wanyu/IteraTeR_v2 huggingface dataset:
Original:  We also implement a low-latency version of TasNet, which we submitted to the DSN Challenge and made public by open-sourcing it.
Revised:  We also implement a low-latency version of TasNet, which we submitted to the DNS Challenge and made public by open-sourcing it.
Edit intent: fluency
Original: For non-Euclidean data such as meshes of humans, a prominent task for generative models is geometric disentanglement;
Revised: Geometric disentanglement,
Edit intent: clarity
Original:  This work introduces a novel mesh feature, the conformal factor and normal feature (CFAN),for use in mesh convolutional autoencoders.
Revised:  This work introduces a mesh feature, the conformal factor and normal feature (CFAN),for use in mesh convolutional autoencoders.
Edit intent: clarity
Original:  We also successfully detect and recover geometric disentanglement in mesh convolutional autoencoders that encode xyz-coordinates directly by registering its latent space to that of CFAN-VAE.
Revised:  We also successfully detect a level of geometric disentanglement in mesh convolutional autoencoders that encode xyz-coordinates directly by registering its latent space to that of CFAN-VAE.
Edit intent: clarity
Original:  We detail the use of miniKanren as an underlying framework for term rewriting and symbolic mathematics, as well as its ability to orchestrate the use of existing Python libraries per .
Revised:  We detail the use of miniKanren as an underlying framework for term rewriting and symbolic mathematics, as well as its ability to orchestrate the use of existing Python libraries .
Edit intent: fluency
Original:  We also discuss the relevance and potential of relational programming for implementing more robust, portable, domain-specific `` math-level '' optimizations--with a slight focus on Bayesian modeling.
Revised:  We also discuss the relevance and potential of relational programming for implementing more robust, portable, domain-specific " math-level '' optimizations--with a slight focus on Bayesian modeling.
Edit intent: fluency
Original:  We also discuss the relevance and potential of relational programming for implementing more robust, portable, domain-specific `` math-level '' optimizations--with a slight focus on Bayesian modeling.
Revised:  We also discuss the relevance and potential of relational programming for implementing more robust, portable, domain-specific `` math-level " optimizations--with a slight focus on Bayesian modeling.
Edit intent: fluency
Original:  One of the biggest remaining obstacles to leveraging the aforementioned methods for improving human decision-making is that the policies they learn are opaque to people.
Revised:  One of the biggest remaining obstacles to leveraging the aforementioned methods is that the policies they learn are opaque to people.
Edit intent: clarity
Original:  We evaluate our new AI-Interpret algorithm and employ it to translate information-acquisition policies discovered through metalevel reinforcement learning.
Revised:  We evaluate our new algorithm and employ it to translate information-acquisition policies discovered through metalevel reinforcement learning.
Edit intent: clarity
Original:  The results of three large behavioral experiments showed that the provision of decision rules as flowcharts significantly improved people's planning strategies and decisions across three different classes of sequential decision problems.
Revised:  The results of large behavioral experiments showed that the provision of decision rules as flowcharts significantly improved people's planning strategies and decisions across three different classes of sequential decision problems.
Edit intent: fluency
Original:  The results of three large behavioral experiments showed that the provision of decision rules as flowcharts significantly improved people's planning strategies and decisions across three different classes of sequential decision problems.
Revised:  The results of three large behavioral experiments showed that the provision of decision rules as flowcharts significantly improved people's planning strategies and decisions across three diferent classes of sequential decision problems.
Edit intent: fluency
Original:  Furthermore, a series of ablation studies confirmed that our AI-Interpret algorithm was critical to the discovery of interpretable decision rules and that it is ready to be applied to other reinforcement learning problems .
Revised:  Furthermore, a series of ablation studies confirmed that AI-Interpret algorithm was critical to the discovery of interpretable decision rules and that it is ready to be applied to other reinforcement learning problems .
Edit intent: clarity
Original:  Furthermore, a series of ablation studies confirmed that our AI-Interpret algorithm was critical to the discovery of interpretable decision rules and that it is ready to be applied to other reinforcement learning problems .
