wanyu/IteraTeR_v2 huggingface dataset:
Original:  We propose a better alternative: a domain-specific language in which generators are  expressed by decorating predicates with lightweight annotations to control both the distribution of generated values as well as the amount of constraint solving that happens before each variable is instantiated.
Revised:  We propose a better alternative: a domain-specific language in which generators are expressed by decorating predicates with lightweight annotations to control both the distribution of generated values and the amount of constraint solving that happens before each variable is instantiated.
Edit intent: coherence
Original:  we show that it can be used in complex domains with comparable bug-finding effectiveness and a significant reduction in testing code size , compared to handwritten generators.
Revised:  we show that it can be used in complex domains with comparable bug-finding effectiveness and a significant reduction in testing code size compared to handwritten generators.
Edit intent: fluency
Original: Retrieved-context models have played a crucial role in the understanding of serial-position effects in free recall.
Revised: A theoretical framework is proposed for the understanding of serial-position effects in free recall.
Edit intent: clarity
Original:  The model discussed in this paper predicts the experimental behavior as an effect of the different level of localization of short and long words in semantic space.
Revised:  In the framework here proposed, these behaviors emerge as an effect of the different level of localization of short and long words in semantic space.
Edit intent: clarity
Original:  Several other predictions are listed , and experiments are proposed to further test the model .
Revised:  Several other predictions are listed and new experiments are proposed to further test the model .
Edit intent: clarity
Original:  Several other predictions are listed , and experiments are proposed to further test the model .
Revised:  Several other predictions are listed , and experiments are proposed .
Edit intent: clarity
Original:  Finally, a possible interpretation of the results is discussed .
Revised:  Finally, an interpretation of the results is discussed .
Edit intent: clarity
Original:  Finally, a possible interpretation of the results is discussed .
Revised:  Finally, a possible interpretation of the above results is presented .
Edit intent: clarity
Original: Simultaneous Wireless Information and Power Transfer ( SWIPT ) has attracted significant attention in the communication community.
Revised:  Wireless Information and Power Transfer ( SWIPT ) has attracted significant attention in the communication community.
Edit intent: clarity
Original: Simultaneous Wireless Information and Power Transfer ( SWIPT ) has attracted significant attention in the communication community.
Revised: Simultaneous Wireless Information and Power Transfer ( WIPT ) has attracted significant attention in the communication community.
Edit intent: fluency
Original:  The problem of waveform design has however never been addressed so far .
Revised:  The problem is that its design has been based on an oversimplified and inaccurate linear model of the energy harvester that leads to inefficient wireless power signal designs .
Edit intent: coherence
Original:  We show that due to the non-linearity of the rectifier and the randomness of the information symbols, the OFDM waveform is less efficient than the multisine waveform for wireless power transfer.
Revised:  We show that due to the nonlinearity of the rectifier and the randomness of the information symbols, the OFDM waveform is less efficient than the multisine waveform for wireless power transfer.
Edit intent: fluency
Original:  This observation motivates the design of a novel SWIPT transceiver architecture relying on the superposition of multisine and OFDM waveforms at the transmitter and a power-splitter receiver equipped with an energy harvester and an information decoder.
Revised:  This observation motivates the design of a novel WIPT transceiver architecture relying on the superposition of multisine and OFDM waveforms at the transmitter and a power-splitter receiver equipped with an energy harvester and an information decoder.
Edit intent: fluency
Original:  The superposed SWIPT waveform is optimized so as to maximize the rate-energy region of the whole system.
Revised:  The superposed WIPT waveform is optimized so as to maximize the rate-energy region of the whole system.
Edit intent: fluency
Original:  The superposed SWIPT waveform is optimized so as to maximize the rate-energy region of the whole system.
Revised:  The superposed SWIPT waveform is optimized so as to characterize the rate-energy region of the whole system.
Edit intent: clarity
Original:  Its design is adaptive to the channel state information and result from a posynomial maximization problem that originates from the non-linearity of the energy harvester . Numerical results illustrate the performance of the derived waveforms and SWIPT architecture.
