wanyu/IteraTeR_v2 huggingface dataset:
Original:  Ground truth experiments showed sensor timing as accurate as 0.8 \mu s and as precise as 0.1 \mu s with localization rates of 1 kHz.
Revised:  Ground truth experiments showed sensor timing as accurate as 0.8 s and as precise as 0.1 \mu s with localization rates of 1 kHz.
Edit intent: fluency
Original:  Ground truth experiments showed sensor timing as accurate as 0.8 \mu s and as precise as 0.1 \mu s with localization rates of 1 kHz.
Revised:  Ground truth experiments showed sensor timing as accurate as 0.8 \mu us and as precise as 0.1 \mu s with localization rates of 1 kHz.
Edit intent: fluency
Original:  Ground truth experiments showed sensor timing as accurate as 0.8 \mu s and as precise as 0.1 \mu s with localization rates of 1 kHz.
Revised:  Ground truth experiments showed sensor timing as accurate as 0.8 \mu s and as precise as 0.1 s with localization rates of 1 kHz.
Edit intent: fluency
Original:  Ground truth experiments showed sensor timing as accurate as 0.8 \mu s and as precise as 0.1 \mu s with localization rates of 1 kHz.
Revised:  Ground truth experiments showed sensor timing as accurate as 0.8 \mu s and as precise as 0.1 \mu us with localization rates of 1 kHz.
Edit intent: fluency
Original:  dependencies between random variables and to make probabilistic inferences about events on a space of ``possible worlds'' . The set of possible worlds with underlying domain D (a set of objects) can be represented by the set W_D of all first-order structures (for a suitable signature) with domain D. Using a formal logic we can describe events on W_D.
Revised:  dependencies between random variables and to make probabilistic inferences about events on a space of "possible worlds" . The set of possible worlds with underlying domain D (a set of objects) can be represented by the set W_D of all first-order structures (for a suitable signature) with domain D. Using a formal logic we can describe events on W_D.
Edit intent: fluency
Original:  The convergence result is obtained by showing that every formula \varphi(x_1, \ldots, x_k) which contains only ``admissible'' aggregation functions (e.g. arithmetic and geometric mean, max and min) is asymptotically equivalent to a formula \psi(x_1, \ldots, x_k) without aggregation functions.
Revised:  The convergence result is obtained by showing that every formula \varphi(x_1, \ldots, x_k) which contains only "admissible" aggregation functions (e.g. arithmetic and geometric mean, max and min) is asymptotically equivalent to a formula \psi(x_1, \ldots, x_k) without aggregation functions.
Edit intent: fluency
Original:  However, integrating devices from many different vendors into an end-to-end automation system is complicated due to the diversity of protocols .
Revised:  However, integrating devices from many different vendors into an end-to-end automation system is complicated due to the diversity of interfaces .
Edit intent: clarity
Original:  Therefore, various approaches for standardization have been considered , and a concept has been proposed for taking them a step further.
Revised:  Therefore, various approaches for standardization are considered in this article , and a concept has been proposed for taking them a step further.
Edit intent: coherence
Original:  Therefore, various approaches for standardization have been considered , and a concept has been proposed for taking them a step further.
Revised:  Therefore, various approaches for standardization have been considered , and a concept is proposed for taking them a step further.
Edit intent: coherence
Original:  This concept enables a mobile manipulator with a vision system to ``learn'' the pose of each device and - utilizing a barcode - fetch interface information from a universal cloud database.
Revised:  This concept enables a mobile manipulator with a vision system to "learn" the pose of each device and - utilizing a barcode - fetch interface information from a universal cloud database.
Edit intent: fluency
Original:  In this paper, we introduce a \textit{stochastic parareal algorithm with the aim of accelerating the convergence of the deterministic parareal algorithm.
Revised:  In this paper, we introduce a \textit{stochastic parareal algorithm with the aim of accelerating the convergence of the deterministic parareal algorithm.
Edit intent: fluency
Original:  Specifically, we give a (2-\Omega(1))-approximate algorithm with O( \sqrt{n\sqrt[8}%DIFDELCMD < ]{%%% m )=O(n^{3/4}) worst-case update time in n-node, m-edge graphs.
Revised:  Specifically, we give a (2-\Omega(1))-approximate algorithm with O( \sqrt{n\sqrt[8}%DIFDELCMD < ]{%%% m^{3/8 )=O(n^{3/4}) worst-case update time in n-node, m-edge graphs.
