wanyu/IteraTeR_v2 huggingface dataset:
Original:  The paper offers a new perspective to probe the area of quantization, and the algorithms proposed can outperform existing methods especially under some bit-width reducing scenarios, when the required post-quantization resolution (number of values) is not significantly lower than that of the original vector .
Revised:  The paper offers a new perspective to probe the area of quantization, and the algorithms proposed can outperform existing methods especially under some bit-width reduction scenarios, when the required post-quantization resolution (number of values) is not significantly lower than that of the original vector .
Edit intent: fluency
Original:  The paper offers a new perspective to probe the area of quantization, and the algorithms proposed can outperform existing methods especially under some bit-width reducing scenarios, when the required post-quantization resolution (number of values) is not significantly lower than that of the original vector .
Revised:  The paper offers a new perspective to probe the area of quantization, and the algorithms proposed can outperform existing methods especially under some bit-width reducing scenarios, when the required post-quantization resolution (number of values) is not significantly lower than the original number .
Edit intent: clarity
Original: Accurate cross-layer information is very useful for optimizing and monitoring mobile networks for specific applications.
Revised: Accurate cross-layer information is very useful to optimize mobile networks for specific applications.
Edit intent: clarity
Original:  However,  the wide adoption of end-to-end encryption and  the absence of common standards has made it very difficult to obtain such information by deep packet inspection (DPI) or cross-layer signaling .
Revised:  However, the wide adoption of end-to-end encryption and due to the absence of common standards has made it very difficult to obtain such information by deep packet inspection (DPI) or cross-layer signaling .
Edit intent: coherence
Original:  However,  the wide adoption of end-to-end encryption and  the absence of common standards has made it very difficult to obtain such information by deep packet inspection (DPI) or cross-layer signaling .
Revised:  However, the wide adoption of end-to-end encryption and the absence of cross-layer signaling .
Edit intent: clarity
Original:  In this paper , we present a traffic profiling system as an alternative solution for HTTP adaptive streaming (HAS) traffic .
Revised:  In this paper , we present a traffic profiling solution to passively estimate parameters of HTTP Adaptive Streaming (HAS) traffic .
Edit intent: clarity
Original:  By observing IP packet flows , our machine learning system detects the video flows as well as the play-back buffer state of an HAS client  in real time.
Revised:  By observing IP packet flows , our machine learning system identifies video flows and detects the state of an HAS client in real time.
Edit intent: clarity
Original:  By observing IP packet flows , our machine learning system detects the video flows as well as the play-back buffer state of an HAS client  in real time.
Revised:  By observing IP packet flows , our machine learning system detects the video flows as well as the play-back buffer state of an HAS client 's play-back buffer in real time.
Edit intent: clarity
Original:  Studying 5 classification methods with an extensive dataset for YouTube's mobile client , shows very high accuracy even with a strong variation of link quality.
Revised:  Our experiments with YouTube's mobile client , shows very high accuracy even with a strong variation of link quality.
Edit intent: clarity
Original:  Since this high performance is achieved for a generic feature set at IP level , our approach requires no DPI , works equally with TCP and UDP, and does not interfere with end-to-end encryption.
Revised:  Since this high performance is achieved for a generic feature set , our approach requires no DPI , works equally with TCP and UDP, and does not interfere with end-to-end encryption.
Edit intent: clarity
Original:  Since this high performance is achieved for a generic feature set at IP level , our approach requires no DPI , works equally with TCP and UDP, and does not interfere with end-to-end encryption.
Revised:  Since this high performance is achieved for a generic feature set at IP level , our approach requires no DPI , and does not interfere with end-to-end encryption.
Edit intent: coherence
Original: In many areas of society we rely on competition to better achieve societal goals.
Revised: In many areas of society we rely on competition to achieve abstract societal goals.
Edit intent: clarity
Original:  Ideally, competition motivates effort and efficiently allocates resources.
Revised:  Ideally, this motivates effort and efficiently allocates resources.
Edit intent: clarity
Original:  However, due to imperfect information, competition generally depends on quantitative proxy measures in order to assess performance.
