wanyu/IteraTeR_v2 huggingface dataset:
Original: Advances in Data Science permeate every field of Transportation Science and Engineering, making it straightforward to imagine that developments in the transportation sector will be  data-driven.
Revised: Advances in Data Science permeate every field of Transportation Science and Engineering, making it straightforward to imagine that developments in the transportation sector that data-driven.
Edit intent: clarity
Original: Advances in Data Science permeate every field of Transportation Science and Engineering, making it straightforward to imagine that developments in the transportation sector will be  data-driven.
Revised: Advances in Data Science permeate every field of Transportation Science and Engineering, making it straightforward to imagine that developments in the transportation sector will be are data-driven.
Edit intent: fluency
Original:  Nowadays, Intelligent Transportation Systems (ITS) could be arguably approached as a "story" intensively producing and consuming large amounts of data.
Revised:  Nowadays, Intelligent Transportation Systems (ITS) could be arguably approached as a ``story'' intensively producing and consuming large amounts of data.
Edit intent: fluency
Original:  A  diversity of sensing devices densely spread over the infrastructure, vehicles or the travelers' personal devices act as sources of data flows that are eventually fed to software running on automatic devices, actuators or control systems producing, in  turn, complex information flows between users, traffic managers, data analysts, traffic modeling scientists, etc.
Revised:  A ~ diversity of sensing devices densely spread over the infrastructure, vehicles or the travelers' personal devices act as sources of data flows that are eventually fed to software running on automatic devices, actuators or control systems producing, in turn, complex information flows between users, traffic managers, data analysts, traffic modeling scientists, etc.
Edit intent: fluency
Original:  A  diversity of sensing devices densely spread over the infrastructure, vehicles or the travelers' personal devices act as sources of data flows that are eventually fed to software running on automatic devices, actuators or control systems producing, in  turn, complex information flows between users, traffic managers, data analysts, traffic modeling scientists, etc.
Revised:  A diversity of sensing devices densely spread over the infrastructure, vehicles or the travelers' personal devices act as sources of data flows that are eventually fed into software running on automatic devices, actuators or control systems producing, in turn, complex information flows between users, traffic managers, data analysts, traffic modeling scientists, etc.
Edit intent: fluency
Original:  A  diversity of sensing devices densely spread over the infrastructure, vehicles or the travelers' personal devices act as sources of data flows that are eventually fed to software running on automatic devices, actuators or control systems producing, in  turn, complex information flows between users, traffic managers, data analysts, traffic modeling scientists, etc.
Revised:  A diversity of sensing devices densely spread over the infrastructure, vehicles or the travelers' personal devices act as sources of data flows that are eventually fed to software running on automatic devices, actuators or control systems producing, in ~ turn, complex information flows between users, traffic managers, data analysts, traffic modeling scientists, etc.
Edit intent: fluency
Original:  A  diversity of sensing devices densely spread over the infrastructure, vehicles or the travelers' personal devices act as sources of data flows that are eventually fed to software running on automatic devices, actuators or control systems producing, in  turn, complex information flows between users, traffic managers, data analysts, traffic modeling scientists, etc.
Revised:  A diversity of sensing devices densely spread over the infrastructure, vehicles or the travelers' personal devices act as sources of data flows that are eventually fed to software running on automatic devices, actuators or control systems producing, in turn, complex information flows among users, traffic managers, data analysts, traffic modeling scientists, etc.
Edit intent: fluency
Original:  These  information flows provide enormous opportunities to improve model development and decision-making.
Revised:  These ~ information flows provide enormous opportunities to improve model development and decision-making.
Edit intent: fluency
Original:  in  other words, for data-based models to fully become actionable.
Revised:  in ~ other words, for data-based models to fully become actionable.
Edit intent: fluency
Original:  Grounded on this described data modeling pipeline for ITS, we  define the characteristics, engineering requisites and challenges intrinsic to its three compounding stages, namely, data fusion, adaptive learning and model evaluation.
Revised:  Grounded on. Grounded in this described data modeling pipeline for ITS, we define the characteristics, engineering requisites and challenges intrinsic to its three compounding stages, namely, data fusion, adaptive learning and model evaluation.
Edit intent: clarity
Original:  Grounded on this described data modeling pipeline for ITS, we  define the characteristics, engineering requisites and challenges intrinsic to its three compounding stages, namely, data fusion, adaptive learning and model evaluation.
Revised:  Grounded on this described data modeling pipeline for ITS, we ~ define the characteristics, engineering requisites and challenges intrinsic to its three compounding stages, namely, data fusion, adaptive learning and model evaluation.
Edit intent: fluency
Original:  We  deliberately generalize model learning to be adaptive, since, in  the core of our paper is the firm conviction that most learners will have to adapt to the ever-changing phenomenon scenario underlying the majority of ITS applications.