Edit intent: fluency
Original:  Our second result is the first deterministic (2+\epsilon)-approximate (weighted ) matching algorithm with O_\epsilon(1)\cdot O(\sqrt[4]{m}) = O_\epsilon(1)\cdot O(n) worst-case update time   .
Revised:  Our second result is the first deterministic (2+\epsilon)-approximate weighted matching algorithm with O_\epsilon(1)\cdot O(\sqrt[4]{m}) = O_\epsilon(1)\cdot O(n) worst-case update time .
Edit intent: fluency
Original:  Our second result is the first deterministic (2+\epsilon)-approximate (weighted ) matching algorithm with O_\epsilon(1)\cdot O(\sqrt[4]{m}) = O_\epsilon(1)\cdot O(n) worst-case update time   .
Revised:  Our second result is the first deterministic (2+\epsilon)-approximate (weighted ) matching algorithm with O_\epsilon(1)\cdot O(\sqrt[4]{m}) = O_\epsilon(1)\cdot O(n) worst-case update time kernels .
Edit intent: fluency
Original:  Our second result is the first deterministic (2+\epsilon)-approximate (weighted ) matching algorithm with O_\epsilon(1)\cdot O(\sqrt[4]{m}) = O_\epsilon(1)\cdot O(n) worst-case update time   .
Revised:  Our second result is the first deterministic (2+\epsilon)-approximate (weighted ) matching algorithm with O_\epsilon(1)\cdot O(\sqrt[4]{m}) = O_\epsilon(1)\cdot O(n) worst-case update time recourse .
Edit intent: fluency
Original:  We evaluate our process using three metrics: quantitative metrics with human evaluations that score output adherence to a target value, and toxicity scoring on outputs;
Revised:  We evaluate our process using three metrics: quantitative metrics with human evaluations that score output adherence to a target value, toxicity scoring on outputs;
Edit intent: fluency
Original:  We also find that when we compare our time-dependent mean-field model to the SIR model with identical rates, the epidemic peak is advanced and more pronounced and modifying the infection rate function has a strong effect on the time dynamics of the epidemic.
Revised:  When we compare our time-dependent mean-field model to the SIR model with identical rates, the epidemic peak is advanced and more pronounced and modifying the infection rate function has a strong effect on the time dynamics of the epidemic.
Edit intent: coherence
Original:  We also find that when we compare our time-dependent mean-field model to the SIR model with identical rates, the epidemic peak is advanced and more pronounced and modifying the infection rate function has a strong effect on the time dynamics of the epidemic.
Revised:  We also find that when we compare our time-dependent mean-field model to the SIR model with equivalent rates, the epidemic peak is advanced and more pronounced and modifying the infection rate function has a strong effect on the time dynamics of the epidemic.
Edit intent: clarity
Original:  We also find that when we compare our time-dependent mean-field model to the SIR model with identical rates, the epidemic peak is advanced and more pronounced and modifying the infection rate function has a strong effect on the time dynamics of the epidemic.
Revised:  We also find that when we compare our time-dependent mean-field model to the SIR model with identical rates, the epidemic peak is advanced and modifying the infection rate function has a strong effect on the time dynamics of the epidemic.
Edit intent: clarity
Original:  Lastly, we explore the effect of social and pharmaceutical interventions on our theoretical framework .
Revised:  We also observe behavior akin to a traveling wave as individuals transition through infectious states .
Edit intent: clarity
Original:  We compare the average and individual reproductive numbers , epidemic dynamics , and intervention strategies for a model incorporating time-dependent infectiousness and a standard SIR model for both fully-mixed and category-mixed populations.
Revised:  We compare the average and individual reproductive numbers and epidemic dynamics for a model incorporating time-dependent infectiousness and a standard SIR model for both fully-mixed and category-mixed populations.
Edit intent: clarity
Original: Some variants of the (block) Gauss-Seidel iteration for the solution of linear systems with M-matrices in (block) Hessenberg form are discussed.
Revised: Some variants of the (block) Gauss--Seidel iteration for the solution of linear systems with M-matrices in (block) Hessenberg form are discussed.
Edit intent: fluency
Original:  Comparison results for the asymptotic convergence rate of some regular splittings are derived: in particular, we prove that for a lower-Hessenberg M-matrix \rho(P_{GS})\geq \rho(P_S)\geq \rho(P_{AGS}), where P_{GS}, P_S, P_{AGS} are the iteration matrices of the Gauss-Seidel , staircase, and anti-Gauss-Seidel method.