Revised:  Its design is adaptive to the channel state information and results from a posynomial maximization problem that originates from the non-linearity of the energy harvester . Numerical results illustrate the performance of the derived waveforms and SWIPT architecture.
Edit intent: fluency
Original:  Its design is adaptive to the channel state information and result from a posynomial maximization problem that originates from the non-linearity of the energy harvester . Numerical results illustrate the performance of the derived waveforms and SWIPT architecture.
Revised:  Its design is adaptive to the channel state information and result from a posynomial maximization problem that originates from the rectifier nonlinearity . Numerical results illustrate the performance of the derived waveforms and SWIPT architecture.
Edit intent: clarity
Original:  Its design is adaptive to the channel state information and result from a posynomial maximization problem that originates from the non-linearity of the energy harvester . Numerical results illustrate the performance of the derived waveforms and SWIPT architecture.
Revised:  Its design is adaptive to the channel state information and result from a posynomial maximization problem that originates from the non-linearity of the energy harvester . Numerical results illustrate the performance of the derived waveforms and WIPT architecture.
Edit intent: fluency
Original:  Key (and refreshing) observations are that 1) a power waveform (superposed to a communication waveform) is useful to enlarge the rate-energy region of SWIPT , 2) a combination of power splitting and time sharing is in general the best strategy, 3) exploiting the nonlinearity of the rectifier is essential to design efficient SWIPT architecture, 4) a non-zero mean Gaussian input distribution outperforms the conventional capacity-achieving zero-mean Gaussian input distribution.
Revised:  Key (and refreshing) observations are that 1) a power waveform (superposed to a communication waveform) is useful to enlarge the rate-energy region of WIPT , 2) a combination of power splitting and time sharing is in general the best strategy, 3) exploiting the nonlinearity of the rectifier is essential to design efficient SWIPT architecture, 4) a non-zero mean Gaussian input distribution outperforms the conventional capacity-achieving zero-mean Gaussian input distribution.
Edit intent: fluency
Original:  Wireless Information and Power Transfer (WIPT) has attracted significant attention in the communication community.
Revised: The design of Wireless Information and Power Transfer (WIPT) has attracted significant attention in the communication community.
Edit intent: clarity
Original:  The problem is that its design has been based on an oversimplified and inaccurate linear model of the energy harvester that leads to inefficient wireless power signal designs .
Revised:  The problem is that its design has been based on an oversimplified and inaccurate linear model of the energy harvester .
Edit intent: clarity
Original:  In this paper, we depart from this linear model and design WIPT transmit waveform and architecture considering the rectifier nonlinearity.
Revised:  In this paper, we depart from this linear model and design WIPT considering the rectifier nonlinearity.
Edit intent: clarity
Original:  This observation motivates the design of a novel WIPT transceiver architecture relying on the superposition of multisine and OFDM waveforms at the transmitter and a power-splitter receiver equipped with an energy harvester and an information decoder .
Revised:  This observation motivates the design of a novel WIPT architecture relying on the superposition of multisine and OFDM waveforms at the transmitter and a power-splitter receiver equipped with an energy harvester and an information decoder .
Edit intent: clarity
Original:  This observation motivates the design of a novel WIPT transceiver architecture relying on the superposition of multisine and OFDM waveforms at the transmitter and a power-splitter receiver equipped with an energy harvester and an information decoder .
Revised:  This observation motivates the design of a novel WIPT transceiver architecture relying on the superposition of multisine and OFDM waveforms at the transmitter .
Edit intent: clarity
Original:  a power waveform (superposed to a communication waveform) is useful to enlarge the rate-energy region of WIPT , 2) a combination of power splitting and time sharing is in general the best strategy , 3) exploiting the nonlinearity of the rectifier is essential to design efficient SWIPT architecture, 4) a non-zero mean Gaussian input distribution outperforms the conventional capacity-achieving zero-mean Gaussian input distribution  .
