wanyu/IteraTeR_v2 huggingface dataset:
Original:  One of the critical challenges facing interacting with IoT devices is addressing billions of devices (things) around the world, including computers, tablets, smartphones, wearable devices, sensors, and embedded computers, etc.
Revised:  One of the critical challenges facing interacting with IoT devices is to address billions of devices (things) around the world, including computers, tablets, smartphones, wearable devices, sensors, and embedded computers, etc.
Edit intent: fluency
Original:  This paper provides a survey on subjecting EPC and non-ID objects to IP identification for IoT devices, including their advantages and disadvantages thereof.
Revised:  This paper provides a survey on subjecting Electronic Product Code and non-ID objects to IP identification for IoT devices, including their advantages and disadvantages thereof.
Edit intent: clarity
Original:  Metrics are proposed and used for evaluating these methods.
Revised:  Different metrics are here proposed and used for evaluating these methods.
Edit intent: clarity
Original:  These major methods are evaluated in terms of their: (i) computational overhead, (ii) scalability, (iii) adaptability, (iv) implementation cost, and (v) whether applicable to already ID-based objects and presented in tabular format.
Revised:  In particular, the main methods are evaluated in terms of their: (i) computational overhead, (ii) scalability, (iii) adaptability, (iv) implementation cost, and (v) whether applicable to already ID-based objects and presented in tabular format.
Edit intent: clarity
Original:  The paper concludes with the fact that this field of research will still be ongoing, but any new technique must  offer the mentioned five evaluative parameters favorably .
Revised:  Finally, the article proves that this field of research will still be ongoing, but any new technique must offer the mentioned five evaluative parameters favorably .
Edit intent: clarity
Original:  The paper concludes with the fact that this field of research will still be ongoing, but any new technique must  offer the mentioned five evaluative parameters favorably .
Revised:  The paper concludes with the fact that this field of research will still be ongoing, but any new technique must favorably offer the mentioned five evaluative parameters favorably .
Edit intent: coherence
Original:  The paper concludes with the fact that this field of research will still be ongoing, but any new technique must  offer the mentioned five evaluative parameters favorably .
Revised:  The paper concludes with the fact that this field of research will still be ongoing, but any new technique must offer the mentioned five evaluative parameters .
Edit intent: clarity
Original:  In particular, cells have been shown to reorient under such perturbations, aligning at specific angles with respect to the stretching direction that depends strongly on the type of cell .
Revised:  In particular, cells have been shown to reorient in a direction that depends strongly on the type of cell .
Edit intent: clarity
Original:  In particular, cells have been shown to reorient under such perturbations, aligning at specific angles with respect to the stretching direction that depends strongly on the type of cell .
Revised:  In particular, cells have been shown to reorient under such perturbations, aligning at specific angles with respect to the stretching direction that depends not only on the type of cell .
Edit intent: clarity
Original: In this paper, we study the interactions between query reformulation and retrieval model relevance estimationin a game theoretical framework.
Revised: In this paper, we study jointly query reformulation and retrieval model relevance estimationin a game theoretical framework.
Edit intent: clarity
Original:  Under the proposed strategic game of information retrieval (IR)  , a query formulator, as one of the players, taking actions to produce the optimal query, is expected to maximize its own utility with respect to the relevance estimation of documents produced by the other player, a retrieval modeler;
Revised:  Under the proposed strategic game of information retrieval (IR) , a query formulator, taking actions to produce the optimal query, is expected to maximize its own utility with respect to the relevance estimation of documents produced by the other player, a retrieval modeler;
Edit intent: clarity
Original:  Their equilibrium or equilibria will be reached when both are the best response to each other.
Revised:  Their equilibrium or equilibria will be reached when both are the best responses to each other.
