wanyu/IteraTeR_v2 huggingface dataset:
Original:  This yields  57\% relative word error rate (WER) reduction on utterances containing OOV words without any degradation on the whole test set.
Revised:  This yields a 57\% relative word error rate (WER) reduction on utterances containing OOV words without any degradation on the whole test set.
Edit intent: fluency
Original:  These low-dimensional models can identify a subspace which contains designs that are invariant in performance--the inactive subspace.
Revised:  These low-dimensional models can identify a subspace which contains designs that are invariant in performance -- the inactive subspace.
Edit intent: fluency
Original: This paper proposes a new model for augmenting algorithms with useful predictions that go beyond worst-case bounds on the algorithm performance.
Revised: We propose a new model for augmenting algorithms with useful predictions that go beyond worst-case bounds on the algorithm performance.
Edit intent: clarity
Original:  Learnability guarantees that predictions can be efficiently constructed from  past data.
Revised:  Learnability ensures that predictions can be efficiently constructed from past data.
Edit intent: fluency
Original:  Instance robustness formally ensures a prediction is robust to modest changes in the problem input .
Revised:  Instance robustness ensures that the prediction is robust to modest changes in the problem input .
Edit intent: clarity
Original:  The paper considers online algorithms with predictions for a network flow allocation problem and the restricted assignment makespan minimization problem .
Revised:  The paper considers online algorithms with predictions for a network flow allocation problem and restricted assignment makespan minimization problem .
Edit intent: fluency
Original:  The paper considers online algorithms with predictions for a network flow allocation problem and the restricted assignment makespan minimization problem .
Revised:  The paper considers online algorithms with predictions for a network flow allocation problem and the restricted assignment makespan minimization .
Edit intent: fluency
Original:  Our first set of contributions is on the problem of verifying TSO- and PSO-consistent executions given a reads-from map,  VTSO-rf and VPSO-rf, respectively.
Revised:  Our first set of contributions is on the problem of verifying TSO- and PSO-consistent executions given a reads-from map, denoted VTSO-rf and VPSO-rf, respectively.
Edit intent: clarity
Original:  The problem has been heavily studied under SC due to its numerous applications, but little is known for TSO and PSO.
Edit intent: coherence
Original:  Our second contribution is an algorithm for SMC under TSO and PSO using the RF equivalence.
Revised:  Based on our solution to these problems, we develop an SMC algorithm under TSO and PSO using the RF equivalence.
Edit intent: clarity
Original:  Our second contribution is an algorithm for SMC under TSO and PSO using the RF equivalence.
Revised:  Our second contribution is an algorithm for SMC under TSO and PSO that uses the RF equivalence.
Edit intent: fluency
Original:  Our algorithm is exploration-optimal, in the sense that it is guaranteed to explore each class of the RF partitioning exactly once, and spends polynomial time per class when k is bounded.
Revised:  The algorithm is exploration-optimal, in the sense that it is guaranteed to explore each class of the RF partitioning exactly once, and spends polynomial time per class when k is bounded.
Edit intent: fluency
Original:  This may be because  technologies emerge or production is moved abroad.
Revised:  This may be because new technologies emerge or production is moved abroad.
Edit intent: clarity
Original:  Our results show that not only we can accurately predict occupational transitions (Accuracy = 76\%), but we account for the asymmetric difficulties of moving between jobs (it is easier to move in one direction than the other).
Revised:  Our results show that not only can we accurately predict occupational transitions (Accuracy = 76\%), but we account for the asymmetric difficulties of moving between jobs (it is easier to move in one direction than the other).
Edit intent: fluency
Original:  By using real-time data, our systems can respond to labor demand shifts as they occur (such as those caused by COVID-19) , and can be leveraged by policy-makers, educators, and jobseekers who are forced to confront the often distressing challenges of having to find new jobs.
Revised:  By using real-time data, our systems can respond to labor demand shifts as they occur (such as those caused by COVID-19) . They can be leveraged by policy-makers, educators, and jobseekers who are forced to confront the often distressing challenges of having to find new jobs.
