wanyu/IteraTeR_v2 huggingface dataset:
Original:  Overall  the results collected on a wide variety of qualitatively different benchmark problems indicate that these methods are generally effective and scale well with respect to the number of parameters and the complexity of the problem.
Revised:  Overall , the results collected on a wide variety of qualitatively different benchmark problems indicate that these methods are generally effective and scale well with respect to the number of parameters and the complexity of the problem.
Edit intent: fluency
Original:  We demonstrate the importance of using suitable fitness functions or reward criteria since functions that are optimal for reinforcement learning algorithms tend to be sub-optimal for evolutionary strategies and vice versa.
Revised:  We demonstrate the importance of using suitable fitness functions or reward criteria since functions that are optimal for reinforcement learning methods are not necessarily effective for evolutionary strategies and vice versa.
Edit intent: clarity
Original: \] The algorithm runs in O(M(n)\log n)\[ O(M(n)\log^2 n) \] bit operations for computing \pi with error O(2^{-n}), where M(n) is the time complexity to multiply two n-bit integers.
Revised: \] The time complexity of the algorithm can be proved to be\[ O(M(n)\log^2 n) \] bit operations for computing \pi with error O(2^{-n}), where M(n) is the time complexity to multiply two n-bit integers.
Edit intent: clarity
Original:  \] The algorithm is self-correcting in the sense that, given an approximated value of \pi as an input, it can compute a more accurate value of \pi with cubic convergence.
Revised:  \] The algorithm is self-correcting in the sense that, given an approximated value of \pi as an input, it can compute a more accurate approximation of \pi with cubic convergence.
Edit intent: clarity
Original:  \] The algorithm had been known for a long time but it might not be regonized as a fast, practial algorithm.
Revised:  \] The algorithm had been known for a long time but it might not be recognized as a fast, practial algorithm.
Edit intent: fluency
Original:  \] The algorithm had been known for a long time but it might not be regonized as a fast, practial algorithm.
Revised:  \] The algorithm had been known for a long time but it might not be regonized as a fast, practical algorithm.
Edit intent: fluency
Original: Recent advances on wireless energy transfer led to a promising solution for powering future Internet of Things (IoT) devices enabled by the upcoming sixth generation (6G) era.
Revised: Recent advances on wireless energy transfer (WET) make it a promising solution for powering future Internet of Things (IoT) devices enabled by the upcoming sixth generation (6G) era.
Edit intent: coherence
Original:  In this paper, we overview the main architectures, challenges and techniques for efficient wireless powering.
Revised:  The main architectures, challenges and techniques for efficient wireless powering.
Edit intent: clarity
Original:  We emphasize on the suitability of Channel State Information (CSI) -free strategies when powering simultaneously a massive number of devices.
Revised:  We emphasize on the suitability of channel state information (CSI) -free strategies when powering simultaneously a massive number of devices.
Edit intent: fluency
Original:   The incompressible fluid is modeled with an artificial compressibility approach in order to avoid the solution of elliptical problems.
Revised:  The incompressible fluid is modeled with an artificial compressibility approach in order to avoid solving elliptical problems.
Edit intent: fluency
Original:  Thresholding of wavelet coefficients allows to introduce dynamically evolving grids and the adaption strategy tracks the solution in both space and scale.
Revised:  Thresholding the wavelet coefficients allows to introduce dynamically evolving grids and the adaption strategy tracks the solution in both space and scale.
Edit intent: fluency
Original:  Thresholding of wavelet coefficients allows to introduce dynamically evolving grids and the adaption strategy tracks the solution in both space and scale.
Revised:  Thresholding of wavelet coefficients allows to generate dynamically evolving grids and the adaption strategy tracks the solution in both space and scale.
Edit intent: clarity
Original:  Thresholding of wavelet coefficients allows to introduce dynamically evolving grids and the adaption strategy tracks the solution in both space and scale.
Revised:  Thresholding of wavelet coefficients allows to introduce dynamically evolving grids , and an adaption strategy tracks the solution in both space and scale.
Edit intent: fluency
Original:  Blocks are distributed among MPI processes and the global topology of the grid is encoded in a tree-like data structure.
Revised:  Blocks are distributed among MPI processes and the global topology of the grid is encoded using a tree-like data structure.