Revised:  Comparison results for the asymptotic convergence rate of some regular splittings are derived: in particular, we prove that for a lower-Hessenberg M-matrix \rho(P_{GS})\geq \rho(P_S)\geq \rho(P_{AGS}), where P_{GS}, P_S, P_{AGS} are the iteration matrices of the Gauss--Seidel , staircase, and anti-Gauss-Seidel method.
Edit intent: fluency
Original:  Comparison results for the asymptotic convergence rate of some regular splittings are derived: in particular, we prove that for a lower-Hessenberg M-matrix \rho(P_{GS})\geq \rho(P_S)\geq \rho(P_{AGS}), where P_{GS}, P_S, P_{AGS} are the iteration matrices of the Gauss-Seidel , staircase, and anti-Gauss-Seidel method.
Revised:  Comparison results for the asymptotic convergence rate of some regular splittings are derived: in particular, we prove that for a lower-Hessenberg M-matrix \rho(P_{GS})\geq \rho(P_S)\geq \rho(P_{AGS}), where P_{GS}, P_S, P_{AGS} are the iteration matrices of the Gauss-Seidel , staircase, and anti-Gauss--Seidel method.
Edit intent: fluency
Original: The univariate Kolmogorov-Smirnov (KS) test is a non-parametric statistical test designed to assess whether a set of data is consistent with a given probability distribution (or, in the two-sample case, whether the two samples come from the same underlying distribution ) .
Revised: The univariate Kolmogorov-Smirnov (KS) test is a non-parametric statistical test designed to assess whether two samples come from the same underlying distribution ) .
Edit intent: clarity
Original: The univariate Kolmogorov-Smirnov (KS) test is a non-parametric statistical test designed to assess whether a set of data is consistent with a given probability distribution (or, in the two-sample case, whether the two samples come from the same underlying distribution ) .
Revised: The univariate Kolmogorov-Smirnov (KS) test is a non-parametric statistical test designed to assess whether a set of data is consistent with a given probability distribution (or, in the two-sample case, whether the two samples come from the same underlying distribution .
Edit intent: fluency
Original:  The versatility of the KS test has made it a cornerstone of statistical analysis and is commonly used across the scientific disciplines.
Revised:  The versatility of the KS test has made it a cornerstone of statistical analysis across the scientific disciplines.
Edit intent: coherence
Original:  Empirically, PlaLaM outperforms existing path planning methods in 2D navigation tasks, especially in the presence of difficult-to-escape local optima, and shows benefits when plugged into  model-based RL with planning components such as PETS.
Revised:  Empirically, PlaLaM outperforms existing path planning methods in 2D navigation tasks, especially in the presence of difficult-to-escape local optima, and shows benefits when plugged into the planning components of model-based RL with planning components such as PETS.
Edit intent: clarity
Original:  Empirically, PlaLaM outperforms existing path planning methods in 2D navigation tasks, especially in the presence of difficult-to-escape local optima, and shows benefits when plugged into  model-based RL with planning components such as PETS.
Revised:  Empirically, PlaLaM outperforms existing path planning methods in 2D navigation tasks, especially in the presence of difficult-to-escape local optima, and shows benefits when plugged into model-based RL such as PETS.
Edit intent: clarity
Original:  We evaluate EvoGrad on two substantial recent meta-learning applications, namely cross-domain few-shot learning with feature-wise transformations and noisy label learning with MetaWeightNet .
Revised:  We evaluate EvoGrad on two substantial recent meta-learning applications, namely cross-domain few-shot learning with feature-wise transformations , noisy label learning with MetaWeightNet .
Edit intent: fluency
Original:  The results show that EvoGrad significantly improves efficiency and enables scaling meta-learning to bigger CNN architectures such as from ResNet18 to ResNet34.
Revised:  The results show that EvoGrad significantly improves efficiency and enables scaling meta-learning to bigger architectures such as from ResNet18 to ResNet34.
Edit intent: clarity
Original: The insertion-delation codes was motivated to correct the synchronization errors.
Revised: The insertion-deletion codes was motivated to correct the synchronization errors.
Edit intent: fluency
Original:  Several new Singleton type upper bounds for the insertion-deletion distances were proved for linear codes over a general finite field%DIFDELCMD < {\bf %%% F _q in 2021.
Revised:  %DIFDELCMD < {\bf %%% F _q in 2021.
Edit intent: coherence
Original:  Several new Singleton type upper bounds for the insertion-deletion distances were proved for linear codes over a general finite field%DIFDELCMD < {\bf %%% F _q in 2021.
Revised:  Several new Singleton type upper bounds for the insertion-deletion distances were proved for linear codes over a general finite field%DIFDELCMD < {\bf %%% _q in 2021.
