wanyu/IteraTeR_v2 huggingface dataset:
Original:  It also confirms that the proposed admission control algorithm works well for various traffic patterns and parameters, and promisingly evinces tractable scalability properties as the number of cores in the crossbarincreases .
Revised:  Furthermore, they confirm that the proposed admission control algorithm works well for various traffic patterns and parameters, and promisingly evinces tractable scalability properties as the number of cores in the crossbarincreases .
Edit intent: clarity
Original:  It also confirms that the proposed admission control algorithm works well for various traffic patterns and parameters, and promisingly evinces tractable scalability properties as the number of cores in the crossbarincreases .
Revised:  It also confirms that the proposed admission control algorithm works well for various traffic patterns and parameters, and evinces a tractable scalability with increase in the number of cores in the crossbarincreases .
Edit intent: clarity
Original:  It also confirms that the proposed admission control algorithm works well for various traffic patterns and parameters, and promisingly evinces tractable scalability properties as the number of cores in the crossbarincreases .
Revised:  It also confirms that the proposed admission control algorithm works well for various traffic patterns and parameters, and promisingly evinces tractable scalability properties as the number of cores of the crossbar .
Edit intent: clarity
Original:  First introduced by Edelsbrunner et al. (Edelsbrunner et al. 2008) , it compresses the components of the level sets of a multivariate mapping and obtains a summary representation of their relationships.
Revised:  First introduced by Edelsbrunner et al. , it compresses the components of the level sets of a multivariate mapping and obtains a summary representation of their relationships.
Edit intent: coherence
Original:  A related construction called the mapper(Singh et al. 2007) , and a special case of mapper called the Joint Contour Net (Carr et al. 2014) have been shown to be effective in visual analytics.
Revised:  A related construction called mapper , and a special case of mapper called the Joint Contour Net (Carr et al. 2014) have been shown to be effective in visual analytics.
Edit intent: coherence
Original:  A related construction called the mapper(Singh et al. 2007) , and a special case of mapper called the Joint Contour Net (Carr et al. 2014) have been shown to be effective in visual analytics.
Revised:  A related construction called the mapper(Singh et al. 2007) , and a special case of the mapper construction called the Joint Contour Net (Carr et al. 2014) have been shown to be effective in visual analytics.
Edit intent: clarity
Original:  A related construction called the mapper(Singh et al. 2007) , and a special case of mapper called the Joint Contour Net (Carr et al. 2014) have been shown to be effective in visual analytics.
Revised:  A related construction called the mapper(Singh et al. 2007) , and a special case of mapper called the Joint Contour Net have been shown to be effective in visual analytics.
Edit intent: coherence
Original:  An open question has been proposed by Dey et al. (Dey et al. 2015) as to whether the mapper  converges to the Reeb space in the limit.
Revised:  An open question has been proposed by Dey et al. as to whether the mapper converges to the Reeb space in the limit.
Edit intent: clarity
Original:  An open question has been proposed by Dey et al. (Dey et al. 2015) as to whether the mapper  converges to the Reeb space in the limit.
Revised:  An open question has been proposed by Dey et al. (Dey et al. 2015) as to whether the mapper construction converges to the Reeb space in the limit.
Edit intent: clarity
Original:  In particular, for any \gamma \leq 1 + O(\log n/n) and any constant C > 0 , we obtain an efficient dimension-preserving reduction from \gamma^{ C n/\log n  }-SVP to \gamma-GapSVP and an efficient dimension-preserving reduction from \gamma^{ Cn }-CVP to \gamma-GapCVP.
Revised:  In particular, for any \gamma \leq 1 + O(\log n/n) , we obtain an efficient dimension-preserving reduction from \gamma^{ C n/\log n }-SVP to \gamma-GapSVP and an efficient dimension-preserving reduction from \gamma^{ Cn }-CVP to \gamma-GapCVP.
Edit intent: clarity
Original:  In particular, for any \gamma \leq 1 + O(\log n/n) and any constant C > 0 , we obtain an efficient dimension-preserving reduction from \gamma^{ C n/\log n  }-SVP to \gamma-GapSVP and an efficient dimension-preserving reduction from \gamma^{ Cn }-CVP to \gamma-GapCVP.
