wanyu/IteraTeR_v2 huggingface dataset:
Original: Radiotherapy can effectively kill malignant cells, but the doses required to cure cancer patients can often not be applied as they come at the cost of severe collateral damage to adjacent healthy tissues.
Revised: Radiotherapy can effectively kill malignant cells, but the doses required to cure cancer patients may inflict severe collateral damage to adjacent healthy tissues.
Edit intent: clarity
Original:  Hyperthermia (HT) is a promising option to improve the outcome of radiation treatment (RT) and is increasingly applied in the clinics by incorporating a broad range of technological advances over the past 15 years .
Revised:  Hyperthermia (HT) is a promising option to improve the outcome of radiation treatment (RT) and is increasingly applied in hospital .
Edit intent: clarity
Original:  We here propose a theoretical model to better understand the thermal enhancement of RT.
Revised:  We here propose a theoretical model in which the thermal enhancement of RT.
Edit intent: clarity
Original:  In our model, the thermal enhancement ratio (TER) is explained by the fraction of cells that is radiosensitised by the infliction of sublethal damage through mild HT.
Revised:  In our model, the thermal enhancement ratio (TER) is explained by the fraction of cells being radiosensitised by the infliction of sublethal damage through mild HT.
Edit intent: clarity
Original:  In the course of further damage , the cells finally lose proliferative capacity and die, in a non-reversible process.
Revised:  Further damage finally kills the cell or inhibits its proliferation in a non-reversible process.
Edit intent: clarity
Original:  this is in agreement with previous empirical observations.
Revised:  in agreement with previous empirical observations.
Edit intent: coherence
Original:  Accordingly, our theoretical calculations well reproduce experimental data from both in-vitro and in-vivo studies for the simultaneous application of mild HT and RT.
Revised:  Our predictions well reproduce experimental data from both in-vitro and in-vivo studies for the simultaneous application of mild HT and RT.
Edit intent: clarity
Original:  Accordingly, our theoretical calculations well reproduce experimental data from both in-vitro and in-vivo studies for the simultaneous application of mild HT and RT.
Revised:  Accordingly, our theoretical calculations well reproduce experimental data from in-vitro and in-vivo studies for the simultaneous application of mild HT and RT.
Edit intent: clarity
Original: We present a new dataset for Visual Question Answering  on document images called DocVQA.
Revised: We present a new dataset for Visual Question Answering (VQA) on document images called DocVQA.
Edit intent: clarity
Original:  The dataset consistsof 50,000 questions defined on 12,000+ document images.
Revised:  The dataset consists of 50,000 questions defined on 12,000+ document images.
Edit intent: fluency
Original:  We provide detailed analysis of the dataset in comparison with similar datasets for VQA and reading comprehension  .
Revised:  Detailed analysis of the dataset in comparison with similar datasets for VQA and reading comprehension .
Edit intent: clarity
Original:  First and second order multirate, as well as time-adaptive Dirichlet-Neumann waveform relaxation (DNWR) methods are derived.
Revised:  First and second order multirate, as well as time-adaptive Dirichlet-Neumann Waveform relaxation (DNWR) methods are derived.
Edit intent: fluency
Original:  Similarly to a previously presented Neumann-Neumann waveform relaxation (NNWR) first and second order multirate methods are obtained.
Edit intent: coherence
Original:  In this study, the market designs of both wholesale markets and ancillary services in Spain are introduced, and the barriers to grid-connected battery storage are investigated under its specific market and regulatory framework.
Revised:  In this study, the barriers to grid-connected battery storage are investigated under its specific market and regulatory framework.
Edit intent: coherence
Original: Generalization, i.e., the ability of addressing problem instances that are not available during the system design and development phase, is a critical goal for intelligent systems.
Revised: Generalization, i.e., the ability of solving problem instances that are not available during the system design and development phase, is a critical goal for intelligent systems.
Edit intent: fluency
Original:  A typical way to achieve good generalization is to exploit vast data to train a model .
Revised:  A typical way to achieve good generalization is to learn a model from vast data .
Edit intent: clarity
Original:  In the context of heuristic search, such a paradigm is termed parameter tuning or algorithm configuration, i.e., configuring the parameters of a search method based on a set of "training " problem instances .
Revised:  In the context of heuristic search, such a paradigm could be implemented as configuring the parameters of a search method based on a set of "training " problem instances .