Edit intent: clarity
Original:  It is a open problem if there exists a sequence of linear%DIFDELCMD < [%%% n_t, k_t _q codes over%DIFDELCMD < {\bf %%% F _q with insdel distances d_t and the lengths n_t go to the infinity, such that t \longrightarrow \infty k_t{n_t \geq 1{2}, and t \longrightarrow \infty d_t{2n_t}>0.
Revised:  It is a open problem if there exists a sequence of linear%DIFDELCMD < [%%% n_t, k_t %DIFDELCMD < {\bf %%% F _q with insdel distances d_t and the lengths n_t go to the infinity, such that t \longrightarrow \infty k_t{n_t \geq 1{2}, and t \longrightarrow \infty d_t{2n_t}>0.
Edit intent: clarity
Original:  It is a open problem if there exists a sequence of linear%DIFDELCMD < [%%% n_t, k_t _q codes over%DIFDELCMD < {\bf %%% F _q with insdel distances d_t and the lengths n_t go to the infinity, such that t \longrightarrow \infty k_t{n_t \geq 1{2}, and t \longrightarrow \infty d_t{2n_t}>0.
Revised:  It is a open problem if there exists a sequence of linear%DIFDELCMD < [%%% n_t, k_t _q codes over%DIFDELCMD < {\bf %%% _q with insdel distances d_t and the lengths n_t go to the infinity, such that t \longrightarrow \infty k_t{n_t \geq 1{2}, and t \longrightarrow \infty d_t{2n_t}>0.
Edit intent: clarity
Original:  } In this paper we give some new Singleton type upper bounds for the insertion-deletion distances for linear codes over%DIFDELCMD < {\bf %%% F _q, which are much stronger than the previous bounds.
Revised:  } In this paper we prove several Singleton type upper bounds for the insertion-deletion distances for linear codes over%DIFDELCMD < {\bf %%% F _q, which are much stronger than the previous bounds.
Edit intent: clarity
Original:  } In this paper we give some new Singleton type upper bounds for the insertion-deletion distances for linear codes over%DIFDELCMD < {\bf %%% F _q, which are much stronger than the previous bounds.
Revised:  } In this paper we give some new Singleton type upper bounds for the insertion-deletion %DIFDELCMD < {\bf %%% F _q, which are much stronger than the previous bounds.
Edit intent: clarity
Original:  } In this paper we give some new Singleton type upper bounds for the insertion-deletion distances for linear codes over%DIFDELCMD < {\bf %%% F _q, which are much stronger than the previous bounds.
Revised:  } In this paper we give some new Singleton type upper bounds for the insertion-deletion distances for linear codes over%DIFDELCMD < {\bf %%% _q, which are much stronger than the previous bounds.
Edit intent: clarity
Original:  Hence over an arbitrary fixed finite field }%DIFDELCMD < {\bf %%% F _q linear codes of rate bigger than or equal to \frac{1{2} have very small insertion-delation error-correcting capabilities.
Revised:  Hence over an arbitrary fixed finite field }%DIFDELCMD < {\bf %%% _q linear codes of rate bigger than or equal to \frac{1{2} have very small insertion-delation error-correcting capabilities.
Edit intent: clarity
Original:  In this paper we prove several Singleton type upper bounds on the insdel distance of linear codes insertion-deletion codes, based on  generalized Hamming weights and the formation of minimum Hamming weight codewords.
Revised:  In this paper we prove several Singleton type upper bounds on the insdel distances of linear insertion-deletion codes, based on generalized Hamming weights and the formation of minimum Hamming weight codewords.
Edit intent: fluency
Original:  In this paper we prove several Singleton type upper bounds on the insdel distance of linear codes insertion-deletion codes, based on  generalized Hamming weights and the formation of minimum Hamming weight codewords.
Revised:  In this paper we prove several Singleton type upper bounds on the insdel distance of linear codes insertion-deletion codes, based on the generalized Hamming weights and the formation of minimum Hamming weight codewords.
Edit intent: fluency
Original:  We apply these upper bounds to some binary cyclic codes and binary Reed-Muller codes with any coordinate ordering, and some binary Reed-Muller codes and  algebraic-geometric codes with certain special coordinate ordering.
Revised:  We apply these upper bounds to some binary cyclic codes and binary Reed-Muller codes with any coordinate ordering, and some binary Reed-Muller codes and algebraic-geometric code with certain special coordinate ordering.
Edit intent: fluency
Original:  These upper bounds are valid for any fixed ordering of coordinate positions.
