wanyu/IteraTeR_v2 huggingface dataset:
Original:  Social media sites have been suspected as a breeding ground of misleading and unsubstantiated narratives about vaccines (5, 7-10), but little is known about how pervasive anti-vaccine views  on the world's largest social media, Facebook , and how online groups produce their false narratives .
Revised:  Social media sites have been suspected as a breeding ground of misleading and unsubstantiated narratives about vaccines , but little is known about how pervasive anti-vaccine views on the world's largest social media, Facebook , and how online groups produce their false narratives .
Edit intent: coherence
Original:  Social media sites have been suspected as a breeding ground of misleading and unsubstantiated narratives about vaccines (5, 7-10), but little is known about how pervasive anti-vaccine views  on the world's largest social media, Facebook , and how online groups produce their false narratives .
Revised:  Social media sites have been suspected as a breeding ground of misleading and unsubstantiated narratives about vaccines (5, 7-10), but little is known about how pervasive anti-vaccine views are on the world's largest social media, Facebook , and how online groups produce their false narratives .
Edit intent: clarity
Original:  Social media sites have been suspected as a breeding ground of misleading and unsubstantiated narratives about vaccines (5, 7-10), but little is known about how pervasive anti-vaccine views  on the world's largest social media, Facebook , and how online groups produce their false narratives .
Revised:  Social media sites have been suspected as a breeding ground of misleading and unsubstantiated narratives about vaccines (5, 7-10), but little is known about how pervasive anti-vaccine views on the world's largest social media, Facebook .
Edit intent: clarity
Original:  Here, we study the prevalence and characteristics of online groups  with anti- and pro-vaccine views on Facebook by analyzing 2,328 Facebook pages and groups and over 1.6 million posts created by them between 2012 and 2020.
Revised:  Here, we study the prevalence of online groups with anti- and pro-vaccine views on Facebook by analyzing 2,328 Facebook pages and groups and over 1.6 million posts created by them between 2012 and 2020.
Edit intent: clarity
Original:  Here, we study the prevalence and characteristics of online groups  with anti- and pro-vaccine views on Facebook by analyzing 2,328 Facebook pages and groups and over 1.6 million posts created by them between 2012 and 2020.
Revised:  Here, we study the prevalence and characteristics of online groups on Facebook with anti- and pro-vaccine views on Facebook by analyzing 2,328 Facebook pages and groups and over 1.6 million posts created by them between 2012 and 2020.
Edit intent: fluency
Original:  Here, we study the prevalence and characteristics of online groups  with anti- and pro-vaccine views on Facebook by analyzing 2,328 Facebook pages and groups and over 1.6 million posts created by them between 2012 and 2020.
Revised:  Here, we study the prevalence and characteristics of online groups with anti- and pro-vaccine views and 2020.
Edit intent: coherence
Original:  Analyses of online information sources that enabled the production of vaccine narratives revealed that vaccine content using low credibility sources was less than 2\% , and anti-vaccine groups have increasingly more utilized other relatively credible sources , such as government sources and legitimate news media.
Revised:  Analyses of online information sources that enabled the production of vaccine narratives revealed that vaccine content using low credibility sources were less than 2\% , and anti-vaccine groups have increasingly more utilized other relatively credible sources , such as government sources and legitimate news media.
Edit intent: fluency
Original:  It was also found that nearly 20\% of sources used by anti-vaccine groups each month were not shared by any pro-vaccine groups, and sources that were more widely used among anti-vaccine groups tended to represent more conservative and  far-right political beliefs .
Revised:  It was also found that nearly 20\% of sources used by anti-vaccine groups each month were not shared by any pro-vaccine groups, and sources that were more widely used among anti-vaccine groups tended to represent more conservative and far-right political views than pro-vaccine groups did .
Edit intent: clarity
Original:  The findings suggest that extensive and targeted interventions are urgently needed to suppress anti-vaccine groups on social media .
Revised:  The findings suggest that expansive and targeted interventions are urgently needed to suppress anti-vaccine groups on social media .
Edit intent: fluency
Original:  The findings suggest that extensive and targeted interventions are urgently needed to suppress anti-vaccine groups on social media .
Revised:  The findings suggest that extensive and targeted interventions are urgently needed to curb the circulation of online narratives against vaccination .