Edit intent: clarity
Original:  However, compared to its counterpart in machine learning, parameter tuning could more often suffer from the lack of training instances, and the obtained configuration may fail to generalize  .
Revised:  However, compared to traditional machine learning, parameter tuning could more often suffer from the lack of training instances, and the obtained configuration may fail to generalize .
Edit intent: clarity
Original:  However, compared to its counterpart in machine learning, parameter tuning could more often suffer from the lack of training instances, and the obtained configuration may fail to generalize  .
Revised:  However, compared to its counterpart in machine learning, PAP construction often suffers from the lack of training instances, and the obtained configuration may fail to generalize .
Edit intent: clarity
Original:  However, compared to its counterpart in machine learning, parameter tuning could more often suffer from the lack of training instances, and the obtained configuration may fail to generalize  .
Revised:  However, compared to its counterpart in machine learning, parameter tuning could more often suffer from the lack of training instances, and the obtained PAPs may fail to generalize .
Edit intent: clarity
Original:  This paper suggests competitive co-evolution as a remedy to this challenge and proposes a framework named Co-Evolution of Parameterized Search (CEPS) . By alternately evolving a configuration population and an instance population, CEPS is capable of obtaining generalizable configurations with few training instances.
Revised:  This paper proposes a novel competitive co-evolution as a remedy to this challenge and proposes a framework named Co-Evolution of Parameterized Search (CEPS) . By alternately evolving a configuration population and an instance population, CEPS is capable of obtaining generalizable configurations with few training instances.
Edit intent: clarity
Original:  This paper suggests competitive co-evolution as a remedy to this challenge and proposes a framework named Co-Evolution of Parameterized Search (CEPS) . By alternately evolving a configuration population and an instance population, CEPS is capable of obtaining generalizable configurations with few training instances.
Revised:  This paper suggests competitive co-evolution scheme, named Co-Evolution of Parameterized Search (CEPS) . By alternately evolving a configuration population and an instance population, CEPS is capable of obtaining generalizable configurations with few training instances.
Edit intent: clarity
Original:  This paper suggests competitive co-evolution as a remedy to this challenge and proposes a framework named Co-Evolution of Parameterized Search (CEPS) . By alternately evolving a configuration population and an instance population, CEPS is capable of obtaining generalizable configurations with few training instances.
Revised:  This paper suggests competitive co-evolution as a remedy to this challenge and proposes a framework named Co-Evolution of Parameterized Search (CEPS) , as a remedy to this challenge. By co-evolving a configuration population and an instance population, CEPS is capable of obtaining generalizable configurations with few training instances.
Edit intent: clarity
Original:  This paper suggests competitive co-evolution as a remedy to this challenge and proposes a framework named Co-Evolution of Parameterized Search (CEPS) . By alternately evolving a configuration population and an instance population, CEPS is capable of obtaining generalizable configurations with few training instances.
Revised:  This paper suggests competitive co-evolution as a remedy to this challenge and proposes a framework named Co-Evolution of Parameterized Search (CEPS) . By alternately evolving a configuration population and an instance population, CEPS is capable of obtaining generalizable PAPs with few training instances.
Edit intent: clarity
Original:  The advantage of CEPS in improving generalization is analytically shown  .
Revised:  The advantage of CEPS in improving generalization is analytically shown in this paper .
Edit intent: clarity
Original:  Two concrete instantiations , namely CEPS-TSP and CEPS-VRPSPDTW, are also presented for the Traveling Salesman Problem (TSP) and the Vehicle Routing Problem with Simultaneous Pickup-Delivery and Time Windows (VRPSPDTW), respectively.
Revised:  Two concrete algorithms , namely CEPS-TSP and CEPS-VRPSPDTW, are also presented for the Traveling Salesman Problem (TSP) and the Vehicle Routing Problem with Simultaneous Pickup-Delivery and Time Windows (VRPSPDTW), respectively.
Edit intent: clarity
Original:  Two concrete instantiations , namely CEPS-TSP and CEPS-VRPSPDTW, are also presented for the Traveling Salesman Problem (TSP) and the Vehicle Routing Problem with Simultaneous Pickup-Delivery and Time Windows (VRPSPDTW), respectively.