Edit intent: clarity
Original:  Different validation tests score accuracy and performance of our new open source code, WABBIT (Wavelet Adaptive Block-Based solver for Interactions with Turbulence), on massively parallel computers using fully adaptive grids.
Revised:  Different validation tests score accuracy and performance of our new open source code, WABBIT (Wavelet Adaptive Block-Based solver for Interactions with Turbulence), on massively parallel computers using fully adaptive grids.
Edit intent: fluency
Original:  We introduce a new graph sparsification technique thatdeterministically computes a low-degree subgraph with additional desired properties.
Revised:  We introduce a new thatdeterministically computes a low-degree subgraph with additional desired properties.
Edit intent: clarity
Original:  We introduce a new graph sparsification technique thatdeterministically computes a low-degree subgraph with additional desired properties.
Revised:  We introduce a new graph sparsification technique deterministically computes a low-degree subgraph with additional desired properties.
Edit intent: fluency
Original:  We introduce a new graph sparsification technique thatdeterministically computes a low-degree subgraph with additional desired properties.
Revised:  We introduce a new graph sparsification technique thatgraph sparsification technique that deterministically computes a low-degree subgraph with additional desired properties.
Edit intent: fluency
Original:  Depending on the specific local problem, the low-degree subgraph also has the property that solving the problem on this subgraph provides a large global progress.
Revised:  Depending on the specific local problem, the low-degree subgraph also has the property that solving the problem on this subgraph provides a large global progress.
Edit intent: fluency
Original:  We obtain the following deterministic MPC algorithms with O(n^{\epsilon}) space on each machine for any constant \epsilon <1 : - We show an O(\log \Delta+\log\log n) communication round algorithms for solving maximal matching and MIS, by derandomizing the well-known randomized algorithm of Luby [SICOMP'86].
Revised:  We obtain the following deterministic MPC algorithms with O(n^{\epsilon}) space on each machine for any constant \epsilon <1 : - We show an O(\log \Delta+\log\log n) communication round algorithms for solving maximal matching and MIS, by derandomizing the well-known randomized algorithm of Luby [SICOMP'86].
Edit intent: fluency
Original:  [FOCS'18], this additive O(\log\log n) factor is conditionally essential.
Revised:  [FOCS'18], this additive O(\log\log n) factor is conditionally essential.
Edit intent: fluency
Original:  Recent work has focused on the regime in which machines have sublinear  memory, with randomized algorithms presented for the tasks of Maximal Matching , Maximal Independent Set (MIS) and (\Delta+1)-Coloring .
Revised:  Recent work has focused on the regime in which machines have sublinear memory, with randomized algorithms presented for the tasks of Maximal Matching and Maximal Independent Set (MIS) and (\Delta+1)-Coloring .
Edit intent: fluency
Original:  Recent work has focused on the regime in which machines have sublinear  memory, with randomized algorithms presented for the tasks of Maximal Matching , Maximal Independent Set (MIS) and (\Delta+1)-Coloring .
Revised:  Recent work has focused on the regime in which machines have sublinear memory, with randomized algorithms presented for the tasks of Maximal Matching , Maximal Independent Set .
Edit intent: coherence
Original:  We  introduce a new graph sparsification technique that deterministically \emph{  computes a low-degree subgraph with additional desired properties.
Revised:  We introduce a new \emph{ computes a low-degree subgraph with additional desired properties.
Edit intent: clarity
Original:  We  introduce a new graph sparsification technique that deterministically \emph{  computes a low-degree subgraph with additional desired properties.
Revised:  We introduce a new graph sparsification technique that deterministically \emph{ that computes a low-degree subgraph with additional desired properties.
Edit intent: fluency
Original:  We obtain the following deterministic MPC algorithms ]  \emph{ with O(n^{\epsilon}) space on each machine for any constant \epsilon > 0: - We show an O(\log \Delta+\log\log n) communication round algorithms for solving maximal matching and MIS, by derandomizing the well-known randomized algorithm of Luby SICOMP'86%DIFDELCMD < ]%%% . Based on the recent work of Ghaffari et al.
