wanyu/IteraTeR_v2 huggingface dataset:
Original:  In order to solve the above-mentioned challenging problems, the alternating optimization (AO)  is applied to decouple the optimization variables to solve the problem.
Revised:  In order to solve the above-mentioned challenging problem, alternating optimization (AO) is applied to decouple the optimization variables to solve the problem.
Edit intent: fluency
Original:  In order to solve the above-mentioned challenging problems, the alternating optimization (AO)  is applied to decouple the optimization variables to solve the problem.
Revised:  In order to solve the above-mentioned challenging problems, the alternating optimization (AO) technique is applied to decouple the optimization variables to solve the problem.
Edit intent: clarity
Original:  The difference-of-convex (DC) programming is applied to solve the non-convex rank-one constraint in solving the IRS energy reflection coefficient and information reflection coefficient.
Revised:  The difference-of-convex (DC) programming is uesd to solve the non-convex rank-one constraint in solving the IRS energy reflection coefficient and information reflection coefficient.
Edit intent: fluency
Original:  The difference-of-convex (DC) programming is applied to solve the non-convex rank-one constraint in solving the IRS energy reflection coefficient and information reflection coefficient.
Revised:  The difference-of-convex (DC) programming is applied to solve the non-convex rank-one constraint in solving IRS energy reflection coefficient and information reflection coefficient.
Edit intent: fluency
Original:  Numerical simulations verify the effectiveness of our proposed algorithm in reducing HAP transmission energy compared to other benchmarks .
Revised:  Numerical simulations verify the superiority of the proposed optimization algorithm in decreasing HAP transmit energy compared with other benchmark schemes .
Edit intent: clarity
Original:  The difference-of-convex (DC) programming is uesd to solve the non-convex rank-one constraint in solving IRS energy reflection coefficient and information reflection coefficient.
Revised:  The difference-of-convex (DC) programming is used to solve the non-convex rank-one constraint in solving IRS energy reflection coefficient and information reflection coefficient.
Edit intent: fluency
Original:  However, many  measures were formulated initially for undirected binary networks.
Revised:  However, many network measures were formulated initially for undirected binary networks.
Edit intent: clarity
Original:  We call these methods "hybrid" and argue that, in many situations, one should prefer fully-weighted definitions.
Revised:  We call these methods ``hybrid'' and argue that, in many situations, one should prefer fully-weighted definitions.
Edit intent: fluency
Original:  Real-world experiments on 8 everyday tasks show that our method can learn a diverse range of skills from just a single human demonstration, whilst also yielding a stable and interpretable controller.
Revised:  Real-world experiments on 8 everyday tasks show that our method can learn a diverse range of skills from a single human demonstration, whilst also yielding a stable and interpretable controller.
Edit intent: clarity
Original:  Spectral sums tr(f[A]) can be computed as the Riemann-Stieltjes integral of f against \Phi[A], so the task of estimating CESM arises frequently in a number of applications, including machine learning.
Revised:  Spectral sums tr(f[A]) can be computed as the Riemann--Stieltjes integral of f against \Phi[A], so the task of estimating CESM arises frequently in a number of applications, including machine learning.
Edit intent: fluency
Original:  We additionally provide (matrix-dependent) a posteriori error bounds for the Wasserstein and Kolmogorov-Smirnov distances between the output of this algorithm and the true CESM.
Revised:  We additionally provide (matrix-dependent) a posteriori error bounds for the Wasserstein and Kolmogorov--Smirnov distances between the output of this algorithm and the true CESM.
Edit intent: fluency
Original: This paper studies time-inconsistent stopping control problems under general multi-dimensional controlled diffusion model .
Revised: This paper considers time-inconsistent stopping control problems under general multi-dimensional controlled diffusion model .
Edit intent: clarity
Original:  This definition for equilibriums is consistent with the ones in pure control/stopping problems and thus can be seen as nontrivial extension to the existing theory.
Edit intent: coherence
Original:  We show that an admissible pair (u,C) of control-stopping policy is equilibrium if and only if the axillary function associated to it solves the extended Hamiltonian system.
Revised:  We show that an admissible pair (u,C) of control-stopping policy is equilibrium if and only if the axillary function associated to it solves the extended HJB system.