Revised:  a power waveform (superposed to a communication waveform) is useful to enlarge the rate-energy region of WIPT . Third, a combination of power splitting and time sharing is in general the best strategy , 3) exploiting the nonlinearity of the rectifier is essential to design efficient SWIPT architecture, 4) a non-zero mean Gaussian input distribution outperforms the conventional capacity-achieving zero-mean Gaussian input distribution .
Edit intent: coherence
Original:  a power waveform (superposed to a communication waveform) is useful to enlarge the rate-energy region of WIPT , 2) a combination of power splitting and time sharing is in general the best strategy , 3) exploiting the nonlinearity of the rectifier is essential to design efficient SWIPT architecture, 4) a non-zero mean Gaussian input distribution outperforms the conventional capacity-achieving zero-mean Gaussian input distribution  .
Revised:  a power waveform (superposed to a communication waveform) is useful to enlarge the rate-energy region of WIPT , 2) a combination of power splitting and time sharing is in general the best strategy . Fourth, a non-zero mean Gaussian input distribution outperforms the conventional capacity-achieving zero-mean Gaussian input distribution .
Edit intent: coherence
Original: Human mobility modelling is of fundamental importance in a wide range of applications, such as the developing of protocols for mobile ad hoc networks or for what-if analysis and simulation in urban ecosystems.
Revised: Human mobility modelling is of fundamental importance in a wide range of applications, such as the developing of protocols for mobile ad-hoc networks or what-if analysis and simulation in urban ecosystems.
Edit intent: fluency
Original: Human mobility modelling is of fundamental importance in a wide range of applications, such as the developing of protocols for mobile ad hoc networks or for what-if analysis and simulation in urban ecosystems.
Revised: Human mobility modelling is of fundamental importance in a wide range of applications, such as the developing of protocols for mobile ad hoc networks or for what-if analysis in urban ecosystems.
Edit intent: clarity
Original:  Current generative models generally fail in accurately reproducing the individuals' recurrent daily schedules and at the same time in accounting for the possibility that individuals may break the routine and modify their habits during periods of unpredictability of variable duration.
Revised:  Current generative models fail in accurately reproducing the individuals' recurrent daily schedules and at the same time in accounting for the possibility that individuals may break the routine and modify their habits during periods of unpredictability of variable duration.
Edit intent: coherence
Original:  Current generative models generally fail in accurately reproducing the individuals' recurrent daily schedules and at the same time in accounting for the possibility that individuals may break the routine and modify their habits during periods of unpredictability of variable duration.
Revised:  Current generative models generally fail in accurately reproducing the individuals' recurrent schedules and at the same time in accounting for the possibility that individuals may break the routine and modify their habits during periods of unpredictability of variable duration.
Edit intent: clarity
Original:  Current generative models generally fail in accurately reproducing the individuals' recurrent daily schedules and at the same time in accounting for the possibility that individuals may break the routine and modify their habits during periods of unpredictability of variable duration.
Revised:  Current generative models generally fail in accurately reproducing the individuals' recurrent daily schedules and at the same time in accounting for the possibility that individuals may break the routine during periods of unpredictability of variable duration.
Edit intent: clarity
Original:  Current generative models generally fail in accurately reproducing the individuals' recurrent daily schedules and at the same time in accounting for the possibility that individuals may break the routine and modify their habits during periods of unpredictability of variable duration.
Revised:  Current generative models generally fail in accurately reproducing the individuals' recurrent daily schedules and at the same time in accounting for the possibility that individuals may break the routine and modify their habits during periods of variable duration.
Edit intent: clarity
Original:  In this article we present DITRAS (DIary-based TRAjectory Simulator), a framework to simulate the spatio-temporal patterns of human mobility in a realistic way . DITRAS operates in two steps: the generation of a mobility diary and the translation of the mobility diary into a mobility trajectory.