Revised:  In particular, for any \gamma \leq 1 + O(\log n/n) and any constant C > 0 , we obtain an efficient dimension-preserving reduction from \gamma^{ C n/\log n ) }-SVP to \gamma-GapSVP and an efficient dimension-preserving reduction from \gamma^{ Cn }-CVP to \gamma-GapCVP.
Edit intent: fluency
Original:  Indeed, the SVP result is actually slightly stronger, as we obtain a reduction to \gamma-unique SVP for the same values of \gamma , a potentially easier problem  .
Revised:  Indeed, the SVP result is actually slightly stronger, as we obtain a reduction to \gamma-unique SVP , a potentially easier problem .
Edit intent: clarity
Original:  We show NP-hardness (under randomized reductions) for any \gamma \leq 1+O(\log n/n), improving on Aggarwal and Dubey, who showed hardness for \gamma \leq 1 + 1/n^{C ^* } for some large unspecified constant C ^* . And, we obtain an efficient dimension-preserving reduction from n-CVP to \gamma-unique SVP (or \gamma-GapSVP), again for any \gamma \leq 1 + O(\log n/n).
Revised:  We show NP-hardness (under randomized reductions) for any \gamma \leq 1+O(\log n/n), improving on Aggarwal and Dubey, who showed hardness for \gamma \leq 1 + 1/n^{C } for some large unspecified constant C ^* . And, we obtain an efficient dimension-preserving reduction from n-CVP to \gamma-unique SVP (or \gamma-GapSVP), again for any \gamma \leq 1 + O(\log n/n).
Edit intent: fluency
Original:  We show NP-hardness (under randomized reductions) for any \gamma \leq 1+O(\log n/n), improving on Aggarwal and Dubey, who showed hardness for \gamma \leq 1 + 1/n^{C ^* } for some large unspecified constant C ^* . And, we obtain an efficient dimension-preserving reduction from n-CVP to \gamma-unique SVP (or \gamma-GapSVP), again for any \gamma \leq 1 + O(\log n/n).
Revised:  We show NP-hardness (under randomized reductions) for any \gamma \leq 1+O(\log n/n), improving on Aggarwal and Dubey, who showed hardness for \gamma \leq 1 + 1/n^{C ^* } for some large unspecified constant C . And, we obtain an efficient dimension-preserving reduction from n-CVP to \gamma-unique SVP (or \gamma-GapSVP), again for any \gamma \leq 1 + O(\log n/n).
Edit intent: fluency
Original:  These results generalize the known equivalence of the search and decision versions of these problems in the exact case when \gamma = 1. Both of these efficient reductions follow from more general dimension-preserving reductions whose running times depend on the search and decision approximation factors.
Revised:  These results generalize the known equivalences of the search and decision versions of these problems in the exact case when \gamma = 1. Both of these efficient reductions follow from more general dimension-preserving reductions whose running times depend on the search and decision approximation factors.
Edit intent: fluency
Original:  Across a wide range of pages, we discover a bursty war/peace structure where the systems can become trapped---sometimes for months---in a computational subspace associated with high levels of rapid-fire conflict . Distinct patterns of behavior sustain the low-conflict subspace, including tit-for-tat reversion.
Revised:  Across a wide range of pages, we discover a bursty war/peace structure where the systems can become trapped---sometimes for months---in a computational subspace associated with high levels of rapid-fire conflict . Distinct patterns of behavior characterize the lower-conflict subspace, including tit-for-tat reversion.
Edit intent: clarity
Original:  While a fraction of the transitions between these subspaces are associated with top-down actions taken by administrators, the effects are weak and of uncertain valence . Surprisingly, we find no statistical signal that transitions are associated with the appearance of particularly anti-social users, and only weak association with significant news events outside the system.
Revised:  While a fraction of the transitions between these subspaces are associated with top-down actions taken by administrators, the effects are weak . Surprisingly, we find no statistical signal that transitions are associated with the appearance of particularly anti-social users, and only weak association with significant news events outside the system.
Edit intent: clarity
Original:  The majority of transitions between high and low conflict states appear to be driven by decentralized processes with no clear locus of control.
Revised:  These findings are consistent with transitions being driven by decentralized processes with no clear locus of control.
