wanyu/IteraTeR_v2 huggingface dataset:
Original:  To ease some of these concerns, mainstream social media platforms like Twitter and Facebook refined their content moderation systems to support soft moderation interventions.
Revised:  To ease these concerns, mainstream social media platforms like Twitter and Facebook refined their content moderation systems to support soft moderation interventions.
Edit intent: coherence
Original:  To ease some of these concerns, mainstream social media platforms like Twitter and Facebook refined their content moderation systems to support soft moderation interventions.
Revised:  To ease some of these concerns, social media platforms like Twitter and Facebook refined their content moderation systems to support soft moderation interventions.
Edit intent: clarity
Original:  Using a mixed-methods approach, we study the users that are sharing tweets with warning labels on Twitter and their political leaning, the engagement that these tweets receive, and how users interact with tweets that have warning labels.
Revised:  Using a mixed-methods approach, we study the users who share tweets with warning labels on Twitter and their political leaning, the engagement that these tweets receive, and how users interact with tweets that have warning labels.
Edit intent: clarity
Original:  By analyzing content engagement, we find that tweets with warning labels tend to receive more engagement .
Revised:  By analyzing content engagement, we find that tweets with warning labels had more engagement compared to tweets without warning labels .
Edit intent: clarity
Original:  Finally, we describe concrete examples of inconsistencies  such as warning labels that are incorrectly added or warning labels that are not added on tweets despite sharing questionable and potentially harmful information.
Revised:  Finally, we describe concrete examples of inconsistencies , such as warning labels that are incorrectly added or warning labels that are not added on tweets despite sharing questionable and potentially harmful information.
Edit intent: fluency
Original:  We also highlight challenges that need to be addressed and important research directions that will facilitate accelerated IoT adoption in these sectors .
Revised:  We also highlight challenges that need to be addressed and important research directions that will facilitate accelerated IoT adoption .
Edit intent: clarity
Original:  In this paper, we discuss the pandemic's  impact on the adoption of the Internet of Things (IoT) in various broad sectors namely healthcare, smart homes, smart buildings, smart cities, transportation and industrial IoT.
Revised:  In this paper, we discuss the pandemic's potential impact on the adoption of the Internet of Things (IoT) in various broad sectors namely healthcare, smart homes, smart buildings, smart cities, transportation and industrial IoT.
Edit intent: clarity
Original:  Our analysis and forecasting of this impact on IoT adoption is based on interviews with many industry experts, a thorough research literature review and a careful examination of reports from leading consulting firms  .
Revised:  Our perspective and forecast of this impact on IoT adoption is based on interviews with many industry experts, a thorough research literature review and a careful examination of reports from leading consulting firms .
Edit intent: clarity
Original:  Our analysis and forecasting of this impact on IoT adoption is based on interviews with many industry experts, a thorough research literature review and a careful examination of reports from leading consulting firms  .
Revised:  Our analysis and forecasting of this impact on IoT adoption is based on a thorough research literature review and a careful examination of reports from leading consulting firms .
Edit intent: clarity
Original:  Our analysis and forecasting of this impact on IoT adoption is based on interviews with many industry experts, a thorough research literature review and a careful examination of reports from leading consulting firms  .
Revised:  Our analysis and forecasting of this impact on IoT adoption is based on interviews with many industry experts, a thorough research literature review , a careful examination of reports from leading consulting firms .
Edit intent: fluency
Original:  For each of these sectors, we also provide the details of recent initiatives taken in the wake of COVID-19.
Revised:  For each of these sectors, we also provide the details of recent initiatives taken in wake of COVID-19.
Edit intent: fluency
Original:  We also highlight  challenges that need to be addressed and important research directions that will facilitate accelerated IoT adoption.
Revised:  We also highlight the challenges that need to be addressed and important research directions that will facilitate accelerated IoT adoption.
Edit intent: fluency
Original:  Furthermore, some platforms make available thousands of robots that allegedly%DIFDELCMD < ] %%% are able to be profitable in real markets.
Revised:  Furthermore, some platforms make available thousands of robots that %DIFDELCMD < ] %%% are able to be profitable in real markets.