Revised:  Furthermore, a series of ablation studies confirmed that our AI-Interpret is critical to the discovery of interpretable decision rules and that it is ready to be applied to other reinforcement learning problems .
Edit intent: clarity
Original:  Furthermore, a series of ablation studies confirmed that our AI-Interpret algorithm was critical to the discovery of interpretable decision rules and that it is ready to be applied to other reinforcement learning problems .
Revised:  Furthermore, a series of ablation studies confirmed that our AI-Interpret algorithm was critical to the discovery of interpretable decision rules .
Edit intent: coherence
Original:  We conclude that the methods and findings presented in this article are an important step towards leveraging automatic strategy discovery to improve human decision-making.
Revised:  We conclude that the methods and findings presented herein are an important step towards leveraging automatic strategy discovery to improve human decision-making.
Edit intent: clarity
Original:  Unlike the propagation of chaos in the classical mean field limit for interacting particle systems , the chaos here is imposed at every discrete time.
Revised:  Unlike the classical mean field limit for interacting particle systems , the chaos here is imposed at every discrete time.
Edit intent: clarity
Original:  Motif-driven analysis is also useful for temporal networks where the number of motifs is significantly larger due to the additional temporal information on edges.
Revised:  Motif-driven analysis is also useful for temporal networks where the spectrum of motifs is significantly larger due to the additional temporal information on edges.
Edit intent: clarity
Original:  In this work, we compare the existing temporal motif models , and evaluate the facets of temporal networks that are overlooked in the literature.
Revised:  In this work, we compare the existing temporal motif models and evaluate the facets of temporal networks that are overlooked in the literature.
Edit intent: fluency
Original:  In addition, we suggest a new lens, event pairs, to study temporal motifs to investigate cause-effect relations .
Revised:  In addition, we suggest a new lens, event pairs, to investigate temporal correlations .
Edit intent: clarity
Original: We introduce *scadnano* URL (short for "scriptable cadnano"), a computational tool for designing synthetic DNA structures.
Revised: We introduce scadnano URL (short for "scriptable cadnano"), a computational tool for designing synthetic DNA structures.
Edit intent: coherence
Original:  Its design is based heavily on cadnano, the most widely-used software for designing DNA origami, with three main differences: 1. scadnano runs entirely in the browser, with *no software installation* \textit{ required.
Revised:  Its design is based heavily on cadnano, the most widely-used software for designing DNA origami, with three main differences: 1. scadnano runs entirely in the browser, with \textit{ required.
Edit intent: coherence
Original:  Its design is based heavily on cadnano, the most widely-used software for designing DNA origami, with three main differences: 1. scadnano runs entirely in the browser, with *no software installation* \textit{ required.
Revised:  Its design is based heavily on cadnano, the most widely-used software for designing DNA origami, with three main differences: 1. scadnano runs entirely in the browser, with *no software installation* \textit{no software installation required.
Edit intent: fluency
Original:  2. scadnano designs, while they can be edited manually, can also be created and edited by a *well-documented Python scripting library* , to help automate tedious tasks.
Revised:  2. scadnano designs, while they can be edited manually, can also be created and edited by a well-documented Python scripting library , to help automate tedious tasks.
Edit intent: fluency
Original:  3. The scadnano file format is *easily human-readable* .
Revised:  3. The scadnano file format is easily human-readable .
Edit intent: fluency
Original:  The format is also somewhat more *expressive* than that of cadnano, able to describe a broader range of DNA structures than just DNA origami.
Revised:  The format is also somewhat more expressive than that of cadnano, able to describe a broader range of DNA structures than just DNA origami.
Edit intent: fluency
Original: We construct deep ReLU neural networks to approximate functions in dilated shift-invariant spaces generated by a continuous function with compact support and study the approximation rates with respect to the number of neurons .
Revised: We construct deep ReLU neural networks for approximating functions in dilated shift-invariant spaces generated by a continuous function with compact support and study the approximation rates with respect to the number of neurons .
Edit intent: clarity
Original: We construct deep ReLU neural networks to approximate functions in dilated shift-invariant spaces generated by a continuous function with compact support and study the approximation rates with respect to the number of neurons .