Revised:  We obtain the following deterministic MPC algorithms SICOMP'86] \emph{ with O(n^{\epsilon}) space on each machine for any constant \epsilon > 0: - We show an O(\log \Delta+\log\log n) communication round algorithms for solving maximal matching and MIS, by derandomizing the well-known randomized algorithm of Luby SICOMP'86%DIFDELCMD < ]%%% . Based on the recent work of Ghaffari et al.
Edit intent: clarity
Original:  We obtain the following deterministic MPC algorithms ]  \emph{ with O(n^{\epsilon}) space on each machine for any constant \epsilon > 0: - We show an O(\log \Delta+\log\log n) communication round algorithms for solving maximal matching and MIS, by derandomizing the well-known randomized algorithm of Luby SICOMP'86%DIFDELCMD < ]%%% . Based on the recent work of Ghaffari et al.
Revised:  We obtain the following deterministic MPC algorithms ] and\emph{ with O(n^{\epsilon}) space on each machine for any constant \epsilon > 0: - We show an O(\log \Delta+\log\log n) communication round algorithms for solving maximal matching and MIS, by derandomizing the well-known randomized algorithm of Luby SICOMP'86%DIFDELCMD < ]%%% . Based on the recent work of Ghaffari et al.
Edit intent: fluency
Original:  We obtain the following deterministic MPC algorithms ]  \emph{ with O(n^{\epsilon}) space on each machine for any constant \epsilon > 0: - We show an O(\log \Delta+\log\log n) communication round algorithms for solving maximal matching and MIS, by derandomizing the well-known randomized algorithm of Luby SICOMP'86%DIFDELCMD < ]%%% . Based on the recent work of Ghaffari et al.
Revised:  We obtain the following deterministic MPC algorithms ] \emph{ with O(n^{\epsilon}) space on each machine for any constant \epsilon > SICOMP'86%DIFDELCMD < ]%%% . Based on the recent work of Ghaffari et al.
Edit intent: coherence
Original:  We obtain the following deterministic MPC algorithms ]  \emph{ with O(n^{\epsilon}) space on each machine for any constant \epsilon > 0: - We show an O(\log \Delta+\log\log n) communication round algorithms for solving maximal matching and MIS, by derandomizing the well-known randomized algorithm of Luby SICOMP'86%DIFDELCMD < ]%%% . Based on the recent work of Ghaffari et al.
Revised:  We obtain the following deterministic MPC algorithms ] \emph{ with O(n^{\epsilon}) space on each machine for any constant \epsilon > 0: - We show an O(\log \Delta+\log\log n) communication round algorithms for solving maximal matching and MIS, by derandomizing the well-known randomized algorithm of Luby SICOMP'86%DIFDELCMD < ]%%% 0. Based on the recent work of Ghaffari et al.
Edit intent: fluency
Original:  [FOCS'18], this additive O(\log\log n) factor is conditionally \emph{ essential.
Revised:  [FOCS'18], this additive O(\log\log n) factor is \emph{ essential.
Edit intent: clarity
Original:  This improves up on \congc the state-of-the-art bound of O(\log^2 \Delta) rounds by Censor-Hillel et al. [DISC'17] . - By employing our graph sparsification technique accompanied with a palette sparsification, we give a deterministic (deg+1)-list coloring (and thus also a (\Delta+1)-coloring) algorithm in O(\log \Delta+\log\log n) rounds .
Revised:  This improves up on \congc, improving upon the state-of-the-art bound of O(\log^2 \Delta) rounds by Censor-Hillel et al. [DISC'17] . - By employing our graph sparsification technique accompanied with a palette sparsification, we give a deterministic (deg+1)-list coloring (and thus also a (\Delta+1)-coloring) algorithm in O(\log \Delta+\log\log n) rounds .
Edit intent: clarity
Original:  This improves up on \congc the state-of-the-art bound of O(\log^2 \Delta) rounds by Censor-Hillel et al. [DISC'17] . - By employing our graph sparsification technique accompanied with a palette sparsification, we give a deterministic (deg+1)-list coloring (and thus also a (\Delta+1)-coloring) algorithm in O(\log \Delta+\log\log n) rounds .
Revised:  This improves up on \congc the state-of-the-art bound of O(\log^2 \Delta) rounds by Censor-Hillel et al. [DISC'17] .
Edit intent: coherence
Original:  The optimal exercise boundary satisfies  nonlinear integral equation of Volterra type.
