wanyu/IteraTeR_v2 huggingface dataset:
Original:  While serving a VU from multiple APs increases the reliability and the spectral efficiency of the assisted users,  an accurate power allocation has to be maintained for each of the transmission time slots.
Revised:  While this increases the reliability and the spectral efficiency of the assisted users, an accurate power allocation has to be maintained for each of the transmission time slots.
Edit intent: clarity
Original:  While serving a VU from multiple APs increases the reliability and the spectral efficiency of the assisted users,  an accurate power allocation has to be maintained for each of the transmission time slots.
Revised:  While serving a VU from multiple APs increases the reliability and the spectral efficiency of the assisted users, it also necessitates an accurate power allocation has to be maintained for each of the transmission time slots.
Edit intent: coherence
Original:  While serving a VU from multiple APs increases the reliability and the spectral efficiency of the assisted users,  an accurate power allocation has to be maintained for each of the transmission time slots.
Revised:  While serving a VU from multiple APs increases the reliability and the spectral efficiency of the assisted users, an accurate power allocation in all transmission time slots.
Edit intent: clarity
Original:  Therefore, it is essential to serve the users with the optimal power level of the APs.
Edit intent: coherence
Original:  As such, we jointly formulate user association and power allocation problems to achieve enhanced reliability and weighted user sum rate.
Revised:  As such, a joint user association and power allocation problems to achieve enhanced reliability and weighted user sum rate.
Edit intent: clarity
Original:  As such, we jointly formulate user association and power allocation problems to achieve enhanced reliability and weighted user sum rate.
Revised:  As such, we jointly formulate user association and power allocation problem is formulated to achieve enhanced reliability and weighted user sum rate.
Edit intent: clarity
Original:  However, the formulated problem is a difficult combinatorial problemand thus, it is remarkably hard to solve.
Revised:  However, the formulated problem is a complex combinatorial problem, remarkably hard to solve.
Edit intent: clarity
Original:  Therefore, we use fine-grained machine learning algorithms  to efficiently optimize joint user associations and power allocations of the APs in a highly mobile vehicular network.
Revised:  Therefore, fine-grained machine learning algorithms to efficiently optimize joint user associations and power allocations of the APs in a highly mobile vehicular network.
Edit intent: coherence
Original:  Therefore, we use fine-grained machine learning algorithms  to efficiently optimize joint user associations and power allocations of the APs in a highly mobile vehicular network.
Revised:  Therefore, we use fine-grained machine learning algorithms are used to efficiently optimize joint user associations and power allocations of the APs in a highly mobile vehicular network.
Edit intent: clarity
Original:  We introduce a distributed single-agent reinforcement learning algorithm, namely SARL-MARL,  which obtains nearly identical genie-aided optimal solutions within  nominal number of training episodes than the baseline solution.
Revised:  Furthermore, a distributed single-agent reinforcement learning algorithm, namely SARL-MARL, which obtains nearly identical genie-aided optimal solutions within nominal number of training episodes than the baseline solution.
Edit intent: coherence
Original:  We introduce a distributed single-agent reinforcement learning algorithm, namely SARL-MARL,  which obtains nearly identical genie-aided optimal solutions within  nominal number of training episodes than the baseline solution.
Revised:  We introduce a distributed single-agent reinforcement learning algorithm, namely SARL-MARL, which obtains nearly identical genie-aided optimal solutions within a nominal number of training episodes than the baseline solution.
Edit intent: fluency
Original:  Simulation results validate that our proposed RL approach outperforms existing schemes and can attain genie-aided optimal performances.
Revised:  Simulation results validate that our solution outperforms existing schemes and can attain genie-aided optimal performances.
Edit intent: clarity
Original:  Since DNN training is incredibly computationally expensive, there is great interest in speeding up  convergence.
Revised:  Since DNN training is incredibly computationally expensive, there is great interest in speeding up the convergence.
Edit intent: fluency
Original:  Furthermore, on both CIFAR and ImageNet, SRSGD reaches similar or even better error rates with  fewer training epochs compared to the SGD baseline.
