wanyu/IteraTeR_v2 huggingface dataset:
Original:  We also reviewed  the licenses, the packages community size , and the dependencies used.
Revised:  We also reviewed the licenses, the size of the packages' community , and the dependencies used.
Edit intent: fluency
Original:  Among other things, our results show that forecasting is by far the most  implemented task, that half of the packages provide access to real datasets or allow generating synthetic data, and that many packages depend on a few libraries (the most used ones being numpy, scipy and pandas).
Revised:  Among other things, our results show that forecasting is by far the most frequently implemented task, that half of the packages provide access to real datasets or allow generating synthetic data, and that many packages depend on a few libraries (the most used ones being numpy, scipy and pandas).
Edit intent: clarity
Original:  One of the lessons learned from this review is that the process of finding a given implementation is not inherently simple, and we hope that this review can help practitioners and researchers navigate the space of Python packages dedicated to time series analysis. 
Revised:  We hope that this review can help practitioners and researchers navigate the space of Python packages dedicated to time series analysis. 
Edit intent: coherence
Original: Simple graph algorithms such as PageRank have recently been the target of numerous hardware accelerators.
Revised: Simple graph algorithms such as PageRank have been the target of numerous hardware accelerators.
Edit intent: clarity
Original:  However, they also come with non-straightforward parallelism and complicated memory access patterns.
Revised:  However, they also come with nonstraightforward parallelism and complicated memory access patterns.
Edit intent: fluency
Original:  In this work, we address this  with a simple yet surprisingly powerful observation: operations on sets of vertices, such as intersection or union, form a large part of many complex graph mining algorithms, and can offer rich and simple parallelism at multiple levels.
Revised:  In this work, we address this problem with a simple yet surprisingly powerful observation: operations on sets of vertices, such as intersection or union, form a large part of many complex graph mining algorithms, and can offer rich and simple parallelism at multiple levels.
Edit intent: clarity
Original:  We propose a novel collective learning control method (namely, CILC) that combines Iterative Learning Control (ILC) with a collective input update strategy.
Revised:  We propose a novel collective learning control method that combines iterative learning control (ILC) with a collective input update strategy.
Edit intent: coherence
Original:  We propose a novel collective learning control method (namely, CILC) that combines Iterative Learning Control (ILC) with a collective input update strategy.
Revised:  We propose a novel collective learning control method (namely, CILC) that combines Iterative Learning Control (ILC) with a collective update strategy.
Edit intent: clarity
Original:  This benefit is leveraged by designing a heterogeneous collective, i.e., a different learning law is assigned to each agent.
Revised:  This benefit is achieved by designing a heterogeneous collective, i.e., a different learning law is assigned to each agent.
Edit intent: clarity
Original:  All theoretical results are confirmed in simulations and experiments with two-wheeled-inverted-pendulums robots (TWIPRs) that jointly learn to perform a desired maneuver.
Revised:  All theoretical results are confirmed in simulations and experiments with two-wheeled-inverted-pendulum robots (TWIPRs) that jointly learn to perform a desired maneuver.
Edit intent: fluency
Original:  All theoretical results are confirmed in simulations and experiments with two-wheeled-inverted-pendulums robots (TWIPRs) that jointly learn to perform a desired maneuver.
Revised:  All theoretical results are confirmed in simulations and experiments with two-wheeled-inverted-pendulums robots (TWIPRs) that jointly learn to perform the desired maneuver.
Edit intent: fluency
Original:  Furthermore, its global convergence can be achieved by the circle criterion for time-delayed systems.
Revised:  Furthermore, its global convergence can be guaranteed by the circle criterion for time-delayed systems.
Edit intent: clarity
Original: Data movement between main memory and the processor is a significant contributor to the execution time and energy consumption of memory-intensive applications.
Revised: Data movement between main memory and the processor is a key contributor to the execution time and energy consumption of memory-intensive applications.