Revised:  We ~ deliberately generalize model learning to be adaptive, since, in the core of our paper is the firm conviction that most learners will have to adapt to the ever-changing phenomenon scenario underlying the majority of ITS applications.
Edit intent: fluency
Original:  We  deliberately generalize model learning to be adaptive, since, in  the core of our paper is the firm conviction that most learners will have to adapt to the ever-changing phenomenon scenario underlying the majority of ITS applications.
Revised:  We deliberately generalize model learning to be adaptive, since, in ~ the core of our paper is the firm conviction that most learners will have to adapt to the ever-changing phenomenon scenario underlying the majority of ITS applications.
Edit intent: fluency
Original:  Finally, we  provide a prospect of current research lines within Data Science that can bring notable advances to data-based ITS modeling, which will eventually bridge the gap towards the practicality and actionability of such models.
Revised:  Finally, we ~ provide a prospect of current research lines within Data Science that can bring notable advances to data-based ITS modeling, which will eventually bridge the gap towards the practicality and actionability of such models.
Edit intent: fluency
Original:  In such systems  autonomous agents interact locally with their users  and remotely with other agents , to make intelligent collective choices , via which they self-regulate the consumption and production of distributed resources.
Revised:  In such systems , autonomous agents interact locally with their users and remotely with other agents , to make intelligent collective choices , via which they self-regulate the consumption and production of distributed resources.
Edit intent: fluency
Original:  In such systems  autonomous agents interact locally with their users  and remotely with other agents , to make intelligent collective choices , via which they self-regulate the consumption and production of distributed resources.
Revised:  In such systems autonomous agents interact locally with their users , and remotely with other agents , to make intelligent collective choices , via which they self-regulate the consumption and production of distributed resources.
Edit intent: fluency
Original:  In such systems  autonomous agents interact locally with their users  and remotely with other agents , to make intelligent collective choices , via which they self-regulate the consumption and production of distributed resources.
Revised:  In such systems autonomous agents interact locally with their users and remotely with other agents to make intelligent collective choices , via which they self-regulate the consumption and production of distributed resources.
Edit intent: fluency
Original:  In such systems  autonomous agents interact locally with their users  and remotely with other agents , to make intelligent collective choices , via which they self-regulate the consumption and production of distributed resources.
Revised:  In such systems autonomous agents interact locally with their users and remotely with other agents , to make intelligent collective choices . Via these interactions they self-regulate the consumption and production of distributed resources.
Edit intent: clarity
Original:  For instance, self-management of traffic flows in Smart Cities.
Edit intent: coherence
Original:  While such complex systems are usually deployed and operated using centralized computing infrastructures, their socio-technical nature requires new value-oriented design paradigms empowering trust, transparency, and alignment with citizens' social values, such as privacy preservation, autonomy, and fairness among citizens' choices.
Revised:  While such complex systems are often deployed and operated using centralized computing infrastructures, their socio-technical nature requires new value-oriented design paradigms empowering trust, transparency, and alignment with citizens' social values, such as privacy preservation, autonomy, and fairness among citizens' choices.
Edit intent: coherence
Original:  While such complex systems are usually deployed and operated using centralized computing infrastructures, their socio-technical nature requires new value-oriented design paradigms empowering trust, transparency, and alignment with citizens' social values, such as privacy preservation, autonomy, and fairness among citizens' choices.
Revised:  While such complex systems are usually deployed and operated using centralized computing infrastructures, the socio-technical nature requires new value-oriented design paradigms empowering trust, transparency, and alignment with citizens' social values, such as privacy preservation, autonomy, and fairness among citizens' choices.
Edit intent: clarity
Original:  Currently, instruments and tools to study such systems and guide the prototyping process from simulation , to live deployment , and ultimately to a robust operation, are missing or not practical  .
Revised:  Currently, instruments and tools to study such systems and guide the prototyping process from simulation to live deployment , and ultimately to a robust operation, are missing or not practical .
Edit intent: fluency
Original:  Currently, instruments and tools to study such systems and guide the prototyping process from simulation , to live deployment , and ultimately to a robust operation, are missing or not practical  .
Revised:  Currently, instruments and tools to study such systems and guide the prototyping process from simulation , to live deployment are missing, or not practical .
Edit intent: clarity
Original:  This architecture empowers the seamless reusability of (i) application-independent decentralized services by an IoT application, and (ii) different IoT applications by the same decentralized service.
Revised:  This new architecture is designed for a seamless reusability of (i) application-independent decentralized services by an IoT application, and (ii) different IoT applications by the same decentralized service.
Edit intent: clarity
Original:  This dual self-integration promises IoT applications that are simpler to prototype  and can interoperate with  services during runtime to self-integrate more complex functionality.
