wanyu/IteraTeR_v2 huggingface dataset:
Original:  The framework has also been successfully deployed on the recommendation system of a worldwide leading E-Commerce companyAlibaba .
Revised:  The framework has also been successfully deployed on the recommendation system of a worldwide leading e-commerce company, Alibaba Group .
Edit intent: clarity
Original:  Its key advantages are simplicity and no extra overhead, commensurate with the scarce communication resources of LoRaWAN . However, we show that this low-overhead approach is susceptible to a {\em frame delay attack that can be implemented by a combination of stealthy jamming and delayed replay.
Revised:  Its key advantages are simplicity and no extra overhead, commensurate with the scarce communication resources of LoRaWAN . However, we show that this approach is susceptible to a {\em frame delay attack that can be implemented by a combination of stealthy jamming and delayed replay.
Edit intent: clarity
Original:  Its key advantages are simplicity and no extra overhead, commensurate with the scarce communication resources of LoRaWAN . However, we show that this low-overhead approach is susceptible to a {\em frame delay attack that can be implemented by a combination of stealthy jamming and delayed replay.
Revised:  Its key advantages are simplicity and no extra overhead, commensurate with the scarce communication resources of LoRaWAN . However, we show that this low-overhead approach is susceptible to a {\em frame delay attack consisting of malicious frame collision and delayed replay.
Edit intent: clarity
Original:   To address this threat, we propose a SoftLoRa gateway design that integrates a commodity LoRaWAN gateway with a low-power software-defined radio receiver to track the inherent frequency biases of LoRaWAN end devices.
Revised:  To address this threat, we propose a SoftLoRa gateway design that integrates a commodity LoRaWAN gateway and a low-power software-defined radio receiver to track the inherent frequency biases of LoRaWAN end devices.
Edit intent: fluency
Original:   To address this threat, we propose a SoftLoRa gateway design that integrates a commodity LoRaWAN gateway with a low-power software-defined radio receiver to track the inherent frequency biases of LoRaWAN end devices.
Revised:  To address this threat, we propose a SoftLoRa gateway design that integrates a commodity LoRaWAN gateway with a low-power software-defined radio receiver to track the inherent frequency biases of the end devices.
Edit intent: fluency
Original:  We conduct the analysis on point sets sampled from 3D shapes  and train a deep neural network for an unsupervised shape clustering task to learn local and global features for distinguishing shapes relative to a given shape set.
Revised:  We conduct the analysis on point sets sampled from 3D shapes and train a deep neural network for an unsupervised shape clustering task to learn local and global features for distinguishing shapes with respect to a given shape set.
Edit intent: clarity
Original: We make use of a family of primitive securities, in the spirit of Arrow-Debreu, to price and hedge in a model-free way path-dependent exotic derivatives in discrete time.
Revised: We estimate prices of exotic options in a discrete-time model-free way path-dependent exotic derivatives in discrete time.
Edit intent: clarity
Original: We study the problem of "isotropically rounding" a polytope K \subseteq R^n, that is, computing a linear transformation which makes the uniform distribution on the polytope have roughly identity covariance matrix.
Revised: We study the problem of "isotropically rounding" a polytope K \subset R^n, that is, computing a linear transformation which makes the uniform distribution on the polytope have roughly identity covariance matrix.
Edit intent: clarity
Original:  We assume that K is defined by m linear inequalities, with guarantee that rB \subseteq K\subseteq RB, where B is the unit ball.
Revised:  We assume K is defined by m linear inequalities, with guarantee that rB \subseteq K\subseteq RB, where B is the unit ball.
Edit intent: fluency
Original:  We assume that K is defined by m linear inequalities, with guarantee that rB \subseteq K\subseteq RB, where B is the unit ball.
Revised:  We assume that K is defined by m linear inequalities, with guarantee that rB \subset K\subset RB, where B is the unit ball.
Edit intent: clarity
Original:  Since the cost of the rounding preprocessing step is in many cases the bottleneck in improving sampling or volume computation, our results imply these tasks can also be achieved in roughly \tilde{O}(mn^{4.
Revised:  Since the rounding preprocessing step is in many cases the bottleneck in improving sampling or volume computation, our results imply these tasks can also be achieved in roughly \tilde{O}(mn^{4.
