering method outperforms the traditional trained output weight approach in terms of speed, accuracy , and sensitivity to reservoir parameters.
Revised:  The examples demonstrate that the proposed clustering method outperforms the traditional trained output weight approach in terms of classification accuracy and sensitivity to reservoir parameters.
Edit intent: clarity
Original:  We model base stations  in the network as a realization of a homogeneous Poisson point process of density \lambda, and compute the SINR for three main cases: the downlink, uplink, and finally the multi-tier downlink, which is characterized by having k tiers of base stations each with a unique density \lambda_i and transmit power p_i.
Revised:  We model base stations (BSs) in the network as a realization of a homogeneous Poisson point process of density \lambda, and compute the SINR for three main cases: the downlink, uplink, and finally the multi-tier downlink, which is characterized by having k tiers of base stations each with a unique density \lambda_i and transmit power p_i.
Edit intent: clarity
Original:  We model base stations  in the network as a realization of a homogeneous Poisson point process of density \lambda, and compute the SINR for three main cases: the downlink, uplink, and finally the multi-tier downlink, which is characterized by having k tiers of base stations each with a unique density \lambda_i and transmit power p_i.
Revised:  We model base stations in the network as a realization of a homogeneous Poisson point process of density \lambda, and compute the SINR for three main cases: the downlink, uplink, and finally the multi-tier downlink, which is characterized by having k tiers of BSs each with a unique density \lambda_i and transmit power p_i.
Edit intent: clarity
Original:  This (p,q)-blossom has been adapted for developing identities and algorithms for (p,q)-Bernstein bases and (p,q)-B ezier curves.
Revised:  This (p,q)-blossom has been adapted for developing identities and algorithms for Bernstein bases and B ezier curves.
Edit intent: fluency
Original:  We also derive for each (p,q)-B ezier curve of degree n , a collection of n ! new, affine invariant, recursive evaluation algorithms . Using two of these new recursive evaluation algorithms, we construct a recursive subdivision algorithm for (p,q)-B zier curves .
Revised:  We also derive for each (p,q)-B ezier curve of degree n , a collection of n ! new, affine invariant, recursive evaluation algorithms . Using two of these new recursive evaluation algorithms, we construct a recursive subdivision algorithm for (p,q)-B are derived .
Edit intent: clarity
Original: Main-memory database systems for multicore servers can achieve excellent performance when processing massive volume of OLTP workloads.
Revised: Main-memory database management systems (DBMS) can achieve excellent performance when processing massive volume of OLTP workloads.
Edit intent: clarity
Original:  In this paper, we show that, by exploiting application semantics, it is possible to achieve speedy failure recovery without introducing any costly logging overhead to the execution of online transactions.
Revised:  In this paper, we show that, by exploiting application semantics, it is possible to achieve speedy failure recovery without introducing any costly logging overhead to the execution of concurrent transactions.
Edit intent: clarity
Original:  TARS leverages a combination of static and dynamic analyses to parallelize the log replay : at compile time, TARS decomposes stored procedures by carefully analyzing dependencies within and across programs;
Revised:  TARS leverages a combination of static and dynamic analyses to parallelize the log recovery : at compile time, TARS decomposes stored procedures by carefully analyzing dependencies within and across programs;
Edit intent: clarity
Original:  at recovery time, a re-execution schedule with a high degree of parallelism is attained through lightweight one-pass scans over transaction parameter values .
Revised:  at recovery time, a re-execution schedule with a high degree of parallelism .
Edit intent: clarity
Original:  As such, recovery latency is remarkably minimized .
Revised:  As such, recovery performance is remarkably increased .
Edit intent: clarity
Original:  We evaluated TARS in a main-memory database prototype running on a 40-core server . Compared to the state-of-the-art mechanisms, TARS yields significantly higher recovery rate without compromising the efficiency of transaction processing.
Revised:  We evaluated TARS in a main-memory DBMS running on a 40-core server . Compared to the state-of-the-art mechanisms, TARS yields significantly higher recovery rate without compromising the efficiency of transaction processing.