Edit intent: clarity
Original:  Across a wide range of pages, we discover a bursty war/peace structure where the systems can become trapped---sometimes for months---in a computational subspace associated with significantly higher levels of conflict-tracking "revert" actions.
Revised:  Across a wide range of pages, we discover a bursty war/peace structure where the systems can become trapped, sometimes for months, in a computational subspace associated with significantly higher levels of conflict-tracking "revert" actions.
Edit intent: fluency
Original:  The bistability we observe empirically may be a consequence of editor turn-over that drives the system to a critical point between them.
Revised:  The bistability we observe empirically may be a consequence of editor turn-over , which drives the system to a critical point between them.
Edit intent: fluency
Original:  We prove that the submodular cuts are facet-defining for the influence maximization problem under certain conditions.
Edit intent: coherence
Original:  Finally, we report our computational experiments , which show that our proposed algorithm outperforms the greedy algorithm for problems with a moderate number of scenarios .
Revised:  Finally, we report our computational experiments , which show that our proposed algorithm outperforms the greedy algorithm .
Edit intent: clarity
Original:   We propose a Benders decomposition algorithm to find the optimal solution to the problem with a finite number of samples.
Revised:  We propose a Benders decomposition algorithm to find the optimal solution to this class of problems with a finite number of samples.
Edit intent: clarity
Original: In animals, gas exchange between blood and tissues occurs in narrow vessels, whose diameter is typically less than that of a red blood cell.
Revised: In animals, gas exchange between blood and tissues occurs in narrow vessels, whose diameter is comparable to that of a red blood cell.
Edit intent: clarity
Original:  Red blood cells must deform to squeeze through these narrow vessels  transiently blocking or occluding the vessels they pass through.
Revised:  Red blood cells must deform to squeeze through these narrow vessels , transiently blocking or occluding the vessels they pass through.
Edit intent: fluency
Original:  Using  models as well as direct observation, we show that these occlusive feedbacks are tuned throughout the trunk network to prevent the vessels closest to the heart from short-circuiting the network.
Revised:  Using mathematical models as well as direct observation, we show that these occlusive feedbacks are tuned throughout the trunk network to prevent the vessels closest to the heart from short-circuiting the network.
Edit intent: clarity
Original: For speech recognition, deep neural network (DNN ) have significantly improved the recognition accuracy in most of benchmark datasets and application domains.
Revised: For speech recognition, deep neural networks (DNNs ) have significantly improved the recognition accuracy in most of benchmark datasets and application domains.
Edit intent: clarity
Original:  However, compared to the conventional Gaussian mixture models (GMMs) , DNN-based acoustic models usually have much larger number of model parameters, making it challenging for their applications in resource constrained platforms, e.g.  mobile devices.
Revised:  However, compared to the conventional Gaussian mixture models , DNN-based acoustic models usually have much larger number of model parameters, making it challenging for their applications in resource constrained platforms, e.g. mobile devices.
Edit intent: clarity
Original:  However, compared to the conventional Gaussian mixture models (GMMs) , DNN-based acoustic models usually have much larger number of model parameters, making it challenging for their applications in resource constrained platforms, e.g.  mobile devices.
Revised:  However, compared to the conventional Gaussian mixture models (GMMs) , DNN-based acoustic models usually have much larger number of model parameters, making it challenging for their applications in resource constrained platforms, e.g. , mobile devices.
Edit intent: fluency
Original:  In this paper, we study the application of the recently proposed highway network to train small-footprint DNNs, which are thinner and deeper {\it  {\it   and have significantly smaller number of model parameters compared to conventional DNNs.
Revised:  In this paper, we study the application of the recently proposed highway network to train small-footprint DNNs, which are {\it {\it and have significantly smaller number of model parameters compared to conventional DNNs.
Edit intent: coherence
Original:  In this paper, we study the application of the recently proposed highway network to train small-footprint DNNs, which are thinner and deeper {\it  {\it   and have significantly smaller number of model parameters compared to conventional DNNs.
Revised:  In this paper, we study the application of the recently proposed highway network to train small-footprint DNNs, which are thinner and deeper {\it {\it , and have significantly smaller number of model parameters compared to conventional DNNs.