Edit intent: clarity
Original:  This improves on the previous bounds of \tilde{O}(mn ^{5\mathrm{polylog}}  (\frac{1}{\varepsilon},\frac{R}{r})+mn^4\delta^{-2}) for volume computation  and \tilde{O}(mn ^{5\mathrm{polylog}}  (\frac{1}{\varepsilon},\frac{R}{r})) for sampling  .
Revised:  This improves on the previous bounds of \tilde{O}(mn \mathrm{polylog}} (\frac{1}{\varepsilon},\frac{R}{r})+mn^4\delta^{-2}) for volume computation and \tilde{O}(mn ^{5\mathrm{polylog}} (\frac{1}{\varepsilon},\frac{R}{r})) for sampling .
Edit intent: fluency
Original:  This improves on the previous bounds of \tilde{O}(mn ^{5\mathrm{polylog}}  (\frac{1}{\varepsilon},\frac{R}{r})+mn^4\delta^{-2}) for volume computation  and \tilde{O}(mn ^{5\mathrm{polylog}}  (\frac{1}{\varepsilon},\frac{R}{r})) for sampling  .
Revised:  This improves on the previous bounds of \tilde{O}(mn ^{5\mathrm{polylog}} (\frac{1}{\varepsilon},\frac{R}{r})+mn^4\delta^{-2}) for volume computation and \tilde{O}(mn \mathrm{polylog}} (\frac{1}{\varepsilon},\frac{R}{r})) for sampling .
Edit intent: fluency
Original:  We achieve this improvement by a novel method of computing polytope membership, where one avoids checking inequalities which are estimated to have a very low probability of being violated.
Revised:  We achieve this improvement by a novel method of computing polytope membership, where one avoids checking inequalities estimated to have a very low probability of being violated.
Edit intent: clarity
Original: We show that the lack of arbitrage in a model with both fixed and proportional transaction costs is equivalent to the existence of a family of absolutely continuous single-step probability measures  together with an adapted process  between the bid-ask spreads that satisfies the martingale property with respect to each of the measures.
Revised: We show that the lack of arbitrage in a model with both fixed and proportional transaction costs is equivalent to the existence of a family of absolutely continuous single-step probability measures , together with an adapted process between the bid-ask spreads that satisfies the martingale property with respect to each of the measures.
Edit intent: fluency
Original:  In this paper, we demonstrate how these two requirements can be satisfied via building a bridge between outfit generation and recommendation.
Revised:  In this paper, we demonstrate these two requirements can be satisfied via building a bridge between outfit generation and recommendation.
Edit intent: fluency
Original:  Through large data analysis, we find that people have similar tastes in individual items and outfits.
Revised:  Through large data analysis, we observe that people have similar tastes in individual items and outfits.
Edit intent: clarity
Original:  Multiple offline and online experiments provide strong quantitative evidence that our framework outperforms alternative methods regarding both compatibility and personalization metrics.
Revised:  Extensive offline and online experiments provide strong quantitative evidence that our framework outperforms alternative methods regarding both compatibility and personalization metrics.
Edit intent: clarity
Original:  As part of this work, we have collected a large-scale dataset consisting of 1.05 million outfits with rich context information, 1.05 billion user click actions from 5.42 million users.
Revised:  As part of this work, we release a large-scale dataset consisting of 1.05 million outfits with rich context information, 1.05 billion user click actions from 5.42 million users.
Edit intent: clarity
Original:  To the best  our knowledge, our dataset is the largest, publicly available, fashion related dataset, and the first to provide user behaviors relating to both outfits and fashion items.
Revised:  To the best of our knowledge, our dataset is the largest, publicly available, fashion related dataset, and the first to provide user behaviors relating to both outfits and fashion items.
Edit intent: fluency
Original:  To the best  our knowledge, our dataset is the largest, publicly available, fashion related dataset, and the first to provide user behaviors relating to both outfits and fashion items.
Revised:  To the best our knowledge, this dataset is the largest, publicly available, fashion related dataset, and the first to provide user behaviors relating to both outfits and fashion items.
Edit intent: fluency
Original:  Therefore, we propose a Personalized Outfit Generation model named POG , which connects user preferences regarding individual items and outfits with Transformer architecture.
Revised:  Therefore, we propose a Personalized Outfit Generation (POG) model , which connects user preferences regarding individual items and outfits with Transformer architecture.