Revised:  The optimal exercise boundary satisfies the nonlinear integral equation of Volterra type.
Edit intent: fluency
Original: This paper presents and studies an approach for constructing auxiliary space preconditioners for finite element problems , using a constrained nonconforming reformulation  that is based on a proposed modified version of the mortar method.
Revised: This paper presents and studies an approach for constructing auxiliary space preconditioners for finite element problems using a constrained nonconforming reformulation that is based on a proposed modified version of the mortar method.
Edit intent: fluency
Original: This paper presents and studies an approach for constructing auxiliary space preconditioners for finite element problems , using a constrained nonconforming reformulation  that is based on a proposed modified version of the mortar method.
Revised: This paper presents and studies an approach for constructing auxiliary space preconditioners for finite element problems , using a constrained nonconforming reformulation , that is based on a proposed modified version of the mortar method.
Edit intent: fluency
Original:  The well-known mortar finite element discretization method is modified to admit a local structure, providing an element-by-element , or subdomain-by-subdomain , assembly property.
Revised:  The well-known mortar finite element discretization method is modified to admit a local structure, providing an element-by-element or subdomain-by-subdomain , assembly property.
Edit intent: fluency
Original:  The well-known mortar finite element discretization method is modified to admit a local structure, providing an element-by-element , or subdomain-by-subdomain , assembly property.
Revised:  The well-known mortar finite element discretization method is modified to admit a local structure, providing an element-by-element , or subdomain-by-subdomain assembly property.
Edit intent: fluency
Original:  This is achieved via the introduction of additional trace finite element spaces and degrees of freedom (unknowns) associated with the interfaces between adjacent elements (or subdomains) .
Revised:  This is achieved via the introduction of additional trace finite element spaces and degrees of freedom (unknowns) associated with the interfaces between adjacent elements or subdomains .
Edit intent: fluency
Original:  The resulting nonconforming formulation and a reduced (Schur complement), via static condensation  on the interfaces , form of it are used in the construction of auxiliary space preconditioners for a given conforming finite element discretization problem.
Revised:  The resulting nonconforming formulation and a reduced via static condensation on the interfaces , form of it are used in the construction of auxiliary space preconditioners for a given conforming finite element discretization problem.
Edit intent: clarity
Original:  The resulting nonconforming formulation and a reduced (Schur complement), via static condensation  on the interfaces , form of it are used in the construction of auxiliary space preconditioners for a given conforming finite element discretization problem.
Revised:  The resulting nonconforming formulation and a reduced (Schur complement), via static condensation on the interfaces are used in the construction of auxiliary space preconditioners for a given conforming finite element discretization problem.
Edit intent: clarity
Original:  The properties of these preconditioners are studied and their performance is illustrated on model second order scalar elliptic problems , utilizing high order elements.
Revised:  The properties of these preconditioners are studied and their performance is illustrated on model second order scalar elliptic problems utilizing high order elements.
Edit intent: fluency
Original: The balanced hypercube BH_n, which is a variant of the hypercube, was proposed as a desired interconnection network topology.
Revised: The balanced hypercube BH_n, a variant of the hypercube, was proposed as a desired interconnection network topology.
Edit intent: coherence
Original:  It has been proved that there exists paired 2-disjoint path cover of BH_n. In this paper, we prove that there exists  (2n-2)-disjoint path cover of BH_n (n\geq2) from S to T, which partially improved some known results.
Revised:  It has been proved that there exists paired 2-disjoint path cover of BH_n. In this paper, we prove that there exists (2n-2)-disjoint path cover of BH_n (n\geq2) from S to T, which improved some known results.
Edit intent: clarity
Original:  The upper bound 2n-2 of the number of disjoint paths in unpaired (2n-2)-disjoint path cover is optimal .
Revised:  The upper bound 2n-2 of the number of disjoint paths in unpaired (2n-2)-disjoint path cover is best possible .
Edit intent: clarity
Original:  We integrate the MATLAB built-in audio data augmenter with other methods that proved their effectiveness in literature.
Revised:  We efficiently implemented several augmentation techniques whose usefulness has been extensively proved in the literature.
Edit intent: clarity
Original: We consider the problem of learning high-level controls over the global structure of sequence generation , particularly in the context of symbolic music generation with complex language models.
