wanyu/IteraTeR_v2 huggingface dataset:
Original:  In particular, we prove that the network coding gap for the completion time of k unicasts  is at most polylogarithmic in k , and there exist instances of k unicasts for which this coding gap is polylogarithmic in k  .
Revised:  In particular, we prove that the network coding gap for the makespan of k unicasts is at most polylogarithmic in k , and there exist instances of k unicasts for which this coding gap is polylogarithmic in k .
Edit intent: clarity
Original:  Events for redeeming and refunding smart contracts to exchange assets are modeled as conflicting events.
Revised:  The redeem and refund events of the smart contracts that exchange assets are modeled as conflicting events.
Edit intent: clarity
Original: Frequently Asked Question (FAQ) retrieval is an important task where the objective is to retrieve the appropriate Question-Answer (QA) pair from a database based on the user's query.
Revised: Frequently Asked Question (FAQ) retrieval is an important task where the objective is to retrieve an appropriate Question-Answer (QA) pair from a database based on the user's query.
Edit intent: fluency
Original: Frequently Asked Question (FAQ) retrieval is an important task where the objective is to retrieve the appropriate Question-Answer (QA) pair from a database based on the user's query.
Revised: Frequently Asked Question (FAQ) retrieval is an important task where the objective is to retrieve the appropriate Question-Answer (QA) pair from a database based on a user's query.
Edit intent: fluency
Original:  In this study, we propose a FAQ retrieval system that considers the similarity between a user's query and a question computed by a traditional unsupervised information retrieval system, as well as the relevance between the query and an answer computed by the recently-proposed BERT model.
Revised:  We propose a FAQ retrieval system that considers the similarity between a user's query and a question computed by a traditional unsupervised information retrieval system, as well as the relevance between the query and an answer computed by the recently-proposed BERT model.
Edit intent: clarity
Original:  In this study, we propose a FAQ retrieval system that considers the similarity between a user's query and a question computed by a traditional unsupervised information retrieval system, as well as the relevance between the query and an answer computed by the recently-proposed BERT model.
Revised:  In this study, we propose a FAQ retrieval system that considers the similarity between a user's query and a question as well as the relevance between the query and an answer computed by the recently-proposed BERT model.
Edit intent: coherence
Original:  We show that f(m,d,K_r)\ge \left(1{2} + d^{-1+\Omega(r^{-1})}\right)m, improving on and generalizing a recent work of Carlson, Kolla, and Trevisan.
Revised:  We show that f(m,d,K_r)\ge \left(1{2} + d^{-1+\Omega(r^{-1})}\right)m, generalizing a recent work of Carlson, Kolla, and Trevisan.
Edit intent: clarity
Original: We propose a novel causal coding scheme with forward error correction (FEC) for a point-to-point communication link with delayed feedback.
Revised: We propose a novel causal coding scheme with forward error correction (FEC) for a point-to-point communication channel with delayed feedback.
Edit intent: clarity
Original:  We investigate the throughput , and the in-order delivery delay of the adaptive causal coding algorithm, and contrast its performance with the one of the selective repeat (SR) ARQ.
Revised:  We investigate the throughput , and the in-order delivery delay of the adaptive causal coding algorithm, and contrast its performance with the one of selective repeat (SR) ARQ.
Edit intent: fluency
Original:  We demonstrate via an experimental study of the protocol that our model can double the throughput gains, and triple the gain in terms of mean in-order delivery delay when the channel is bursty , while keeping the difference between the maximum and mean in-order delivery delay is much smaller than SR ARQ . Closing the delay gap along with boosting the throughput is very promising for enabling ultra-reliable low-latency communications applications.
Revised:  We demonstrate via an experimental study of the protocol that our model can double the throughput gains, and triple the gain in terms of mean in order delivery delay when the channel is bursty , while keeping the difference between the maximum and mean in-order delivery delay is much smaller than SR ARQ . Closing the delay gap along with boosting the throughput is very promising for enabling ultra-reliable low-latency communications applications.
