wanyu/IteraTeR_v2 huggingface dataset:
Original:  To alleviate this challenging problem, we first decompose the original problem into two subproblems, namely, an integer non-linear  subchannel allocation subproblem and a non-convex power control subproblem.
Revised:  To alleviate this problem, we first decompose the original problem into two subproblems, namely, an integer non-linear subchannel allocation subproblem and a non-convex power control subproblem.
Edit intent: clarity
Original: Plasmonic nanostructures can significantly improve the performance of photoconductive devices (PCDs) .
Revised: Plasmonic nanostructures significantly improve the performance of photoconductive devices (PCDs) .
Edit intent: clarity
Original:  In the mean time, they introduce intricate structures and complex scattering, which lead new challenges to simulations .
Edit intent: coherence
Original:  In this work, a multiphysics framework based on discontinuous Galerkin (DG) methods is proposed to model the nonlinearly-coupled multiphysics processes in plasmonic PCDs.
Revised:  In this work, a multiphysics framework making use of discontinuous Galerkin (DG) methods is proposed to model the nonlinearly-coupled multiphysics processes in plasmonic PCDs.
Edit intent: clarity
Original:  The accuracy and applicability of the resulting multiphysics framework are demonstrated via simulations of conventional and plasmonic PCAs .
Revised:  The accuracy and applicability of the resulting multiphysics framework are demonstrated via simulations of conventional and plasmonic PCDs .
Edit intent: clarity
Original:  The calculus is also fail-safe in that, under minimal assumptions, all formal calculations are guaranteed to yield mathematically well-defined stochastic processes.
Revised:  The calculus is also fail-safe in that, under minimal assumptions, all informal calculations yield mathematically well-defined stochastic processes.
Edit intent: clarity
Original: Using  purely probabilistic argument, we prove the global well-posedness of multidimensional superquadratic backward stochastic differential equations (BSDEs) without Markovian assumption.
Revised: Using a purely probabilistic argument, we prove the global well-posedness of multidimensional superquadratic backward stochastic differential equations (BSDEs) without Markovian assumption.
Edit intent: fluency
Original:  Using a purely probabilistic argument, we prove the global well-posedness of multidimensional superquadratic backward stochastic differential equations (BSDEs) without Markovian assumption.
Revised: (Working Paper) Using a purely probabilistic argument, we prove the global well-posedness of multidimensional superquadratic backward stochastic differential equations (BSDEs) without Markovian assumption.
Edit intent: clarity
Original:  However, it inevitably encounters the severe sparsity of short text representation , making the previous clustering approaches still far from satisfactory.
Revised:  However, it inevitably encounters the severe sparsity of short text representations , making the previous clustering approaches still far from satisfactory.
Edit intent: fluency
Original:  To further facilitate the model training process , we apply adversarial training to the unsupervised clustering setting, by adding perturbations to the cluster representations.
Revised:  To further ensure robust model training for short texts , we apply adversarial training to the unsupervised clustering setting, by adding perturbations to the cluster representations.
Edit intent: clarity
Original:  To further facilitate the model training process , we apply adversarial training to the unsupervised clustering setting, by adding perturbations to the cluster representations.
Revised:  To further facilitate the model training process , we apply adversarial training to the unsupervised clustering setting, by injecting perturbations into the cluster representations.
Edit intent: clarity
Original:  Extensive experiments on three real-world short text datasets demonstrate the superiority of the proposed model over several strong competitors, verifying that  adversarial training yields a substantial performance gain .
Revised:  Extensive experiments on three real-world short text datasets demonstrate the superiority of the proposed model over several strong competitors, verifying that adversarial training yields substantial performance gains .
Edit intent: fluency
Original: We add logarithmic-bounded second-order quantifiers to the inflationary fixed-point logic, and find on ordered structures the new logic \exists^{\log^{\omega}}IFP captures the limited nondeterminism class \betaP.
Revised: We extend the inflationary fixed-point logic, and find on ordered structures the new logic \exists^{\log^{\omega}}IFP captures the limited nondeterminism class \betaP.
Edit intent: clarity
Original:  A new version of Ehrenfeucht-Fraisse game for the new logic is also designed in order to study its expressive power  .
Revised:  In order to study its expressive power .
Edit intent: coherence
Original:  To understand the limits of our argument we study a class of maps we call \textit{generally neighborly embeddings \emph{ , which map generic point sets into neighborly position.
Revised:  To understand the limits of our argument we study a class of maps we call \textit{ \emph{ , which map generic point sets into neighborly position.
Edit intent: clarity
Original:  To understand the limits of our argument we study a class of maps we call \textit{generally neighborly embeddings \emph{ , which map generic point sets into neighborly position.
Revised:  To understand the limits of our argument we study a class of maps we call \textit{generally neighborly embeddings \emph{generally neighborly embeddings , which map generic point sets into neighborly position.