Edit intent: clarity
Original:  We introduce pLUTo ( processing-in-memory with lookup table [LUT] operations), a new DRAM substrate that leverages the high area density of DRAM to enable the massively parallel storing and querying of lookup tables (LUTs).
Revised:  We introduce pLUTo ( processing-using-memory with lookup table [LUT] operations), a new DRAM substrate that leverages the high area density of DRAM to enable the massively parallel storing and querying of lookup tables (LUTs).
Edit intent: clarity
Original:  When running a state-of-the-art binary neural network in a single DRAM subarray, pLUTo outperforms the baseline CPU and GPU implementations by 33\times and 8\times, respectively, while simultaneously achieving energy savings of 110%DIFDELCMD < \timesand %%%  80\times  .
Revised:  When running a state-of-the-art binary neural network in a single DRAM subarray, pLUTo outperforms the optimized CPU and GPU implementations by 33\times and 8\times, respectively, while simultaneously achieving energy savings of 110%DIFDELCMD < \timesand %%% 80\times .
Edit intent: clarity
Original:  When running a state-of-the-art binary neural network in a single DRAM subarray, pLUTo outperforms the baseline CPU and GPU implementations by 33\times and 8\times, respectively, while simultaneously achieving energy savings of 110%DIFDELCMD < \timesand %%%  80\times  .
Revised:  When running a state-of-the-art binary neural network in a single DRAM subarray, pLUTo outperforms the baseline CPU and GPU implementations by 33\times %DIFDELCMD < \timesand %%% 80\times .
Edit intent: coherence
Original: Current factory adaptive cruise control (ACC) systems consist of an upper-level planner that computes the optimal trajectory of the vehicle and a low-level controller in charge of executing it.
Revised: Current commercial adaptive cruise control (ACC) systems consist of an upper-level planner that computes the optimal trajectory of the vehicle and a low-level controller in charge of executing it.
Edit intent: clarity
Original: Current factory adaptive cruise control (ACC) systems consist of an upper-level planner that computes the optimal trajectory of the vehicle and a low-level controller in charge of executing it.
Revised: Current factory adaptive cruise control (ACC) systems consist of an upper-level planner controller that decides the optimal trajectory of the vehicle and a low-level controller in charge of executing it.
Edit intent: clarity
Original: Current factory adaptive cruise control (ACC) systems consist of an upper-level planner that computes the optimal trajectory of the vehicle and a low-level controller in charge of executing it.
Revised: Current factory adaptive cruise control (ACC) systems consist of an upper-level planner that computes the optimal trajectory that should be followed, and a low-level controller in charge of executing it.
Edit intent: clarity
Original:  In this paper, we show that the low-level controller can have a significant impact on SS.
Revised:  In this paper, we show that the low-level controller has a significant impact on SS.
Edit intent: clarity
Original:  We find that i) a fast controller improves the SS, ii) a slow controller can result from either insufficient control gains or from an undershooting gas/brake system or both, and iii) although the integral gain is helpful for effective control, the integral windup can cause overshooting, and in turn, undermines the SSof the ACC . Accordingly, we suggest tuning up the proportional/feedforward gain and ensuring the gas/brake is not to undershoot.
Revised:  We find that i) a slow controller deteriorates the SS, ii) a slow controller can result from either insufficient control gains or from an undershooting gas/brake system or both, and iii) although the integral gain is helpful for effective control, the integral windup can cause overshooting, and in turn, undermines the SSof the ACC . Accordingly, we suggest tuning up the proportional/feedforward gain and ensuring the gas/brake is not to undershoot.
Edit intent: clarity
Original:  We find that i) a fast controller improves the SS, ii) a slow controller can result from either insufficient control gains or from an undershooting gas/brake system or both, and iii) although the integral gain is helpful for effective control, the integral windup can cause overshooting, and in turn, undermines the SSof the ACC . Accordingly, we suggest tuning up the proportional/feedforward gain and ensuring the gas/brake is not to undershoot.