Edit intent: clarity
Original:  We provide almost equivalent conditions to the boundary term of this Hamiltonian system, which is basically the celebrated smooth fitting principles.
Revised:  We provide almost equivalent conditions to the boundary term of this Hamiltonian system, which is related to the celebrated smooth fitting principles.
Edit intent: clarity
Original:  Finally, the amount of time for emergency response and the total energy consumption are simultaneously minimized by a multiobjective evolutionary algorithm based on decomposition (MOEA/D), subject to a given set of minimum signal-to-interference- plus-noise ratio (SINR), number of UAVs, transmit power, and energy constraints.
Revised:  Finally, the amount of time for emergency response and the total energy consumption are simultaneously minimized by a multiobjective evolutionary algorithm based on decomposition (MOEA/D), subject to a given set of minimum signal-to-interference-plus-noise ratio (SINR), number of UAVs, transmit power, and energy constraints.
Edit intent: fluency
Original:  This is the case for the establishment of a conservation network when connectivity needs cannot explicitly account for every species.
Edit intent: coherence
Original:  Objectives - The objective was to assess the relevance of designing priority areas for connectivity for groups of species based on common dispersal abilities.
Revised:  Objectives - The objective was to assess the relevance of identifying priority areas for connectivity for groups of species based on common dispersal abilities.
Edit intent: clarity
Original:  Methods - The study was located at the Thau Lagoon territory (Occitanie Region, France) as a demonstrator for the methodological approach.
Revised:  Methods - The study was located at the Thau Lagoon territory to demonstrate the methodological approach.
Edit intent: clarity
Original:  Ecological niche modelling (ENM) was used to quantify species resistance and to identify suitable habitat patches.
Revised:  Ecological niche modelling was used to quantify species resistance and to identify suitable habitat patches.
Edit intent: clarity
Original:  We coupled  least-cost path  with circuit theory to assess species connectivity.
Revised:  We coupled the least-cost path with circuit theory to assess species connectivity.
Edit intent: fluency
Original:  We coupled  least-cost path  with circuit theory to assess species connectivity.
Revised:  We coupled least-cost path methodology with circuit theory to assess species connectivity.
Edit intent: clarity
Original:  Results - We found important differences in identified priority areas between groups having dissimilar dispersal abilities, with low overlap between highly connected areas.
Revised:  Results - We found important differences in identified priority areas between groups with dissimilar dispersal abilities, with low overlap between highly connected areas.
Edit intent: fluency
Original:  Results - We found important differences in identified priority areas between groups having dissimilar dispersal abilities, with low overlap between highly connected areas.
Revised:  Results - We found important differences in identified priority areas between groups having dissimilar dispersal abilities, with little overlap between highly connected areas.
Edit intent: clarity
Original:  We identified a gap in between the level of protection of low dispersal species and highly connected areas.
Revised:  We identified a gap between the level of protection of low dispersal species and highly connected areas.
Edit intent: clarity
Original:  We found mismatches between existing corridors and connectivity for low dispersal species and higher impact of expected urban sprawl projects on highly connected areas for high dispersal species .
Revised:  We found mismatches between existing corridors and connectivity in low dispersal species and higher impact of expected urban sprawl projects on highly connected areas for high dispersal species .
Edit intent: clarity
Original:  We found mismatches between existing corridors and connectivity for low dispersal species and higher impact of expected urban sprawl projects on highly connected areas for high dispersal species .
Revised:  We found mismatches between existing corridors and connectivity for low dispersal species , and a greater impact in areas of expected urban sprawl projects on highly connected areas for high dispersal species .
Edit intent: clarity
Original:  We found mismatches between existing corridors and connectivity for low dispersal species and higher impact of expected urban sprawl projects on highly connected areas for high dispersal species .
Revised:  We found mismatches between existing corridors and connectivity for low dispersal species and higher impact of expected urban sprawl projects on favourably connected areas for high dispersal species .
Edit intent: clarity
Original:  The agents make decisions with the aim of attaining as high social positions as possible relative to other agents .
Revised:  The agents make decisions with the aim of attaining as high socio-economic standings as possible relative to other agents .
Edit intent: clarity
Original:  They evaluate their social positions based on the local and regional infection rates, compliance to the authorities' regulations, regional drops in economic activity, and the efforts they make to mitigate the spread of epidemic.