Revised: We construct deep ReLU neural networks to approximate functions in dilated shift-invariant spaces generated by a continuous function with compact support and study the approximation rates with respect to the width and depth of neural networks .
Edit intent: clarity
Original:  The network construction is based on the bit extraction and data fitting capacity of deep neural networks.
Revised:  The network construction is based on the bit extraction and data-fitting capacity of deep neural networks.
Edit intent: fluency
Original:  Combining with existing results of approximation from shift-invariant spaces, we are able to estimate the approximation rates of classical function spaces such as Sobolev spaces and Besov spaces  .
Revised:  As applications of our main results, the approximation rates of classical function spaces such as Sobolev spaces and Besov spaces .
Edit intent: clarity
Original:  In this paper, using WiFi data collected directly from the infrastructure, we present a detailed analysis of the impact of %DIFDELCMD < \virus %DIFDELCMD < %%%  related policies on the staff and students of three different college campuses.
Revised:  In this paper, using WiFi data collected directly from the infrastructure, we present a detailed analysis of the impact of %DIFDELCMD < \virus %DIFDELCMD < %%% virus related policies on the staff and students of three different college campuses.
Edit intent: fluency
Original:  Our study focuses on two different key metrics, 1) %DIFDELCMD < {\em %DIFDELCMD < %%% Occupancy , defined as the number of people in a building, on average, in a specific hour, and 2) %DIFDELCMD < {\em %%% Mobility , defined as the number of places visited by an individual, on average, in a specific hour.
Revised:  Our study focuses on two different key metrics, 1) %DIFDELCMD < {\em %DIFDELCMD < %%% Occupancy , defined as the number of people in a building, on average, in a specific hour, and 2) %DIFDELCMD < {\em %%% Mobility , defined as the number of places visited by an individual, on average, in a specific hour.
Edit intent: fluency
Original:  Our results show that online learning, split-team, and other space management policies are effective at lowering %DIFDELCMD < {\em %%% Occupancy .
Revised:  Our results show that online learning, split-team, and other space management policies are effective at lowering %DIFDELCMD < {\em %%% Occupancy .
Edit intent: fluency
Original:  However, they do not change the %DIFDELCMD < {\em %%% Mobility patterns for individuals who are still moving around.
Revised:  However, they do not change the %DIFDELCMD < {\em %%% Mobility patterns for individuals who are still moving around.
Edit intent: fluency
Original:  Reducing %DIFDELCMD < {\em %%% Mobility requires introducing strict stay-at-home or lockdown orders, but doing so increases %DIFDELCMD < {\em %%% Occupancy in residential spaces.
Revised:  Reducing %DIFDELCMD < {\em %%% Mobility requires introducing strict stay-at-home or lockdown orders, but doing so increases %DIFDELCMD < {\em %%% Occupancy in residential spaces.
Edit intent: fluency
Original:  Two of these campuses are in Singapore, while the third is in the Northeastern United States.
Revised:  Two of these campuses are in Singapore, and the third is in the Northeastern United States.
Edit intent: coherence
Original:  Our results show that online learning, split-team, and other space management policies are effective at lowering Occupancy .
Revised:  Our results show that online learning, split-team, and other space management policies effectively lower occupancy .
Edit intent: clarity
Original:  We present our results and then discuss the implications of the findings for policymakers .
Revised:  We demonstrate how this data source can be put to practical application for institutional crowd control and discuss the implications of the findings for policymakers .
Edit intent: clarity
Original:  We present our results and then discuss the implications of the findings for policymakers .
Revised:  We present our results and then discuss the implications of our findings for policy-making .
Edit intent: clarity
Original:  In this paper, we investigate the feasibility of automatically assigning a coarse-grained primary classification using the MSC scheme, by regarding the problem as a multi class classification machine learning task.
Revised:  In this paper, we investigate the feasibility of automatically assigning a coarse-grained primary classification using the MSC scheme, by regarding the problem as a multi-class classification machine learning task.
Edit intent: fluency
Original:  We find that the our method achieves an (F _{1 )-score of over 77\%, which is remarkably close to the agreement of zb and MR ((F _{1 )-score of 81\%).