Edit intent: clarity
Original:  We evaluated TARS in a main-memory database prototype running on a 40-core server . Compared to the state-of-the-art mechanisms, TARS yields significantly higher recovery rate without compromising the efficiency of transaction processing.
Revised:  We evaluated TARS in a main-memory database prototype running on a 40-core machine . Compared to the state-of-the-art mechanisms, TARS yields significantly higher recovery rate without compromising the efficiency of transaction processing.
Edit intent: clarity
Original:  We evaluated TARS in a main-memory database prototype running on a 40-core server . Compared to the state-of-the-art mechanisms, TARS yields significantly higher recovery rate without compromising the efficiency of transaction processing.
Revised:  We evaluated TARS in a main-memory database prototype running on a 40-core server . Compared to several state-of-the-art mechanisms, TARS yields significantly higher recovery rate without compromising the efficiency of transaction processing.
Edit intent: clarity
Original: We perform a statistical-mechanical study of the asymptotic behaviors of stochastic cell fate decision between proliferation and differentiation.
Revised: We study the asymptotic behaviors of stochastic cell fate decision between proliferation and differentiation.
Edit intent: clarity
Original:  We propose a model based on a self-replicating Langevin system, where cells choose their fate (i.e. , proliferation or differentiation) , depending on the local cell density.
Revised:  We propose a model of a self-replicating Langevin system, where cells choose their fate (i.e. , proliferation or differentiation) , depending on the local cell density.
Edit intent: clarity
Original:  We propose a model based on a self-replicating Langevin system, where cells choose their fate (i.e. , proliferation or differentiation) , depending on the local cell density.
Revised:  We propose a model based on a self-replicating Langevin system, where cells choose their fate (i.e. proliferation or differentiation) , depending on the local cell density.
Edit intent: fluency
Original:  We propose a model based on a self-replicating Langevin system, where cells choose their fate (i.e. , proliferation or differentiation) , depending on the local cell density.
Revised:  We propose a model based on a self-replicating Langevin system, where cells choose their fate (i.e. , proliferation or differentiation) depending on local cell density.
Edit intent: fluency
Original:  Our results provide a unified platform for the study of stochastic cell fate decision in terms of nonequilibrium statistical physics .
Revised:  Our results provide a general platform for the study of stochastic cell fate decision in terms of nonequilibrium statistical physics .
Edit intent: clarity
Original:  Our results provide a unified platform for the study of stochastic cell fate decision in terms of nonequilibrium statistical physics .
Revised:  Our results provide a unified platform for the study of stochastic cell fate decision in terms of nonequilibrium statistical mechanics .
Edit intent: clarity
Original:  Based on this model, we propose a scenario for multi-cellular organisms to maintain the density of cells (i.e., homeostasis) through  cell-cell interactions , which is regarded as self-organized criticality .
Revised:  Based on this model, we propose a scenario for multi-cellular organisms to maintain the density of cells (i.e., homeostasis) through cell-cell interactions .
Edit intent: coherence
Original: Primary User Emulation Attack (PUEA), in which attackers emulate primary user signals causing restriction of secondary access on the attacked channels, is a serious security problem in Cognitive Radio Networks  CRNs).
Revised: Primary User Emulation Attack (PUEA), in which attackers emulate primary user signals causing restriction of secondary access on the attacked channels, is a serious security problem in Cognitive Radio Networks ( CRNs).
Edit intent: fluency
Original:  Network managers could adopt a surveillance process on disallowed channels for identifying illegal channel occupation of selfish PUE attackers and hence mitigating selfish PUEA.
Revised:  Network managers could adopt a surveillance process on disallowed channels for identifying illegal channel occupation of selfish PUEA attackers and hence mitigating selfish PUEA.
Edit intent: fluency
Original:  In this paper, we adopt a sequence-form representation of the gamebetween the selfish attack and the surveillance process, called surveillance game, to formulate the relation between the selfish attack and the surveillance process in multi-channel CRNs and explore the Nash Equilibrium (NE)  .
Revised:  In this paper, we formulate a game, called multi-channel surveillance game, to formulate the relation between the selfish attack and the surveillance process in multi-channel CRNs and explore the Nash Equilibrium (NE) .