Edit intent: fluency
Original: It is well known that the modern steganography methods are designed under the framework of distortion minimization, and thus the design of embedding cost is a key issue .
Revised: It is well known that the designing or improving embedding cost becomes a key issue .
Edit intent: clarity
Original:  Instead of designing embedding cost in existing works, we propose a novel framework to enhance the steganography security via stego post-processing .
Revised:  Instead of designing embedding cost in existing works, we propose a novel framework to enhance the steganography security via post-processing .
Edit intent: fluency
Original:  To ensure the correct extraction of hidden message , we firstly analyze the characteristics of STCs (Syndrome-Trellis Codes) that are widely used in current steganography methods , and then design the rule for post-modification.
Revised:  To ensure the correct extraction of hidden message , we firstly analyze the characteristics of STCs (Syndrome-Trellis Codes) , and then design the rule for post-modification.
Edit intent: clarity
Original:  Furthermore, since the steganography artifacts are typically reflected on image residuals, the proposed post-processing aims to reduce the residual distance between cover and the resulting stego .
Revised:  Furthermore, since the steganography artifacts are typically reflected on image residuals, we try to reduce the residual distance between cover and the resulting stego .
Edit intent: clarity
Original:  To this end, we model the proposed stego post-processing as a non-linear integer programming, and implement it via heuristic search.
Revised:  To this end, we model the post-processing as a non-linear integer programming, and implement it via heuristic search.
Edit intent: clarity
Original:  In addition, we carefully determine several important settings in our algorithm , such as the candidate embedding units to be dealt with , the direction and amplitude of post-modification, the adaptive filters for getting residuals, and the distance measure of residuals.
Revised:  In addition, we carefully determine several important issues in the proposed post-processing , such as the candidate embedding units to be dealt with , the direction and amplitude of post-modification, the adaptive filters for getting residuals, and the distance measure of residuals.
Edit intent: clarity
Original:  In addition, we carefully determine several important settings in our algorithm , such as the candidate embedding units to be dealt with , the direction and amplitude of post-modification, the adaptive filters for getting residuals, and the distance measure of residuals.
Revised:  In addition, we carefully determine several important settings in our algorithm , such as the candidate embedding units to be modified , the direction and amplitude of post-modification, the adaptive filters for getting residuals, and the distance measure of residuals.
Edit intent: clarity
Original:  Extensive experimental results evaluated on both hand-crafted steganalytic features and deep learning based ones demonstrate that the proposed method can  enhance the security performance of various steganography methods effectively and efficiently.
Revised:  Extensive experimental results evaluated on both hand-crafted steganalytic features and deep learning based ones demonstrate that the proposed method can effectively enhance the security performance of various steganography methods effectively and efficiently.
Edit intent: fluency
Original:  Underlying these poor results are the multiple legitimate spelling variations for a given name, as opposed to regular text that typically possesses a single way to be spelled correctly.
Revised:  Underlying these poor results are the multiple legitimate spelling variations for a given name, as opposed to regular text with a single way to be spelled correctly.
Edit intent: clarity
Original:  Today, most of the techniques suggesting related names based on pattern matching and phonetic encoding approaches .
Revised:  Today, most of the techniques used to suggest related names in an online search are based on pattern matching and phonetic encoding approaches .
Edit intent: clarity
Original:  Today, most of the techniques suggesting related names based on pattern matching and phonetic encoding approaches .
Revised:  Today, most of the techniques suggesting related names based on pattern matching and phonetic encoding .
Edit intent: clarity
Original:  Here, we propose a novel approach to tackle the problem of similar name suggestions.
Revised:  Here, we propose a revolutionary approach to tackle the problem of similar name suggestions.
Edit intent: clarity
Original:  Our novel algorithm utilizes historical data collected from genealogy websites  along with graph algorithms.
Revised:  Our novel algorithm utilizes historical data collected from genealogy websites , along with graph algorithms.
Edit intent: fluency
Original:  In contrast to previous approaches that suggest similar names based on encoded representations or patterns , we propose a general approach that suggests similar names based on the construction and analysis of  family trees.
Revised:  In contrast to previous approaches , we propose a general approach that suggests similar names based on the construction and analysis of family trees.
Edit intent: clarity
Original:  In contrast to previous approaches that suggest similar names based on encoded representations or patterns , we propose a general approach that suggests similar names based on the construction and analysis of  family trees.
Revised:  In contrast to previous approaches that suggest similar names based on encoded representations or patterns , we propose a general method that suggests similar names based on the construction and analysis of family trees.
Edit intent: clarity
Original:  Using this valuable and historical information and combining it with network algorithms provides a large name-based graph that offers a great number of suggestions based on historical ancestors.
Edit intent: coherence
Original:  Similar names are extracted from the graph based on generic ordering functions that outperform other algorithms suggesting names based on a single dimension, which limits their performance.