Revised:  Furthermore, on both CIFAR and ImageNet, SRSGD reaches similar or even better error rates with significantly fewer training epochs compared to the SGD baseline.
Edit intent: clarity
Original: All proper scoring rules incentivize an expert to predict accurately (report their true estimate), but not all proper scoring rules equally incentivize precision . Rather than consider the expert's belief as exogenously given, we consider a model where a rational expert can endogenously refine their belief by repeatedly paying a fixed cost, and is incentivized to do so by a proper scoring rule.
Revised: All proper scoring rules incentivize an expert to predict accurately (report their true estimate), but not all proper scoring rules equally incentivize precision . Rather than consider the expert's belief as exogenously given, we consider a model where a rational expert can endogenously refine their belief by repeatedly paying a fixed cost, and is incentivized to do so by a proper scoring rule.
Edit intent: fluency
Original: All proper scoring rules incentivize an expert to predict accurately (report their true estimate), but not all proper scoring rules equally incentivize precision . Rather than consider the expert's belief as exogenously given, we consider a model where a rational expert can endogenously refine their belief by repeatedly paying a fixed cost, and is incentivized to do so by a proper scoring rule.
Revised: All proper scoring rules incentivize an expert to predict accurately (report their true estimate), but not all proper scoring rules equally incentivize precision . Rather than treating the expert's belief as exogenously given, we consider a model where a rational expert can endogenously refine their belief by repeatedly paying a fixed cost, and is incentivized to do so by a proper scoring rule.
Edit intent: fluency
Original:  Specifically, our expert aims to predict the probability that a biased coin flipped tomorrow will land heads or tails , and can flip the coin any number of times today at a cost of c per flip.
Revised:  Specifically, our expert aims to predict the probability that a biased coin flipped tomorrow will land heads , and can flip the coin any number of times today at a cost of c per flip.
Edit intent: clarity
Original:  Our first main result defines an incentivization index for proper scoring rules, and proves that this index measures the expected error of the expert's estimate (where the number of flips today is chosen adaptively to maximize the predictor's expected payoff).
Revised:  Our first main result defines an incentivization index for proper scoring rules, and proves that this index measures the expected error of the expert's estimate (where the number of flips today is chosen adaptively to maximize the predictor's expected payoff).
Edit intent: fluency
Original:  In contrast, even dropping all fairness requirements, there is no truthful allocation mechanism (without money) that maximizes welfare when players have XOS valuationswith dichotomous marginals .
Revised:  We then show that our mechanism with random priorities is envy-free ex-ante, while having all the above properties ex-post. Furthermore, we present several impossibility results precluding similar results for the larger class of XOS valuations .
Edit intent: coherence
Original: This paper introduces two subcycling algorithms for particle orbits in variational, geometric particle-in-cell methods that address the Vlasov-Maxwell system in magnetized plasmas.
Revised: This paper introduces two subcycling algorithms for particle orbits in variational, geometric particle-in-cell methods that address the Vlasov--Maxwell system in magnetized plasmas.
Edit intent: fluency
Original:  Both algorithms retain the electromagnetic gauge invariance of the discrete action, guaranteeing a local charge conservation law, and the variational approach provides a bounded long-time energy behaviour .
Revised:  Both algorithms retain the electromagnetic gauge invariance of the discrete action, guaranteeing a local charge conservation law, and the variational approach provides a bounded long-time energy behavior .
Edit intent: fluency
Original: This paper introduces two subcycling algorithms for particle orbits in variational, geometric particle-in-cell methods that address the Vlasov--Maxwell system in magnetized plasmas.
Revised: This paper introduces two subcycling algorithms for particle orbits in variational, geometric particle-in-cell methods addressing the Vlasov--Maxwell system in magnetized plasmas.
Edit intent: clarity
Original:  The purpose of subcycling is to allow for time steps in the global field solves at or longer than the gyroperiod time scale while sampling the local particle cyclotron orbits accurately.
Revised:  The purpose of subcycling is to allow for time steps in the global field solves at or longer than the gyroperiod time scale while sampling the local cyclotron orbits accurately.