Revised:  We find that i) a fast controller improves the SS, (ii) slow controllers are common as they arise from insufficient control gains or from an undershooting gas/brake system or both, and iii) although the integral gain is helpful for effective control, the integral windup can cause overshooting, and in turn, undermines the SSof the ACC . Accordingly, we suggest tuning up the proportional/feedforward gain and ensuring the gas/brake is not to undershoot.
Edit intent: clarity
Original:  We find that i) a fast controller improves the SS, ii) a slow controller can result from either insufficient control gains or from an undershooting gas/brake system or both, and iii) although the integral gain is helpful for effective control, the integral windup can cause overshooting, and in turn, undermines the SSof the ACC . Accordingly, we suggest tuning up the proportional/feedforward gain and ensuring the gas/brake is not to undershoot.
Revised:  We find that i) a fast controller improves the SS, ii) a slow controller can result from either insufficient control gains or from an undershooting gas/brake system or both, and (iii) the integral term in a slow controller causes undesired overshooting which affects the SS . Accordingly, we suggest tuning up the proportional/feedforward gain and ensuring the gas/brake is not to undershoot.
Edit intent: clarity
Original:  The results of this paper are validated both numerically and empirically on commercial cars.
Revised:  The results of this paper are validated both numerically and empirically with data from commercial cars.
Edit intent: clarity
Original:   The protocol is strategyproof for both MA and MP in the sense that they cannot benefit from strategic behavior .
Revised:  The protocol is verifiable for both MA and MP in the sense that they cannot benefit from strategic behavior .
Edit intent: clarity
Original:   The protocol is strategyproof for both MA and MP in the sense that they cannot benefit from strategic behavior .
Revised:  The protocol is strategyproof for both MA and MP in the sense that dishonesty from one party can be detected by the other .
Edit intent: clarity
Original:  The protocol can be readily extended to the more realistic setting with multiple MPs via secure multi-party computation.
Revised:  The protocol can be readily extended to the more general setting with multiple MPs via secure multi-party computation.
Edit intent: clarity
Original:  Specifically, we represent the ideology of a news source on a topic by corpus-contextualized topic embedding utilizing a language model that has been finetuned on recognizing partisanship of the news articles,  and measure the polarization between sources using cosine similarity .
Revised:  Specifically, utilizing a language model that has been finetuned on recognizing partisanship of the news articles, and measure the polarization between sources using cosine similarity .
Edit intent: clarity
Original:  Specifically, we represent the ideology of a news source on a topic by corpus-contextualized topic embedding utilizing a language model that has been finetuned on recognizing partisanship of the news articles,  and measure the polarization between sources using cosine similarity .
Revised:  Specifically, we represent the ideology of a news source on a topic by corpus-contextualized topic embedding utilizing a language model that has been finetuned on recognizing partisanship of the news articles, we represent the ideology of a news corpus on a topic by corpus-contextualized topic embedding and measure the polarization between sources using cosine similarity .
Edit intent: clarity
Original:  Specifically, we represent the ideology of a news source on a topic by corpus-contextualized topic embedding utilizing a language model that has been finetuned on recognizing partisanship of the news articles,  and measure the polarization between sources using cosine similarity .
Revised:  Specifically, we represent the ideology of a news source on a topic by corpus-contextualized topic embedding utilizing a language model that has been finetuned on recognizing partisanship of the news articles, and measure the polarization using cosine distance .
Edit intent: clarity
Original:  We apply our method to a corpus of news about COVID-19 pandemic.
Revised:  We apply our method to a dataset of news articles about the COVID-19 pandemic.
Edit intent: clarity
Original:  Extensive experiments on different news sources and topics demonstrate the effectiveness of our method to precisely capture the topical polarizationand alignment between different news sources.
Revised:  Extensive experiments on different news sources and topics demonstrate the efficacy of our method to precisely capture the topical polarizationand alignment between different news sources.
Edit intent: fluency
Original: Product quantization (PQ) is a popular approach for maximum inner product search (MIPS), which is widely used in ad-hoc retrieval.
Revised: Product quantization (PQ) is a widely used technique for ad-hoc retrieval.