Revised:  However, competition generally depends on quantitative proxy measures in order to assess performance.
Edit intent: coherence
Original:  However, due to imperfect information, competition generally depends on quantitative proxy measures in order to assess performance.
Revised:  However, due to imperfect information, competition generally depends on imperfect proxy measures in order to assess performance.
Edit intent: clarity
Original:  This leads to an increasing use of such quantitative proxies in modern societies.
Edit intent: coherence
Original:  Examples include: in science, the publication count of an author , in healthcare, the number of patients treated  or in business, the profit achieved.
Revised:  Examples include: in science, the publication count of an author ; in healthcare, the number of patients treated or in business, the profit achieved.
Edit intent: fluency
Original:  Examples include: in science, the publication count of an author , in healthcare, the number of patients treated  or in business, the profit achieved.
Revised:  Examples include: in science, the publication count of an author , in healthcare, the number of patients treated ; or in business, the profit achieved.
Edit intent: fluency
Original:  Here, we construct an agent based model to explore  the basic components and dynamics of such a process .
Revised:  Here, we construct an agent based model to explore the basic components and dynamics of proxy based competition .
Edit intent: clarity
Original:  To paraphrase what has become known as Goodhart\textit{  's or Campbell's law: Any proxy measure in a competitive societal system becomes a target for the competing individuals (or groups), promoting corruption of the measure .
Revised:  To paraphrase what has become known as Goodhart\textit{any proxy measure in a competitive societal system becomes a target for the competitors, promoting corruption of the measure 's or Campbell's law: Any proxy measure in a competitive societal system becomes a target for the competing individuals (or groups), promoting corruption of the measure .
Edit intent: fluency
Original:  We find, that an individual level intrinsic motivation towards the societal goal can bound an evolution towards corrupt practices .
Revised:  We find, that an individual level intrinsic motivation towards the societal goal .
Edit intent: clarity
Original:  Overall, the model provides the first sketch of a general theory of proxy based competition in complex societal systems .
Revised:  Overall, the theory offers mechanistic insight to subjects as diverse as the scientific reproducibility crisis and the threat of global warming .
Edit intent: clarity
Original:  Recent works have shown the possibility of generating imperceptibly perturbed image inputs (a.k.a., adversarial examples) to fool well-trained DNN models into making arbitrary predictions.
Revised:  Recent works have shown the possibility of generating imperceptibly perturbed image inputs (a.k.a., adversarial examples) to fool well-trained DNN classifiers into making arbitrary predictions.
Edit intent: clarity
Original:  To address this problem, we propose a training recipe named DeepDefense .
Revised:  To address this problem, we propose a training recipe named "deep defense" .
Edit intent: fluency
Original:  We contribute to the study of this trade-off by the introduction of an abstract machine, inspired by Girard's Geometry of Interaction (GoI), a machine combining token passing and graph rewriting.
Revised:  We contribute to the study of this trade-off , we introduce an abstract machine, inspired by Girard's Geometry of Interaction (GoI), a machine combining token passing and graph rewriting.
Edit intent: coherence
Original:  Analysing time cost of its execution classifies the machine as "efficient" in Accattoli's taxonomy of abstract machines.
Revised:  Analysing time cost of its execution classifies the machine as ``efficient'' in Accattoli's taxonomy of abstract machines.
Edit intent: fluency
Original:  Intuitively, we should connect the detector neuron to the neurons that fire during the patterns, or during subsections ofthem .
Revised:  Intuitively, we should connect the detector neuron to the neurons that fire during (subsections of) the patterns .
Edit intent: coherence
Original:  When increasing the number of patterns, the SNR decreases slowly, and remains acceptable for tens of independent patterns.
Revised:  Surprisingly, when increasing the number of patterns, the SNR decreases slowly, and remains acceptable for tens of independent patterns.
Edit intent: coherence
Original:  Here we investigate how a single  neuron can optimally signal the presence of one given pattern (localist coding), or of either one of several patterns (distributed coding, i.e. the neuron's response is ambiguous but the identity of the pattern could be inferred from the response of multiple neurons) .