Edit intent: clarity
Original:  This work presents HiTab, a free and open dataset for the research community to study question answering (QA) and natural language generation (NLG) over hierarchical tables.
Revised:  This work presents HiTab, a free and open dataset to study question answering (QA) and natural language generation (NLG) over hierarchical tables.
Edit intent: clarity
Original:  HiTab is a cross-domain dataset constructed from a wealth of statistical reports  and Wikipedia pages, and has unique characteristics: (1) nearly all tables are hierarchical, and (2) both target sentences for NLG and questions for QA are revised from high-quality descriptions in statistical reports that are meaningfuland diverse . (3) HiTab provides fine-grained annotations on both entity and quantity alignment.
Revised:  HiTab is a cross-domain dataset constructed from a wealth of statistical reports and Wikipedia pages, and has unique characteristics: (1) nearly all tables are hierarchical, and (2) both target sentences for NLG and questions for QA are revised from original, meaningful, and diverse descriptive sentences authored by analysts and professions of reports . (3) HiTab provides fine-grained annotations on both entity and quantity alignment.
Edit intent: clarity
Original:  HiTab is a cross-domain dataset constructed from a wealth of statistical reports  and Wikipedia pages, and has unique characteristics: (1) nearly all tables are hierarchical, and (2) both target sentences for NLG and questions for QA are revised from high-quality descriptions in statistical reports that are meaningfuland diverse . (3) HiTab provides fine-grained annotations on both entity and quantity alignment.
Revised:  HiTab is a cross-domain dataset constructed from a wealth of statistical reports and Wikipedia pages, and has unique characteristics: (1) nearly all tables are hierarchical, and (2) both target sentences for NLG and questions for QA are revised from high-quality descriptions in statistical reports that are meaningfuland diverse . (3) HiTab provides fine-grained annotations of entity and quantity alignment.
Edit intent: clarity
Original:  Then given annotations of entity and quantity alignment , we propose partially supervised training , which helps models to largely reduce spurious predictions in the QA task.
Revised:  Then given annotations of entity and quantity alignment , which helps models to largely reduce spurious predictions in the QA task.
Edit intent: clarity
Original: Due to the variety of cyber-attacks or threats, the cybersecurity community has been enhancing the traditional security control mechanisms to an advanced level so that automated tools can encounter potential security threats.
Revised: Due to the variety of cyber-attacks or threats, the cybersecurity community enhances the traditional security control mechanisms to an advanced level so that automated tools can encounter potential security threats.
Edit intent: coherence
Original:  Very recently a term , Cyber Threat Intelligence (CTI) has been represented as one of the proactive and robust mechanisms because of its automated cybersecurity threat prediction based on data.
Revised:  Very recently , Cyber Threat Intelligence (CTI) has been represented as one of the proactive and robust mechanisms because of its automated cybersecurity threat prediction based on data.
Edit intent: clarity
Original:  Very recently a term , Cyber Threat Intelligence (CTI) has been represented as one of the proactive and robust mechanisms because of its automated cybersecurity threat prediction based on data.
Revised:  Very recently a term , Cyber Threat Intelligence (CTI) has been presented as one of the proactive and robust mechanisms because of its automated cybersecurity threat prediction based on data.
Edit intent: clarity
Original:  In general , CTI collects and analyses data from various sources e.g.  online security forums, social media where cyber enthusiasts, analysts, even cybercriminals discuss cyber or computer security related topics and discovers potential threats based on the analysis.
Revised:  In general , CTI collects and analyses data from various sources e.g. , online security forums, social media where cyber enthusiasts, analysts, even cybercriminals discuss cyber or computer security related topics and discovers potential threats based on the analysis.
Edit intent: fluency
Original:  In general , CTI collects and analyses data from various sources e.g.  online security forums, social media where cyber enthusiasts, analysts, even cybercriminals discuss cyber or computer security related topics and discovers potential threats based on the analysis.
Revised:  In general , CTI collects and analyses data from various sources e.g. online security forums, social media where cyber enthusiasts, analysts, even cybercriminals discuss cyber or computer security-related topics and discovers potential threats based on the analysis.
Edit intent: fluency
Original:  As the manual analysis of every such discussion i.e. posts on online platforms  is time-consuming, inefficient, and susceptible to errors, CTI as an automated tool can perform uniquely to detect cyber threats.