Edit intent: fluency
Original:  The architecture has been implemented on 3.09 mm2 core area in UMC 65 nm technology , capable of a throughput of 274 GOp/s at 369 GOp/s /Wwith an external memory bandwidth of just 525 MB /  s full-duplex - a decrease of more than 90\% from previous work .
Revised:  The architecture has been implemented on 3.09 mm2 core area in UMC 65 nm technology , capable of a throughput of 274 GOp/s at 369 GOp/s / s full-duplex - a decrease of more than 90\% from previous work .
Edit intent: clarity
Original:  The architecture has been implemented on 3.09 mm2 core area in UMC 65 nm technology , capable of a throughput of 274 GOp/s at 369 GOp/s /Wwith an external memory bandwidth of just 525 MB /  s full-duplex - a decrease of more than 90\% from previous work .
Revised:  The architecture has been implemented on 3.09 mm2 core area in UMC 65 nm technology , capable of a throughput of 274 GOp/s at 369 GOp/s /Wwith an external memory bandwidth of just 525 MB / s performance .
Edit intent: clarity
Original: A partial (k-1)-spread in PG(n-1,q) is a collection of (k-1)-dimensional subspaces with trivial intersection such that each point is covered exactly once.
Revised: A partial (k-1)-spread in PG(n-1,q) is a collection of (k-1)-dimensional subspaces with trivial intersection , i.e., each point is covered exactly once.
Edit intent: clarity
Original:  So far the maximum size of a partial (k-1)-spread in PG(n-1,q) was know for the cases n\equiv 0\pmod k, n\equiv 1\pmod k and n\equiv 2\pmod k with the additional requirements q=2 and k=3.
Revised:  So far the maximum size of a partial (k-1)-spread in PG(n-1,q) was known for the cases n\equiv 0\pmod k, n\equiv 1\pmod k and n\equiv 2\pmod k with the additional requirements q=2 and k=3.
Edit intent: fluency
Original:  The analysis is performed in the limit of small noise -- that is, we modulate the noise by a factor \varepsilon \searrow 0 -- and on a long time horizon.
Revised:  The analysis is performed in the limit of small noise - that is, we modulate the noise by a factor \varepsilon \searrow 0 -- and on a long time horizon.
Edit intent: fluency
Original:  The analysis is performed in the limit of small noise -- that is, we modulate the noise by a factor \varepsilon \searrow 0 -- and on a long time horizon.
Revised:  The analysis is performed in the limit of small noise -- that is, we modulate the noise by a factor \varepsilon \searrow 0 - and on a long time horizon.
Edit intent: fluency
Original: Recently an algorithm, was discovered, which separates points in n-dimension by planes in such a manner that no two points are left unseparated by at least one plane{[}1-3{]}.
Revised: Recently an algorithm, was discovered, which separates points in n-dimension by planes in such a manner that no two points are left un-separated by at least one plane{[}1-3{]}.
Edit intent: fluency
Original:  By using this new algorithm we show that there are two ways of classification by a neural network, for a large dimension feature space, both of which are non-iterative and deterministic and we apply both these methods to a classical pattern recognition problem  and present the results.
Revised:  By using this new algorithm we show that there are two ways of classification by a neural network, for a large dimension feature space, both of which are non-iterative and deterministic . To demonstrate the power of both these methods to a classical pattern recognition problem and present the results.
Edit intent: clarity
Original:  It is expected these methods will now be widely used for the training of neural networks for Deep Learning not only because of their non-iterative and deterministic nature but also because of their efficiency and speed and will supercede other classification methods which are iterative in nature and rely on error minimization.
Revised:  It is expected these methods will now be widely used for the training of neural networks for Deep Learning not only because of their non-iterative and deterministic nature but also because of their efficiency and speed and will supersede other classification methods which are iterative in nature and rely on error minimization.
Edit intent: fluency
Original:  We investigate whether the model is able to consistently reproduce the implied volatility of FX cross rates , once the single components are calibrated to univariate shifted lognormal mixture dynamics models  .
Revised:  We investigate whether the model is able to consistently reproduce the implied volatility of FX cross rates once the single components are calibrated to univariate shifted lognormal mixture dynamics models .