Edit intent: fluency
Original:  We demonstrate via an experimental study of the protocol that our model can double the throughput gains, and triple the gain in terms of mean in-order delivery delay when the channel is bursty , while keeping the difference between the maximum and mean in-order delivery delay is much smaller than SR ARQ . Closing the delay gap along with boosting the throughput is very promising for enabling ultra-reliable low-latency communications applications.
Revised:  We demonstrate via an experimental study of the protocol that our model can double the throughput gains, and triple the gain in terms of mean in-order delivery delay when the channel is bursty . Furthermore, the difference between the maximum and mean in-order delivery delay is much smaller than SR ARQ . Closing the delay gap along with boosting the throughput is very promising for enabling ultra-reliable low-latency communications applications.
Edit intent: coherence
Original:  We demonstrate via an experimental study of the protocol that our model can double the throughput gains, and triple the gain in terms of mean in-order delivery delay when the channel is bursty , while keeping the difference between the maximum and mean in-order delivery delay is much smaller than SR ARQ . Closing the delay gap along with boosting the throughput is very promising for enabling ultra-reliable low-latency communications applications.
Revised:  We demonstrate via an experimental study of the protocol that our model can double the throughput gains, and triple the gain in terms of mean in-order delivery delay when the channel is bursty , while keeping the difference between the maximum and mean in order delivery delay is much smaller than SR ARQ . Closing the delay gap along with boosting the throughput is very promising for enabling ultra-reliable low-latency communications applications.
Edit intent: fluency
Original:  We demonstrate via an experimental study of the protocol that our model can double the throughput gains, and triple the gain in terms of mean in-order delivery delay when the channel is bursty , while keeping the difference between the maximum and mean in-order delivery delay is much smaller than SR ARQ . Closing the delay gap along with boosting the throughput is very promising for enabling ultra-reliable low-latency communications applications.
Revised:  We demonstrate via an experimental study of the protocol that our model can double the throughput gains, and triple the gain in terms of mean in-order delivery delay when the channel is bursty , while keeping the difference between the maximum and mean in-order delivery delay is much smaller than that of SR-ARQ . Closing the delay gap along with boosting the throughput is very promising for enabling ultra-reliable low-latency communications applications.
Edit intent: clarity
Original: The traditional reversible data hiding technique is based on  image modification which is more easily analyzed and attacked .
Revised: The traditional reversible data hiding technique is based on cover image modification which is more easily analyzed and attacked .
Edit intent: fluency
Original:  In this paper, a novel somewhat reversible data hiding scheme ( SRDH ) by image to image translate is proposed.
Revised:  In this paper, a novel somewhat reversible data hiding scheme ( SRDH ) by image translation is proposed.
Edit intent: clarity
Original:  We call the scheme somewhat because it is not completely reversible . Experimental results have verified the correctness of the scheme.
Revised:  We call the scheme somewhat because it is not completely reversible . Experimental results have verified the effectiveness of the scheme.
Edit intent: clarity
Original:  In this research paper, we raise an idea about the value of Handle, called PID Kernel Information, which is the critical metadata describing the minimal information for identifying the PID object.
Revised:  In this paper, we raise an idea about the value of Handle, called PID Kernel Information, which is the critical metadata describing the minimal information for identifying the PID object.
Edit intent: clarity
Original:  This study presents the Labelled Latent Dirichlet Allocation (L-LDA)-incorporated Support Vector Machine (SVM) classifier with the supporting computing strategy for using publicly available Twitter data , which is 1\% of the total twitter data, in determining transportation related events (i.e., incidents, congestions, special events, construction and other events) to provide reliable information to travelers.
Revised:  This study presents the Labelled Latent Dirichlet Allocation (L-LDA)-incorporated Support Vector Machine (SVM) classifier with the supporting computing strategy on publicly available Twitter data , which is 1\% of the total twitter data, in determining transportation related events (i.e., incidents, congestions, special events, construction and other events) to provide reliable information to travelers.