Edit intent: fluency
Original:  We derive our equilibrium theory of IR using normal-form representations: when a standard relevance feedback algorithm is coupled with a retrieval model, they  share the same objective function and thus would form a partnership game;
Revised:  We derive our equilibrium theory of IR using normal-form representations: when a standard relevance feedback algorithm is coupled with a retrieval model, they would share the same objective function and thus would form a partnership game;
Edit intent: fluency
Original:  We derive our equilibrium theory of IR using normal-form representations: when a standard relevance feedback algorithm is coupled with a retrieval model, they  share the same objective function and thus would form a partnership game;
Revised:  We derive our equilibrium theory of IR using normal-form representations: when a standard relevance feedback algorithm is coupled with a retrieval model, they share the same objective function and thus form a partnership game;
Edit intent: clarity
Original:  by contrast, pseudo relevance feedback pursues a rather different objective than that of retrieval models, therefore the interactions between them would lead to a general-sum game (though implicitly collaborative).
Revised:  by contrast, pseudo relevance feedback pursues a rather different objective than that of retrieval models, therefore the interaction between them would lead to a general-sum game (though implicitly collaborative).
Edit intent: coherence
Original:  Our game theoretical analyses not only yield useful insights into the two major aspects of IR, but also offer new practical algorithms for achieving the equilibrium state of retrieval which have been shown to bring consistent performance improvements in both text retrieval and item recommendation applications .
Revised:  Our game-theoretical analyses not only yield useful insights into the two major aspects of IR, but also offer new practical algorithms for achieving the equilibrium state of retrieval which have been shown to bring consistent performance improvements in both text retrieval and item recommendation applications .
Edit intent: fluency
Original:  Our game theoretical analyses not only yield useful insights into the two major aspects of IR, but also offer new practical algorithms for achieving the equilibrium state of retrieval which have been shown to bring consistent performance improvements in both text retrieval and item recommendation applications .
Revised:  Our game theoretical analyses not only yield useful insights into the two major aspects of IR, but also offer new practical algorithms for achieving the equilibrium state of retrieval which have been shown to bring consistent performance improvements in both text retrieval and item recommendation .
Edit intent: clarity
Original: We present a simple and effective method for computing double- and single-layer potentials for Laplace's equation in three dimensions close to the boundary.
Revised: We present a simple and effective method for evaluating double-and single-layer potentials for Laplace's equation in three dimensions close to the boundary.
Edit intent: clarity
Original:  (ii) integrate first with respect to azimuth using the Periodic Trapezoid Rule, which is a natural averaging operation yielding a relatively smooth function of the  polar angle ;
Revised:  (ii) integrate first with respect to the polar angle ;
Edit intent: coherence
Original:  (ii) integrate first with respect to azimuth using the Periodic Trapezoid Rule, which is a natural averaging operation yielding a relatively smooth function of the  polar angle ;
Revised:  (ii) integrate first with respect to azimuth using the Periodic Trapezoid Rule, which is a natural averaging operation yielding a relatively smooth function of the the polar angle ;
Edit intent: fluency
Original:  and (iii) integrate with respect to the polar angle ( rather than the cosine of the polar angle ) using an open, Gauss-Legendre quadrature rule mapped to 0,\pi%DIFDELCMD < ]%%% . We find that the asymptotic behavior of the error for this method in the limit of small evaluation distance from the boundary is quadratic for the modified double-layer potential after applying a subtraction method to it, and linear for the single-layer potential.
Revised:  and (iii) integrate with respect to the polar angle ( rather than the cosine of the polar angle 0,\pi%DIFDELCMD < ]%%% . We find that the asymptotic behavior of the error for this method in the limit of small evaluation distance from the boundary is quadratic for the modified double-layer potential after applying a subtraction method to it, and linear for the single-layer potential.
Edit intent: clarity
Original:  and (iii) integrate with respect to the polar angle ( rather than the cosine of the polar angle ) using an open, Gauss-Legendre quadrature rule mapped to 0,\pi%DIFDELCMD < ]%%% . We find that the asymptotic behavior of the error for this method in the limit of small evaluation distance from the boundary is quadratic for the modified double-layer potential after applying a subtraction method to it, and linear for the single-layer potential.