Revised:  They evaluate their social positions based on the local and regional infection rates, compliance to the authorities' regulations, regional drops in economic activity, and efforts to mitigate the spread of epidemic.
Edit intent: clarity
Original:  We find that the willingness of populations to comply with authorities' recommendations has the most drastic effect to the spreading of epidemic : periodic waves spread almost unimpeded in non-compliant populations, while in compliant ones the spread is minimal with a chaotic spreading pattern and significantly lower infection rates.
Revised:  We find that the willingness of population to comply with authorities' recommendations has the most drastic effect to the spreading of epidemic : periodic waves spread almost unimpeded in non-compliant populations, while in compliant ones the spread is minimal with a chaotic spreading pattern and significantly lower infection rates.
Edit intent: fluency
Original:  We find that the willingness of populations to comply with authorities' recommendations has the most drastic effect to the spreading of epidemic : periodic waves spread almost unimpeded in non-compliant populations, while in compliant ones the spread is minimal with a chaotic spreading pattern and significantly lower infection rates.
Revised:  We find that the willingness of populations to comply with authorities' recommendations has the most drastic effect on the epidemic spreading : periodic waves spread almost unimpeded in non-compliant populations, while in compliant ones the spread is minimal with a chaotic spreading pattern and significantly lower infection rates.
Edit intent: clarity
Original:  We find that the willingness of populations to comply with authorities' recommendations has the most drastic effect to the spreading of epidemic : periodic waves spread almost unimpeded in non-compliant populations, while in compliant ones the spread is minimal with a chaotic spreading pattern and significantly lower infection rates.
Revised:  We find that the willingness of populations to comply with authorities' recommendations has the most drastic effect to the spreading of epidemic : periodic waves spread almost unimpeded in non-compliant populations, while in compliant ones the spread is minimal with chaotic spreading pattern and significantly lower infection rates.
Edit intent: fluency
Original:  Health and economic concerns of agents turned out to have lesser roles, the former increasing their efforts and the latter decreasing them.
Revised:  Health and economic concerns of agents turn out to have lesser roles, the former increasing their efforts and the latter decreasing them.
Edit intent: fluency
Original:  Results: The model significantly outperformed the baseline for every input segment length (p\leq10^{-9}), for all EEG frequency bands except the theta band (p\leq0.001) and for receptive field sizes larger than 125 ~ ms (p\leq0.05).
Revised:  Results: The model significantly outperformed the baseline for every input segment length (p\leq10^{-9}), for all EEG frequency bands except the theta band (p\leq0.001) and for receptive field sizes larger than 125 ms (p\leq0.05).
Edit intent: clarity
Original: Objective: Currently, only behavioral speech understanding tests are available, which require active participation of the person  .
Revised: Objective: Currently, only behavioral speech understanding tests are available, which require active participation of the person being tested .
Edit intent: clarity
Original:  We present a deep-learning-based model incorporating dilated convolutions that  can be used to predict speech intelligibility without subject-specific (re)training.
Revised:  We present a deep-learning-based model incorporating dilated convolutions that can be used as a proxy for speech intelligibility without subject-specific (re)training.
Edit intent: clarity
Original:  Methods : We evaluated the performance of the model as a function of input segment length, EEG frequency band and receptive field size while comparing it to a baseline model . Next, we evaluated performance on held-out data and finetuning.
Revised:  Approach : We evaluated the performance of the model as a function of input segment length, EEG frequency band and receptive field size while comparing it to a baseline model . Next, we evaluated performance on held-out data and finetuning.
Edit intent: fluency
Original:  Methods : We evaluated the performance of the model as a function of input segment length, EEG frequency band and receptive field size while comparing it to a baseline model . Next, we evaluated performance on held-out data and finetuning.
Revised:  Methods : We evaluated the performance of the model as a function of input segment length, EEG frequency band and receptive field size while comparing it to multiple baseline models . Next, we evaluated performance on held-out data and finetuning.
Edit intent: clarity
Original:  Results: The model significantly outperformed the baseline  for every input segment length (p%DIFDELCMD < \leq10%%% ^{-9 , for all EEG frequency bands except the theta band (p%DIFDELCMD < \leq0%%% .001) and for receptive field sizes larger than 125 ms(p%DIFDELCMD < \leq0%%% .05) . Additionally, finetuning significantly increased the accuracy (p%DIFDELCMD < \leq0%%% .05) on a held-out dataset.
