wanyu/IteraTeR_v2 huggingface dataset:
Original:  However , we show that for  PSPACE L1 functions  and a class of PSPACE computable measure-preserving ergodic transformations, the ergodic average exists  and is equal to the space average on every EXPSPACE random.
Revised:  In contrast , we show that for PSPACE L1 functions and a class of PSPACE computable measure-preserving ergodic transformations, the ergodic average exists and is equal to the space average on every EXPSPACE random.
Edit intent: coherence
Original:  However , we show that for  PSPACE L1 functions  and a class of PSPACE computable measure-preserving ergodic transformations, the ergodic average exists  and is equal to the space average on every EXPSPACE random.
Revised:  However , we show that for a class of PSPACE L1 functions and a class of PSPACE computable measure-preserving ergodic transformations, the ergodic average exists and is equal to the space average on every EXPSPACE random.
Edit intent: coherence
Original:  However , we show that for  PSPACE L1 functions  and a class of PSPACE computable measure-preserving ergodic transformations, the ergodic average exists  and is equal to the space average on every EXPSPACE random.
Revised:  However , we show that for PSPACE L1 functions , and a class of PSPACE computable measure-preserving ergodic transformations, the ergodic average exists and is equal to the space average on every EXPSPACE random.
Edit intent: coherence
Original:  However , we show that for  PSPACE L1 functions  and a class of PSPACE computable measure-preserving ergodic transformations, the ergodic average exists  and is equal to the space average on every EXPSPACE random.
Revised:  However , we show that for PSPACE L1 functions and a class of PSPACE computable measure-preserving ergodic transformations, the ergodic average exists for all PSPACE randoms and is equal to the space average on every EXPSPACE random.
Edit intent: clarity
Original:  Computer graphics approaches rely on Physically Based Simulations (PBS) to animate clothes.
Revised:  Classical approaches rely on Physically Based Simulations (PBS) to animate clothes.
Edit intent: clarity
Original:  By using deep models, we can obtain high-resolution garments that can be efficiently deployed in real-time.
Edit intent: coherence
Original:  Furthermore, we show it is possible to train these models in an amount of time comparable to a PBS of a few fixed sequences.
Revised:  Furthermore, we show it is possible to train these models in an amount of time comparable to a PBS of a few sequences.
Edit intent: clarity
Original:  Other deep-based approaches for cloth dynamics learn the distribution of huge volumes of simulated data.
Revised:  While deep-based approaches for cloth dynamics learn the distribution of huge volumes of simulated data.
Edit intent: fluency
Original:  We wish to understand to what extent such a framework may provide reliable stress predictions inside and outside the training set, i. e. for unseen coarse scale geometries and stress distributions and/or unseen defect geometries.
Revised:  We wish to understand to what extent such a framework provides reliable stress predictions inside and outside the training set, i. e. for unseen coarse scale geometries and stress distributions and/or unseen defect geometries.
Edit intent: clarity
Original:  Ultimately , we aim to develop efficient offline data generation and online data acquisition methods to maximise the domain of validity of the CNN predictions.
Revised:  Ultimately , we aim to develop efficient offline data generation methods to maximise the domain of validity of the CNN predictions.
Edit intent: clarity
Original:  To achieve these ambitious goals, we will deploy a Bayesian approach providing not point estimates, but credible intervals of the fine-scale stress field , as a means to evaluate the uncertainty of the predictions.
Revised:  To achieve these ambitious goals, we will deploy a Bayesian approach providing not point estimates, but credible intervals of the fine-scale stress field to evaluate the uncertainty of the predictions.
Edit intent: clarity
Original:  The uncertainty quantified by the network will automatically encompass the lack of knowledge due to unseen macro and micro features , and the lack of knowledge due to the potential lack of scale separability.
Revised:  This will automatically encompass the lack of knowledge due to unseen macro and micro features , and the lack of knowledge due to the potential lack of scale separability.
Edit intent: clarity
Original:  In this work we will investigate stress prediction in 2D composite structures with randomly distributed circular pores .
Revised:  In this work we will investigate stress prediction in 2D porous structures with randomly distributed circular pores .