Edit intent: fluency
Original:  In this paper, we propose a method for testing Foreign Exchange (FX) trading strategies that can provide realistic expectationsabout strategy's  performance.
Revised:  In this paper, we propose a method for testing Foreign Exchange (FX) trading strategies that provides realistic expectations, regarding the strategy's performance.
Edit intent: clarity
Original:  This method addresses  many pitfalls that can fool even experience practitioners and researchers .
Revised:  This method addresses This method addresses many pitfalls that can fool even experience practitioners and researchers .
Edit intent: fluency
Original:  We present the results of applying such method in several famous autonomous strategies in many different financial assets.
Revised:  We present the results of applying our method to several famous autonomous strategies in many different financial assets.
Edit intent: clarity
Original:  We present the results of applying such method in several famous autonomous strategies in many different financial assets.
Revised:  We present the results of applying such method in several famous autonomous trading strategies, which are used to manage a diverse selection of financial assets.
Edit intent: clarity
Original:  Analyzing these results , we can realize that it is very hard to build a reliable strategy and many published strategies are far from being reliable vehicles of investment.
Revised:  The results show that many of these published strategies are far from being reliable vehicles of investment.
Edit intent: coherence
Original:  The proposed method can be used to select among potential robots, establishes minimal periods and requirements for the test executions .
Revised:  The proposed method can be used to evaluate potential strategies .
Edit intent: clarity
Original: Despite the increasing importance of strain localization modeling (e.g., failure analysis) in computer-aided engineering, there is a lack of effective approaches to consistently modeling related material behaviors across multiple length scales.
Revised: Despite the increasing importance of strain localization modeling (e.g., failure analysis) in computer-aided engineering, there is a lack of effective approaches to capturing relevant material behaviors consistently across multiple length scales.
Edit intent: clarity
Original:  We aim to address this gap within the framework of deep material networks (DMN) - a physics-based machine learning model with embedded mechanics in the building blocks.
Revised:  We aim to address this gap within the framework of deep material networks (DMN) -- a machine learning model with embedded mechanics in the building blocks.
Edit intent: clarity
Original:  A new cell division scheme is proposed to track the scale transition through the network, and its consistency is ensured by the physics of fitting parameters.
Revised:  A new cell-division scheme is proposed to track the scale transition through the network, and its consistency is ensured by the physics of fitting parameters.
Edit intent: fluency
Original:  Besides  single material point studies , we apply the multiscale model to concurrent multiscale simulations for the dynamic crush of a particle-reinforced composite tube and various tests on carbon fiber reinforced polymer composites.
Revised:  Besides single material point , we apply the multiscale model to concurrent multiscale simulations for the dynamic crush of a particle-reinforced composite tube and various tests on carbon fiber reinforced polymer composites.
Edit intent: clarity
Original:  Weak constraint 4D-Var estimates the model error and minimises a series of linear least-squares cost functions using the conjugate gradient (CG) method;
Revised:  Weak constraint 4D-Var estimates the model error and minimises a series of linear least-squares cost functionsfunctions, which can be achieved using the conjugate gradient (CG) method;
Edit intent: clarity
Original:  As far as we know, there is no work which thoroughly compares different saliency maps for Deep Reinforcement Learning agents.
Revised:  As far as we know, there is no work that thoroughly compares different saliency maps for Deep Reinforcement Learning agents.
Edit intent: fluency
Original: One 15mer peptide of SARS-CoV-2 with the sequence CFLGYFCTCYFGLFC is identified in this study initially through tblastx searches . Binding predictions of that peptide to the MHC supertype representatives are performed and the potential epitopes are retrieved through the results.
Revised: Aim: This study is looking for a common pathogenicity between SARS-CoV-2 with the sequence CFLGYFCTCYFGLFC is identified in this study initially through tblastx searches . Binding predictions of that peptide to the MHC supertype representatives are performed and the potential epitopes are retrieved through the results.
Edit intent: coherence
Original:  On the other hand, peptide with the YFYLFSLELF sequence in the human proteome is homologous to the P. falciparum peptide with the sequence FFYTFYFELF, which is in turn homologous to the YFCTCYFGLF of SARS-CoV-2.