Revised:  This dual self-integration promises IoT applications that are simpler to prototype , and can interoperate with services during runtime to self-integrate more complex functionality.
Edit intent: fluency
Original:  Such self-integration provides stronger validation  and improves efficiency of resource utilization: computational resources are shared, cutting down deployment and operational costs.
Revised:  Such integration provides stronger validation and improves efficiency of resource utilization: computational resources are shared, cutting down deployment and operational costs.
Edit intent: clarity
Original: The problem of answering Boolean conjunctive queries over the guarded fragment is decidable, however, as yet no practical decision procedure exists.
Revised: Answering Boolean conjunctive queries over the guarded fragment is decidable, however, as yet no practical decision procedure exists.
Edit intent: clarity
Original:  In particular, we show that using a separation rule and top-variable-based techniques, one can rewrite Boolean conjunctive queries into a set of (loosely) guarded clauses , so that querying the (loosely) guarded fragment can be reduced to deciding the (loosely) guarded fragment .
Revised:  The difficulty in querying a knowledge base of (loosely) guarded clauses , so that querying the (loosely) guarded fragment can be reduced to deciding the (loosely) guarded fragment .
Edit intent: clarity
Original:  For odd n, we also prove that the diameter of H_n is at least linear and at most log-linear in n.
Revised:  For odd n, we also prove that the diameter of H_n is linear in n.
Edit intent: clarity
Original: In this paper we investigate the structure of a flip graph on non-crossing perfect matchings in the plane.
Revised: In this paper we investigate the structure of flip graphs on non-crossing perfect matchings in the plane.
Edit intent: fluency
Original:  Consider the set of all non-crossing straight-line perfect matchings on a set of 2n points that are placed equidistantly on the unit circle.
Revised:  Specifically, consider all non-crossing straight-line perfect matchings on a set of 2n points that are placed equidistantly on the unit circle.
Edit intent: clarity
Original: Attention in machine learning is largely bottom-up, whereas people also deploy top-down, goal-directed attention .
Revised: People deploy top-down, goal-directed attention .
Edit intent: clarity
Original:  Motivated by neuroscience research, we evaluated a plug-and-play, top-down attention layer that is easily added to existing deep convolutional neural networks (DCNNs).
Revised:  Motivated by neuroscience research, we evaluated a plug-and-play, top-down attention layer that is easily added to existing deep convolutional neural network (DCNNs).
Edit intent: fluency
Original:  These theoretical results suggest that top-down attention can effectively reconfigure general-purpose DCNNs to better suit the current task goal .
Revised:  These theoretical results suggest that goal-directed attention can reconfigure general-purpose DCNNs to better suit the current task goal .
Edit intent: clarity
Original: Question Answering (QA) is a natural language processing task that aims at retrieving relevant answers to user questions.
Revised: Question Answering (QA) is a natural language processing task that aims at obtaining relevant answers to user questions.
Edit intent: clarity
Original:  While much progress has been made in this area, biomedical questions are still a challenge to most QA approaches, due to the complexity of the domain and limited availability of training sets.
Revised:  While some progress has been made in this area, biomedical questions are still a challenge to most QA approaches, due to the complexity of the domain and limited availability of training sets.
Edit intent: clarity
Original:  The proposed framework extracts questions from selected forums as well as answers that contain citations that can be mapped to a unique entry of a digital library .
Revised:  The proposed framework extracts from selected forums as well as answers that contain citations that can be mapped to a unique entry of a digital library .
Edit intent: clarity
Original:  The proposed framework extracts questions from selected forums as well as answers that contain citations that can be mapped to a unique entry of a digital library .
Revised:  The proposed framework extracts questions from selected forums the questions and the respective answers that contain citations that can be mapped to a unique entry of a digital library .
Edit intent: clarity
Original:  The proposed framework extracts questions from selected forums as well as answers that contain citations that can be mapped to a unique entry of a digital library .
Revised:  The proposed framework extracts questions from selected forums as well as answers that contain citations .
Edit intent: clarity
Original:  Also, we  trained a state-of-the-art deep learning model that obtained higher scores in most test batches than a model trained only on a dataset manually annotated by experts.
Revised:  Also, we trained a state-of-the-art deep learning model that obtained similar performance to using a dataset manually annotated by experts.
Edit intent: clarity
Original:  The framework described in this paper can be used to update the SciQA corpus from the same forums as new posts are made, and from other forums that support their answers with documents. 
Revised:  The proposed framework can be used to update the SciQA corpus from the same forums as new posts are made, and from other forums that support their answers with documents. 
Edit intent: clarity
Original: Even before the start of the COVID-19 pandemic, bus ridership in the United States  attained its lowest level since 1973.