Edit intent: clarity
Original:  and the improvements over non-differentiable baselines are not consistently positive in reality.
Revised:  and the improvements over previous non-supervised baselines are limited in reality.
Edit intent: clarity
Original:  Extensive experiments on 4 real-world datasets validate the effectiveness of our proposed methods .
Revised:  Extensive experiments on 4 real-world datasets , whose results verify the effectiveness of our proposed methods .
Edit intent: clarity
Original:  Extensive experiments on 4 real-world datasets validate the effectiveness of our proposed methods .
Revised:  Extensive experiments on 4 real-world datasets validate the effectiveness of MoPQ .
Edit intent: clarity
Original: Graph Neural Networks (GNNs) have been widely used for the representation learning of various structured graph data , typically through message passing among nodes by aggregating their neighborhood information via different operations .
Revised: Graph Neural Networks (GNNs) have been widely used for the representation learning of various structured graph data .
Edit intent: clarity
Original:  This paper addresses this gap, and presents the first analytical models capable to accurately model the performance of vehicle-to-vehicle communications based on the IEEE 802.
Revised:  This paper addresses this gap, and presents new analytical models that accurately model the performance of vehicle-to-vehicle communications based on the IEEE 802.
Edit intent: clarity
Original:  Experiments on synthetic and real-world data confirm our HIPPer model outperforms HIP and several other baselines on the task of interval-censored inference .
Revised:  Experiments on synthetic and real-world data . We find that on real-world datasets that ourMBP process outperforms HIP for the task of interval-censored inference .
Edit intent: clarity
Original:  Experiments on synthetic and real-world data confirm our HIPPer model outperforms HIP and several other baselines on the task of interval-censored inference .
Revised:  Experiments on synthetic and real-world data confirm our HIPPer model outperforms HIP and several other baselines on the task of popularity prediction .
Edit intent: clarity
Original:  We find that on real-world datasets that ourMBP process outperforms HIP for the task of popularity prediction.
Revised:  We find that on real-world datasets that our MBP process outperforms HIP for the task of popularity prediction.
Edit intent: fluency
Original: We introduce the generalized join the shortest queue model with retrials \textit{ and two infinite capacity orbit queues.
Revised: We introduce the \textit{ and two infinite capacity orbit queues.
Edit intent: clarity
Original: We introduce the generalized join the shortest queue model with retrials \textit{ and two infinite capacity orbit queues.
Revised: We introduce the generalized join the shortest queue model with retrials \textit{generalized join the shortest queue model with retrials and two infinite capacity orbit queues.
Edit intent: fluency
Original:  Useful numerical examples are presented  and shown that the results obtained through the asymptotic analysis and the heuristic approach agreed.
Revised:  Useful numerical examples are presented , and shown that the results obtained through the asymptotic analysis and the heuristic approach agreed.
Edit intent: fluency
Original:  We discuss how well the systems we analyze perform and examine how close to optimality they are.
Revised:  We discuss how well the systems we analyze performs and examine how close to optimality they are.
Edit intent: fluency
Original:  In particular, we answer an open question that was raised in our earlier paper regarding the optimality of the system denoted as P_2 .
Revised:  In particular, we answer an open question that was raised in our earlier paper regarding the optimality of the system denoted as P2 .
Edit intent: clarity
Original:  In this paper, we measure freshness of information using the recently adopted "age of information" performance measure.
Revised:  In this paper, we measure freshness of information using the "age of information" performance measure.
Edit intent: clarity
Original:  In particular, we answer an open question that was raised in 9%DIFDELCMD < ] %%% regarding the optimality of the system denoted as P2 .
Revised:  In particular, 9%DIFDELCMD < ] %%% regarding the optimality of the system denoted as P2 .
Edit intent: clarity
Original:  We consider the problem of channel modeling  with deterministic channel propagation and the related physical characteristics of THz bands, and study the effectiveness of various machine learning algorithms to estimate the channel.
