wanyu/IteraTeR_v2 huggingface dataset:
Original:  of f by a {\em canonical set} S \subseteq V is a set function g given by g(X) = f(X \vartriangle S) for X \subseteq V,where X \vartriangle S = (X \setminus S) \cup (S \setminus X) is the%DIFDELCMD < {\it %%% symmetric difference between X and S. Despite that submodular functions and SD-transformations are regarded as counterparts of convex functions and affine transformations in finite discrete space, not all SD-transformations do not preserve the submodularity.
Revised:  of f by a {\em canonical set} S \subseteq V is a set function g given by g(X) = f(X \vartriangle S) for X \subseteq V,where X \vartriangle S = (X \setminus S) \cup (S \setminus X) is the%DIFDELCMD < {\it %%% symmetric difference between X and S. Submodularity and SD-transformations are regarded as counterparts of convex functions and affine transformations in finite discrete space, not all SD-transformations do not preserve the submodularity.
Edit intent: clarity
Original:  of f by a {\em canonical set} S \subseteq V is a set function g given by g(X) = f(X \vartriangle S) for X \subseteq V,where X \vartriangle S = (X \setminus S) \cup (S \setminus X) is the%DIFDELCMD < {\it %%% symmetric difference between X and S. Despite that submodular functions and SD-transformations are regarded as counterparts of convex functions and affine transformations in finite discrete space, not all SD-transformations do not preserve the submodularity.
Revised:  of f by a {\em canonical set} S \subseteq V is a set function g given by g(X) = f(X \vartriangle S) for X \subseteq V,where X \vartriangle S = (X \setminus S) \cup (S \setminus X) is the%DIFDELCMD < {\it %%% symmetric difference between X and S. Despite that submodular functions and SD-transformations are regarded as the counterparts of convexity and affine transformations in finite discrete space, not all SD-transformations do not preserve the submodularity.
Edit intent: fluency
Original:  of f by a {\em canonical set} S \subseteq V is a set function g given by g(X) = f(X \vartriangle S) for X \subseteq V,where X \vartriangle S = (X \setminus S) \cup (S \setminus X) is the%DIFDELCMD < {\it %%% symmetric difference between X and S. Despite that submodular functions and SD-transformations are regarded as counterparts of convex functions and affine transformations in finite discrete space, not all SD-transformations do not preserve the submodularity.
Revised:  of f by a {\em canonical set} S \subseteq V is a set function g given by g(X) = f(X \vartriangle S) for X \subseteq V,where X \vartriangle S = (X \setminus S) \cup (S \setminus X) is the%DIFDELCMD < {\it %%% symmetric difference between X and S. Despite that submodular functions and SD-transformations are regarded as counterparts of convex functions and affine transformations in a discrete space, not all SD-transformations do not preserve the submodularity.
Edit intent: clarity
Original:  of f by a {\em canonical set} S \subseteq V is a set function g given by g(X) = f(X \vartriangle S) for X \subseteq V,where X \vartriangle S = (X \setminus S) \cup (S \setminus X) is the%DIFDELCMD < {\it %%% symmetric difference between X and S. Despite that submodular functions and SD-transformations are regarded as counterparts of convex functions and affine transformations in finite discrete space, not all SD-transformations do not preserve the submodularity.
Revised:  of f by a {\em canonical set} S \subseteq V is a set function g given by g(X) = f(X \vartriangle S) for X \subseteq V,where X \vartriangle S = (X \setminus S) \cup (S \setminus X) is the%DIFDELCMD < {\it %%% symmetric difference between X and S. Despite that submodular functions and SD-transformations are regarded as counterparts of convex functions and affine transformations in finite discrete space, respectively. However, submodularity is not preserved under SD-transformations do not preserve the submodularity.
Edit intent: clarity
Original:  Starting with a characterization of SD-stransformations that preserve the submodularity, this paper investigates the problem of discovering a canonical set S, given the SD-transformation g of a submodular function f by S, provided that g(X) is given by an oracle.
Revised:  Starting with a characterization of SD-stransformations preserving submodularity. Then, we are concerned with the problem of discovering a canonical set S, given the SD-transformation g of a submodular function f by S, provided that g(X) is given by an oracle.