Revised:  We find that our method achieves an (F _{1 )-score of over 77\%, which is remarkably close to the agreement of zb and MR ((F _{1 )-score of 81\%).
Edit intent: fluency
Original:  We find that the our method achieves an (F _{1 )-score of over 77\%, which is remarkably close to the agreement of zb and MR ((F _{1 )-score of 81\%).
Revised:  We find that the our method achieves an (F _1 )-score of over 77\%, which is remarkably close to the agreement of zb and MR ((F _{1 )-score of 81\%).
Edit intent: fluency
Original:  We find that the our method achieves an (F _{1 )-score of over 77\%, which is remarkably close to the agreement of zb and MR ((F _{1 )-score of 81\%).
Revised:  We find that the our method achieves an (F _{1 )-score of over 77\%, which is remarkably close to the agreement of zb and MR ((F _1 )-score of 81\%).
Edit intent: fluency
Original:  Moreover, we find that the method's confidence score allows for reducing the effort by 86 %DIFDELCMD < \\%%% %DIF < compared  to the manual coarse-grained classification effort while maintaining a precision of 81\% for automatically classified articles.
Revised:  Moreover, we find that the method's confidence score allows for reducing the effort by 86 %DIFDELCMD < \\%%% %DIF < compared \% compared to the manual coarse-grained classification effort while maintaining a precision of 81\% for automatically classified articles.
Edit intent: fluency
Original:  This paper surveys deep learning algorithms, IoT cyber security and risk models, and established mathematical formulas to identify the best approach for developing a dynamic and self-adapting system for predictive cyber risk analytics supported with Artificial Intelligence and Machine Learning and real-time intelligence in edge computing.
Revised:  This paper surveys deep learning algorithms, IoT cyber security and risk models, and established mathematical formulas to identify the best approach for developing a dynamic and self adapting system for predictive cyber risk analytics supported with Artificial Intelligence and Machine Learning and real-time intelligence in edge computing.
Edit intent: fluency
Original:  This paper surveys deep learning algorithms, IoT cyber security and risk models, and established mathematical formulas to identify the best approach for developing a dynamic and self-adapting system for predictive cyber risk analytics supported with Artificial Intelligence and Machine Learning and real-time intelligence in edge computing.
Revised:  This paper surveys deep learning algorithms, IoT cyber security and risk models, and established mathematical formulas to identify the best approach for developing a dynamic and self-adapting system for predictive cyber risk analytics supported with Artificial Intelligence and Machine Learning and real time intelligence in edge computing.
Edit intent: fluency
Original:  This engine instigates a step change by applying Artificial Intelligence and Machine Learning embedded at the edge of IoT networks, to deliver safe and functional real-time intelligence for predictive cyber risk analytics.
Revised:  This engine instigates a step change by applying Artificial Intelligence and Machine Learning embedded at the edge of IoT networks, to deliver safe and functional real time intelligence for predictive cyber risk analytics.
Edit intent: fluency
Original:  This integration is mainly concerned with  death data which are not available at NUTS-3 level from official data channels.
Revised:  This integration is mainly concerned with death data which are not available at NUTS-3 level from open official data data channels.
Edit intent: clarity
Original:  An adjusted time-dependent SIRD model is used to predict the behaviour of the epidemics , specifically the number of susceptible, infected, deceased and recovered people.
Revised:  An adjusted time-dependent SIRD model is used to predict the behavior of the epidemic , specifically the number of susceptible, infected, deceased and recovered people.
Edit intent: fluency
Original:  Model performance is evaluated using comparison with real data.
Revised:  Predictive model performance is evaluated using comparison with real data.
Edit intent: clarity
Original:  The introduction of approaches for estimating connectivity strength  is followed.
Revised:  The introduction of the methods for estimating connectivity strength is followed.
Edit intent: clarity
Original: In this paper, we develop the notion of controllability for uniform hypergraphs via tensor algebra and the theory of polynomial control .
Revised: In this paper, we develop a notion of controllability for uniform hypergraphs via tensor algebra and the theory of polynomial control .