Edit intent: clarity
Original:  In this work we will investigate stress prediction in 2D composite structures with randomly distributed circular pores .
Revised:  In this work we will investigate stress prediction in 2D composite structures with randomly distributed circular holes .
Edit intent: clarity
Original: The purpose of this work is to train an Encoder-Decoder Convolutional Neural Networks (CNN) to automatically add local fine-scale stress corrections to coarse stress predictions around unresolved microscale features .
Revised: The purpose of this work is to train an Encoder-Decoder Convolutional Neural Network that will generate fine-scale stress corrections to coarse stress predictions around unresolved microscale features .
Edit intent: clarity
Original: The purpose of this work is to train an Encoder-Decoder Convolutional Neural Networks (CNN) to automatically add local fine-scale stress corrections to coarse stress predictions around unresolved microscale features .
Revised: The purpose of this work is to train an Encoder-Decoder Convolutional Neural Networks (CNN) to automatically add local fine-scale stress corrections to coarse predictions around unresolved microscale features .
Edit intent: fluency
Original:  To achieve these ambitious goals, we will deploy a Bayesian approach providing not point estimates, but credible intervals of the fine-scale stress field to evaluate the uncertainty of the predictions .
Revised:  To achieve these ambitious goals, we will deploy a Bayesian approach providing credible intervals to evaluate the uncertainty of the predictions .
Edit intent: clarity
Original:  In addition to our legal search reproducability study, we investigate BERT-PLI for document retrieval in the patent domain.
Revised:  In addition to our legal search reproducibility study, we investigate BERT-PLI for document retrieval in the patent domain.
Edit intent: fluency
Original:  For reproducability and transparency as well as to benefit the community we make our source code and the trained models publicly available.
Revised:  For reproducibility and transparency as well as to benefit the community we make our source code and the trained models publicly available.
Edit intent: fluency
Original:  Our analysis is based on a methodology which illustrates how we gathered the data, extracted the topics of the citing articles, and visualised the results.
Revised:  Our analysis is based on a methodology which illustrates how we gathered the data, extracted the topics of the citing articles, and visualized the results.
Edit intent: fluency
Original:  Such results concerned the analysis of the entities citing Wakefield et al.  and their related in-text citations.
Revised:  Such results concerned the analysis of the entities citing Wakefield et al. 's article and their related in-text citations.
Edit intent: clarity
Original:  Citing articles have started discussing/ dealing with the retraction of Wakefield et al.  even before its full retraction, happened in 2010.
Revised:  Citing articles have started either discussing or dealing with the retraction of Wakefield et al. even before its full retraction, happened in 2010.
Edit intent: clarity
Original:  Citing articles have started discussing/ dealing with the retraction of Wakefield et al.  even before its full retraction, happened in 2010.
Revised:  Citing articles have started discussing/ dealing with the retraction of Wakefield et al. 's article even before its full retraction, happened in 2010.
Edit intent: clarity
Original:  Social sciences studies were among those that have mostly discussed the retractionphenomena .
Revised:  Social sciences studies were among those that have mostly discussed its retraction .
Edit intent: clarity
Original:  In addition, when observing the in-text citations, we noticed how a large part of the citations received by Wakefield et al.'s article have been focused on general discussions without recalling strictly medical details, especially after the full retraction.
Revised:  In addition, when observing the in-text citations, we noticed that a large part of the citations received by Wakefield et al.'s article have been focused on general discussions without recalling strictly medical details, especially after the full retraction.
Edit intent: fluency
Original:  In addition, when observing the in-text citations, we noticed how a large part of the citations received by Wakefield et al.'s article have been focused on general discussions without recalling strictly medical details, especially after the full retraction.
Revised:  In addition, when observing the in-text citations, we noticed how a large part of the citations received by Wakefield et al.'s article has focused on general discussions without recalling strictly medical details, especially after the full retraction.
Edit intent: fluency
Original:  Medical studies did not hesitate in acknowledging the retraction and even gave strong negative statements on it in some occasions .