Revised:  Here we investigated how a single neuron can optimally signal the presence of one given pattern (localist coding), or of either one of several patterns (distributed coding, i.e. the neuron's response is ambiguous but the identity of the pattern could be inferred from the response of multiple neurons) .
Edit intent: fluency
Original:  Here we investigate how a single  neuron can optimally signal the presence of one given pattern (localist coding), or of either one of several patterns (distributed coding, i.e. the neuron's response is ambiguous but the identity of the pattern could be inferred from the response of multiple neurons) .
Revised:  Here we investigate how a single spiking neuron can optimally signal the presence of one given pattern (localist coding), or of either one of several patterns (distributed coding, i.e. the neuron's response is ambiguous but the identity of the pattern could be inferred from the response of multiple neurons) .
Edit intent: clarity
Original:  Here we investigate how a single  neuron can optimally signal the presence of one given pattern (localist coding), or of either one of several patterns (distributed coding, i.e. the neuron's response is ambiguous but the identity of the pattern could be inferred from the response of multiple neurons) .
Revised:  Here we investigate how a single neuron can optimally respond to one given pattern (localist coding), or of either one of several patterns (distributed coding, i.e. the neuron's response is ambiguous but the identity of the pattern could be inferred from the response of multiple neurons) .
Edit intent: clarity
Original:  Here we investigate how a single  neuron can optimally signal the presence of one given pattern (localist coding), or of either one of several patterns (distributed coding, i.e. the neuron's response is ambiguous but the identity of the pattern could be inferred from the response of multiple neurons) .
Revised:  Here we investigate how a single neuron can optimally signal the presence of one given pattern (localist coding), or to either one of several patterns (distributed coding, i.e. the neuron's response is ambiguous but the identity of the pattern could be inferred from the response of multiple neurons) .
Edit intent: fluency
Original:  Using a ] threshold-free leaky integrate-and-fire (LIF) neuron with time constant \tau, non-plastic unitary synapses and homogeneous Poisson inputs , we derived analytically the signal-to-noise ratio (SNR) of the resulting pattern detector, even in the presence of jitter.
Revised:  Using a ] threshold-free leaky integrate-and-fire (LIF) neuron model with non-plastic unitary synapses and homogeneous Poisson inputs , we derived analytically the signal-to-noise ratio (SNR) of the resulting pattern detector, even in the presence of jitter.
Edit intent: clarity
Original:  Surprisingly, when increasing the number of patterns, the SNR decreases slowly, and remains acceptable for  tens of independent patterns.
Revised:  Surprisingly, when increasing the number of patterns, the SNR decreases slowly, and remains acceptable for several tens of independent patterns.
Edit intent: clarity
Original:  Next, we wondered if spike-timing-dependent plasticity (STDP) could enable a neuron to reach the theoretical optimum.
Revised:  In addition, we investigated whether spike-timing-dependent plasticity (STDP) could enable a neuron to reach the theoretical optimum.
Edit intent: clarity
Original:  Tens of independent patterns could be learned by a single neuron with a low adaptive threshold, in contrast with previous studies, in which higher thresholds led to localist coding only.
Revised:  Tens of independent patterns could be learned by a single neuron using a low adaptive threshold, in contrast with previous studies, in which higher thresholds led to localist coding only.
Edit intent: fluency
Original:  Taken together these results suggest that coincidence detection and STDP are powerful mechanisms,  compatible with distributed coding  .
Revised:  Taken together these results suggest that coincidence detection and STDP are powerful mechanisms, fully compatible with distributed coding .
Edit intent: clarity
Original:  In order to maintain the retention rate and the delivery rate of advertisement, we adopt Deep Neural Network (DNN) to develop a notification/ pop-up recommendation system " Click-sequence-aware Deep Neural Network (CDNN) " enabled by collaborative filtering-based hybrid user behavioral analysis.
Revised:  In order to maintain the retention rate and the delivery rate of advertisement, we adopt Deep Neural Network (DNN) to develop a pop-up recommendation system " Click-sequence-aware Deep Neural Network (CDNN) " enabled by collaborative filtering-based hybrid user behavioral analysis.