Revised:  Two concrete instantiations , namely CEPS-TSP and CEPS-VRPSPDTW, are presented for the Traveling Salesman Problem (TSP) and the Vehicle Routing Problem with Simultaneous Pickup-Delivery and Time Windows (VRPSPDTW), respectively.
Edit intent: clarity
Original:  The level set method (LSM) is the most popular approach for solving the model , via implicitly representing the contour by a level set function.
Revised:  The level set method (LSM) is the most popular approach for solving the models , via implicitly representing the contour by a level set function.
Edit intent: fluency
Original:  However, the LSM suffers from high computation burden and numerical instability, requiring additional regularization terms or re-initialization techniques.
Revised:  However, the LSM suffers from high computational burden and numerical instability, requiring additional regularization terms or re-initialization techniques.
Edit intent: fluency
Original:  Compared to the LSM, the ICTM is simpler and much more efficient and stable .
Revised:  Compared to the LSM, the ICTM is simpler and much more efficient .
Edit intent: clarity
Original:  In addition, the ICTM enjoys most desired features (e.g., topological changes) of the level set-based methods.
Revised:  In addition, the ICTM enjoys most desired features of the level set-based methods.
Edit intent: clarity
Original:  Extensive experiments, on 2D synthetic, 2D ultrasound, 3D CT, and 3D MR images for nodule, organ and lesion segmentation, demonstrate that the ICTM not only obtains comparable or even better segmentation results (compared to the LSM) but also achieves dozens or hundreds of times acceleration.
Revised:  Extensive experiments, on 2D synthetic, 2D ultrasound, 3D CT, and 3D MR images for nodule, organ and lesion segmentation, demonstrate that the proposed method not only obtains comparable or even better segmentation results (compared to the LSM) but also achieves dozens or hundreds of times acceleration.
Edit intent: clarity
Original:  Extensive experiments, on 2D synthetic, 2D ultrasound, 3D CT, and 3D MR images for nodule, organ and lesion segmentation, demonstrate that the ICTM not only obtains comparable or even better segmentation results (compared to the LSM) but also achieves dozens or hundreds of times acceleration.
Revised:  Extensive experiments, on 2D synthetic, 2D ultrasound, 3D CT, and 3D MR images for nodule, organ and lesion segmentation, demonstrate that the ICTM not only obtains comparable or even better segmentation results (compared to the LSM) but also achieves significant acceleration.
Edit intent: clarity
Original:  Our focus here is on partial recovery, i.e., we look for a one-to-one mapping which is correct on a fraction of the nodes of the graph rather than on all of them, and we assume that the two input graphs to the problem are correlated Erd\"os-R\'enyis-R\'enyi } graphs of parameters (n,q,s).
Revised:  Our focus here is on partial recovery, i.e., we look for a one-to-one mapping which is correct on a fraction of the nodes of the graph rather than on all of them, and we assume that the two input graphs to the problem are correlated Erd\H{os-R\'enyi } graphs of parameters (n,q,s).
Edit intent: clarity
Original:  Our focus here is on partial recovery , i.e., we look for a one-to-one mapping which is correct on a fraction of the nodes of the graph rather than on all of them, and we assume that the two input graphs to the problem are correlated Erdos-R\'enyi graphs of parameters (n,q,s).
Revised:  Our focus here is on partial recovery , i.e., we look for a one-to-one mapping which is correct on a fraction of the nodes of the graph rather than on all of them, and we assume that the two input graphs to the problem are correlated Erdos-R\'enyi graphs of parameters (n,q,s).
Edit intent: fluency
Original:  In the present study structure of 3CL^{pro is used to study drug: 3CL^{pro interactions and thus to investigate whether all or any of the main chemical constituents of Tinospora cordifolia (e.g., berberine (C_{20 , \beta-sitosterol (C_{29 (C_{21H_{25}NO_{4})} \rm{(C_{28}H_{58}O))} can be used as an anti-viral drug against SARS-CoV-2.
Revised:  In the present study , is used to study drug: 3CL^{pro interactions and thus to investigate whether all or any of the main chemical constituents of Tinospora cordifolia (e.g., berberine (C_{20 , \beta-sitosterol (C_{29 (C_{21H_{25}NO_{4})} \rm{(C_{28}H_{58}O))} can be used as an anti-viral drug against SARS-CoV-2.