Revised:  and (iii) integrate with respect to the polar angle ( rather than the cosine of the polar angle ) using an open, Gauss-Legendre quadrature rule mapped to 0,\pi%DIFDELCMD < ]%%% . We find that the asymptotic behavior of the error for this method in the limit of small evaluation distance from the boundary , and the error is linear for the single-layer potential.
Edit intent: coherence
Original:  A 2N-point periodic trapezoid rule is used to compute the integral with respect to the azimuthal angle which becomes a natural and effective averaging operation in this coordinate system.
Revised:  A 2N-point periodic trapezoid rule is used to compute the integral with respect to the azimuthal angle which acts as a natural and effective averaging operation in this coordinate system.
Edit intent: clarity
Original:  In this paper, we provide a current picture of the rapidly evolving quantum computing landscape by comparing four software platforms--Forest (pyQuil), QISKit , ProjectQ, and the Quantum Developer Kit--that enable researchers to use real and simulated quantum devices.
Revised:  In this paper, we provide a current picture of the rapidly evolving quantum computing landscape by comparing four software platforms---Forest (pyQuil), QISKit , ProjectQ, and the Quantum Developer Kit--that enable researchers to use real and simulated quantum devices.
Edit intent: fluency
Original:  In this paper, we provide a current picture of the rapidly evolving quantum computing landscape by comparing four software platforms--Forest (pyQuil), QISKit , ProjectQ, and the Quantum Developer Kit--that enable researchers to use real and simulated quantum devices.
Revised:  In this paper, we provide a current picture of the rapidly evolving quantum computing landscape by comparing four software platforms--Forest (pyQuil), Qiskit , ProjectQ, and the Quantum Developer Kit--that enable researchers to use real and simulated quantum devices.
Edit intent: fluency
Original:  In this setting, we study a novel problem ofsocial welfare maximization : given item budgets, find an optimal allocation of items to seed nodes that maximizes the sum of expected utilities derived by users when the diffusion terminates .
Revised:  In this setting, we study a novel problem ofsocial welfare maximization formulate the problem of social welfare maximization in this novel setting .
Edit intent: clarity
Original:  We show the expected social welfare is monotone but neither submodular nor supermodular .
Revised:  We show that while the objective function is neither submodular nor supermodular .
Edit intent: clarity
Original:  Nevertheless, we show that a simple greedy allocation can ensure a (1-1/e-\epsilon) -approximation to the optimum .
Revised:  Nevertheless, we show that a simple greedy allocation algorithm achieves a factor of (1-1/e-\epsilon) -approximation to the optimum .
Edit intent: clarity
Original:  With extensive experiments on real and synthetic datasets, we show that our algorithm significantly outperforms all the baselines.
Revised:  With extensive experiments on real and synthetic datasets, that it significantly outperforms all the baselines.
Edit intent: clarity
Original:  With extensive experiments on real and synthetic datasets, we show that our algorithm significantly outperforms all the baselines.
Revised:  With extensive experiments on real and synthetic datasets, we show that our algorithm significantly outperforms all baselines.
Edit intent: fluency
Original:  The efficiency of all algorithms is demonstrated on a number of numerical examples, and we achieve up to more than an order of magnitude higher compression ratios than previous approaches to using the tensor ring format.
Revised:  The efficiency of all algorithms is demonstrated on a number of numerical examples, and in certain cases, we demonstrate significantly higher compression ratios than previous approaches to using the tensor ring format.
Edit intent: clarity
Original:  The efficiency of all algorithms is demonstrated on a number of numerical examples, and we achieve up to more than an order of magnitude higher compression ratios than previous approaches to using the tensor ring format.
Revised:  The efficiency of all algorithms is demonstrated on a number of numerical examples, and we achieve up to more than an order of magnitude higher compression ratios when compared to previous approaches to using the tensor ring format.
Edit intent: clarity
Original: An adversarial machine learning approach is introduced to launch jamming attacks on wireless communications and a defense strategy is provided .
Revised: An adversarial machine learning approach is introduced to launch jamming attacks on wireless communications and a defense strategy is presented .