Edit intent: clarity
Original:  Both  algorithms retain the electromagnetic gauge invariance of the discrete action, guaranteeing a local charge conservation law, and the variational approach provides a bounded long-time energy behavior.
Revised:  Both our algorithms retain the electromagnetic gauge invariance of the discrete action, guaranteeing a local charge conservation law, and the variational approach provides a bounded long-time energy behavior.
Edit intent: clarity
Original:  The requirement for gauge invariance  leads to a peculiar subcycling scheme where the magnetic field is orbit-averaged and the effect of the electric field on the particle orbits is evaluated once during the sybcycling period.
Revised:  The requirement for gauge invariance , however, leads to a peculiar subcycling scheme where the magnetic field is orbit-averaged and the effect of the electric field on the particle orbits is evaluated once during the sybcycling period.
Edit intent: coherence
Original:  The requirement for gauge invariance  leads to a peculiar subcycling scheme where the magnetic field is orbit-averaged and the effect of the electric field on the particle orbits is evaluated once during the sybcycling period.
Revised:  The requirement for gauge invariance leads to a peculiarity in the particle push: the magnetic field is orbit-averaged and the effect of the electric field on the particle orbits is evaluated once during the sybcycling period.
Edit intent: clarity
Original:  The requirement for gauge invariance  leads to a peculiar subcycling scheme where the magnetic field is orbit-averaged and the effect of the electric field on the particle orbits is evaluated once during the sybcycling period.
Revised:  The requirement for gauge invariance leads to a peculiar subcycling scheme where the magnetic field is orbit-averaged but the effect of the electric field on the particle orbits is evaluated once during the sybcycling period.
Edit intent: coherence
Original:  The requirement for gauge invariance  leads to a peculiar subcycling scheme where the magnetic field is orbit-averaged and the effect of the electric field on the particle orbits is evaluated once during the sybcycling period.
Revised:  The requirement for gauge invariance leads to a peculiar subcycling scheme where the magnetic field is orbit-averaged and the effect of the electric field is evaluated only once during the sybcycling period.
Edit intent: clarity
Original:  The requirement for gauge invariance  leads to a peculiar subcycling scheme where the magnetic field is orbit-averaged and the effect of the electric field on the particle orbits is evaluated once during the sybcycling period.
Revised:  The requirement for gauge invariance leads to a peculiar subcycling scheme where the magnetic field is orbit-averaged and the effect of the electric field on the particle orbits is evaluated once during the subcycling period.
Edit intent: fluency
Original:  Numerical tests with this algorithm indicate that artificial oscillations may occur if the relative electric field impulse on the particles grows large.
Revised:  Numerical tests then indicate a possibility of artificial oscillations if the relative electric field impulse on the particles grows large.
Edit intent: clarity
Original:  The second algorithm , a fully implicit one, is proposed to remedy the possible issues of the semi-explicit algorithm.
Revised:  The second algorithm , a fully implicit one, is proposed to remedy the possible issues of the first algorithm.
Edit intent: clarity
Original:  It is observed that both  magnetic and electric field can be orbit-averaged , the gauge invariance and consequently the charge conservation retained, while the algorithm remains variational.
Revised:  It is observed that both the magnetic and electric field can be orbit-averaged , the gauge invariance and consequently the charge conservation retained, while the algorithm remains variational.
Edit intent: fluency
Original:  It is observed that both  magnetic and electric field can be orbit-averaged , the gauge invariance and consequently the charge conservation retained, while the algorithm remains variational.
Revised:  It is observed that both magnetic and electric impulses on particle motion can be orbit-averaged , the gauge invariance and consequently the charge conservation retained, while the algorithm remains variational.
Edit intent: clarity
Original: This paper introduces two subcycling algorithms for particle orbits in variational, geometric particle-in-cell methods addressing the Vlasov--Maxwell system in magnetized plasmas.
Revised: This paper investigates subcycling of particle orbits in variational, geometric particle-in-cell methods addressing the Vlasov--Maxwell system in magnetized plasmas.
Edit intent: clarity
Original:  The purpose of subcycling is to allow different time steps for different particle species and ideally time steps longer than the electron gyroperiod for the global field solves while sampling the local cyclotron orbits accurately.