Revised:  On the other hand, peptide with the YFYLFSLELF sequence in the human proteome is homologous to the P. falciparum is homologous to the YFCTCYFGLF of SARS-CoV-2.
Edit intent: coherence
Original:  These results allow one to suspect the risk of autoimmune responses in the HLA*A24 :02  serotypes, upon being infected especially with SARS-CoV-2 . This work may lead to clinical and experimental studies for the identification of certain HLA serotypes as risk groups and highlights the importance of relevant considerations in the vaccine studies .
Revised:  These results allow one to suspect the risk of autoimmune responses in the HLA*A24 :02 serotypes, upon getting infected with SARS-CoV-2 . This work may lead to clinical and experimental studies for the identification of certain HLA serotypes as risk groups and highlights the importance of relevant considerations in the vaccine studies .
Edit intent: clarity
Original:  Whereas the core of the assignment game is always non-empty, that of the general graph matching game the core can be empty.
Revised:  Whereas the core of the assignment game is always non-empty, that of the general graph matching game can be empty.
Edit intent: clarity
Original:  We show that this bound is best possible -- it is the integrality gap of the natural underlying LP.
Revised:  This bound is best possible -- it is the integrality gap of the natural underlying LP.
Edit intent: coherence
Original:  We show that this bound is best possible -- it is the integrality gap of the natural underlying LP.
Revised:  We show that this bound is best possible , since it is the integrality gap of the natural underlying LP.
Edit intent: coherence
Original:  The core is a quintessential solution concept in cooperative game theory.
Revised:  The core is a key solution concept in cooperative game theory.
Edit intent: clarity
Original:  It contains  ways of distributing the total worth of a game among agents in such a way that no sub-coalition has incentive to secede from the grand coalition.
Revised:  It contains all ways of distributing the total worth of a game among agents in such a way that no sub-coalition has incentive to secede from the grand coalition.
Edit intent: clarity
Original:  Our  2/3-approximate imputation implies that a sub-coalition will be able to gain at most a 3/2 factor by seceding, and less in typical cases.
Revised:  Our 2/3-approximate imputation implies that a sub-coalition will gain at most a 3/2 factor by seceding, and less in typical cases.
Edit intent: clarity
Original:  Whereas the core of the assignment game is always non-empty, that of the general graph matching game can be empty.
Revised:  Whereas the core of this game is always non-empty, that of the general graph matching game can be empty.
Edit intent: clarity
Original:  {\em   The core is a key solution concept in cooperative game theory.
Revised:  {\em competitiveness The core is a key solution concept in cooperative game theory.
Edit intent: fluency
Original:  {\em   The core is a key solution concept in cooperative game theory.
Revised:  {\em The core is a quintessential solution concept in cooperative game theory.
Edit intent: clarity
Original: The computation of probability density functions (PDF) using approximate maps (surrogate models) is a building block in such diverse fields as forward uncertainty quantification (UQ), sampling algorithms, learning, and inverse problems.
Revised: The estimation of probability density functions (PDF) using approximate maps (surrogate models) is a building block in such diverse fields as forward uncertainty quantification (UQ), sampling algorithms, learning, and inverse problems.
Edit intent: clarity
Original: The computation of probability density functions (PDF) using approximate maps (surrogate models) is a building block in such diverse fields as forward uncertainty quantification (UQ), sampling algorithms, learning, and inverse problems.
Revised: The computation of probability density functions (PDF) using approximate maps is a fundamental building block in such diverse fields as forward uncertainty quantification (UQ), sampling algorithms, learning, and inverse problems.
Edit intent: clarity
Original:  In the field of UQ, the{\em   generalized Polynomial Chaos (gPC) method is widely popular and yields excellent approximations of the map and its moment .
Revised:  In the field of UQ, the{\em moments generalized Polynomial Chaos (gPC) method is widely popular and yields excellent approximations of the map and its moment .
Edit intent: fluency
Original:  But can the pushforward PDF be approximated with spectral accuracy as well?
Revised:  But can the PDF of the quantity of interest be approximated with spectral accuracy as well?