Revised:  Medical studies did not hesitate in acknowledging the retraction and often provided strong negative statements on it in some occasions .
Edit intent: clarity
Original:  Medical studies did not hesitate in acknowledging the retraction and even gave strong negative statements on it in some occasions .
Revised:  Medical studies did not hesitate in acknowledging the retraction and even gave strong negative statements on it .
Edit intent: clarity
Original: Sources of commonsense knowledge aim to support applications in natural language understanding, computer vision, and knowledge graphs.
Revised: Sources of commonsense knowledge support applications in natural language understanding, computer vision, and knowledge graphs.
Edit intent: clarity
Original:  These sources contain complementary knowledge to each other, which makes their integration desired.
Revised:  Given their complementarity, their integration is desired.
Edit intent: clarity
Original:  Yet, such integration is not trivial because of their different foci, modeling approaches, and sparse overlap  .
Revised:  Yet, their different foci, modeling approaches, and sparse overlap .
Edit intent: coherence
Original:  In this paper, we propose to consolidate commonsense knowledge by following five principles .
Revised:  In this paper, we consolidate commonsense knowledge by following five principles .
Edit intent: clarity
Original:  We perform analysis of CSKG and its various text and graph embeddings, showing that CSKG is a well-connected graph and that its embeddings provide a useful entry point to the graph.
Revised:  We analyze CSKG and its various text and graph embeddings, showing that CSKG is a well-connected graph and that its embeddings provide a useful entry point to the graph.
Edit intent: clarity
Original:  We perform analysis of CSKG and its various text and graph embeddings, showing that CSKG is a well-connected graph and that its embeddings provide a useful entry point to the graph.
Revised:  We perform analysis of CSKG and its various text and graph embeddings, showing that CSKG is well-connected graph and that its embeddings provide a useful entry point to the graph.
Edit intent: fluency
Original:  We perform analysis of CSKG and its various text and graph embeddings, showing that CSKG is a well-connected graph and that its embeddings provide a useful entry point to the graph.
Revised:  We perform analysis of CSKG and its various text and graph embeddings, showing that CSKG is a well-connected and that its embeddings provide a useful entry point to the graph.
Edit intent: fluency
Original:  The DoM indicator can differentiate the sets for certain important features, such as convergence ,spread ,uniformity , andcardinality .
Revised:  The DoM indicator can differentiate the sets for certain important features, such as ,spread ,uniformity , andcardinality .
Edit intent: clarity
Original:  The DoM indicator can differentiate the sets for certain important features, such as convergence ,spread ,uniformity , andcardinality .
Revised:  The DoM indicator can differentiate the sets for certain important features, such as convergence spread ,uniformity , andcardinality .
Edit intent: fluency
Original:  The DoM indicator can differentiate the sets for certain important features, such as convergence ,spread ,uniformity , andcardinality .
Revised:  The DoM indicator can differentiate the sets for certain important features, such as convergence , ,uniformity , andcardinality .
Edit intent: clarity
Original:  The DoM indicator can differentiate the sets for certain important features, such as convergence ,spread ,uniformity , andcardinality .
Revised:  The DoM indicator can differentiate the sets for certain important features, such as convergence ,spread uniformity , andcardinality .
Edit intent: fluency
Original:  The DoM indicator can differentiate the sets for certain important features, such as convergence ,spread ,uniformity , andcardinality .
Revised:  The DoM indicator can differentiate the sets for certain important features, such as convergence ,spread , , andcardinality .
Edit intent: clarity
Original:  The DoM indicator can differentiate the sets for certain important features, such as convergence ,spread ,uniformity , andcardinality .
Revised:  The DoM indicator can differentiate the sets for certain important features, such as convergence ,spread ,uniformity cardinality .
Edit intent: fluency
Original:  Algorithms, such as IBEA, MOEA/D, NSGA-III, NSGA-II, and SPEA2 are used to generate the solution sets (however any other algorithms can also be used with the proposed MIP-DoM indicator) . \%The results confirm the effectiveness of the MIP-DoM in problems with over three objective functions .