Revised: Even before the start of the COVID-19 pandemic, bus ridership in the United States had attained its lowest level since 1973.
Edit intent: fluency
Original:  In three of the four agencies, the elasticity is a decreasing function of prior frequency, meaning that low-frequency routes are the most sensitive to frequency change .
Revised:  In three of the four agencies, the elasticity is a decreasing function of prior frequency, meaning that low-frequency routes are the most sensitive to changes in frequency .
Edit intent: clarity
Original:  The model is trained with a monotonic RNN-T loss well-suited to frame-synchronous, streaming decoding.
Revised:  The model is trained with the RNN-T loss well-suited to frame-synchronous, streaming decoding.
Edit intent: clarity
Original:  The model is trained with a monotonic RNN-T loss well-suited to frame-synchronous, streaming decoding.
Revised:  The model is trained with a monotonic RNN-T loss well-suited to streaming decoding.
Edit intent: clarity
Original:  We also show that the full attention version of our model achieves competitive performance compared to existing LibriSpeech benchmarksfor attention-based models trained with cross-entropy loss .
Revised:  We also show that the full attention version of our model beats the-state-of-the art accuracy on the LibriSpeech benchmarks .
Edit intent: clarity
Original:  Our approach is able to provide accurate eigenvalue and eigenfunction approximations in several numerical examples, including Fokker-Planck operator , linear and nonlinear Schr\"odinger operators in high dimensions.
Revised:  Our approach is able to provide accurate eigenvalue and eigenfunction approximations in several numerical examples, including Fokker-Planck operator and the linear and nonlinear Schr\"odinger operators in high dimensions.
Edit intent: fluency
Original:  Code is available  URL
Revised:  Code is available at URL
Edit intent: clarity
Original:  However, using this feature requires new interference mitigation schemes capable to handle two additional types of interference between cells in opposite transmission direction: DL to UL and UL to DL interference.
Revised:  However, the use of this feature requires new interference mitigation schemes capable to handle two additional types of interference between cells in opposite transmission direction: DL to UL and UL to DL interference.
Edit intent: fluency
Original:  The aim of this work is to provide a complete analytical approach to model inter-cell interference in macro-cells deployment and dense small-cells .
Revised:  The aim of this work is to provide a complete analytical approach to model inter-cell interference in macro-cell and dense small-cell networks .
Edit intent: clarity
Original:  We derive the explicit expressions of Interference to Signal Ratio (ISR) metric at each position of the network, in both DL and UL, to quantify the impact of each type of interference on the perceived performance.
Revised:  We derive the explicit expressions of Interference to Signal Ratio (ISR) at each position of the network, in both DL and UL, to quantify the impact of each type of interference on the perceived performance.
Edit intent: clarity
Original:  We derive the explicit expressions of Interference to Signal Ratio (ISR) metric at each position of the network, in both DL and UL, to quantify the impact of each type of interference on the perceived performance.
Revised:  We derive the explicit expressions of Interference to Signal Ratio (ISR) metric at each position of the network, in both DL and UL, to quantify the impact of each type of interference on the system performance.
Edit intent: clarity
Original:  Also, we provide the explicit expressions of the coverage probability as a functions of different system parameters for both macro-cells and small-cells deployments .
Revised:  Also, we provide the explicit expressions of the coverage probability as functions of different system parameters for both macro-cells and small-cells deployments .
Edit intent: fluency
Original:  Also, we provide the explicit expressions of the coverage probability as a functions of different system parameters for both macro-cells and small-cells deployments .
Revised:  Also, we provide the explicit expressions of the coverage probability as a functions of different system parameters by covering different scenarios .
Edit intent: clarity
Original: We propose  a novel topological layer for general deep learning models based on persistent landscapes, in which we can efficiently exploit underlying topological features of the input data structure.
Revised: We propose a novel topological layer for general deep learning models based on persistence landscapes, in which we can efficiently exploit underlying topological features of the input data structure.
Edit intent: fluency
Original:  We use the robust DTM function and show differentiability with respect to layer inputs, for a general persistent homology with arbitrary filtration.
Revised:  We show differentiability with respect to layer inputs, for a general persistent homology with arbitrary filtration.
Edit intent: coherence
Original:  Thus, our proposed layer can be placed anywhere in the network architecture and feed critical information on the topological features of input data into subsequent layers to improve the learnability of the networks toward a given task.
Revised:  Thus, our proposed layer can be placed anywhere in the network and feed critical information on the topological features of input data into subsequent layers to improve the learnability of the networks toward a given task.
Edit intent: clarity
Original:  We provide a tight stability theorem, and show that the proposed layer is robust towards noise and outliers.
Revised:  We provide a tight stability theorem, and show that the proposed layer is robust against noise and outliers.
Edit intent: clarity