Revised:  As the manual analysis of every such discussion ( posts on online platforms is time-consuming, inefficient, and susceptible to errors, CTI as an automated tool can perform uniquely to detect cyber threats.
Edit intent: coherence
Original:  As the manual analysis of every such discussion i.e. posts on online platforms  is time-consuming, inefficient, and susceptible to errors, CTI as an automated tool can perform uniquely to detect cyber threats.
Revised:  As the manual analysis of every such discussion i.e. posts on online platforms ) is time-consuming, inefficient, and susceptible to errors, CTI as an automated tool can perform uniquely to detect cyber threats.
Edit intent: fluency
Original:  In this paper, our goal is to identify and explore relevant CTI from hacker forums by using different supervised and unsupervised learning  techniques.
Revised:  In this paper, we identify and explore relevant CTI from hacker forums by using different supervised and unsupervised learning techniques.
Edit intent: clarity
Original:  We also tested the classifiers on a leaked dataset with labels named nulled.io as our ground truth.
Revised:  We also employ the classifiers on a leaked dataset with labels named nulled.io as our ground truth.
Edit intent: clarity
Original:  We also tested the classifiers on a leaked dataset with labels named nulled.io as our ground truth.
Revised:  We also tested the classifiers on a labeled leaked dataset as our ground truth.
Edit intent: clarity
Original:  In theory, it is related, though subtly different, to classical problems including the dynamic all-pairs shortest paths problem , and the decremental shortest paths \emph{  problem  .
Revised:  In theory, it is related, though subtly different, to classical problems including the dynamic all-pairs shortest paths problem , and the \emph{ problem .
Edit intent: clarity
Original:  Most of the available drift detection methods  require access to  true labels during inference time .
Revised:  Most of the available drift detection methods require access to the true labels during inference time .
Edit intent: fluency
Original:  It utilizes metric learning of a constrained low-dimensional embedding representation of the input data , which is best suited for the classification task.
Revised:  It utilizes a constrained low-dimensional embedding representation of the input data , which is best suited for the classification task.
Edit intent: clarity
Original:  It utilizes metric learning of a constrained low-dimensional embedding representation of the input data , which is best suited for the classification task.
Revised:  It utilizes metric learning of a constrained low-dimensional embedding representation of the input data . This way, it is best suited for the classification task.
Edit intent: coherence
Original:  In this chapter, we describe recent progress in the study of active transport in such complex environments, focusing on two prominent biological systems---bacteria and eukaryotic cells---as archetypes of active matter.
Revised:  In this chapter, we describe recent progress in the study of active transport in such complex environments, focusing on two prominent biological systems -- bacteria and eukaryotic cells -- as archetypes of active matter.
Edit intent: fluency
Original:  Furthermore, given the diverse forms of active matter---ranging from enzymes and driven biopolymer assemblies, to microorganisms and synthetic microswimmers, to larger animals and even robots---we also describe connections to other active systems as well as more general theoretical/computational models of transport processes in complex environments.
Revised:  Furthermore, given the diverse forms of active matter -- ranging from enzymes and driven biopolymer assemblies, to microorganisms and synthetic microswimmers, to larger animals and even robots---we also describe connections to other active systems as well as more general theoretical/computational models of transport processes in complex environments.
Edit intent: fluency
Original:  Furthermore, given the diverse forms of active matter---ranging from enzymes and driven biopolymer assemblies, to microorganisms and synthetic microswimmers, to larger animals and even robots---we also describe connections to other active systems as well as more general theoretical/computational models of transport processes in complex environments.
Revised:  Furthermore, given the diverse forms of active matter---ranging from enzymes and driven biopolymer assemblies, to microorganisms and synthetic microswimmers, to larger animals and even robots -- we also describe connections to other active systems as well as more general theoretical/computational models of transport processes in complex environments.
Edit intent: fluency
Original:  To solve the aforementioned problems, we propose a \textbf{Deep Self-Adaptive Hashing~(DSAH) model to adaptively capture the semantic information with two special designs: Adaptive Neighbor Discovery~(AND) andPairwise Information Content~(PIC) .