Revised:  Results: The model significantly outperformed the baseline models for every input segment length (p%DIFDELCMD < \leq10%%% ^{-9 , for all EEG frequency bands except the theta band (p%DIFDELCMD < \leq0%%% .001) and for receptive field sizes larger than 125 ms(p%DIFDELCMD < \leq0%%% .05) . Additionally, finetuning significantly increased the accuracy (p%DIFDELCMD < \leq0%%% .05) on a held-out dataset.
Edit intent: clarity
Original:  Results: The model significantly outperformed the baseline  for every input segment length (p%DIFDELCMD < \leq10%%% ^{-9 , for all EEG frequency bands except the theta band (p%DIFDELCMD < \leq0%%% .001) and for receptive field sizes larger than 125 ms(p%DIFDELCMD < \leq0%%% .05) . Additionally, finetuning significantly increased the accuracy (p%DIFDELCMD < \leq0%%% .05) on a held-out dataset.
Revised:  Results: The model significantly outperformed the baseline for every input segment length %DIFDELCMD < \leq10%%% ^{-9 , for all EEG frequency bands except the theta band (p%DIFDELCMD < \leq0%%% .001) and for receptive field sizes larger than 125 ms(p%DIFDELCMD < \leq0%%% .05) . Additionally, finetuning significantly increased the accuracy (p%DIFDELCMD < \leq0%%% .05) on a held-out dataset.
Edit intent: fluency
Original:  Results: The model significantly outperformed the baseline  for every input segment length (p%DIFDELCMD < \leq10%%% ^{-9 , for all EEG frequency bands except the theta band (p%DIFDELCMD < \leq0%%% .001) and for receptive field sizes larger than 125 ms(p%DIFDELCMD < \leq0%%% .05) . Additionally, finetuning significantly increased the accuracy (p%DIFDELCMD < \leq0%%% .05) on a held-out dataset.
Revised:  Results: The model significantly outperformed the baseline for every input segment length (p%DIFDELCMD < \leq10%%% , for all EEG frequency bands except the theta band (p%DIFDELCMD < \leq0%%% .001) and for receptive field sizes larger than 125 ms(p%DIFDELCMD < \leq0%%% .05) . Additionally, finetuning significantly increased the accuracy (p%DIFDELCMD < \leq0%%% .05) on a held-out dataset.
Edit intent: coherence
Original:  Results: The model significantly outperformed the baseline  for every input segment length (p%DIFDELCMD < \leq10%%% ^{-9 , for all EEG frequency bands except the theta band (p%DIFDELCMD < \leq0%%% .001) and for receptive field sizes larger than 125 ms(p%DIFDELCMD < \leq0%%% .05) . Additionally, finetuning significantly increased the accuracy (p%DIFDELCMD < \leq0%%% .05) on a held-out dataset.
Revised:  Results: The model significantly outperformed the baseline for every input segment length (p%DIFDELCMD < \leq10%%% ^{-9 , for all EEG frequency bands except the %DIFDELCMD < \leq0%%% .001) and for receptive field sizes larger than 125 ms(p%DIFDELCMD < \leq0%%% .05) . Additionally, finetuning significantly increased the accuracy (p%DIFDELCMD < \leq0%%% .05) on a held-out dataset.
Edit intent: clarity
Original:  Results: The model significantly outperformed the baseline  for every input segment length (p%DIFDELCMD < \leq10%%% ^{-9 , for all EEG frequency bands except the theta band (p%DIFDELCMD < \leq0%%% .001) and for receptive field sizes larger than 125 ms(p%DIFDELCMD < \leq0%%% .05) . Additionally, finetuning significantly increased the accuracy (p%DIFDELCMD < \leq0%%% .05) on a held-out dataset.
Revised:  Results: The model significantly outperformed the baseline for every input segment length (p%DIFDELCMD < \leq10%%% ^{-9 , for all EEG frequency bands except the theta band (p%DIFDELCMD < \leq0%%% .001) and for receptive field sizes larger than 125 ms(p%DIFDELCMD < \leq0%%% .05) . Additionally, finetuning significantly increased the accuracy %DIFDELCMD < \leq0%%% .05) on a held-out dataset.