Edit intent: clarity
Original:  A submodular function f on V is said to be { %DIFDELCMD < \it %DIFDELCMD < %%% \em strict} if f(X) + f(Y) > f(X \cup Y) - f(X \cap Y) holds whenever both X \setminus Y and Y \setminus X are nonempty.
Revised:  A submodular function f on V is said to be { %DIFDELCMD < \it %DIFDELCMD < %%% \em strict} if f(X) + f(Y) > f(X \cup Y) + f(X \cap Y) holds whenever both X \setminus Y and Y \setminus X are nonempty.
Edit intent: fluency
Original:  We show that the problem is solvable by using {\rm O}(|V|) oracle calls when f is strictly submodular, although it requires exponentially many oracle calls in general.
Revised:  We show that the problem is solved by using {\rm O}(|V|) oracle calls when f is strictly submodular, although it requires exponentially many oracle calls in general.
Edit intent: clarity
Original: A set function f on a finite set V is %DIFDELCMD < {\em %%% submodular if f(X) + f(Y) \geq f(X \cup Y) + f(X \cap Y) for any pair X, Y \subseteq V.
Revised: A set function f on a finite set V is %DIFDELCMD < {\em %%% submodular if f(X) + f(Y) \geq f(X \cup Y) + f(X \cap Y) for any pair X, Y \subseteq V.
Edit intent: fluency
Original:  The %DIFDELCMD < {\em %DIFDELCMD < %%% symmetric difference transformation (%DIFDELCMD < {\em %%%  SD-transformation ) of f by a %DIFDELCMD < {\em %DIFDELCMD < %%% canonical set S \subseteq V is a set function g given by g(X)
Revised:  The %DIFDELCMD < {\em %DIFDELCMD < %%% symmetric difference transformation %DIFDELCMD < {\em %%% SD-transformation ) of f by a %DIFDELCMD < {\em %DIFDELCMD < %%% canonical set S \subseteq V is a set function g given by g(X)
Edit intent: fluency
Original:  The %DIFDELCMD < {\em %DIFDELCMD < %%% symmetric difference transformation (%DIFDELCMD < {\em %%%  SD-transformation ) of f by a %DIFDELCMD < {\em %DIFDELCMD < %%% canonical set S \subseteq V is a set function g given by g(X)
Revised:  The %DIFDELCMD < {\em %DIFDELCMD < %%% symmetric difference transformation (%DIFDELCMD < {\em %%% SD-transformation ) of f by a %DIFDELCMD < {\em %DIFDELCMD < %%% canonical set S \subseteq V is a set function g given by g(X)
Edit intent: fluency
Original:  A submodular function f on V is said to be %DIFDELCMD < {\em %%% strict if f(X) + f(Y) > f(X \cup Y) + f(X \cap Y) holds whenever both X \setminus Y and Y \setminus X are nonempty.
Revised:  A submodular function f on V is said to be %DIFDELCMD < {\em %%% strict if f(X) + f(Y) > f(X \cup Y) + f(X \cap Y) holds whenever both X \setminus Y and Y \setminus X are nonempty.
Edit intent: fluency
Original:  Also, we show that the smallest largest-area triangle can be found in O(n^2 \log n) time .
Revised:  Also, we show that the smallest largest-area triangle can be done in O(n^2 \log n) time .
Edit intent: clarity
Original:  Finally, we discuss to what extent our results can be generalized to larger values of k .
Revised:  We also discuss to what extent our results can be generalized to larger values of k .
Edit intent: coherence
Original: Recent researches on neural network have shown great advantage in computer vision over traditional algorithms based on handcrafted features and models.
Revised: Recent researches on neural network have shown significant advantage in computer vision over traditional algorithms based on handcrafted features and models.
Edit intent: clarity
Original:  But the great computation and storage complexity of neural network based algorithms poses great difficulty on its application.
Revised:  But the high computation and storage complexity of neural network based algorithms poses great difficulty on its application.
Edit intent: clarity
Original:  Investigation from software to hardware, from circuit level to system level is carried out to complete analysis of FPGA based neural network accelerator design and serves as a guide to future work.
Revised:  An investigation from software to hardware, from circuit level to system level is carried out to complete analysis of FPGA based neural network accelerator design and serves as a guide to future work.