Revised:  Similar names are extracted from the graph using generic ordering functions that outperform other algorithms suggesting names based on a single dimension, which limits their performance.
Edit intent: fluency
Original:  Similar names are extracted from the graph based on generic ordering functions that outperform other algorithms suggesting names based on a single dimension, which limits their performance.
Revised:  Similar names are extracted from the graph based on generic ordering functions that outperform other algorithms that suggest names based on a single dimension, which limits their performance.
Edit intent: fluency
Original:  Utilizing a large-scale online genealogy dataset with over 17M profiles and more than 200K unique first names, we constructed a large name-based graph.
Revised:  Utilizing a large-scale online genealogy dataset with over 17 million profiles and more than 200K unique first names, we constructed a large name-based graph.
Edit intent: fluency
Original:  Utilizing a large-scale online genealogy dataset with over 17M profiles and more than 200K unique first names, we constructed a large name-based graph.
Revised:  Utilizing a large-scale online genealogy dataset with over 17M profiles and more than 200,000 unique first names, we constructed a large name-based graph.
Edit intent: fluency
Original:  Utilizing a large-scale online genealogy dataset with over 17M profiles and more than 200K unique first names, we constructed a large name-based graph.
Revised:  Utilizing a large-scale online genealogy dataset with over 17M profiles and more than 200K unique first names, we constructed a vast name-based graph.
Edit intent: clarity
Original:  Using this graph along with 7,399 labeled given names with their true synonyms, we evaluated our proposed approach and showed that comparing our algorithm to other algorithms, including phonetic and string similarity algorithms, provides superior performance in terms of accuracy, F1, and precision .
Revised:  Using this graph along with 7,399 labeled given names with their true synonyms, we evaluated our proposed approach . The results showed that our approach gave superior performance in terms of accuracy, F1, and precision .
Edit intent: clarity
Original:  We suggest our algorithm as a useful  tool for suggesting similar names based on constructing a name-based graph using family trees.
Revised:  We suggest our algorithm as a useful and valuable tool for suggesting similar names based on constructing a name-based graph using family trees.
Edit intent: clarity
Original:  However, web search engines suffer from low numbers of accurate results to a query containing names.
Revised:  However, Web search engines provide few accurate results to a query containing names.
Edit intent: clarity
Original:  However, web search engines suffer from low numbers of accurate results to a query containing names.
Revised:  However, web search engines suffer from low numbers of accurate results to queries containing names.
Edit intent: fluency
Original:  Underlying these poor results are the multiple legitimate spelling variations for a given name , as opposed to regular text with a single way to be spelled correctly .
Revised:  In contrast to a general text which has only one correct spelling, there are several legitimate spellings of a given name , as opposed to regular text with a single way to be spelled correctly .
Edit intent: clarity
Original:  Underlying these poor results are the multiple legitimate spelling variations for a given name , as opposed to regular text with a single way to be spelled correctly .
Revised:  Underlying these poor results are the multiple legitimate spelling variations for a given name .
Edit intent: coherence
Original:  Today, most of the techniques used to suggest related names in an online search are based on pattern matching and phonetic encoding .
Revised:  Today, most techniques used to suggest related names in an online search are based on pattern matching and phonetic encoding .
Edit intent: clarity
Original:  Today, most of the techniques used to suggest related names in an online search are based on pattern matching and phonetic encoding .
Revised:  Today, most of the techniques used to suggest synonyms in online search are based on pattern matching and phonetic encoding .
Edit intent: clarity
Original:  Here, we propose a revolutionary approach to tackle the problem of similar name suggestions .
Revised:  As a result, there is a need for an effective tool for improved synonym suggestion. In this paper, we propose a revolutionary approach to tackle the problem of similar name suggestions .
Edit intent: coherence
Original:  Here, we propose a revolutionary approach to tackle the problem of similar name suggestions .
Revised:  Here, we propose a revolutionary approach for tackling the problem of similar name suggestions .
Edit intent: fluency
Original:  Here, we propose a revolutionary approach to tackle the problem of similar name suggestions .
Revised:  Here, we propose a revolutionary approach to tackle the problem of synonym suggestion .
Edit intent: clarity
Original:  In contrast to previous approaches, we propose a general method that suggests similar names based on the construction and analysis of digitized ancestral family trees.
Revised:  In contrast to previous approaches, we propose a general method that suggests similar names based on the construction of a graph-based on names derived from generated digitized ancestral family trees.
Edit intent: clarity
Original:  Similar names are extracted from the graph using generic ordering functions that outperform other algorithms that suggest names based on a single dimension, which limits their performance.
Revised:  Synonyms are extracted from the graph using generic ordering functions that outperform other algorithms that suggest names based on a single dimension, which limits their performance.