Revised:  To solve the aforementioned problems, we propose a \textbf{Deep Self-Adaptive Hashing (DSAH) model to adaptively capture the semantic information with two special designs: Adaptive Neighbor Discovery~(AND) andPairwise Information Content~(PIC) .
Edit intent: fluency
Original:  To solve the aforementioned problems, we propose a \textbf{Deep Self-Adaptive Hashing~(DSAH) model to adaptively capture the semantic information with two special designs: Adaptive Neighbor Discovery~(AND) andPairwise Information Content~(PIC) .
Revised:  To solve the aforementioned problems, we propose a \textbf{Deep Self-Adaptive Hashing~(DSAH) model to adaptively capture the semantic information with two special designs: andPairwise Information Content~(PIC) .
Edit intent: clarity
Original:  To solve the aforementioned problems, we propose a \textbf{Deep Self-Adaptive Hashing~(DSAH) model to adaptively capture the semantic information with two special designs: Adaptive Neighbor Discovery~(AND) andPairwise Information Content~(PIC) .
Revised:  To solve the aforementioned problems, we propose a \textbf{Deep Self-Adaptive Hashing~(DSAH) model to adaptively capture the semantic information with two special designs: Adaptive Neighbor Discovery~(AND) Pairwise Information Content~(PIC) .
Edit intent: fluency
Original:  To solve the aforementioned problems, we propose a \textbf{Deep Self-Adaptive Hashing~(DSAH) model to adaptively capture the semantic information with two special designs: Adaptive Neighbor Discovery~(AND) andPairwise Information Content~(PIC) .
Revised:  To solve the aforementioned problems, we propose a \textbf{Deep Self-Adaptive Hashing~(DSAH) model to adaptively capture the semantic information with two special designs: Adaptive Neighbor Discovery~(AND) andAdaptive Neighbor Discovery (AND) and Pairwise Information Content (PIC) .
Edit intent: coherence
Original:  Extensive experiments on several benchmark datasets demonstrate that the above two technologies facilitate the deep hashing model to achieve superior performance in a self-adaptive manner .
Revised:  Extensive experiments on several datasets demonstrate that the above two technologies facilitate the deep hashing model to achieve superior performance in a self-adaptive manner .
Edit intent: clarity
Original:  Extensive experiments on several benchmark datasets demonstrate that the above two technologies facilitate the deep hashing model to achieve superior performance in a self-adaptive manner .
Revised:  Extensive experiments on several benchmark datasets demonstrate that the above two technologies facilitate the deep hashing model to achieve superior performance .
Edit intent: clarity
Original:  However, complete program synthesis of industry-grade programming languages has not been researched extensively .
Revised:  However, complete program synthesis of industry-grade programming languages remains an open problem .
Edit intent: clarity
Original:  Code will be released at URL
Revised:  Code is released at URL
Edit intent: clarity
Original:  Though foundation models are based on conventional deep learning and transfer learning, their scale results in new emergent capabilities,and their effectiveness across so many tasks incentivizes homogenization.
Revised:  Though foundation models are based on standard deep learning and transfer learning, their scale results in new emergent capabilities,and their effectiveness across so many tasks incentivizes homogenization.
Edit intent: clarity
Original:  We propose a linear regression model, where, for a given client, we theoretically compare the performance of various algorithms in the high-dimensional asymptotic limit.
Revised:  We analyze a linear regression model, where, for a given client, we theoretically compare the performance of various algorithms in the high-dimensional asymptotic limit.
Edit intent: clarity
Original:  Our theory suggests that Fine-tuned Federated Averaging (FTFA), i.e., Federated Averaging followed by local training, and the ridge regularized variant Ridge-tuned Federated Averaging (RTFA) are competitive with more sophisticated meta-learning and proximal-regularized approaches.
Revised:  Our theory suggests that Federated Averaging with client fine-tuning is competitive than more intricate meta-learning and proximal-regularized approaches.
Edit intent: clarity
Original:  In addition to being conceptually simpler, FTFA and RTFA are computationally more efficient than its competitors.
Revised:  In addition to being conceptually simpler, FTFA and RTFA are computationally more efficient than their competitors.
Edit intent: fluency
Original:  In particular, we demonstrate problematic behavior of these methods that can lead to undesired oscillations or order reduction  . Extreme cases of the latter manifest as spurious steady states.