Edit intent: coherence
Original:  By using real-time data, our systems can respond to labor demand shifts as they occur (such as those caused by COVID-19) , and can be leveraged by policy-makers, educators, and jobseekers who are forced to confront the often distressing challenges of having to find new jobs.
Revised:  By using real-time data, our systems can respond to labor demand shifts as they occur (such as those caused by COVID-19) , and can be leveraged by policy-makers, educators, and job seekers who are forced to confront the often distressing challenges of having to find new jobs.
Edit intent: fluency
Original:  By using real-time data, our systems can respond to labor demand shifts as they occur (such as those caused by COVID-19) , and can be leveraged by policy-makers, educators, and jobseekers who are forced to confront the often distressing challenges of having to find new jobs.
Revised:  By using real-time data, our systems can respond to labor demand shifts as they occur (such as those caused by COVID-19) , and can be leveraged by policy-makers, educators, and jobseekers who are forced to confront the often distressing challenges of finding new jobs.
Edit intent: coherence
Original: As ecosystems might lose their biodiversity and even change from the functional state to the extinct state due to environmental degradation, resilience restoration thus plays an increasingly important role in recovering the service and functions of the systems .
Revised: Many systems may switch to an undesired state due to environmental degradation, resilience restoration thus plays an increasingly important role in recovering the service and functions of the systems .
Edit intent: clarity
Original:  Impeded by the difficulty of high dimensionality, nonlinearity, and stochastic effects , however, there is little understanding of the bistability and transitions for spatially-extended systems in noisy environment .
Revised:  Impeded by the difficulty of high dimensionality, nonlinearity, and stochastic effects .
Edit intent: coherence
Original:  More importantly, this approach is not restricted to ecosystems , but it can be generally used to study resilience and transitions in various dynamical systems with alternative stable states .
Revised:  More importantly, this approach is not limited to ecosystems and has applications in various dynamical systems with alternative stable states .
Edit intent: clarity
Original:  In this work, we propose a weak supervision based approach for detecting code search intent in search queries for C \# and Java programming languages.
Revised:  In this work, we propose a weak supervision based approach for detecting code search intent in search queries for C and Java programming languages.
Edit intent: coherence
Original: ChampaignABSTRACTWe propose an end-to-end trainable approach to single-channel speech separation with unknown number of speakers.
Revised: We propose an end-to-end trainable approach to single-channel speech separation with unknown number of speakers.
Edit intent: coherence
Original:  Our approach extends the MulCat source separation backbonewith additional output heads: a count-head to infer the num-ber of speakers, and decoder-heads for reconstructing theoriginal signals.
Revised:  Our approach extends the MulCat source separation backbone with additional output heads: a count-head to infer the num-ber of speakers, and decoder-heads for reconstructing theoriginal signals.
Edit intent: fluency
Original:  Our approach extends the MulCat source separation backbonewith additional output heads: a count-head to infer the num-ber of speakers, and decoder-heads for reconstructing theoriginal signals.
Revised:  Our approach extends the MulCat source separation backbonewith additional output heads: a count-head to infer the number of speakers, and decoder-heads for reconstructing theoriginal signals.
Edit intent: fluency
Original:  Our approach extends the MulCat source separation backbonewith additional output heads: a count-head to infer the num-ber of speakers, and decoder-heads for reconstructing theoriginal signals.
Revised:  Our approach extends the MulCat source separation backbonewith additional output heads: a count-head to infer the num-ber of speakers, and decoder-heads for reconstructing the original signals.
Edit intent: fluency
Original:  Beyond the model, we also propose a metricon how to evaluate source separation with variable numberof speakers.
Revised:  Beyond the model, we also propose a metric on how to evaluate source separation with variable numberof speakers.
Edit intent: fluency
Original:  Beyond the model, we also propose a metricon how to evaluate source separation with variable numberof speakers.