Edit intent: clarity
Original:  This study presents the Labelled Latent Dirichlet Allocation (L-LDA)-incorporated Support Vector Machine (SVM) classifier with the supporting computing strategy for using publicly available Twitter data , which is 1\% of the total twitter data, in determining transportation related events (i.e., incidents, congestions, special events, construction and other events) to provide reliable information to travelers.
Revised:  This study presents the Labelled Latent Dirichlet Allocation (L-LDA)-incorporated Support Vector Machine (SVM) classifier with the supporting computing strategy for using publicly available Twitter data in determining transportation-related events to provide reliable information to travelers.
Edit intent: coherence
Original:  In total, almost 700,010 tweets are analyzed to extract relevant transportation related information for one week.
Revised:  Approximately 700,010 tweets are analyzed to extract relevant transportation related information for one week.
Edit intent: clarity
Original:  In total, almost 700,010 tweets are analyzed to extract relevant transportation related information for one week.
Revised:  In total, almost 700,010 tweets are analyzed to extract relevant transportation-related information for one week.
Edit intent: fluency
Original:  For a large geographic area like New York City and its surrounding areas, using parallel computation, 30 times speedup is achieved compared to the sequential processing in analyzing transportation related tweets.
Edit intent: coherence
Original:  To further categorize the transportation related tweets into sub-classes: incident, congestion, construction, special events, and other events, three supervised classifiers are used: L-LDA, SVM, and L-LDA incorporated SVM.
Revised:  To further categorize the transportation-related tweets into sub-classes: incident, congestion, construction, special events, and other events, three supervised classifiers are used: L-LDA, SVM, and L-LDA incorporated SVM.
Edit intent: fluency
Original:  The analytical framework, which uses the L-LDA incorporated SVM, can classify roadway transportation related data from Twitter with over 98.3\% accuracy, which is significantly higher than the accuracies achieved by standalone L-LDA and SVM.
Revised:  Findings from this study demonstrate that the analytical framework, which uses the L-LDA incorporated SVM, can classify roadway transportation related data from Twitter with over 98.3\% accuracy, which is significantly higher than the accuracies achieved by standalone L-LDA and SVM.
Edit intent: clarity
Original:  The analytical framework, which uses the L-LDA incorporated SVM, can classify roadway transportation related data from Twitter with over 98.3\% accuracy, which is significantly higher than the accuracies achieved by standalone L-LDA and SVM.
Revised:  The analytical framework, which uses the L-LDA incorporated SVM, can classify roadway transportation-related data from Twitter with over 98.3\% accuracy, which is significantly higher than the accuracies achieved by standalone L-LDA and SVM.
Edit intent: fluency
Original:  The minimum system size to see the instability grows with the response time  , proportional to \tau in the large delay limit.
Revised:  The minimum system size to see the instability grows with the response time \tau , proportional to \tau in the large delay limit.
Edit intent: fluency
Original:  Moreover, the results also demonstrate that the proposed deep RL approach can significantly improve the achievable sum-AoI per process compared to baseline policies such as the distance-based and random walk policies.
Revised:  Moreover, the results also demonstrate that the proposed deep RL approach can significantly improve the achievable sum-AoI per process compared to the baseline policies, such as the distance-based and random walk policies.
Edit intent: fluency
Original:  The method is based on a Gaussian mixture free energy estimator , and exploits the shape of the estimated density landscape.
Revised:  The method is based on a Gaussian mixture free energy estimator and exploits the shape of the estimated density landscape.
Edit intent: fluency
Original:  The core states that naturally arise from the clustering allow for detailed characterization of the conformational ensemble in a parameter-free way .
Revised:  The core states that naturally arise from the clustering allow for detailed characterization of the conformational ensemble .
Edit intent: clarity
Original:  Finally, the method is applied to a temperature enhanced molecular dynamics simulation of Ca 2 + -bound Calmodulin.
Revised:  Finally, the method is applied to a temperature enhanced molecular dynamics simulation of Ca2 + -bound Calmodulin.