Edit intent: coherence
Original: Recent researches on neural network have shown significant advantage in computer vision over traditional algorithms based on handcrafted features and models.
Revised: Recent researches on neural network have shown significant advantage in machine learning over traditional algorithms based on handcrafted features and models.
Edit intent: clarity
Original:  But the high computation and storage complexity of neural network based algorithms poses great difficulty on its application.
Revised:  But the high computation and storage complexity of neural network inference poses great difficulty on its application.
Edit intent: clarity
Original:  On the other hand, FPGA based neural network accelerator is becoming a research topic.
Revised:  On the other hand, FPGA-based neural network inference accelerator is becoming a research topic.
Edit intent: clarity
Original:  Various FPGA based accelerator designs have been proposed with software and hardware optimization techniques to achieve high speed and energy efficiency.
Revised:  Various FPGA-based accelerator designs have been proposed with software and hardware optimization techniques to achieve high speed and energy efficiency.
Edit intent: fluency
Original:  An investigation from software to hardware, from circuit level to system level is carried out to complete analysis of FPGA based neural network accelerator design and serves as a guide to future work.
Revised:  An investigation from software to hardware, from circuit level to system level is carried out to complete analysis of FPGA-based neural network inference accelerator design and serves as a guide to future work.
Edit intent: clarity
Original:  A common method for combating this disease is through the use of copper hydroxide as a fungicide, which can have damaging effects both on the coffee tree and on human health.
Revised:  A common method for combating this disease is using copper hydroxide as a fungicide, which can have damaging effects both on the coffee tree and on human health.
Edit intent: coherence
Original:  A novel method for biological control of coffee rust  has been proven to be an effective alternative to copper hydroxide fungicides is anti-fungal compounds.
Revised:  A novel method for biological control of coffee rust has been proven to be an effective alternative to copper hydroxide fungicides as anti-fungal compounds.
Edit intent: fluency
Original:  In this paper, we develop and explore a spatial stochastic model for the interaction of bacteria and coffee rust in a coffee plantation.
Revised:  In this paper, we develop and explore a spatial stochastic model for this interaction in a coffee plantation.
Edit intent: clarity
Original:  As well as, analyse equilibria for specific control strategies, compute conditions for stability under specific conditions, and perform numerical experiments under local and global control strategies  .
Revised:  We analyze equilibria for specific control strategies, compute conditions for stability under specific conditions, and perform numerical experiments under local and global control strategies .
Edit intent: coherence
Original: Similarity measure as a fundamental task in heterogeneous information network analysis has been applied to many areas, e.g.  product recommendation, clustering and web search.
Revised: Similarity measure as a fundamental task in heterogeneous information network analysis has been applied to many areas, e.g. , product recommendation, clustering and web search.
Edit intent: fluency
Original:  The state-of-the-art metrics depend on meta paths or meta structures specified by users  .
Revised:  The state-of-the-art metrics depend on the meta-path or meta-structure specified by users .
Edit intent: fluency
Original:  In this paper, a novel similarity measure on heterogeneous information networks, called Deep Meta Structure based Similarity (DMSS ), is proposed.
Revised:  In this paper, a novel similarity measure in heterogeneous information networks, called Deep Meta Structure based Similarity (DMSS ), is proposed.
Edit intent: fluency
Original:  The deep meta structure as a schematic structure on heterogeneous information networks provides a unified framework integrating all the meta paths and meta structures.
Revised:  The recurrent meta-structure as a schematic structure on heterogeneous information networks provides a unified framework integrating all the meta paths and meta structures.
Edit intent: clarity
Original:  The deep meta structure as a schematic structure on heterogeneous information networks provides a unified framework integrating all the meta paths and meta structures.
Revised:  The deep meta structure as a schematic structure in heterogeneous information networks provides a unified framework integrating all the meta paths and meta structures.
Edit intent: fluency
Original:  In order to formalize the semantics encapsulated in the deep meta structure, we decompose it into several deep meta paths, and then combine all the commuting matrices of these deep meta paths according to different weights.
Revised:  In order to formalize the semantics encapsulated in the deep meta structure, we decompose it into several deep meta paths, and then combine all the commuting matrices of the recurrent meta-paths and meta-trees. All of the commuting matrices of the recurrent meta-paths and meta-trees are combined according to different weights.