Revised:  Beyond the model, we also propose a metricon how to evaluate source separation with variable number of speakers.
Edit intent: fluency
Original:  Specifically, we cleared up the issue on how toevaluate the quality when the ground-truth hasmore or lessspeakersthan the ones predicted by the model.
Revised:  Specifically, we cleared up the issue on how to evaluate the quality when the ground-truth hasmore or lessspeakersthan the ones predicted by the model.
Edit intent: fluency
Original:  Specifically, we cleared up the issue on how toevaluate the quality when the ground-truth hasmore or lessspeakersthan the ones predicted by the model.
Revised:  Specifically, we cleared up the issue on how toevaluate the quality when the ground-truth hasmore or less speakers than the ones predicted by the model.
Edit intent: fluency
Original:  We evaluateour approach on the WSJ0-mix datasets, with mixtures upto five speakers.
Revised:  We evaluate our approach on the WSJ0-mix datasets, with mixtures upto five speakers.
Edit intent: fluency
Original:  We evaluateour approach on the WSJ0-mix datasets, with mixtures upto five speakers.
Revised:  We evaluateour approach on the WSJ0-mix datasets, with mixtures up to five speakers.
Edit intent: fluency
Original:  We demonstrate that our approach outper-forms state-of-the-art in counting the number of speakers andremains competitive in quality of reconstructed signals.
Revised:  We demonstrate that our approach outperforms state-of-the-art in counting the number of speakers andremains competitive in quality of reconstructed signals.
Edit intent: fluency
Original:  We demonstrate that our approach outper-forms state-of-the-art in counting the number of speakers andremains competitive in quality of reconstructed signals.
Revised:  We demonstrate that our approach outper-forms state-of-the-art in counting the number of speakers and remains competitive in quality of reconstructed signals.
Edit intent: fluency
Original: Let F, G and H be simple graphs.
Revised: For simple graphs G and H be simple graphs.
Edit intent: clarity
Original:  The size Ramsey number r(G,H) of G and H is the smallest possible size of F such that for any red-blue coloring of its edges, F contains either a red G or a blue H. Similarly, we can define the connected size Ramsey number {r}_c(G,H) of G and H by adding the prerequisite that F must be connected.
Revised:  The size Ramsey number r(G,H) is the smallest possible size of F such that for any red-blue coloring of its edges, F contains either a red G or a blue H. Similarly, we can define the connected size Ramsey number {r}_c(G,H) of G and H by adding the prerequisite that F must be connected.
Edit intent: fluency
Original:  The size Ramsey number r(G,H) of G and H is the smallest possible size of F such that for any red-blue coloring of its edges, F contains either a red G or a blue H. Similarly, we can define the connected size Ramsey number {r}_c(G,H) of G and H by adding the prerequisite that F must be connected.
Revised:  The size Ramsey number r(G,H) of G and H is the smallest possible size of F such that for any red-blue coloring of its edges, F contains either a red G or a blue H. Similarly, we can define the connected size Ramsey number {r}_c(G,H) by adding the prerequisite that F must be connected.
Edit intent: fluency
Original:  We are  interested in the cases where G is either a 2K_2 or a 3K_2, and where H is either a cycle C_n or a union of paths nP_m  {r} .
Revised:  We are mainly interested in the cases where G is either a 2K_2 or a 3K_2, and where H is either a cycle C_n or a union of paths nP_m {r} .
Edit intent: coherence
Original:  For this industrial application, we bring together the scientific computing topics of: mathematical modeling of gas transport networks, numerical simulation of hyperbolic partial differential equation, and model order reduction for nonlinear parametric systems.
Revised:  For this industrial application, we bring together the scientific computing topics of: mathematical modeling of gas transport networks, numerical simulation of hyperbolic partial differential equation, and model reduction for nonlinear parametric systems.
Edit intent: clarity
Original:  But, to ensure fulfillment of contracts under these new circumstances, a vast number of possible scenarios, incorporating uncertain supply and demand, has to be simulated ahead of time.