Revised:  Algorithms, such as IBEA, MOEA/D, NSGA-III, NSGA-II, and SPEA2 are used to generate the solution sets (however any other algorithms can also be used with the proposed MIP-DoM indicator) .
Edit intent: coherence
Original:  The DoM indicator has an intuitive and physical meaning, similar to the \epsilon-indicator, and calculates the minimum total move of members of one set needed to weakly dominate each member of the other set.
Revised:  The DoM indicator has an intuitive and physical meaning, similar to the \epsilon-indicator, and calculates the minimum total move of members of one set so that all elements in another set are to be dominated or identical to at least one member of the other set.
Edit intent: clarity
Original:  The DoM indicator has an intuitive and physical meaning, similar to the \epsilon-indicator, and calculates the minimum total move of members of one set needed to weakly dominate each member of the other set.
Revised:  The DoM indicator has an intuitive and physical meaning, similar to the \epsilon-indicator, and calculates the minimum total move of members of one set needed to weakly dominate each member of the first set.
Edit intent: clarity
Original: Recent work on audio-visual navigation assumes a constantly-sounding target and restricts the role of audio to signaling the target's spatial placement .
Revised: Recent work on audio-visual navigation assumes a constantly-sounding target and restricts the role of audio to signaling the target's position .
Edit intent: clarity
Original:  In support of the new task, we also expand the SoundSpaces audio simulation platform to provide semantically grounded object sounds for an array of objects in Matterport3D.
Revised:  In support of the new task, we also expand the SoundSpaces audio simulations to provide semantically grounded object sounds for an array of objects in Matterport3D.
Edit intent: clarity
Original:  In support of the new task, we also expand the SoundSpaces audio simulation platform to provide semantically grounded object sounds for an array of objects in Matterport3D.
Revised:  In support of the new task, we also expand the SoundSpaces audio simulation platform to provide semantically grounded sounds for an array of objects in Matterport3D.
Edit intent: fluency
Original:  The log scores of the Simplex and Best-Average mixtures, for example, are approximately 7\% better than that of the ex post best individual forecaster, and 15\% better than that of the median forecaster.
Edit intent: coherence
Original:  A common form of IR involves ranking of documents -- or short passages -- in response to keyword-based queries.
Revised:  A common form of IR involves ranking of documents--or short passages--in response to keyword-based queries.
Edit intent: fluency
Original:  In many real-life IR tasks, the retrieval involves extremely large collections -- such as the document index of a commercial Web search engine -- containing billions of documents.
Revised:  In many real-life IR tasks, the retrieval involves extremely large collections--such as the document index of a commercial Web search engine -- containing billions of documents.
Edit intent: fluency
Original:  In many real-life IR tasks, the retrieval involves extremely large collections -- such as the document index of a commercial Web search engine -- containing billions of documents.
Revised:  In many real-life IR tasks, the retrieval involves extremely large collections -- such as the document index of a commercial Web search engine--containing billions of documents.
Edit intent: fluency
Original: Superpixel algorithms , which group pixels similar in color and other low-level properties , are increasingly used for pre-processing in image segmentation.
Revised: Superpixel algorithms grouping pixels with similar color and other low-level properties , are increasingly used for pre-processing in image segmentation.
Edit intent: clarity
Original: Superpixel algorithms , which group pixels similar in color and other low-level properties , are increasingly used for pre-processing in image segmentation.
Revised: Superpixel algorithms , which group pixels similar in color and other low-level properties are increasingly used for pre-processing in image segmentation.
Edit intent: fluency
Original:  Motivated by improving superpixel regularity , we propose a diagram-based superpixel generation method called Power-SLIC.
Revised:  Motivated by improving superpixel regularity , we propose a diagram method called Power-SLIC.
Edit intent: clarity
Original:  On the BSDS500 data set, Power-SLIC outperforms other state-of-the-art algorithms in terms of compactness and boundary precision, and its boundary adherence is the most robust against varying levels of Gaussian noise.
Revised:  Power-SLIC outperforms other state-of-the-art algorithms in terms of compactness and boundary precision, and its boundary adherence is the most robust against varying levels of Gaussian noise.