Edit intent: coherence
Original:  In order to maintain the retention rate and the delivery rate of advertisement, we adopt Deep Neural Network (DNN) to develop a notification/ pop-up recommendation system " Click-sequence-aware Deep Neural Network (CDNN) " enabled by collaborative filtering-based hybrid user behavioral analysis.
Revised:  In order to maintain the retention rate and the delivery rate of advertisement, we adopt Deep Neural Network (DNN) to develop a notification/ pop-up recommendation system " Click-sequence-aware Deep Neural Network (CDNN) " enabled by collaborative filteringbased hybrid user behavioral analysis.
Edit intent: fluency
Original:  In order to maintain the retention rate and the delivery rate of advertisement, we adopt Deep Neural Network (DNN) to develop a pop-up recommendation system " Clicksequence-aware deeP neural network (DNN)-based Pop-uPs recOmmendation (C-3PO)" enabled by collaborative filteringbased hybrid user behavioral analysis.
Revised:  In order to maintain the retention rate and the delivery rate of advertisement, we adopt Deep Neural Network (DNN) to develop a pop-up recommendation system " Click sequence-aware deeP neural network (DNN)-based Pop-uPs recOmmendation (C-3PO)" enabled by collaborative filteringbased hybrid user behavioral analysis.
Edit intent: fluency
Original:  In order to maintain the retention rate and the delivery rate of advertisement, we adopt Deep Neural Network (DNN) to develop a pop-up recommendation system " Clicksequence-aware deeP neural network (DNN)-based Pop-uPs recOmmendation (C-3PO)" enabled by collaborative filteringbased hybrid user behavioral analysis.
Revised:  In order to maintain the retention rate and the delivery rate of advertisement, we adopt Deep Neural Network (DNN) to develop a pop-up recommendation system " Clicksequence-aware deeP neural network (DNN)-based Pop-uPs recOmmendation (C-3PO)" enabled by collaborative filtering-based hybrid user behavioral analysis.
Edit intent: fluency
Original: Many current approaches to the design of intrusion detec- tion systems apply feature selection in a static, non-adaptive fashion.
Revised: Many current approaches to the design of intrusion detection systems apply feature selection in a static, non-adaptive fashion.
Edit intent: fluency
Original:  Some illustrative numerical experiments with two popular benchmark datasets show that our approach al- lows to adapt to the changes in normal network behaviour and novel attack patterns which have not been experienced before.
Revised:  Some illustrative numerical experiments with two popular benchmark datasets show that our approach allows to adapt to the changes in normal network behaviour and novel attack patterns which have not been experienced before.
Edit intent: fluency
Original: Here, we prove that finding a root of a quadratic polynomial system with non-negative variables is a NP-hard problem .
Revised: Here, we prove that finding a root of a quadratic polynomial equation system is a NP-hard problem .
Edit intent: clarity
Original:  We investigate the impact of this model on the meanand the variance of interference at the origin in comparison with a PPP modelof equal intensity .
Revised:  We study the mean, the variance and the skewness of interference at the origin in comparison with a PPP modelof equal intensity .
Edit intent: clarity
Original:  We investigate the impact of this model on the meanand the variance of interference at the origin in comparison with a PPP modelof equal intensity .
Revised:  We investigate the impact of this model on the meanand the variance of interference at the origin with this deployment model .
Edit intent: clarity
Original:  Even though the pair correlation function becomes much more complex as compared to the PPP, we develop simple models to capture the impact of hardcore distance on the variance of interference  .
Revised:  Even though the pair correlation function becomes complicated, we devise simple formulae to capture the impact of hardcore distance on the variance of interference .
Edit intent: clarity
Original:  We show how to relate the variance of interference due to a lattice to that of a PPP of half intensity under Rayleigh fading.
Revised:  We show how to relate the variance of interference due to a lattice to that of a PPP under Rayleigh fading.
Edit intent: clarity
Original: Data cleaning is critical for effective data analytics on many real-world data collected .
Revised: Effective data analytics on many real-world data collected .
Edit intent: clarity
Original:  In an experiment testing the user' s understanding of the synthesized transformation logic, Unifacta users achieved a success rate about twice that of Flashfill users.