Revised:  But, to ensure fulfillment of contracts under these circumstances, a vast number of possible scenarios, incorporating uncertain supply and demand, has to be simulated ahead of time.
Edit intent: clarity
Original:  For this industrial application, we bring together the scientific computing topics of: mathematical modeling of gas transport networks, numerical simulation of hyperbolic partial differential equation, and  model reduction for nonlinear parametric systems.
Revised:  For this industrial application, we bring together the scientific computing topics of: mathematical modeling of gas transport networks, numerical simulation of hyperbolic partial differential equation, and model reduction for nonlinear systems.
Edit intent: clarity
Original:  Our goal is to provide a general tool to deal with the time evolution of several nonlinear optimality systems in many-query context, where a system must be analysed for various physical and geometrical features.
Revised:  Our goal is to provide a tool to deal with the time evolution of several nonlinear optimality systems in many-query context, where a system must be analysed for various physical and geometrical features.
Edit intent: clarity
Original:  Optimal control is a tool which can be used in order to fill the gab between collected data and mathematical model and it is usually related to very time consuming activities: inverse problems, statistics, etc. Standard discretization techniques may lead to unbearable simulations for real applications.
Revised:  Optimal control can be used in order to fill the gab between collected data and mathematical model and it is usually related to very time consuming activities: inverse problems, statistics, etc. Standard discretization techniques may lead to unbearable simulations for real applications.
Edit intent: clarity
Original:  Optimal control is a tool which can be used in order to fill the gab between collected data and mathematical model and it is usually related to very time consuming activities: inverse problems, statistics, etc. Standard discretization techniques may lead to unbearable simulations for real applications.
Revised:  Optimal control is a tool which can be used in order to fill the gap between collected data and mathematical model and it is usually related to very time consuming activities: inverse problems, statistics, etc. Standard discretization techniques may lead to unbearable simulations for real applications.
Edit intent: fluency
Original:  The generality of the proposed algorithm is validated with a numerical test based on environmental sciences: a reduced optimal control problem governed by  Shallow Waters Equations parametrized not only in the physics features, but also in the geometrical ones.
Revised:  The proposed algorithm is validated with a numerical test based on environmental sciences: a reduced optimal control problem governed by Shallow Waters Equations parametrized not only in the physics features, but also in the geometrical ones.
Edit intent: clarity
Original:  We will show how the reduced model can be useful in order to recover desired velocity and height profiles more rapidly with respect to the standard simulation, not loosing in accuracy.
Revised:  We will show how the reduced model can be useful in order to recover desired velocity and height profiles more rapidly with respect to the standard simulation, not losing accuracy.
Edit intent: clarity
Original: Reconfigurable intelligent surfaces (RISs) have been introduced to improve the signal propagation characteristics by focusing the signal power in the preferred direction, thus making the communication environment 'smart' .
Revised: Reconfigurable intelligent surfaces (RISs) have been introduced to improve the signal propagation characteristics by focusing the signal power in the preferred direction, thus making the communication environment "smart" .
Edit intent: fluency
Original:  The typical use cases and applications for the 'smart' environment include beyond 5G communication networks, smart cities, etc.
Revised:  The typical use cases and applications for the "smart" environment include beyond 5G communication networks, smart cities, etc.
Edit intent: fluency
Original:  Challenging environments (CEs) comprise a range of scenarios, which share the fact that it is extremely difficult to establish a communication link using conventional technology due to many impairments typically associated with the propagation medium and increased signal scattering.
Revised:  Challenging environments comprise a range of scenarios, which share the fact that it is extremely difficult to establish a communication link using conventional technology due to many impairments typically associated with the propagation medium and increased signal scattering.
Edit intent: clarity
Original:  This paperaims at filling this gap by providing a motivation for the application of RISs in CEs .
Revised:  In this paper, we aim at filling this gap by providing a motivation for the application of RISs in CEs .
Edit intent: fluency
Original:  In addition, novel research challenges to be addressed in this context are discussed .