Edit intent: clarity
Original:  It is noteworthy that the weights can be determined by the proposed strategy .
Revised:  Note that the weights can be determined by the proposed strategy .
Edit intent: coherence
Original:  As a result, DMSS is defined by virtue of the final commuting matrix and therefore is robust to different schematic structures . Experimental evaluations show that the state-of-the-art metrics are really sensitive to meta paths or meta structures in terms of clustering and ranking.
Revised:  As a result, DMSS is defined by virtue of the final commuting matrix . Experimental evaluations show that the state-of-the-art metrics are really sensitive to meta paths or meta structures in terms of clustering and ranking.
Edit intent: coherence
Original:  Besides, DMSS outperforms the state-of-the-art metrics in terms of ranking and clustering in the case of selecting an appropriate decaying parameter .
Revised:  Besides, DMSS outperforms the state-of-the-art metrics in terms of ranking and clustering tasks .
Edit intent: clarity
Original:  Second, due to the difficulty on training deep neural networks, existing models utilize a shallow architecture, and thus limit the expressiveness potential of deep learning.
Revised:  Second, due to the difficulty on training deep neural networks, existing models utilize a shallow architecture, and thus limit the expressive potential of deep learning.
Edit intent: fluency
Original:  To tackle these issues, we present a novel recommender framework called Deep Collaborative Autoencoder ( DCAE) for both explicit feedback and implicit feedback , which can effectively capture the relationship between interactions via its non-linear expressiveness .
Revised:  To tackle these issues, we present a novel recommender framework called Deep Collaborative Autoencoder ( DCAE) for both explicit feedback and implicit feedback , which can effectively capture the relationship between interactions via a non-linear expressiveness .
Edit intent: fluency
Original:  Moreover, we propose a popularity-based error reweighting module and a sparsity-aware data-augmentation strategy for DCAE to prevent overfitting on the implicit setting .
Revised:  Moreover, to prevent overfitting on the implicit setting, we propose an error reweighting module and a sparsity-aware data-augmentation strategy for DCAE to prevent overfitting on the implicit setting .
Edit intent: coherence
Original:  Moreover, we propose a popularity-based error reweighting module and a sparsity-aware data-augmentation strategy for DCAE to prevent overfitting on the implicit setting .
Revised:  Moreover, we propose a popularity-based error reweighting module and a sparsity-aware data-augmentation strategy .
Edit intent: coherence
Original:  Although some recent works have focused on combining deep learning with recommendation, we highlight three issues of existing works .
Revised:  Although some recent works have focused on combining deep learning with recommendation, we highlight three issues of existing models .
Edit intent: clarity
Original:  Second, due to the difficulty on training deep neural networks, existing models utilize a shallow architecture, and thus limit the expressive potential of deep learning.
Revised:  Second, due to the difficulty on training deep neural networks, existing explicit models do not fully exploit the expressive potential of deep learning.
Edit intent: clarity
Original:  Third, neural network models are easy to overfit on the implicit setting , because negative interactions are not taken into account .
Revised:  Third, neural network models are easier to overfit on the implicit setting , because negative interactions are not taken into account .
Edit intent: clarity
Original:  NCAE can effectively capture the relationship between interactions via a non-linear matrix factorization process.
Revised:  NCAE can effectively capture the subtle hidden relationships between interactions via a non-linear matrix factorization process.
Edit intent: clarity
Original: We formulate an age-structure three stage nonlinear partial differential equation model that features {\it nonlinear} recidivism to the infected ({\it infectious}) class from the {\it temporarily} recovered class.
Revised: We formulate an age-structured three-staged nonlinear partial differential equation model that features {\it nonlinear} recidivism to the infected ({\it infectious}) class from the {\it temporarily} recovered class.
Edit intent: fluency
Original:  As a result, a backward-bifurcation exists under necessary  conditions.
Revised:  As a result, a backward-bifurcation exists under necessary and sufficient conditions.
Edit intent: clarity
Original:  A generalized numerical framework is established and numerical experiments are explored under which necessary conditions are needed for two positive solutions to exist in the {\it infectious} class.
Revised:  A generalized numerical framework is established and numerical experiments are explored for two positive solutions to exist in the {\it infectious} class.