Revised:  The purpose of subcycling is to allow different time steps for different particle species and , ideally, time steps longer than the electron gyroperiod for the global field solves while sampling the local cyclotron orbits accurately.
Edit intent: fluency
Original:  Both our algorithms retain the electromagnetic gauge invariance of the discrete action, guaranteeing a local charge conservation law, and the variational approach provides a bounded long-time energy behavior .
Revised:  The considered algorithms retain the electromagnetic gauge invariance of the discrete action, guaranteeing a local charge conservation law, and the variational approach provides a bounded long-time energy behavior .
Edit intent: clarity
Original:  Both our algorithms retain the electromagnetic gauge invariance of the discrete action, guaranteeing a local charge conservation law, and the variational approach provides a bounded long-time energy behavior .
Revised:  Both our algorithms retain the electromagnetic gauge invariance of the discrete action, guaranteeing a local charge conservation law, while the variational approach provides a bounded long-time energy behavior .
Edit intent: coherence
Original:  Simulations under a variety of settings demonstrate the competitive performance of our decomposition-based method, called LCD-AMP, in comparison with the (modified version of) PC-like algorithm.
Revised:  Simulations under a variety of settings demonstrate the competitive performance of our decomposition-based method, called LCD-AMP, in comparison with the (modified versions of) PC-like algorithm.
Edit intent: fluency
Original:  We empirically show that the results of both algorithms are more accurate and stable when the sample size is reasonably large and the underlying graph is sparse.
Revised:  We empirically show that the results of both algorithms are more accurate and stabler when the sample size is reasonably large and the underlying graph is sparse.
Edit intent: clarity
Original:  Our key conclusionis that , regardless of whether a hyperbolic or an exponentialmodel is employed , quantized versions are a better fit to the experimental data than their continuous versions .
Revised:  In conclusion , regardless of whether a hyperbolic or an exponentialmodel is employed , quantized versions are a better fit to the experimental data than their continuous versions .
Edit intent: clarity
Original:  Our key conclusionis that , regardless of whether a hyperbolic or an exponentialmodel is employed , quantized versions are a better fit to the experimental data than their continuous versions .
Revised:  Our key conclusionis that , regardless of hyperbolic or exponential , quantized versions are a better fit to the experimental data than their continuous versions .
Edit intent: clarity
Original:  Our key conclusionis that , regardless of whether a hyperbolic or an exponentialmodel is employed , quantized versions are a better fit to the experimental data than their continuous versions .
Revised:  Our key conclusionis that , regardless of whether a hyperbolic or an exponentialmodel is employed , quantized versions of these models are better fit to the experimental data than their continuous versions .
Edit intent: clarity
Original:  Our key conclusionis that , regardless of whether a hyperbolic or an exponentialmodel is employed , quantized versions are a better fit to the experimental data than their continuous versions .
Revised:  Our key conclusionis that , regardless of whether a hyperbolic or an exponentialmodel is employed , quantized versions are a better fit to the experimental data than their continuous forms .
Edit intent: clarity
Original:  While artificial neural networks have led to significant improvements in different tasks in cold start knowledge graph population , the overall F1 of the  system remains quite low.
Revised:  While artificial neural networks have led to significant improvements in the different tasks that are part of KBP , the overall F1 of the system remains quite low.
Edit intent: clarity
Original:  This problem is more acute in personal knowledge graph population which presents additional challenges with regard to data protection, fairness and privacy.
Revised:  This problem is more acute in personal knowledge bases, which present additional challenges with regard to data protection, fairness and privacy.
Edit intent: clarity
Original:  The transition to chaos in the two models do not coincide and have qualitatively different causes.
Revised:  The transitions to chaos in the two models do not coincide and have qualitatively different causes.
Edit intent: fluency
Original: Neurons communicate with spikes, which are discrete events in time.
Revised: Cortical neurons communicate with spikes, which are discrete events in time.
Edit intent: clarity
Original: Cortical neurons communicate with spikes, which are discrete events in time .
Revised: Neurons in the brain communicate with spikes, which are discrete events in time .