Edit intent: clarity
Original:  A cognitive transmitter uses a pre-trained classifier to predict  current channel status based on recent sensing results and decides whether to transmit or not, whereas a jammer collects channel status and ACKs to build a deep learning classifier that reliably predicts whether there will be a successful transmission next and effectively jams these transmissions .
Revised:  A cognitive transmitter uses a pre-trained classifier to predict the current channel status based on recent sensing results and decides whether to transmit or not, whereas a jammer collects channel status and ACKs to build a deep learning classifier that reliably predicts whether there will be a successful transmission next and effectively jams these transmissions .
Edit intent: fluency
Original:  A cognitive transmitter uses a pre-trained classifier to predict  current channel status based on recent sensing results and decides whether to transmit or not, whereas a jammer collects channel status and ACKs to build a deep learning classifier that reliably predicts whether there will be a successful transmission next and effectively jams these transmissions .
Revised:  A cognitive transmitter uses a pre-trained classifier to predict current channel status based on recent sensing results and decides whether to transmit or not, whereas a jammer collects channel status and ACKs to build a deep learning classifier that reliably predicts the next successful transmissions and effectively jams these transmissions .
Edit intent: clarity
Original:  A cognitive transmitter uses a pre-trained classifier to predict  current channel status based on recent sensing results and decides whether to transmit or not, whereas a jammer collects channel status and ACKs to build a deep learning classifier that reliably predicts whether there will be a successful transmission next and effectively jams these transmissions .
Revised:  A cognitive transmitter uses a pre-trained classifier to predict current channel status based on recent sensing results and decides whether to transmit or not, whereas a jammer collects channel status and ACKs to build a deep learning classifier that reliably predicts whether there will be a successful transmission next and effectively jams them .
Edit intent: clarity
Original:  This jamming approach is shown to reduce the performance of the transmitter much more severely compared with randomized or sensing-based jamming.
Revised:  This jamming approach is shown to reduce the transmitter's performance much more severely compared with randomized or sensing-based jamming.
Edit intent: clarity
Original:  This jamming approach is shown to reduce the performance of the transmitter much more severely compared with randomized or sensing-based jamming.
Revised:  This jamming approach is shown to reduce the performance of the transmitter much more severely compared with random or sensing-based jamming.
Edit intent: fluency
Original:  Then, a defense scheme is introduced for the transmitter that prevents the jammer from building a reliable classifier by deliberately taking a small number of wrong actions  (in form of a causative attack launched against the jammer) when it accesses the spectrum .
Revised:  As a defense scheme is introduced for the transmitter that prevents the jammer from building a reliable classifier by deliberately taking a small number of wrong actions (in form of a causative attack launched against the jammer) when it accesses the spectrum .
Edit intent: fluency
Original:  Then, a defense scheme is introduced for the transmitter that prevents the jammer from building a reliable classifier by deliberately taking a small number of wrong actions  (in form of a causative attack launched against the jammer) when it accesses the spectrum .
Revised:  Then, a defense scheme , the transmitter deliberately takes a small number of wrong actions (in form of a causative attack launched against the jammer) when it accesses the spectrum .
Edit intent: clarity
Original:  Then, a defense scheme is introduced for the transmitter that prevents the jammer from building a reliable classifier by deliberately taking a small number of wrong actions  (in form of a causative attack launched against the jammer) when it accesses the spectrum .
Revised:  Then, a defense scheme is introduced for the transmitter that prevents the jammer from building a reliable classifier by deliberately taking a small number of wrong actions (in form of a causative attack against the jammer) when it accesses the spectrum .
Edit intent: clarity
Original:  Then, a defense scheme is introduced for the transmitter that prevents the jammer from building a reliable classifier by deliberately taking a small number of wrong actions  (in form of a causative attack launched against the jammer) when it accesses the spectrum .