Revised:  In this article we present DITRAS (DIary-based TRAjectory Simulator), a framework to simulate the spatio-temporal patterns of human mobility . DITRAS operates in two steps: the generation of a mobility diary and the translation of the mobility diary into a mobility trajectory.
Edit intent: coherence
Original:  The mobility diary is constructed by a Markov model which captures the tendency of individuals to follow or break their routine.
Revised:  We propose a data-driven algorithm which constructs a diary generator from real data, capturing the tendency of individuals to follow or break their routine.
Edit intent: clarity
Original:  The mobility trajectory is produced by a model based on the concept of preferential exploration and preferential return.
Revised:  We also propose a trajectory generator based on the concept of preferential exploration and preferential return.
Edit intent: clarity
Original: Human mobility modelling is of fundamental importance in a wide range of applications, such as the developing of protocols for mobile ad-hoc networks or what-if analysis in urban ecosystems.
Revised: The generation of realistic spatio-temporal trajectories of human mobility is of fundamental importance in a wide range of applications, such as the developing of protocols for mobile ad-hoc networks or what-if analysis in urban ecosystems.
Edit intent: clarity
Original:  Current generative models fail in accurately reproducing the individuals' recurrent schedules and at the same time in accounting for the possibility that individuals may break the routine during periods of variable duration.
Revised:  Current generative algorithms fail in accurately reproducing the individuals' recurrent schedules and at the same time in accounting for the possibility that individuals may break the routine during periods of variable duration.
Edit intent: clarity
Original:  We instantiate DITRAS with the proposed diary and trajectory generators and compare the resulting spatio-temporal model with real data and synthetic data produced by other spatio-temporal mobility models , built by instantiating DITRAS with several combinations of diary and trajectory generators.
Revised:  We instantiate DITRAS with the proposed diary and trajectory generators and compare the resulting algorithm with real data and synthetic data produced by other spatio-temporal mobility models , built by instantiating DITRAS with several combinations of diary and trajectory generators.
Edit intent: clarity
Original:  We instantiate DITRAS with the proposed diary and trajectory generators and compare the resulting spatio-temporal model with real data and synthetic data produced by other spatio-temporal mobility models , built by instantiating DITRAS with several combinations of diary and trajectory generators.
Revised:  We instantiate DITRAS with the proposed diary and trajectory generators and compare the resulting spatio-temporal model with real data and synthetic data produced by other generative algorithms , built by instantiating DITRAS with several combinations of diary and trajectory generators.
Edit intent: clarity
Original:  We show that the proposed model reproduces the statistical properties of real trajectories in the most accurate way, making a step forward the understanding of the origin of the spatio-temporal patterns of human mobility.
Revised:  We show that the proposed algorithm reproduces the statistical properties of real trajectories in the most accurate way, making a step forward the understanding of the origin of the spatio-temporal patterns of human mobility.
Edit intent: clarity
Original: Dynamic Time Warping (DTW) is one of the basic similarity measures between curves or general temporal sequences (e.g., time series) that are represented as sequence of points in some metric space (X,  ).
Revised: Dynamic Time Warping (DTW) is one of the basic similarity measures between curves or general temporal sequences (e.g., time series) that are represented as sequences of points in some metric space (X, ).
Edit intent: fluency
Original:  The DTW measure is massively used in many practical fields of computer science , and computing the DTW between two sequences is a classical problem in P. Despite extensive efforts to find more efficient algorithms, the best-known algorithm for computing DTW is a long-standing dynamic programming algorithm that requires quadratic runtime, which is believed to be optimal, even for the one-dimensional case X = \mathbb{R , which is perhaps one of the most used in practice.
Revised:  The DTW measure is massively used in various fields of computer science , and computing the DTW between two sequences is a classical problem in P. Despite extensive efforts to find more efficient algorithms, the best-known algorithm for computing DTW is a long-standing dynamic programming algorithm that requires quadratic runtime, which is believed to be optimal, even for the one-dimensional case X = \mathbb{R , which is perhaps one of the most used in practice.