Edit intent: fluency
Original:  Results: The model significantly outperformed the baseline  for every input segment length (p%DIFDELCMD < \leq10%%% ^{-9 , for all EEG frequency bands except the theta band (p%DIFDELCMD < \leq0%%% .001) and for receptive field sizes larger than 125 ms(p%DIFDELCMD < \leq0%%% .05) . Additionally, finetuning significantly increased the accuracy (p%DIFDELCMD < \leq0%%% .05) on a held-out dataset.
Revised:  Results: The model significantly outperformed the baseline for every input segment length (p%DIFDELCMD < \leq10%%% ^{-9 , for all EEG frequency bands except the theta band (p%DIFDELCMD < \leq0%%% .001) and for receptive field sizes larger than 125 ms(p%DIFDELCMD < \leq0%%% .05) . Additionally, finetuning significantly increased the accuracy (p%DIFDELCMD < \leq0%%% on a held-out dataset.
Edit intent: fluency
Original: Shared microarchitectural state has become a prime target for side-channel attacks that leverage timing measurements to leak information across security domains . Combined with speculative execution, they cause vulnerabilities like Spectre and Meltdown.
Revised: Speculative vulnerabilities such as Spectre and Meltdown expose speculative execution state that can be exploited to leak information across security domains . Combined with speculative execution, they cause vulnerabilities like Spectre and Meltdown.
Edit intent: clarity
Original: Shared microarchitectural state has become a prime target for side-channel attacks that leverage timing measurements to leak information across security domains . Combined with speculative execution, they cause vulnerabilities like Spectre and Meltdown.
Revised: Shared microarchitectural state has become a prime target for side-channel attacks that leverage timing measurements to leak information across security domains via side-channels.
Edit intent: clarity
Original:  Such vulnerabilities often stay undetected for a long time because we lack the tools for systematic testing of CPUs against them.
Revised:  Such vulnerabilities often stay undetected for a long time as we lack the tools for systematic testing of CPUs against them.
Edit intent: coherence
Original:  Such vulnerabilities often stay undetected for a long time because we lack the tools for systematic testing of CPUs against them.
Revised:  Such vulnerabilities often stay undetected for a long time because we lack the tools for systematic testing of CPUs to find them.
Edit intent: clarity
Original:  We base our approach on speculation contracts, which we employ to specify the permitted side effects of program execution on the  microarchitectural state.
Revised:  We build on speculation contracts, which we employ to specify the permitted side effects of program execution on the microarchitectural state.
Edit intent: clarity
Original:  We propose a technique, called Model-based Relational Fuzzing (MRF) , that enables testing of CPUs against these specifications.
Revised:  We propose a Model-based Relational Fuzzing (MRF) , that enables testing of CPUs against these specifications.
Edit intent: clarity
Original:  We propose a technique, called Model-based Relational Fuzzing (MRF) , that enables testing of CPUs against these specifications.
Revised:  We propose a technique, called Model-based Relational Testing (MRT) technique to empirically assess the CPU compliance with these specifications.
Edit intent: clarity
Original:  We implement MRF in a fuzzing framework called Revizor, and showcase its effectiveness on real Intel x86 CPUs : It automatically detects violations of a rich set of contracts, or indicates their absence.
Revised:  We implement MRF in a fuzzing framework called Revizor, and showcase its effectiveness on real Intel x86 CPUs . Revizor automatically detects violations of a rich set of contracts, or indicates their absence.
Edit intent: coherence
Original:  In particular, UEs connect either directly to BSs by access links or indirectly through UAVs to BSs by joint access and backhaul links, where the BSs provide wireless backhaul to the UAVs .
Revised:  In particular, a UE connects either directly to BSs by access links or indirectly through UAVs to BSs by joint access and backhaul links, where the BSs provide wireless backhaul to the UAVs .
Edit intent: clarity
Original:  In particular, UEs connect either directly to BSs by access links or indirectly through UAVs to BSs by joint access and backhaul links, where the BSs provide wireless backhaul to the UAVs .
Revised:  In particular, UEs connect either directly to BSs by access links or indirectly through UAVs to BSs by joint access and backhaul ) .
Edit intent: coherence