Revised:  Then, a defense scheme is introduced for the transmitter that prevents the jammer from building a reliable classifier by deliberately taking a small number of wrong actions (in form of a causative attack launched against the jammer) and therefore prevents the jammer from building a reliable classifier .
Edit intent: coherence
Original:  The transmitter systematically selects when to take wrong actions and adapts the level of defense to machine learning-based or conventional jamming behavior in order to mislead the jammer into making prediction errors and consequently increase its throughput.
Revised:  The transmitter systematically selects when to take wrong actions and adapts the level of defense to mislead the jammer into making prediction errors and consequently increase its throughput.
Edit intent: clarity
Original:  This makes all gradient-flow methods available for the analysis, which could previously not be used, as it was not known, whether a rigorous gradient flow formulation exists.
Revised:  This makes all gradient flow methods available for the analysis, which could previously not be used, as it was not known, whether a rigorous gradient flow formulation exists.
Edit intent: clarity
Original:  Uniqueness of invariant measures and ergodic properties for the associated Feller semigroups  are also discussed.
Revised:  Uniqueness of invariant measures , ergodic properties for the associated Feller semigroups are also discussed.
Edit intent: fluency
Original:  Evaluating the Hessian, H, of the loss function on these hypersurfaces, we observe 1) an unusual excess of the number of positive eigenvalues of H, and 2) a large value of Tr(H) / |  H|  at a well defined range of configuration space radii, corresponding to a thick, hollow, spherical shell we refer to as the Goldilocks zone.
Revised:  Evaluating the Hessian, H, of the loss function on these hypersurfaces, we observe 1) an unusual excess of the number of positive eigenvalues of H, and 2) a large value of Tr(H) / | | H| at a well defined range of configuration space radii, corresponding to a thick, hollow, spherical shell we refer to as the Goldilocks zone.
Edit intent: fluency
Original:  Evaluating the Hessian, H, of the loss function on these hypersurfaces, we observe 1) an unusual excess of the number of positive eigenvalues of H, and 2) a large value of Tr(H) / |  H|  at a well defined range of configuration space radii, corresponding to a thick, hollow, spherical shell we refer to as the Goldilocks zone.
Revised:  Evaluating the Hessian, H, of the loss function on these hypersurfaces, we observe 1) an unusual excess of the number of positive eigenvalues of H, and 2) a large value of Tr(H) / | H| | at a well defined range of configuration space radii, corresponding to a thick, hollow, spherical shell we refer to as the Goldilocks zone.
Edit intent: fluency
Original:  We observe this effect for fully-connected neural networks over a range of network widths and depths on MNIST and CIFAR-10  with the ReLU non-linearity.
Revised:  We observe this effect for fully-connected neural networks over a range of network widths and depths on MNIST and CIFAR-10 datasets with the ReLU non-linearity.
Edit intent: clarity
Original:  Furthermore, we demonstrate that initializing a neural network at a number of points and selecting for high measures of local convexity such as Tr(H) / |  H|  , number of positive eigenvalues of H, or low initial loss, leads to statistically significantly faster training on MNIST.
Revised:  Furthermore, we demonstrate that initializing a neural network at a number of points and selecting for high measures of local convexity such as Tr(H) / | | H| , number of positive eigenvalues of H, or low initial loss, leads to statistically significantly faster training on MNIST.
Edit intent: fluency
Original:  Furthermore, we demonstrate that initializing a neural network at a number of points and selecting for high measures of local convexity such as Tr(H) / |  H|  , number of positive eigenvalues of H, or low initial loss, leads to statistically significantly faster training on MNIST.
Revised:  Furthermore, we demonstrate that initializing a neural network at a number of points and selecting for high measures of local convexity such as Tr(H) / | H| | , number of positive eigenvalues of H, or low initial loss, leads to statistically significantly faster training on MNIST.
Edit intent: fluency
Original:  Based on our observations, we hypothesize that the Goldilocks zone contains a high density of suitable initialization configurations.
Revised:  Based on our observations, we hypothesize that the Goldilocks zone contains an unusually high density of suitable initialization configurations.
Edit intent: clarity