Edit intent: fluency
Original:  The simplicial depth  \sigma_P(q) of a point q is the number of d-simplices with vertices in P that contain q in their convex hulls.
Revised:  The simplicial depth , \sigma_P(q) of a point q is the number of d-simplices with vertices in P that contain q in their convex hulls.
Edit intent: fluency
Original:  The trivial solution requires O(n^{d+1}) time whereas it is generally believed that one cannot do better than O(n^{d-1}) . So far, no efficient approximation algorithms for computing simplicial depth are known .
Revised:  The trivial solution requires O(n^{d+1}) time whereas it is generally believed that one cannot do better than O(n^{d-1}) .
Edit intent: coherence
Original:  To generalise two-component feedback loops to symplectic manifolds in this paper we introduce and study the properties of deformed Hamiltonian vector fields on Lagrangian fibrations.
Revised:  To generalise TCFLs to symplectic manifolds in this paper we introduce and study the properties of deformed Hamiltonian vector fields on Lagrangian fibrations.
Edit intent: clarity
Original:  We describe why these objects have some interesting applications to symplectic geometry and discuss how their physical interpretation motivates new problems in Floer theory, mirror symmetry, and the study of D-K\"{a .
Revised:  We describe why these objects have some interesting applications to symplectic geometry and discuss how their physical interpretation motivates new problems in mathematics .
Edit intent: clarity
Original: In this preliminary study, we examine whether random samples from within given Library of Congress Classification Outline areasyield significantly different topic models.
Revised: In this preliminary study, we test the sensitivity of the topic models to the sampling process by taking random samples of books in the Hathi Trust Digital Library within different Library of Congress Classification Outline areasyield significantly different topic models.
Edit intent: clarity
Original: This technical report consists of two components: an administrative report for the HathiTrust Research Center (HTRC) Advanced Collaborative Support (ACS) program and a research report on the variance of topic models trained over random samples of books in the Hathi Trust.
Edit intent: coherence
Original:  In this study, we test the sensitivity of the topic models to the sampling process by taking random samples of books in the Hathi Trust Digital Library within different Library of Congress Classification (LCC) areas .
Revised:  In this study, we test the sensitivity of the topic models to the sampling process by taking random samples of books in the Hathi Trust Digital Library from different areas of the Library of Congress Classification (LCC) areas .
Edit intent: clarity
Original:  In this study, we test the sensitivity of the topic models to the sampling process by taking random samples of books in the Hathi Trust Digital Library within different Library of Congress Classification (LCC) areas .
Revised:  In this study, we test the sensitivity of the topic models to the sampling process by taking random samples of books in the Hathi Trust Digital Library within different Library of Congress Classification Outline .
Edit intent: clarity
Original:  However, the decomposition of these measures by sample size differs by field and by number of topics  .
Revised:  However, the decomposition of these measures by sample size differs by number of topics .
Edit intent: clarity
Original: Human behaviour is largely shaped by local social interactions and depends on the structure of connections between individuals in social networks .
Revised: Large-scale transitions in societies are associated with both individual behavioural change and restructuring of the social network .
Edit intent: clarity
Original:  Our simulations corroborate empirical findings: we found a reduced prevalence of smoking . Remaining smokers were suffering from reduced influence in the network and were preferentially connected to other smokers.
Revised:  Our simulations corroborate empirical findings: The prevalence of smoking . Remaining smokers were suffering from reduced influence in the network and were preferentially connected to other smokers.
Edit intent: clarity
Original:  Our results thus suggest a generative mechanism for the co-evolution of individual behaviour and social network structure .
Revised:  Our results thus suggest a generative mechanism for co-evolution of individual behaviour and social network structure .
Edit intent: fluency
Original:  Because these algorithms are implemented in hardwaretoday, they cannot be changed after being built.
Revised:  Because these algorithms cannot be changed after being built.
Edit intent: clarity
Original:  This paper presents Domino, a C-like imperative language to express data-plane algorithms . Domino introduces the notion of a packet transaction , defined as a sequential code block that is atomic and isolated from other such code blocks.
Revised:  This paper presents Domino, a C-like imperative language to express data-plane algorithms . Domino introduces the notion of a packet transaction : a sequential code block that is atomic and isolated from other such code blocks.
Edit intent: coherence