Revised:  Some or our upper bounds are valid for any fixed ordering of coordinate positions.
Edit intent: clarity
Original:  We apply these upper bounds to some binary cyclic codes and binary Reed-Muller codes with any coordinate ordering, and some binary Reed-Muller codes and one algebraic-geometric code with certain special coordinate ordering .
Revised:  We apply these upper bounds to some binary cyclic codes with any rearrangement of coordinate positions, binary Reed-Muller codes and one algebraic-geometric code with certain special coordinate ordering .
Edit intent: clarity
Original: The insertion-deletion codes was motivated to correct the synchronization errors.
Revised: The insertion-deletion codes were motivated to correct the synchronization errors.
Edit intent: fluency
Original:  In this paper we prove several Singleton type upper bounds on the insdel distances of linear insertion-deletion codes, based on the generalized Hamming weights and the formation of minimum Hamming weight codewords.
Revised:  In this paper we prove several Singleton type upper bounds on the insdel distances of linear codes, which are based on the generalized Hamming weights and the formation of minimum Hamming weight codewords.
Edit intent: coherence
Original:  Our bound are stronger than some previous known bounds.
Revised:  Our bounds are stronger than some previous known bounds.
Edit intent: fluency
Original:  Some or our upper bounds are valid for any fixed ordering of coordinate positions.
Edit intent: coherence
Original:  We apply these upper bounds to some binary cyclic codes with any rearrangement of coordinate positions , binary Reed-Muller codes and one algebraic-geometric code from elliptic curves .
Revised:  We apply these upper bounds to some cyclic codes and one algebraic-geometric code with any rearrangement of coordinate positions , binary Reed-Muller codes and one algebraic-geometric code from elliptic curves .
Edit intent: fluency
Original:  Note that the values of \Delta and \frac{1{n\gamma} increase as the dependence between items strengthens.
Revised:  Note that {n\gamma} increase as the dependence between items strengthens.
Edit intent: clarity
Original:  In the }  special case of independently distributed items, \Delta=0 and 1{n\gamma} \geq 1, and our results recover the known constant factor approximations for a XOS buyer.
Revised:  In the } in the special case of independently distributed items, \Delta=0 and 1{n\gamma} \geq 1, and our results recover the known constant factor approximations for a XOS buyer.
Edit intent: fluency
Original:  In the }  special case of independently distributed items, \Delta=0 and 1{n\gamma} \geq 1, and our results recover the known constant factor approximations for a XOS buyer.
Revised:  In the } special case of independently distributed items, \Delta=0 and 1{n\gamma} \leq 1, and our results recover the known constant factor approximations for a XOS buyer.
Edit intent: fluency
Original:  For collaborative filtering, the classical method is training the model offline, then perform the online testing, but this approach can no longer handle the dynamic changes in user preferences which is the so-called cold start .
Revised:  For collaborative filtering, the classical method is training the model offline, then perform the online testing, but this approach can no longer handle the dynamic changes in user preferences which is the so-called cold start .
Edit intent: fluency
Original:  In contrast to worst case energy stability estimates, this refined stability analysis reflects the existence of stable flow structures in turbulence over extended time , and the robustness of average quantities .
Revised:  In contrast to worst case energy stability estimates, this refined stability analysis reflects the existence of stable flow structures in turbulence over extended time .
Edit intent: clarity
Original: This article does not introduce new mathematical ideas, it is more a state of the art June 2021 picture about solving polynomial systems efficiently by reconstructing a rational univariate representation  with a very high probability of correctness using Groebner revlex computation, Berlekamp-Massey algorithm and Hankel linear system solving modulo several primes in parallel.
Revised: This article does not introduce new mathematical ideas, it was more a state of the art June 2021 picture about solving polynomial systems efficiently by reconstructing a rational univariate representation with a very high probability of correctness using Groebner revlex computation, Berlekamp-Massey algorithm and Hankel linear system solving modulo several primes in parallel.
Edit intent: fluency
Original: Version 1 of this preprint did not introduce new mathematical ideas, it was more a state of the art June 2021 picture about solving polynomial systems efficiently by reconstructing a rational univariate representation (rur) with a very high probability of correctness using Groebner revlex computation, Berlekamp-Massey algorithm and Hankel linear system solving modulo several primes in parallel.
Revised: This paper is about solving polynomial systems efficiently by reconstructing a rational univariate representation (rur) with a very high probability of correctness using Groebner revlex computation, Berlekamp-Massey algorithm and Hankel linear system solving modulo several primes in parallel.
Edit intent: coherence