Revised:  In an experiment testing the user' s understanding of the transformation logic, Unifacta users achieved a success rate about twice that of Flashfill users.
Edit intent: clarity
Original:  In an experiment testing the user' s understanding of the synthesized transformation logic, Unifacta users achieved a success rate about twice that of Flashfill users.
Revised:  In an experiment testing the user' s understanding of the synthesized transformation logic, Unifacta users achieved a success rate about twice that of the FlashFill users.
Edit intent: fluency
Original:  Human-in-the-loop tools have been proposed to speed up the process of data transformation, using the Programming By Example (PBE) approach .
Revised:  Programming By Example (PBE) approach .
Edit intent: coherence
Original:  The results show improvements over the state of the art  in saving user effort and enhancing comprehensibility , without loss of efficiency or expressive power.
Revised:  The results show improvements over the state of the art tools in saving user effort and enhancing comprehensibility , without loss of efficiency or expressive power.
Edit intent: clarity
Original:  The results show improvements over the state of the art  in saving user effort and enhancing comprehensibility , without loss of efficiency or expressive power.
Revised:  The results show improvements over the state of the art in saving user verification effort , without loss of efficiency or expressive power.
Edit intent: clarity
Original:  In a user effort study on data sets of various sizes, when the data size grew by a factor of 30, the user effort required by the CLX prototype grew 1.2 x whereas that required by FlashFill grew 9.1 x. In another test assessing the users' understanding of the transformation logic , the CLX users achieved a success rate about twice that of the FlashFill users.
Revised:  In a user effort study on data sets of various sizes, when the data size grew by a factor of 30, the user verification time required by the CLX prototype grew 1.2 x whereas that required by FlashFill grew 9.1 x. In another test assessing the users' understanding of the transformation logic , the CLX users achieved a success rate about twice that of the FlashFill users.
Edit intent: clarity
Original:  In a user effort study on data sets of various sizes, when the data size grew by a factor of 30, the user effort required by the CLX prototype grew 1.2 x whereas that required by FlashFill grew 9.1 x. In another test assessing the users' understanding of the transformation logic , the CLX users achieved a success rate about twice that of the FlashFill users.
Revised:  In a user effort study on data sets of various sizes, when the data size grew by a factor of 30, the user effort required by the CLX prototype grew 1.2 x whereas that required by FlashFill grew 9.1 x. In another test assessing the users' understanding of the transformation logic , the CLX users achieved a success rate about twice that of FlashFill users.
Edit intent: fluency
Original: Geometric matrix completion ~ (GMC) has been proposed for recommendation by integrating the relationship ~ (link) graphs among users/items into matrix completion ~ (MC).
Revised: Geometric matrix completion (GMC) has been proposed for recommendation by integrating the relationship ~ (link) graphs among users/items into matrix completion ~ (MC).
Edit intent: fluency
Original: Geometric matrix completion ~ (GMC) has been proposed for recommendation by integrating the relationship ~ (link) graphs among users/items into matrix completion ~ (MC).
Revised: Geometric matrix completion ~ (GMC) has been proposed for recommendation by integrating the relationship (link) graphs among users/items into matrix completion ~ (MC).
Edit intent: fluency
Original: Geometric matrix completion ~ (GMC) has been proposed for recommendation by integrating the relationship ~ (link) graphs among users/items into matrix completion ~ (MC).
Revised: Geometric matrix completion ~ (GMC) has been proposed for recommendation by integrating the relationship ~ (link) graphs among users/items into matrix completion (MC).
Edit intent: fluency
Original:  Traditional \mbox{GMC methods typically adopt graph regularization to impose smoothness priors for \mbox{MC . Recently, geometric deep learning on graphs ~(\mbox{GDLG ) is proposed to solve the GMC problem, showing better performance than existing GMC methods including traditional graph regularization based methods.
Revised:  Traditional GMC methods typically adopt graph regularization to impose smoothness priors for \mbox{MC . Recently, geometric deep learning on graphs ~(\mbox{GDLG ) is proposed to solve the GMC problem, showing better performance than existing GMC methods including traditional graph regularization based methods.
Edit intent: fluency