Edit intent: clarity
Original:  In the present study structure of 3CL^{pro is used to study drug: 3CL^{pro interactions and thus to investigate whether all or any of the main chemical constituents of Tinospora cordifolia (e.g., berberine (C_{20 , \beta-sitosterol (C_{29 (C_{21H_{25}NO_{4})} \rm{(C_{28}H_{58}O))} can be used as an anti-viral drug against SARS-CoV-2.
Revised:  In the present study structure of 3CL^{pro is used to study drug: 3CLpro interactions and thus to investigate whether all or any of the main chemical constituents of Tinospora cordifolia (e.g., berberine (C_{20 , \beta-sitosterol (C_{29 (C_{21H_{25}NO_{4})} \rm{(C_{28}H_{58}O))} can be used as an anti-viral drug against SARS-CoV-2.
Edit intent: fluency
Original:  In the present study structure of 3CL^{pro is used to study drug: 3CL^{pro interactions and thus to investigate whether all or any of the main chemical constituents of Tinospora cordifolia (e.g., berberine (C_{20 , \beta-sitosterol (C_{29 (C_{21H_{25}NO_{4})} \rm{(C_{28}H_{58}O))} can be used as an anti-viral drug against SARS-CoV-2.
Revised:  In the present study structure of 3CL^{pro is used to study drug: 3CL^{pro interactions and thus to investigate whether all or any of the main chemical constituents of Tinospora cordifolia (e.g., berberine , \beta-sitosterol (C_{29 (C_{21H_{25}NO_{4})} \rm{(C_{28}H_{58}O))} can be used as an anti-viral drug against SARS-CoV-2.
Edit intent: coherence
Original: Our goal in this paper aims to investigate the causality in the decision making of movie recommendations from a Recommender perspective through the behavior of users' affective moods.
Revised: This paper investigates the causality in the decision making of movie recommendations from a Recommender perspective through the behavior of users' affective moods.
Edit intent: coherence
Original: Our goal in this paper aims to investigate the causality in the decision making of movie recommendations from a Recommender perspective through the behavior of users' affective moods.
Revised: Our goal in this paper aims to investigate the causality in the decision making of movie recommendations through the users' affective moods.
Edit intent: clarity
Original:  We illustrate a method of assigning emotional tags to a movie by  auto-detection of the affective attributes in the movie  overview.
Revised:  We illustrate a method of assigning emotional tags to a movie by the auto-detection of the affective attributes in the movie overview.
Edit intent: fluency
Original:  We illustrate a method of assigning emotional tags to a movie by  auto-detection of the affective attributes in the movie  overview.
Revised:  We illustrate a method of assigning emotional tags to a movie by auto-detection of the affective features in the movie overview.
Edit intent: clarity
Original:  We illustrate a method of assigning emotional tags to a movie by  auto-detection of the affective attributes in the movie  overview.
Revised:  We illustrate a method of assigning emotional tags to a movie by auto-detection of the affective attributes in the movie 's overview.
Edit intent: clarity
Original:  We apply a text-based Emotion Detection and Recognition model, which trained by the short text of tweets , and then transfer the model learning to detect the implicit affective features of a movie from the movie overview.
Revised:  We apply a text-based Emotion Detection and Recognition model, which trained by tweets short messages and transfers the learned model to detect movie overviews' implicit affective features of a movie from the movie overview.
Edit intent: clarity
Original:  We vectorize the affective movie tags through embedding to represent the mood  of the movie.
Revised:  We vectorize the affective movie tags to represent the mood of the movie.
Edit intent: clarity
Original:  Whereas we vectorize the user's emotional features by averaging all the watched movie' s vectors , and when incorporated the average ratings from the user rated for all watchedmovies, we obtain the weighted vector .
Revised:  We obtain the user's emotional features by averaging all the watched movie' s vectors , and when incorporated the average ratings from the user rated for all watchedmovies, we obtain the weighted vector .
Edit intent: clarity
Original:  Whereas we vectorize the user's emotional features by averaging all the watched movie' s vectors , and when incorporated the average ratings from the user rated for all watchedmovies, we obtain the weighted vector .
Revised:  Whereas we vectorize the user's emotional features by taking the average of all the movies' affective vectors the user has watched .
Edit intent: clarity
Original:  We present how to valuate  wide range of financial derivatives for such  model.
Revised:  We present how to valuate a wide range of financial derivatives for such model.