Edit intent: clarity
Original: Invasion of the red imported fire ant  Solenopsis invicta Buren causes destructive effects to native biodiversity, agriculture, and public health.
Revised: Invasion by the red imported fire ant Solenopsis invicta Buren causes destructive effects to native biodiversity, agriculture, and public health.
Edit intent: fluency
Original: Invasion of the red imported fire ant  Solenopsis invicta Buren causes destructive effects to native biodiversity, agriculture, and public health.
Revised: Invasion of the red imported fire ant , Solenopsis invicta Buren causes destructive effects to native biodiversity, agriculture, and public health.
Edit intent: fluency
Original: Invasion of the red imported fire ant  Solenopsis invicta Buren causes destructive effects to native biodiversity, agriculture, and public health.
Revised: Invasion of the red imported fire ant Solenopsis invicta Buren , has destructive effects on native biodiversity, agriculture, and public health.
Edit intent: fluency
Original:  Due to its aggressive foraging behavior and high reproductive capability , the fire ant has established wild populations in most of the imported regions .
Revised:  This ant's aggressive foraging behaviour and high reproductive capability , the fire ant has established wild populations in most of the imported regions .
Edit intent: clarity
Original:  Due to its aggressive foraging behavior and high reproductive capability , the fire ant has established wild populations in most of the imported regions .
Revised:  Due to its aggressive foraging behavior and high reproductive capability have enabled its establishment of wild populations in most of the imported regions .
Edit intent: clarity
Original:  Due to its aggressive foraging behavior and high reproductive capability , the fire ant has established wild populations in most of the imported regions .
Revised:  Due to its aggressive foraging behavior and high reproductive capability , the fire ant has established wild populations in most regions into which it has been imported .
Edit intent: clarity
Original:  The key to successful eradication is thorough  monitoring and destruction of the nests in the early stage of invasion to prevent its range expansion.
Revised:  The key to successful eradication is thorough nest monitoring and destruction of the nests in the early stage of invasion to prevent its range expansion.
Edit intent: fluency
Original:  The key to successful eradication is thorough  monitoring and destruction of the nests in the early stage of invasion to prevent its range expansion.
Revised:  The key to successful eradication is thorough monitoring and destruction during early invasion to prevent its range expansion.
Edit intent: clarity
Original:  The key to successful eradication is thorough  monitoring and destruction of the nests in the early stage of invasion to prevent its range expansion.
Revised:  The key to successful eradication is thorough monitoring and destruction of the nests in the early stage of invasion to prevent range expansion.
Edit intent: clarity
Original:  Here the question is, how intense in temporal and spatial scale should monitoring be to eradicate the fire ant?
Revised:  The question is: How intense must monitoring be on temporal and spatial scale should monitoring be to eradicate the fire ant?
Edit intent: clarity
Original:  Here the question is, how intense in temporal and spatial scale should monitoring be to eradicate the fire ant?
Revised:  Here the question is, how intense in temporal and spatial scales to eradicate the fire ant?
Edit intent: clarity
Original:  Assuming that the fire ant was introduced to a region , and monitoring was conducted immediately after a nest was detected in order to detect all other potentially established nests, we developed a mathematical model to investigate the detection rate .
Revised:  Assuming that the ant was introduced to a region , and monitoring was conducted immediately after a nest was detected in order to detect all other potentially established nests, we developed a mathematical model to investigate the detection rate .
Edit intent: clarity
Original:  Assuming that the fire ant was introduced to a region , and monitoring was conducted immediately after a nest was detected in order to detect all other potentially established nests, we developed a mathematical model to investigate the detection rate .
Revised:  Assuming that the fire ant was introduced into a region and that monitoring was conducted immediately after a nest was detected in order to detect all other potentially established nests, we developed a mathematical model to investigate the detection rate .
Edit intent: fluency
Original:  Assuming that the fire ant was introduced to a region , and monitoring was conducted immediately after a nest was detected in order to detect all other potentially established nests, we developed a mathematical model to investigate the detection rate .
Revised:  Assuming that the fire ant was introduced to a region , and monitoring was conducted immediately after nest detection in an effort to detect all other potentially established nests, we developed a mathematical model to investigate the detection rate .
Edit intent: clarity