Edit intent: clarity
Original: This paper proposes a novel and scalable reinforcement learning approach for simultaneous routing and spectrum access in wireless ad-hoc networks.
Revised: This paper proposes a novel scalable reinforcement learning approach for simultaneous routing and spectrum access in wireless ad-hoc networks.
Edit intent: clarity
Original:   In this paper, we account for the inherent signal-to-interference-plus-noise ratio (SINR) in the physical layer and propose a more scalable approach in which a single agent is associated with each flow . Specifically, a single agent makes all routing and spectrum access decisions as it moves along the frontier nodes of each flow .
Revised:  In this paper, we account for the physical-layer signal-to-interference-plus-noise ratio (SINR) in the physical layer and propose a more scalable approach in which a single agent is associated with each flow . Specifically, a single agent makes all routing and spectrum access decisions as it moves along the frontier nodes of each flow .
Edit intent: clarity
Original:   In this paper, we account for the inherent signal-to-interference-plus-noise ratio (SINR) in the physical layer and propose a more scalable approach in which a single agent is associated with each flow . Specifically, a single agent makes all routing and spectrum access decisions as it moves along the frontier nodes of each flow .
Revised:  In this paper, we account for the inherent signal-to-interference-plus-noise ratio (SINR) in the physical layer and propose a more scalable approach in which a single agent is associated with each flow and makes routing and spectrum access decisions as it moves along the frontier nodes of each flow .
Edit intent: clarity
Original:   In this paper, we account for the inherent signal-to-interference-plus-noise ratio (SINR) in the physical layer and propose a more scalable approach in which a single agent is associated with each flow . Specifically, a single agent makes all routing and spectrum access decisions as it moves along the frontier nodes of each flow .
Revised:  In this paper, we account for the inherent signal-to-interference-plus-noise ratio (SINR) in the physical layer and propose a more scalable approach in which a single agent is associated with each flow . Specifically, a single agent makes all routing and spectrum access decisions as it moves along the frontier nodes .
Edit intent: clarity
Original:  The agent is trained according to the physical layer characteristics of the environment using the future bottleneck SINR as a novel reward definition.
Revised:  The agent is trained according to the physical-layer characteristics of the environment using the future bottleneck SINR as a novel reward definition.
Edit intent: fluency
Original:  It learns to avoid interference by intelligently allocating spectrum slots and making routing decisions for the entire network in a scalable manner .
Revised:  It learns to avoid interference by intelligently making joint routing and spectrum allocation decisions based on the geographical location information of the neighbouring nodes .
Edit intent: clarity
Original: The novel 2019 coronavirus disease ( COVID-19 ) has infected over 65 million people worldwide as of December 4, 2020, pushing the world to the brink of social and economic collapse.
Revised: With COVID-19 ) has infected over 65 million people worldwide as of December 4, 2020, pushing the world to the brink of social and economic collapse.
Edit intent: coherence
Original:  We perform extensive experiments, and our results demonstrate that the proposed algorithm not only significantly improves long-range wide area network (LoRaWAN) 's packet delivery ratio (PDR) but is also able to support mobile end-devices (EDs) while ensuring lower power consumption .
Revised:  We perform extensive experiments, and our results demonstrate that the proposed algorithm not only significantly improves LoRaWAN 's packet delivery ratio (PDR) but is also able to support mobile end-devices (EDs) while ensuring lower power consumption .
Edit intent: clarity
Original:  We show that LoRaDRL's output improves the performance of state-of-the-art techniques resulting in some cases an improvement of more than 500 \% in terms of PDR compared to learning-based \\%DIF > in terms of PDR compared to learning-based techniques.
Revised:  We show that LoRaDRL's output improves the performance of state-of-the-art techniques resulting in some cases an improvement of more than 500 \\%DIF > in terms of PDR compared to learning-based techniques.
Edit intent: fluency
Original:  Additionally, we conduct a user study to evaluate our approach in a use casewhich was inspired by a healthcare scenario .
Revised:  Additionally, we conduct a user study to evaluate our approach in an exemplary medical use case .
Edit intent: clarity