Edit intent: clarity
Original:  The DTW measure is massively used in many practical fields of computer science , and computing the DTW between two sequences is a classical problem in P. Despite extensive efforts to find more efficient algorithms, the best-known algorithm for computing DTW is a long-standing dynamic programming algorithm that requires quadratic runtime, which is believed to be optimal, even for the one-dimensional case X = \mathbb{R , which is perhaps one of the most used in practice.
Revised:  The DTW measure is massively used in many practical fields of computer science , and computing the DTW between two sequences is a classical problem in P. Despite extensive efforts to find more efficient algorithms, the best-known algorithm for computing DTW is a long-standing dynamic programming algorithms that require quadratic runtime, which is believed to be optimal, even for the one-dimensional case X = \mathbb{R , which is perhaps one of the most used in practice.
Edit intent: fluency
Original:  The DTW measure is massively used in many practical fields of computer science , and computing the DTW between two sequences is a classical problem in P. Despite extensive efforts to find more efficient algorithms, the best-known algorithm for computing DTW is a long-standing dynamic programming algorithm that requires quadratic runtime, which is believed to be optimal, even for the one-dimensional case X = \mathbb{R , which is perhaps one of the most used in practice.
Revised:  The DTW measure is massively used in many practical fields of computer science , and computing the DTW between two sequences is a classical problem in P. Despite extensive efforts to find more efficient algorithms, the best-known algorithm for computing DTW is a long-standing dynamic programming algorithm that requires quadratic runtime, even for the one-dimensional case X = \mathbb{R , which is perhaps one of the most used in practice.
Edit intent: coherence
Original:  In this paper, we break the nearly 50 years old quadratic time bound for computing DTW  between two sequences of n points in \mathbb{R}, by presenting a deterministic algorithm that runs in O\left( n^2 \log\log\log n / \log\log n \right) time.
Revised:  In this paper, we break the nearly 50 years old quadratic time bound for computing DTW between two sequences of n points in \mathbb{R}, by presenting a deterministic algorithms that run in O\left( n^2 \log\log\log n / \log\log n \right) time.
Edit intent: fluency
Original:  Our algorithm can be extended to work also for higher dimensional spaces X = \mathbb{R}^d, for any constant d, when the underlying distance-metric %DIFDELCMD < \operatorname{dist} %%%  is polyhedral (e.g., L_1, L_\infty).
Revised:  Our algorithms can be extended to work also for higher dimensional spaces X = \mathbb{R}^d, for any constant d, when the underlying distance-metric %DIFDELCMD < \operatorname{dist} %%% is polyhedral (e.g., L_1, L_\infty).
Edit intent: fluency
Original: Dynamic Time Warping (DTW) and Geometric Edit Distance (GED) are basic similarity measures between curves or general temporal sequences (e.g., time series) that are represented as sequences of points in some metric space (X, \mathsf{dist ).
Revised: Dynamic Time Warping (DTW) and Geometric Edit Distance (GED) are basic similarity measures between curves or general temporal sequences (e.g., time series) that are represented as sequences of points in some metric space (X, \mathrm{dist ).
Edit intent: clarity
Original:  The DTW and GED measures are massively used in various fields of computer science and computational biology,
Revised:  The DTW and GED measures are massively used in various fields of computer science , computational biology,
Edit intent: fluency
Original:  consequently , the tasks of computing these measures are among the core problems in P. Despite extensive efforts to find more efficient algorithms, the best-known algorithms for computing the DTW or GED between two sequences of points in X = R^d are long-standing dynamic programming algorithms that require quadratic runtime, even for the one-dimensional case d = 1, which is perhaps one of the most used in practice.
Revised:  and engineering. Consequently , the tasks of computing these measures are among the core problems in P. Despite extensive efforts to find more efficient algorithms, the best-known algorithms for computing the DTW or GED between two sequences of points in X = R^d are long-standing dynamic programming algorithms that require quadratic runtime, even for the one-dimensional case d = 1, which is perhaps one of the most used in practice.
Edit intent: coherence