Edit intent: clarity
Original: We present a certified two-step parameterized Model Order Reduction (pMOR) technique for wave equation and elastodynamic Partial Differential Equations (PDE) . pMOR techniques for parameterized time domain PDEs offer opportunities for faster solution estimation.
Revised: We present a two-level parameterized Model Order Reduction (pMOR) technique for wave equation and elastodynamic Partial Differential Equations (PDE) . pMOR techniques for parameterized time domain PDEs offer opportunities for faster solution estimation.
Edit intent: clarity
Original:  Towards that end, we develop a two-step Port-Reduced Reduced-Basis Component approach (PR-RBC) for linear hyperbolic time domain PDEs.
Revised:  Towards that end, we develop a two-step Port-Reduced Reduced-Basis Component (PR-RBC) for linear hyperbolic time domain PDEs.
Edit intent: clarity
Original: We study stochastic combinatorial optimization problems where the objective is to minimize the expected maximum load (a.k.a.  the makespan).
Revised: We study stochastic combinatorial optimization problems where the objective is to minimize the expected maximum load (a.k.a. \ the makespan).
Edit intent: fluency
Original:  Specifically, we give an O(\log\log m)-approximation algorithm for all these problems.
Edit intent: coherence
Original:  We also show that this LP has an \Omega(\log^* m) integrality gap  even for the problem of selecting intervals on a line .
Revised:  We also show that this LP has an \Omega(\log^* m) integrality gap , even for the problem of selecting intervals on a line .
Edit intent: fluency
Original: We consider the minimum set cover problem in a dynamic setting.
Revised: In the dynamic minimum set cover problem in a dynamic setting.
Edit intent: clarity
Original:  Let ndenote the }  number of sets in S, and let m and f respectively denote the maximum number of elements in the universe and the maximum frequency of an element across all the updates.
Revised:  Let ndenote the } number of sets , number of elements in the universe and the maximum frequency of an element across all the updates.
Edit intent: clarity
Original:  On the other hand ] , the line of work by Bhattacharya et al.
Revised:  On the other hand ] , the line of work by 
Edit intent: clarity
Original:  ICALP `15%DIFDELCMD < ]%%% , Bhattacharya et al.
Revised:  %DIFDELCMD < ]%%% , Bhattacharya et al.
Edit intent: coherence
Original:  ICALP `15%DIFDELCMD < ]%%% , Bhattacharya et al.
Revised:  ICALP `15%DIFDELCMD < ]%%% 
Edit intent: coherence
Original:  IPCO `17%DIFDELCMD < ]%%% , Gupta et al.
Revised:  %DIFDELCMD < ]%%% , Gupta et al.
Edit intent: coherence
Original:  IPCO `17%DIFDELCMD < ]%%% , Gupta et al.
Revised:  IPCO `17%DIFDELCMD < ]%%% Gupta et al.
Edit intent: fluency
Original:  [STOC ` 17], Abboud et al.
Revised:  [STOC ' 17], Abboud et al.
Edit intent: fluency
Original:  [STOC ` 19]  and Bhattacharya et al.
Revised:  [STOC ' 19] and Bhattacharya et al.
Edit intent: fluency
Original:  [STOC ` 19]  and Bhattacharya et al.
Revised:  [STOC ` 19] , and Bhattacharya et al.
Edit intent: fluency
Original: Spatio-temporal information is increasingly used for driving a plethora of intelligent transportation, smart-city, and crowd-sensing applications.
Revised: Spatio-temporal information is used for driving a plethora of intelligent transportation, smart-city, and crowd-sensing applications.
Edit intent: clarity
Original:  At the same time, different types of data marketplaces are proposed for de-siloing and monetising individual and enterprise data .
Revised:  Since data is now considered a valuable production factor, data marketplaces have appeared to help individuals and enterprises bring it to market to satisfy the ever-growing demand. In such marketplaces, several sources may need to combine their data in order to meet the requirements of different applications .
Edit intent: coherence
Original:  Applying the Shapley value to large datasets from many sources is  computationally challenging.
Revised:  Applying the Shapley value to large datasets from many sources is , of course, computationally challenging.
Edit intent: coherence