Revised: We consider the problem of learning high-level controls over the global structure of generated sequences , particularly in the context of symbolic music generation with complex language models.
Edit intent: clarity
Original:  We show it is possible to combine this global embedding with other temporally distributed embeddings, enabling improved control over the separate aspects of performance style and and melody.
Revised:  We show it is possible to combine this global representation with other temporally distributed embeddings, enabling improved control over the separate aspects of performance style and and melody.
Edit intent: clarity
Original:  We show it is possible to combine this global embedding with other temporally distributed embeddings, enabling improved control over the separate aspects of performance style and and melody.
Revised:  We show it is possible to combine this global embedding with other temporally distributed embeddings, enabling improved control over the separate aspects of performance style and melody.
Edit intent: fluency
Original:  Empirically, we demonstrate the effectiveness of our method on a variety of music generation tasks on the MAESTRO dataset and a YouTube dataset with 10,000+ hours of piano performances, where we achieve improvements in terms of log-likelihood and mean listening scores as compared to relevant baselines.
Revised:  Empirically, we demonstrate the effectiveness of our method on various music generation tasks on the MAESTRO dataset and a YouTube dataset with 10,000+ hours of piano performances, where we achieve improvements in terms of log-likelihood and mean listening scores as compared to relevant baselines.
Edit intent: clarity
Original:  Empirically, we demonstrate the effectiveness of our method on a variety of music generation tasks on the MAESTRO dataset and a YouTube dataset with 10,000+ hours of piano performances, where we achieve improvements in terms of log-likelihood and mean listening scores as compared to relevant baselines.
Revised:  Empirically, we demonstrate the effectiveness of our method on a variety of music generation tasks on the MAESTRO dataset and a YouTube dataset with 10,000+ hours of piano performances, where we achieve improvements in terms of log-likelihood and mean listening scores as compared to baselines.
Edit intent: clarity
Original:  The growth of multiple affiliations is prevalent in all disciplines and it is stronger in high impact journals.
Revised:  The growth of multiple affiliations is prevalent in all fields and it is stronger in high impact journals.
Edit intent: clarity
Original:  We extend past work on sized types for the Calculus of (Co) \- Inductive Constructions (CIC) with support for global definitions found in Gallina, and extend the sized-type inference algorithm to support completely unannotated Gallina terms.
Revised:  We extend past work on sized types for the Calculus of (Co) Inductive Constructions (CIC) with support for global definitions found in Gallina, and extend the sized-type inference algorithm to support completely unannotated Gallina terms.
Edit intent: fluency
Original:  In this paper, we introduce a novel BERT-wise pre-training scheme for a protein sequence representation model called PLUS, which stands for Protein sequence representations Learned Using Structural information.
Revised:  In this paper, we introduce a novel pre-training scheme for a protein sequence representation model called PLUS, which stands for Protein sequence representations Learned Using Structural information.
Edit intent: coherence
Original:  In this paper, we introduce a novel BERT-wise pre-training scheme for a protein sequence representation model called PLUS, which stands for Protein sequence representations Learned Using Structural information.
Revised:  In this paper, we introduce a novel BERT-wise pre-training scheme called PLUS, which stands for Protein sequence representations Learned Using Structural information.
Edit intent: clarity
Original: Motivation: Bridging the exponential gap between the number of unlabeled and labeled protein sequences , a couple of works have adopted semi-supervised learning for protein sequence modeling.
Revised: Motivation: Bridging the exponentially growing gap between the number of unlabeled and labeled protein sequences , a couple of works have adopted semi-supervised learning for protein sequence modeling.
Edit intent: clarity
Original: Motivation: Bridging the exponential gap between the number of unlabeled and labeled protein sequences , a couple of works have adopted semi-supervised learning for protein sequence modeling.
Revised: Motivation: Bridging the exponential gap between the number of unlabeled and labeled proteins , a couple of works have adopted semi-supervised learning for protein sequence modeling.
Edit intent: clarity
Original:  Nonetheless, the current pre-training methods mostly rely on a language modeling pre-training task and often show limited performances.
Revised:  Nonetheless, the current pre-training methods mostly rely on a language modeling task and often show limited performances.
Edit intent: fluency