Revised:  In addition, novel research challenges to be addressed in this context are described .
Edit intent: clarity
Original: At online retail platforms, it is crucial to actively detect risks of fraudulent transactions to improve our customer experience , minimize loss, and prevent unauthorized chargebacks.
Revised: At online retail platforms, it is crucial to actively detect the risks of transactions to improve our customer experience , minimize loss, and prevent unauthorized chargebacks.
Edit intent: clarity
Original:  we present xFraud, an explainable Fraud transaction prediction system. xFraud is composed of a predictor which learns expressive representations for malicious transaction detection from the heterogeneous transaction graph via a self-attentive heterogeneous graph neural network , and an explainer that generates meaningful and human understandable explanations from graphs to facilitate further process in business unit.
Revised:  we present xFraud, an explainable fraud transaction prediction framework which is mainly composed of a predictor which learns expressive representations for malicious transaction detection from the heterogeneous transaction graph via a self-attentive heterogeneous graph neural network , and an explainer that generates meaningful and human understandable explanations from graphs to facilitate further process in business unit.
Edit intent: clarity
Original:  we present xFraud, an explainable Fraud transaction prediction system. xFraud is composed of a predictor which learns expressive representations for malicious transaction detection from the heterogeneous transaction graph via a self-attentive heterogeneous graph neural network , and an explainer that generates meaningful and human understandable explanations from graphs to facilitate further process in business unit.
Revised:  we present xFraud, an explainable Fraud transaction prediction system. xFraud is composed of a predictor which learns expressive representations for malicious transaction detection from the heterogeneous transaction graph via a self-attentive heterogeneous graph neural network , and an explainer that generates meaningful and human understandable explanations from graphs to facilitate further processes in the business unit.
Edit intent: fluency
Original:  In our experiments with xFraud on two real transaction networks with up to ten millions transactions, we are able to achieve an area under a curve (AUC) score that outperforms baseline models and graph embedding methods .
Revised:  In our experiments with xFraud on real transaction networks with up to ten millions transactions, we are able to achieve an area under a curve (AUC) score that outperforms baseline models and graph embedding methods .
Edit intent: clarity
Original:  In addition, we show how the explainer could benefit the understanding towards model predictions and enhance model trustworthiness for real-world fraud transaction cases .
Revised:  In addition, we show that xFraud explainer can generate reasonable explanations to significantly assist the business analysis via both quantitative and qualitative evaluations .
Edit intent: coherence
Original:  We  run extensive experiments to compare eight different configurations of GNNs paired with DE to predict node labels over eight real-world graphs.
Revised:  We also run extensive experiments to compare eight different configurations of GNNs paired with DE to predict node labels over eight real-world graphs.
Edit intent: coherence
Original:  Lastly, we reach three pieces of conclusions on how to use GNNs and DE properly in node classification tasks .
Revised:  Lastly, we reach three pieces of conclusions on how to use GNNs and DE properly in tasks of node classification .
Edit intent: clarity
Original:  We also explore the structural properties of the winner determination problem that cause this phenomenon, and we use the insights gained to investigate how impactful complex bidding manipulations may be.
Revised:  We also explore the structural properties of the winner determination problem that cause this phenomenon, and we use the insights gained to investigate how impactful complex bidding may be.
Edit intent: clarity
Original:  Thus, this phenomenon can greatly impact the auction's outcome , and should not be ignored by bidders and auction designers alike.
Revised:  Thus, this phenomenon can greatly impact the auction's outcome and should not be ignored by bidders and auction designers alike.
Edit intent: fluency
Original: Mixed membership community detection is a challenge problem in network analysis  .
Revised: Community detection in network analysis .
Edit intent: clarity
Original:  Quantum gambling theory has been studied, and it often brings non-trivial consequences that classical theory can not explain.
Revised:  Quantum gambling theory has garnered considerable attention. Studies have shown that the quantum gambling theory often yields nontrivial consequences that classical theory can not explain.
Edit intent: clarity