Edit intent: clarity
Original:  Similar names are extracted from the graph using generic ordering functions that outperform other algorithms that suggest names based on a single dimension, which limits their performance.
Revised:  Similar names are extracted from this graph constructed using generic ordering functions that outperform other algorithms that suggest names based on a single dimension, which limits their performance.
Edit intent: clarity
Original:  Similar names are extracted from the graph using generic ordering functions that outperform other algorithms that suggest names based on a single dimension, which limits their performance.
Revised:  Similar names are extracted from the graph using generic ordering functions that outperform other algorithms that suggest names based on a single dimension, a factor that limits their performance.
Edit intent: clarity
Original:  The results showed that our approach gave superior performance in terms of accuracy, F1, and precision compared to other algorithms, including phonetic and string similarity algorithms .
Revised:  The results showed that our approach gave superior performance in terms of accuracy, F1, and precision compared to other algorithms, including phonetic encoding, string similarity algorithms .
Edit intent: clarity
Original:  In contrast to a general text which has only one correct spelling, there are several legitimate spellings of a given name.
Revised:  In contrast to a general word which has only one correct spelling, there are several legitimate spellings of a given name.
Edit intent: clarity
Original:  Today, most techniques used to suggest synonyms in online search are based on pattern matching and phonetic encoding, however , they frequently have poor performance .
Revised:  Today, most techniques used to suggest synonyms in online search are based on pattern matching and phonetic encoding, however they often perform poorly .
Edit intent: clarity
Original:  Our novel algorithm titled GRAFT utilizes historical data collected from genealogy websites, along with network algorithms.
Revised:  Our novel algorithm , GRAFT, utilizes historical data collected from genealogy websites, along with network algorithms.
Edit intent: clarity
Original:  This is a general algorithm that suggests synonyms based on the construction of a graph-based on names derived from generated digitized ancestral family trees.
Revised:  GRAFT is a general algorithm that suggests synonyms based on the construction of a graph-based on names derived from generated digitized ancestral family trees.
Edit intent: clarity
Original:  This is a general algorithm that suggests synonyms based on the construction of a graph-based on names derived from generated digitized ancestral family trees.
Revised:  This is a general algorithm that suggests synonyms using a graph based on names derived from generated digitized ancestral family trees.
Edit intent: clarity
Original:  This is a general algorithm that suggests synonyms based on the construction of a graph-based on names derived from generated digitized ancestral family trees.
Revised:  This is a general algorithm that suggests synonyms based on the construction of a graph-based on names derived from digitized ancestral family trees.
Edit intent: clarity
Original:  Synonyms are extracted from this graph  constructed using generic ordering functions that outperform other algorithms that suggest synonyms based on a single dimension, a factor that limits their performance.
Revised:  Synonyms are extracted from this graph , which is constructed using generic ordering functions that outperform other algorithms that suggest synonyms based on a single dimension, a factor that limits their performance.
Edit intent: coherence
Original:  We evaluated GRAFT's performance on  forenames and surnames, including the utilization of a large-scale online genealogy dataset with over 17 million profiles and more than 200 ,000 unique forenames and surnames.
Revised:  We evaluated GRAFT's performance on forenames and surnames, including a large-scale online genealogy dataset with over 17 million profiles and more than 200 ,000 unique forenames and surnames.
Edit intent: clarity
Original:  For comparison, we compared its performance at suggesting synonyms to nine algorithms, including phonetic encoding, string similarity algorithms, and machine and deep learning techniques .
Revised:  For comparison, we compared its performance at suggesting synonyms to nine algorithms, including phonetic encoding, string similarity algorithms, and machine and deep learning algorithms .
Edit intent: clarity
Original:  The results show that GRAFTfound superior to the evaluated algorithms with respect to both forenames and surnames and demonstrate its use as a tool to improve synonym suggestion.
Revised:  The results show GRAFT's superiority with respect to both forenames and surnames and demonstrate its use as a tool to improve synonym suggestion.
Edit intent: clarity
Original:  We also extend SPM to compute a certain generalized tensor decomposition , enabling generalized principal component analysis at extremely low SNR.
Revised:  We also extend SPM to compute a certain generalized tensor decomposition , enabling generalized principal component analysis at low SNR.
Edit intent: clarity
Original:  For tensors of rank up to roughly the square root of the number of tensor entries, we obtain provable guarantees for most steps of SPM, by drawing on results from  algebraic geometry and dynamical systems.
Revised:  For tensors of rank up to roughly the square root of the number of tensor entries, by drawing on results from algebraic geometry and dynamical systems.
Edit intent: clarity
Original:  We also extend SPM to compute  symmetric block term tensor decompositions , enabling generalized principal component analysis at low SNR .
Revised:  We also extend SPM to compute symmetric block term tensor decompositions , enabling generalized principal component analysis .
Edit intent: clarity