Edit intent: clarity
Original:  We provide convergence rates for PDFs using colocation and Galerkin gPC methods  in all dimensions , guaranteeing exponential rates for analytic maps .
Revised:  We provide convergence rates for PDFs using collocation and Galerkin gPC methods in all dimensions , guaranteeing exponential rates for analytic maps .
Edit intent: fluency
Original:  We also incorporate a wide variety of popular techniques from modern NAS literature , including multiobjective optimization and varying controller methods, to showcase their promise in the RL field and discuss possible extensions .
Revised:  We also incorporate a wide variety of popular techniques from modern NAS literature including multiobjective optimization and varying controller methods, to showcase their promise in the RL field and discuss possible extensions .
Edit intent: fluency
Original:  We also incorporate a wide variety of popular techniques from modern NAS literature , including multiobjective optimization and varying controller methods, to showcase their promise in the RL field and discuss possible extensions .
Revised:  We also incorporate a wide variety of popular techniques from modern NAS literature , including multiobjective optimization along with various controller methods, to showcase their promise in the RL field and discuss possible extensions .
Edit intent: clarity
Original: We  introduce ES-ENAS, a simple yet general evolutionary joint optimization procedure by combining continuous optimization via Evolutionary Strategies (ES) and combinatorial optimization via Efficient NAS (ENAS) in a highly scalable and intuitive way    .
Revised: We introduce ES-ENAS, a simple joint optimization procedure by combining continuous optimization via Evolutionary Strategies (ES) and combinatorial optimization via Efficient NAS (ENAS) in a highly scalable and intuitive way .
Edit intent: coherence
Original: We  introduce ES-ENAS, a simple yet general evolutionary joint optimization procedure by combining continuous optimization via Evolutionary Strategies (ES) and combinatorial optimization via Efficient NAS (ENAS) in a highly scalable and intuitive way    .
Revised: We introduce ES-ENAS, a simple yet general evolutionary joint optimization procedure by combining Evolutionary Strategies (ES) and combinatorial optimization via Efficient NAS (ENAS) in a highly scalable and intuitive way .
Edit intent: clarity
Original: We  introduce ES-ENAS, a simple yet general evolutionary joint optimization procedure by combining continuous optimization via Evolutionary Strategies (ES) and combinatorial optimization via Efficient NAS (ENAS) in a highly scalable and intuitive way    .
Revised: We introduce ES-ENAS, a simple yet general evolutionary joint optimization procedure by combining continuous optimization via Evolutionary Strategies (ES) and combinatorial optimization techniques in a highly scalable and intuitive way .
Edit intent: clarity
Original:  Our main insight is noticing that ES is already a highly distributed algorithm involving hundreds of forward passes which can not only be used for training neural network weights, but also for jointly training a NAS controller, both in a blackbox fashion.
Revised:  Our main insight is noticing that ES is already a highly distributed algorithm involving hundreds of blackbox evaluations which can not only be used for training neural network weights, but also for jointly training a NAS controller, both in a blackbox fashion.
Edit intent: clarity
Original:  By doing so, we also bridge the gap from NAS research in supervised learning settings to the reinforcement learning scenario through this relatively simple marriage between two different yet common lines of research .
Revised:  By doing so, we also bridge the gap from NAS research in supervised learning settings to the reinforcement learning scenario through this relatively simple marriage between two different lines of research .
Edit intent: clarity
Original:  We demonstrate the utility and effectiveness of our method over a large search space by training highly combinatorial neural network architectures for RL problems in continuous control, via edge pruning and quantization .
Revised:  We demonstrate the utility and effectiveness of our method over a large search space by training highly combinatorial neural network architectures via edge pruning and quantization .
Edit intent: clarity
Original:  and combinatorial optimization techniques in a highly scalable and intuitive way, inspired by the one-shot orsupernet paradigm introduced in Efficient Neural Architecture Search (ENAS) . Our main insight is noticing that ES is already a highly distributed algorithm involving hundreds of blackbox evaluations which can not only be used for training neural network weights, but also for feedback to a combinatorial optimizer .