Edit intent: fluency
Original:  Finally, the method is applied to a temperature enhanced molecular dynamics simulation of Ca 2 + -bound Calmodulin.
Revised:  Finally, the method is applied to a temperature enhanced molecular dynamics simulation of Ca 2 + bound Calmodulin.
Edit intent: fluency
Original:  Nvidia 's current CUBLAS implementation delivers only a fraction of the potential performance (as given by the roofline model ) in this case.
Revised:  NVIDIA 's current CUBLAS implementation delivers only a fraction of the potential performance (as given by the roofline model ) in this case.
Edit intent: fluency
Original:  Nvidia 's current CUBLAS implementation delivers only a fraction of the potential performance (as given by the roofline model ) in this case.
Revised:  Nvidia 's current CUBLAS implementation delivers only a fraction of the potential performance as indicated by the roofline model ) in this case.
Edit intent: clarity
Original:  Nvidia 's current CUBLAS implementation delivers only a fraction of the potential performance (as given by the roofline model ) in this case.
Revised:  Nvidia 's current CUBLAS implementation delivers only a fraction of the potential performance (as given by the roofline model in this case.
Edit intent: fluency
Original:  We describe the challenges and key properties of an implementation that can achieve perfect performance.
Revised:  We describe the challenges and key characteristics of an implementation that can achieve perfect performance.
Edit intent: clarity
Original:  We describe the challenges and key properties of an implementation that can achieve perfect performance.
Revised:  We describe the challenges and key properties of an implementation that can achieve close to optimal performance.
Edit intent: clarity
Original:  We further evaluate different approaches of parallelization and thread distribution, and devise a flexible, configurable mapping scheme.
Revised:  We further evaluate different strategies of parallelization and thread distribution, and devise a flexible, configurable mapping scheme.
Edit intent: clarity
Original:  A code generation approach enables a simultaneously flexible and specialized implementation with autotuning.
Revised:  To ensure flexibility and allow for highly tailored implementations we use code generation combined with autotuning.
Edit intent: clarity
Original:  This results in perfect performance for a large range of matrix sizes in the domain of interest , and at least 2/3 of maximum performance for the rest on an Nvidia Volta GPGPU.
Revised:  For a large range of matrix sizes in the domain of interest , and at least 2/3 of maximum performance for the rest on an Nvidia Volta GPGPU.
Edit intent: clarity
Original:  This results in perfect performance for a large range of matrix sizes in the domain of interest , and at least 2/3 of maximum performance for the rest on an Nvidia Volta GPGPU.
Revised:  This results in perfect performance for a large range of matrix sizes in the domain of interest we achieve at least 2/3 of maximum performance for the rest on an Nvidia Volta GPGPU.
Edit intent: clarity
Original:  In the case of on-to-one correspondence between names and phone numbers (n=s), the algorithm offers inverse phonebook search too.
Revised:  In the case of one-to-one correspondence between names and phone numbers (n=s), the algorithm offers inverse phonebook search too.
Edit intent: fluency
Original: We present fully polynomial approximation schemes for general classes of Holant problems with complex edge weights, which we call Holant polynomials.
Revised: We present fully polynomial approximation schemes for a broad class of Holant problems with complex edge weights, which we call Holant polynomials.
Edit intent: clarity
Original:  Our method involves establishing zero-free regions for the partition functions of polymer models and using the high-energy terms of the cluster expansion to approximate them.
Revised:  Our method involves establishing zero-free regions for the partition functions of polymer models and using the most significant terms of the cluster expansion to approximate them.
Edit intent: clarity
Original: With the improvement of pattern recognition and feature extraction of the Deep Neural Networks (DNNs), more and more problems are attempted to solve from the view of images.
Revised: With the improvement of pattern recognition and feature extraction of Deep Neural Networks (DNNs), more and more problems are attempted to solve from the view of images.
Edit intent: fluency
Original:  In this study, an improved ReConNN model is proposed to address the mentioned weaknesses.