Edit intent: clarity
Original:  In this paper, we adopt a sequence-form representation of the gamebetween the selfish attack and the surveillance process, called surveillance game, to formulate the relation between the selfish attack and the surveillance process in multi-channel CRNs and explore the Nash Equilibrium (NE)  .
Revised:  In this paper, we adopt a sequence-form representation of the gamebetween the selfish attack and the surveillance process, called surveillance game, between the selfish attack and the surveillance process in multi-channel CRNs and explore the Nash Equilibrium (NE) .
Edit intent: coherence
Original:  In this paper, we adopt a sequence-form representation of the gamebetween the selfish attack and the surveillance process, called surveillance game, to formulate the relation between the selfish attack and the surveillance process in multi-channel CRNs and explore the Nash Equilibrium (NE)  .
Revised:  In this paper, we adopt a sequence-form representation of the gamebetween the selfish attack and the surveillance process, called surveillance game, to formulate the relation between the selfish attack and the surveillance process in multi-channel CRNs . The sequence-form representation method is adopted to determine the Nash Equilibrium (NE) .
Edit intent: coherence
Original:  In this paper, we adopt a sequence-form representation of the gamebetween the selfish attack and the surveillance process, called surveillance game, to formulate the relation between the selfish attack and the surveillance process in multi-channel CRNs and explore the Nash Equilibrium (NE)  .
Revised:  In this paper, we adopt a sequence-form representation of the gamebetween the selfish attack and the surveillance process, called surveillance game, to formulate the relation between the selfish attack and the surveillance process in multi-channel CRNs and explore the Nash Equilibrium (NE) of the game .
Edit intent: clarity
Original: Recent work has shown good recognition results in 3D data using 3D convolutional networks.
Revised: Recent work has shown good recognition results in 3D object recognition using 3D convolutional networks.
Edit intent: clarity
Original:  In this paper, we argue that the object orientation plays an important role in 3D recognition.
Revised:  In this paper, we show that the object orientation plays an important role in 3D recognition.
Edit intent: clarity
Original:  To this end, we approach the category-level classification task as a multi-task problem, in which the network is forced to predict the pose of the object in addition to the class label  .
Revised:  To this end, we approach the category-level classification task as a multi-task problem, in which the network is trained to predict the pose of the object in addition to the class label .
Edit intent: clarity
Original:  We implemented different network architectures for this purpose and tested them on different datasets representing various 3D data sources: LiDAR data, CAD models and RGBD images.
Revised:  We test our suggested architecture on several datasets representing various 3D data sources: LiDAR data, CAD models and RGBD images.
Edit intent: clarity
Original:  We implemented different network architectures for this purpose and tested them on different datasets representing various 3D data sources: LiDAR data, CAD models and RGBD images.
Revised:  We implemented different network architectures for this purpose and tested them on different datasets representing various 3D data sources: LiDAR data, CAD models , and RGB-D images.
Edit intent: fluency
Original: Visual media have become a crucial part of our social lives.
Revised: Visual multimedia have become an inseparable part of our social lives.
Edit intent: clarity
Original:  a computational learning paradigm that has shown outstanding performance in several vision tasks , can be  applied to the task of visual sentiment prediction by fine-tuning  a state-of-the-art CNN . We analyze its architecture , studying several performance boosting techniques, which led to a network tuned to achieve a 6.1 \% absolute accuracy improvement over the previous state-of-the-art on a dataset of images from a popular social media platform.
Revised:  a now de facto computational machine learning tool particularly in the area of Computer Vision , can be applied to the task of visual sentiment prediction by fine-tuning a state-of-the-art CNN . We analyze its architecture , studying several performance boosting techniques, which led to a network tuned to achieve a 6.1 \% absolute accuracy improvement over the previous state-of-the-art on a dataset of images from a popular social media platform.
Edit intent: clarity
Original:  a computational learning paradigm that has shown outstanding performance in several vision tasks , can be  applied to the task of visual sentiment prediction by fine-tuning  a state-of-the-art CNN . We analyze its architecture , studying several performance boosting techniques, which led to a network tuned to achieve a 6.1 \% absolute accuracy improvement over the previous state-of-the-art on a dataset of images from a popular social media platform.