Edit intent: fluency
Original: In this paper, we develop the notion of controllability for uniform hypergraphs via tensor algebra and the theory of polynomial control .
Revised: In this paper, we develop the notion of controllability for hypergraphs via tensor algebra and the theory of polynomial control .
Edit intent: clarity
Original:  As data drove most of the decisions made in this global contingency, its quality is a critical variable for decision-making actors, and therefore should be carefully curated.
Revised:  As data drove most of the decisions made in this global contingency, their quality is a critical variable for decision-making actors, and therefore should be carefully curated.
Edit intent: fluency
Original:  In this work, we analyze the sources of error in the typically reported epidemiologic variables and the different tests used for diagnosis, and their impact on our understanding of COVID-19 spreading dynamics.
Revised:  In this work, we analyze the sources of error in typically reported epidemiological variables and usual tests used for diagnosis, and their impact on our understanding of COVID-19 spreading dynamics.
Edit intent: clarity
Original:  Doing so, we aim to raise public awareness of the need for proper data reporting and processing protocols  .
Revised:  In doing so, we aim to raise public awareness of the need for proper data reporting and processing protocols .
Edit intent: fluency
Original:  Firstly, we normalize the trajectory data by map-matching algorithms and extract  turning behaviors, parking behaviors, and average speeds of vehicles.
Revised:  Firstly, we normalize the trajectory data by map matching algorithms and extract turning behaviors, parking behaviors, and average speeds of vehicles.
Edit intent: fluency
Original:  Firstly, we normalize the trajectory data by map-matching algorithms and extract  turning behaviors, parking behaviors, and average speeds of vehicles.
Revised:  Firstly, we normalize the trajectory data by map-matching algorithms and extract key driving behaviors, i.e., turning behaviors, parking behaviors, and average speeds of vehicles.
Edit intent: clarity
Original:  Firstly, we normalize the trajectory data by map-matching algorithms and extract  turning behaviors, parking behaviors, and average speeds of vehicles.
Revised:  Firstly, we normalize the trajectory data by map-matching algorithms and extract turning behaviors, parking behaviors, and speeds of vehicles.
Edit intent: clarity
Original:  Finally, we extract the spatiotemporal patterns of traffic violations to infer traffic violation-prone locations in cities and build an inference system .
Revised:  Finally, we extract the spatiotemporal patterns of traffic violations to infer traffic violation-prone locations .
Edit intent: clarity
Original:  To evaluate the proposed framework , we conduct extensive studies on large-scale, real-world vehicle GPS trajectories collected from two cities located in the east and west of China , respectively.
Revised:  To evaluate the effectiveness of the proposed method , we conduct extensive studies on large-scale, real-world vehicle GPS trajectories collected from two cities located in the east and west of China , respectively.
Edit intent: clarity
Original:  To evaluate the proposed framework , we conduct extensive studies on large-scale, real-world vehicle GPS trajectories collected from two cities located in the east and west of China , respectively.
Revised:  To evaluate the proposed framework , we conduct extensive studies on large-scale, real-world vehicle GPS trajectories collected from two Chinese cities , respectively.
Edit intent: clarity
Original:  Evaluation results confirm that the proposed framework can infer traffic violation-prone locations in cities effectively and efficiently  .
Revised:  Evaluation results confirm that the proposed framework infers traffic violation-prone locations in cities effectively and efficiently .
Edit intent: clarity
Original:  Evaluation results confirm that the proposed framework can infer traffic violation-prone locations in cities effectively and efficiently  .
Revised:  Evaluation results confirm that the proposed framework can infer traffic violation-prone locations effectively and efficiently .
Edit intent: clarity
Original:  In this study we develop a mathematical model of the immune system that incorporates both the innate and adaptive immune compartments, named the integrated immune branch (IIB) model , and investigate how immune behavior changes in response to a sequence of pathogen encounters  .
Revised:  In this study we develop a mathematical framework of coupled innate and adaptive immune compartments, named the integrated immune branch (IIB) model , and investigate how immune behavior changes in response to a sequence of pathogen encounters .
Edit intent: clarity