Revised:  and combinatorial optimization techniques in a highly scalable and intuitive way, inspired by the orsupernet paradigm introduced in Efficient Neural Architecture Search (ENAS) . Our main insight is noticing that ES is already a highly distributed algorithm involving hundreds of blackbox evaluations which can not only be used for training neural network weights, but also for feedback to a combinatorial optimizer .
Edit intent: clarity
Original:  and combinatorial optimization techniques in a highly scalable and intuitive way, inspired by the one-shot orsupernet paradigm introduced in Efficient Neural Architecture Search (ENAS) . Our main insight is noticing that ES is already a highly distributed algorithm involving hundreds of blackbox evaluations which can not only be used for training neural network weights, but also for feedback to a combinatorial optimizer .
Revised:  and combinatorial optimization techniques in a highly scalable and intuitive way, inspired by the one-shot supernet paradigm introduced in Efficient Neural Architecture Search (ENAS) . Our main insight is noticing that ES is already a highly distributed algorithm involving hundreds of blackbox evaluations which can not only be used for training neural network weights, but also for feedback to a combinatorial optimizer .
Edit intent: fluency
Original:  and combinatorial optimization techniques in a highly scalable and intuitive way, inspired by the one-shot orsupernet paradigm introduced in Efficient Neural Architecture Search (ENAS) . Our main insight is noticing that ES is already a highly distributed algorithm involving hundreds of blackbox evaluations which can not only be used for training neural network weights, but also for feedback to a combinatorial optimizer .
Revised:  and combinatorial optimization techniques in a highly scalable and intuitive way, inspired by the one-shot orone-shot or supernet paradigm introduced in Efficient Neural Architecture Search (ENAS) . Our main insight is noticing that ES is already a highly distributed algorithm involving hundreds of blackbox evaluations which can not only be used for training neural network weights, but also for feedback to a combinatorial optimizer .
Edit intent: fluency
Original:  and combinatorial optimization techniques in a highly scalable and intuitive way, inspired by the one-shot orsupernet paradigm introduced in Efficient Neural Architecture Search (ENAS) . Our main insight is noticing that ES is already a highly distributed algorithm involving hundreds of blackbox evaluations which can not only be used for training neural network weights, but also for feedback to a combinatorial optimizer .
Revised:  and combinatorial optimization techniques in a highly scalable and intuitive way, inspired by the one-shot orsupernet paradigm introduced in Efficient Neural Architecture Search (ENAS) .
Edit intent: coherence
Original:  Consider a metric space (X, d_X ]  ), a graph H over X is a \vartheta-reliable t-spanner if, for every set of failed vertices B\subset X, there is a superset B^+\supseteq B such that the induced subgraph H X\setminus B%DIFDELCMD < ] %DIFDELCMD < %%% preserves all the distances between points in X\setminus B^+ up to a stretch factor t, while the expected size of B^+ is as most (1+\vartheta)|B|.
Revised:  Consider a metric space (X, d_X ] ), a X\setminus B%DIFDELCMD < ] %DIFDELCMD < %%% preserves all the distances between points in X\setminus B^+ up to a stretch factor t, while the expected size of B^+ is as most (1+\vartheta)|B|.
Edit intent: clarity
Original:  Har-Peled and Ol { \'{a \em  } h \\%DIF > of the nodes fail.
Revised:  Har-Peled and Ol { \em } h \\%DIF > of the nodes fail.
Edit intent: fluency
Original: We study the adhesion of a droplet  with insoluble surfactant laid on its capillary surface to a textured substrate.
Revised: We study spreading of a droplet with insoluble surfactant laid on its capillary surface to a textured substrate.
Edit intent: clarity
Original: We study the adhesion of a droplet  with insoluble surfactant laid on its capillary surface to a textured substrate.
Revised: We study the adhesion of a droplet , with insoluble surfactant laid on its capillary surface to a textured substrate.
Edit intent: fluency
Original: We study the adhesion of a droplet  with insoluble surfactant laid on its capillary surface to a textured substrate.
Revised: We study the adhesion of a droplet with insoluble surfactant covering its capillary surface to a textured substrate.
Edit intent: clarity