Edit intent: fluency
Original:  We present how to valuate  wide range of financial derivatives for such  model.
Revised:  We present how to valuate wide range of financial derivatives for such a model.
Edit intent: fluency
Original:  Finally two cases of applications of the novel ZBDT model were introduced.
Revised:  Finally two cases of applications of the novel ZBDT model are introduced.
Edit intent: fluency
Original:  The second case is an application  in the structure of United State sovereign bonds of the ZBDT model in the current 2020 economic slowdown caused by the Coronavirus pandemic.
Revised:  The second case is an application of the ZBDT model in the structure of United State sovereign bonds of the ZBDT model in the current 2020 economic slowdown caused by the Coronavirus pandemic.
Edit intent: fluency
Original:  The second case is an application  in the structure of United State sovereign bonds of the ZBDT model in the current 2020 economic slowdown caused by the Coronavirus pandemic.
Revised:  The second case is an application in the structure of United States sovereign bonds in the current 2020 economic slowdown caused by the Coronavirus pandemic.
Edit intent: clarity
Original:  In particular, for a low rank 3-order tensor with \Theta(n) parameters, Barak and Moitra conjectured that \Omega(n ^{ 3 /2}) samples are needed for polynomial time computation based on a reduction of a specific hard instance of a rank 1 tensor to the random 3-XOR distinguishability problem .
Revised:  In particular, for a low rank 3-order tensor with \Theta(n) parameters, Barak and Moitra conjectured that \Omega(n ^{ 3 /2}) samples in order to guarantee consistent estimation .
Edit intent: clarity
Original:  If the sum of each latent factor vector is bounded away from zero, we present }  an algorithm that can perform tensor estimation with O(n^{1+\kappa}) samples for a t-order tensor, significantly less than the previous achievable bound of O(n^{t/2), and close to the lower bound of \Omega(n).
Revised:  If the sum of each latent factor vector is bounded away from zero, we present } an algorithm that can perform tensor estimation with O(n^{1+\kappa}) samples for ), and close to the lower bound of \Omega(n).
Edit intent: clarity
Original:  We propose a weak supervision strategy that iteratively uses ColBERT to create its own training data.
Revised:  We propose an efficient weak supervision strategy that iteratively uses ColBERT to create its own training data.
Edit intent: clarity
Original:  This greatly improves OpenQA retrieval on both Natural Questions and TriviaQA, and the resulting end-to-end OpenQA system attains state-of-the-art performance on both of those datasets.
Revised:  This greatly improves OpenQA retrieval on both Natural Questions and TriviaQA, and the resulting system attains state-of-the-art performance on both of those datasets.
Edit intent: clarity
Original: Machine learning (ML) models are widely used in many domains including media processing and generation, computer vision, medical diagnosis, embedded systems, high-performance and scientific computing, and recommendation systems .
Revised: Machine learning (ML) models are widely used in many important domains .
Edit intent: clarity
Original:  Unstructured sparsity and tensors with varying dimensions yield irregular-shaped computation, communication, and memory access patterns;
Revised:  Unstructured sparsity and tensors with varying dimensions yield irregular computation, communication, and memory access patterns;
Edit intent: clarity
Original:  This paper provides a comprehensive survey on how to efficiently execute sparse and irregular tensor computations of ML models on hardware accelerators.
Revised:  This paper provides a comprehensive survey on the efficient execution of sparse and irregular tensor computations of ML models on hardware accelerators.
Edit intent: clarity
Original:  In particular, it discusses additional enhancement modules in  architecture design and  software support;
Revised:  In particular, it discusses enhancement modules in architecture design and software support;
Edit intent: clarity
Original:  In particular, it discusses additional enhancement modules in  architecture design and  software support;
Revised:  In particular, it discusses additional enhancement modules in the architecture design and software support;
Edit intent: fluency
Original:  In particular, it discusses additional enhancement modules in  architecture design and  software support;
Revised:  In particular, it discusses additional enhancement modules in architecture design and the software support;
Edit intent: fluency
Original:   highlights further opportunities in terms of hardware/software/ algorithm co-design optimizations and joint optimizations among described hardware and software enhancement modules .
Revised:  highlights further opportunities in terms of hardware/software/ model co-design optimizations and joint optimizations among described hardware and software enhancement modules .
Edit intent: clarity