Revised:  In this study, an improved ReConNN method is proposed to address the mentioned weaknesses.
Edit intent: clarity
Original:  Through experiments, comparisons and analyses, the improved one is demonstrated to outperform in accuracy, efficiency and cost .
Revised:  Through experiments, comparisons and analyses, the improved method is demonstrated to outperform in accuracy, efficiency and cost .
Edit intent: clarity
Original:  Through experiments, comparisons and analyses, the improved one is demonstrated to outperform in accuracy, efficiency and cost .
Revised:  Through experiments, comparisons and analyses, the improved one is demonstrated to outperform the former one in terms of its accuracy, efficiency and cost .
Edit intent: clarity
Original:  Through experiments, comparisons and analyses, the improved one is demonstrated to outperform in accuracy, efficiency and cost .
Revised:  Through experiments, comparisons and analyses, the improved one is demonstrated to outperform in accuracy, efficiency and costs .
Edit intent: fluency
Original: Nevertheless, the identical relevance assumption does not allow analyzing systems where some vertices represent strategic physical locations (e.g. hospitals, administrative building, schools, water and energy sources, etc.) or representative persons (e.g. presidents, prime ministers, intellectuals, etc.) for which the relevance cannot be derived from the connectivity network structure without embedding the information about the vertex intrinsic relevance .
Revised: Nevertheless, the identical relevance assumption does not allow analyzing systems where some vertices represent strategic physical locations (e.g. , hospitals, water and energy sources, etc.) or representative persons (e.g. presidents, prime ministers, intellectuals, etc.) for which the relevance cannot be derived from the connectivity network structure without embedding the information about the vertex intrinsic relevance .
Edit intent: clarity
Original: Nevertheless, the identical relevance assumption does not allow analyzing systems where some vertices represent strategic physical locations (e.g. hospitals, administrative building, schools, water and energy sources, etc.) or representative persons (e.g. presidents, prime ministers, intellectuals, etc.) for which the relevance cannot be derived from the connectivity network structure without embedding the information about the vertex intrinsic relevance .
Revised: Nevertheless, the identical relevance assumption does not allow analyzing systems where some vertices represent strategic physical locations (e.g. hospitals, administrative building, schools, water and energy sources, etc.) or institutional roles (e.g. presidents, prime ministers, intellectuals, etc.) for which the relevance cannot be derived from the connectivity network structure without embedding the information about the vertex intrinsic relevance .
Edit intent: clarity
Original: Nevertheless, the identical relevance assumption does not allow analyzing systems where some vertices represent strategic physical locations (e.g. hospitals, administrative building, schools, water and energy sources, etc.) or representative persons (e.g. presidents, prime ministers, intellectuals, etc.) for which the relevance cannot be derived from the connectivity network structure without embedding the information about the vertex intrinsic relevance .
Revised: Nevertheless, the identical relevance assumption does not allow analyzing systems where some vertices represent strategic physical locations (e.g. hospitals, administrative building, schools, water and energy sources, etc.) or representative persons (e.g. , presidents, agencies, etc.) for which the relevance cannot be derived from the connectivity network structure without embedding the information about the vertex intrinsic relevance .
Edit intent: clarity
Original: Nevertheless, the identical relevance assumption does not allow analyzing systems where some vertices represent strategic physical locations (e.g. hospitals, administrative building, schools, water and energy sources, etc.) or representative persons (e.g. presidents, prime ministers, intellectuals, etc.) for which the relevance cannot be derived from the connectivity network structure without embedding the information about the vertex intrinsic relevance .
Revised: Nevertheless, the identical relevance assumption does not allow analyzing systems where some vertices represent strategic physical locations (e.g. hospitals, administrative building, schools, water and energy sources, etc.) or representative persons (e.g. presidents, prime ministers, intellectuals, etc.) . In these cases, the connectivity network structure without embedding the information about the vertex intrinsic relevance .
Edit intent: clarity