Revised:  We consider the problem of channel modeling with deterministic channel propagation and the related physical characteristics of THz bands, and benchmark various machine learning algorithms to estimate the channel.
Edit intent: clarity
Original:  In a second step, we propose a dynamic version of the TAMP algorithm Logic- Geometric Programming (LGP).
Revised:  In a second step, we propose a dynamic version of the TAMP algorithm Logic-Geometric Programming (LGP).
Edit intent: fluency
Original:  We assess the efficacy of the approach by training the prediction algorithms and testing the framework on the publicly available MoGaze dataset 
Revised:  We assess the efficacy of the approach by training the prediction algorithms and testing the framework on the publicly available MoGaze dataset .
Edit intent: fluency
Original:  Among the many time series learning tasks of great importance, we here focus on semi-supervised learning which benefits of a graph representation of the data.
Revised:  Among the many time series learning tasks of great importance, we here focus on semi-supervised learning based on a graph representation of the data.
Edit intent: clarity
Original:  Two main aspects are involved in this task : A suitable distance measure to evaluate the similarities between time series, and a learning method to make predictions based on these distances.
Revised:  Two main aspects are involved in this task . A suitable distance measure to evaluate the similarities between time series, and a learning method to make predictions based on these distances.
Edit intent: fluency
Original:  These dense representations have been used in efficient text comparison and embedding-based retrieval.
Revised:  These dense representations have been used in efficient text comparison and retrieval.
Edit intent: clarity
Original:  In this paper, we show that machine learning methods can be used to automatically optimize the parameters of the risk score model, provided we have access to exposure and outcome data.
Revised:  In this paper, we show how to automatically learn these parameters from data. Our method needs access to exposure and outcome data.
Edit intent: clarity
Original:  Although this data is already being collected  in an aggregated, privacy-preserving way  by several health authorities, in this paper we limit ourselves to simulated data, so that we can systematically study the different factors that affect the feasibility of the approach.
Revised:  Although this data is already being collected ( in an aggregated, privacy-preserving way by several health authorities, in this paper we limit ourselves to simulated data, so that we can systematically study the different factors that affect the feasibility of the approach.
Edit intent: fluency
Original:  Although this data is already being collected  in an aggregated, privacy-preserving way  by several health authorities, in this paper we limit ourselves to simulated data, so that we can systematically study the different factors that affect the feasibility of the approach.
Revised:  Although this data is already being collected in an aggregated, privacy-preserving way ) by several health authorities, in this paper we limit ourselves to simulated data, so that we can systematically study the different factors that affect the feasibility of the approach.
Edit intent: fluency
Original:  The approach extends to higher dimensions, and we showcase its use by solving a Poisson problem with homogeneneous Dirichlet boundary conditions over the 4D hypercube.
Revised:  The approach extends to higher dimensions, and we showcase its use by solving a Poisson problem with homogeneous Dirichlet boundary conditions over the 4D hypercube.
Edit intent: fluency
Original: Recently, our proposed recurrent neural network (RNN) based all deep learning minimum variance distortionless response (ADL-MVDR) beamformer method yielded superior performance over the conventional MVDR by replacing the matrix inversion and eigenvalue decomposition with two RNNs . In this work, we present a self-attentive RNN beamformer to further improve our previous RNN-based beamformer by leveraging on the powerful modeling capability of self-attention.
Revised: Recently, our proposed recurrent neural network (RNN) based all deep learning minimum variance distortionless response (ADL-MVDR) beamformer method yielded superior performance over the conventional MVDR by replacing the matrix inversion and eigenvalue decomposition with two recurrent neural networks . In this work, we present a self-attentive RNN beamformer to further improve our previous RNN-based beamformer by leveraging on the powerful modeling capability of self-attention.
Edit intent: clarity
Original: When establishing a visual connection between a virtual reality user and an augmented reality user, it is important to consider that the augmented reality user may face a surplus of information.
Revised: When establishing a visual connection between a virtual reality user and an augmented reality user, it is important to consider whether the augmented reality user may face a surplus of information.
Edit intent: style