Revised:  a computational learning paradigm that has shown outstanding performance in several vision tasks , can be applied to the task of visual sentiment prediction . We accomplish this through fine-tuning a state-of-the-art CNN . We analyze its architecture , studying several performance boosting techniques, which led to a network tuned to achieve a 6.1 \% absolute accuracy improvement over the previous state-of-the-art on a dataset of images from a popular social media platform.
Edit intent: clarity
Original:  a computational learning paradigm that has shown outstanding performance in several vision tasks , can be  applied to the task of visual sentiment prediction by fine-tuning  a state-of-the-art CNN . We analyze its architecture , studying several performance boosting techniques, which led to a network tuned to achieve a 6.1 \% absolute accuracy improvement over the previous state-of-the-art on a dataset of images from a popular social media platform.
Revised:  a computational learning paradigm that has shown outstanding performance in several vision tasks , can be applied to the task of visual sentiment prediction by fine-tuning experiments using a state-of-the-art CNN . We analyze its architecture , studying several performance boosting techniques, which led to a network tuned to achieve a 6.1 \% absolute accuracy improvement over the previous state-of-the-art on a dataset of images from a popular social media platform.
Edit intent: clarity
Original:  a computational learning paradigm that has shown outstanding performance in several vision tasks , can be  applied to the task of visual sentiment prediction by fine-tuning  a state-of-the-art CNN . We analyze its architecture , studying several performance boosting techniques, which led to a network tuned to achieve a 6.1 \% absolute accuracy improvement over the previous state-of-the-art on a dataset of images from a popular social media platform.
Revised:  a computational learning paradigm that has shown outstanding performance in several vision tasks , can be applied to the task of visual sentiment prediction by fine-tuning a state-of-the-art CNN and via rigorous architecture analysis, we present several modifications that lead to accuracy improvements over prior art on a dataset of images from a popular social media platform.
Edit intent: clarity
Original:  Finally, we present visualizations of local patterns that the network associates to each image 's sentiment .
Revised:  We additionally present visualizations of local patterns that the network associates to each image 's sentiment .
Edit intent: clarity
Original:  Finally, we present visualizations of local patterns that the network associates to each image 's sentiment .
Revised:  Finally, we present visualizations of local patterns that the network learned to associate with image sentiment for insight into how visual positivity (or negativity) is perceived by the model .
Edit intent: clarity
Original:  We describe zenvisage's general purpose visual query language, ZQL ("zee-quel") for specifying the desired visual trend, pattern, or insight - zenvisage draws from use-cases in a variety of domains, including biology, mechanical engineering, commerce, and server monitoring .
Revised:  We describe zenvisage's general purpose visual query language, ZQL ("zee-quel") for specifying the desired visual trend, pattern, or insight - ZQL draws from use-cases in a variety of domains, including biology, mechanical engineering, commerce, and server monitoring .
Edit intent: fluency
Original:  While analysts are free to use ZQL directly, we also expose zenvisage via a visual specification interface , which we also describe in this paper.
Revised:  While analysts are free to use ZQL directly, we also expose ZQL via a visual specification interface , which we also describe in this paper.
Edit intent: fluency
Original:  While analysts are free to use ZQL directly, we also expose zenvisage via a visual specification interface , which we also describe in this paper.
Revised:  While analysts are free to use ZQL directly, we also expose zenvisage via a visual specification interface that we describe in this paper.
Edit intent: fluency
Original:  We then describe our architecture and optimizations, preliminary experiments in supporting and optimizing for ZQL queries in our initial zenvisage prototype, as well as a user study to evaluate whether data scientists are able to effectively use zenvisage for real applications.
Revised:  We then describe our architecture and optimizations, preliminary experiments in supporting and optimizing for ZQL queries in our initial zenvisage prototype, and a user study to evaluate whether data scientists are able to effectively use zenvisage for real applications.
Edit intent: coherence
Original: Common methods for imaging the 3D microstructure of the brain often require slicing the brain, imaging these slices, and stitching the images back together .
Revised: Methods for resolving the 3D microstructure of the brain often require slicing the brain, imaging these slices, and stitching the images back together .
Edit intent: clarity