Revised:  In particular, we demonstrate problematic behaviors of these methods that can lead to undesired oscillations or order reduction . Extreme cases of the latter manifest as spurious steady states.
Edit intent: fluency
Original:  This data-driven approach is based on leveraging prior knowledge of clean speech patterns and does not explicitly exploit the linear-filter structure in reverberation, i.e., that reverberation results from a linear convolution between a room impulse response (RIR) and a dry source signal.
Revised:  This data-driven approach is based on leveraging prior knowledge of clean speech patterns and seldom explicitly exploits the linear-filter structure in reverberation, i.e., that reverberation results from a linear convolution between a room impulse response (RIR) and a dry source signal.
Edit intent: clarity
Original:  In this paper, we introduce a reformulation of the GW convolution . Using our reformulation, many properties of the GW convolution can be easily derived, including a new formula for how the curvature of the space would affect the curvature of the function through the GW convolution.
Revised:  In this paper, we study properties of the GW convolution . Using our reformulation, many properties of the GW convolution can be easily derived, including a new formula for how the curvature of the space would affect the curvature of the function through the GW convolution.
Edit intent: clarity
Original:  Theoretically, our gradient estimation method improves the order of estimation error from O%DIFDELCMD < \left( \left( %%% n + 3%DIFDELCMD < \right)%%% ^{3/2 }%DIFDELCMD < \right) %%% to O%DIFDELCMD < \left( %%% n^{3/2 }%DIFDELCMD < \right)%%% , where n is the dimension of the manifold.
Revised:  Theoretically, our gradient estimation method improves the order of estimation error from O%DIFDELCMD < \left( \left( %%% %DIFDELCMD < \right)%%% ^{3/2 }%DIFDELCMD < \right) %%% to O%DIFDELCMD < \left( %%% n^{3/2 }%DIFDELCMD < \right)%%% , where n is the dimension of the manifold.
Edit intent: coherence
Original:  Theoretically, our gradient estimation method improves the order of estimation error from O%DIFDELCMD < \left( \left( %%% n + 3%DIFDELCMD < \right)%%% ^{3/2 }%DIFDELCMD < \right) %%% to O%DIFDELCMD < \left( %%% n^{3/2 }%DIFDELCMD < \right)%%% , where n is the dimension of the manifold.
Revised:  Theoretically, our gradient estimation method improves the order of estimation error from O%DIFDELCMD < \left( \left( %%% n + 3%DIFDELCMD < \right)%%% }%DIFDELCMD < \right) %%% to O%DIFDELCMD < \left( %%% n^{3/2 }%DIFDELCMD < \right)%%% , where n is the dimension of the manifold.
Edit intent: coherence
Original:  Theoretically, our gradient estimation method improves the order of estimation error from O%DIFDELCMD < \left( \left( %%% n + 3%DIFDELCMD < \right)%%% ^{3/2 }%DIFDELCMD < \right) %%% to O%DIFDELCMD < \left( %%% n^{3/2 }%DIFDELCMD < \right)%%% , where n is the dimension of the manifold.
Revised:  Theoretically, our gradient estimation method improves the order of estimation error from O%DIFDELCMD < \left( \left( %%% n + 3%DIFDELCMD < \right)%%% ^{3/2 }%DIFDELCMD < \right) %%% %DIFDELCMD < \left( %%% n^{3/2 }%DIFDELCMD < \right)%%% , where n is the dimension of the manifold.
Edit intent: coherence
Original:  Empirically, our method outperforms the best existing method for gradient estimation over Riemannian manifolds , as evidenced by thorough experimental evaluations .
Revised:  Empirically, our method outperforms the best existing method for gradient estimation over Riemannian manifolds is introduced .
Edit intent: clarity
Original:  In this paper, we propose a general meta learning approach to computing approximate Nash equilibrium for finite n-player normal-form games.
Revised:  In this paper, we study the learnability of approximate Nash equilibrium for finite n-player normal-form games.
Edit intent: clarity
Original:  Existing methods mainly rely on a variety of constraints to achieve the pose transfer over 3D meshes, e.g., the need for the manually encoding for shape and pose disentanglement.
Revised:  Existing methods mainly rely on a variety of constraints to achieve the pose transfer over 3D meshes, e.g., the need for manually encoding for shape and pose disentanglement.
Edit intent: fluency