Edit intent: clarity
Original:  Extensive offline and online experiments provide strong quantitative evidence that our framework outperforms alternative methods regarding both compatibility and personalization metrics.
Revised:  Extensive offline and online experiments provide strong quantitative evidence that our method outperforms alternative methods regarding both compatibility and personalization metrics.
Edit intent: clarity
Original:  This is primarily because the conventional mean squared error (MSE) loss cannot reflect auditory perception well.
Revised:  The main reason is that the conventional mean squared error (MSE) loss cannot reflect auditory perception well.
Edit intent: clarity
Original:  This is primarily because the conventional mean squared error (MSE) loss cannot reflect auditory perception well.
Revised:  This is primarily because the conventional mean squared error (MSE) loss cannot represent auditory perception well.
Edit intent: clarity
Original:  Among the human-perception-related metrics, the perceptual evaluation of speech quality (PESQ) is a typical one, and has been proven to provide a high correlation to the quality scores rated by humans.
Revised:  One of the typical hu-man-perception-related metrics, which is the perceptual evaluation of speech quality (PESQ) is a typical one, and has been proven to provide a high correlation to the quality scores rated by humans.
Edit intent: coherence
Original:  Among the human-perception-related metrics, the perceptual evaluation of speech quality (PESQ) is a typical one, and has been proven to provide a high correlation to the quality scores rated by humans.
Revised:  Among the human-perception-related metrics, the perceptual evaluation of speech quality (PESQ) , has been proven to provide a high correlation to the quality scores rated by humans.
Edit intent: coherence
Original:  The inclusion of electrical coupling generally implies the emergence of a supercritical Hopf bifurcation and, hence, neuronal synchrony.
Revised:  The inclusion of electrical coupling generally implies neuronal synchrony by virtue of a supercritical Hopf bifurcation and, hence, neuronal synchrony.
Edit intent: clarity
Original:  However, EEMD is shown to outperform WPT in transfer learning applications with accuracy of up to 84\%.
Revised:  However, our experimental results show that EEMD can outperform WPT in transfer learning applications with accuracy of up to 84\%.
Edit intent: clarity
Original:  We show that such a framework can be utilized to achieve fairness criteria such as equality of opportunity and demographic parity depending on the choice of the desired distribution.
Revised:  We show that such a framework can be tailored to achieve fairness criteria such as equality of opportunity and demographic parity depending on the choice of the desired distribution.
Edit intent: clarity
Original:  However,  DL-based methods also have some critical drawbacks, such as insufficient modeling of user representation and ignoring to distinguish the different types of interactions (i.e., user behavior) among users and items .
Revised:  However, DL-based methods , especially regarding to how to design an effective DL model for sequential recommendation .
Edit intent: coherence
Original: We revisit the task of compressing an ensemble of quantum states  in the one-shot setting.
Revised: We revisit the task of visible compression of an ensemble of quantum states in the one-shot setting.
Edit intent: clarity
Original:  The protocols achieving the best compression use shared entanglement that may be much larger than the original message, while others ( with potentially larger communication cost ) have entanglement cost bounded by the message length .
Revised:  The protocols achieving the best compression use shared entanglement that may be much larger than the original message, while others ( with potentially larger communication cost , have entanglement cost bounded by the message length .
Edit intent: fluency
Original:  Motivated by questions in communication complexity, we lift certain restrictions imposed on compression protocols in tasks such as state-splitting and channel simulation.
Revised:  Motivated by questions in communication complexity, we lift certain restrictions that are placed on compression protocols in tasks such as state-splitting and channel simulation.
Edit intent: clarity
Original:  Moreover, in the presence of  entanglement, the communication cost of compression can be arbitrarily smaller than the entanglement cost.
Revised:  Moreover, in the presence of shared entanglement, the communication cost of compression can be arbitrarily smaller than the entanglement cost.
Edit intent: clarity
Original:  The quantum information cost of the protocol can thus be arbitrarily smaller than the cost of compression without  entanglement.
Revised:  The quantum information cost of the protocol can thus be arbitrarily smaller than the cost of compression without shared entanglement.
Edit intent: clarity
Original:  In this work, we present algorithms that automatically annotates a PEG with labels, and  build their corresponding recovery expressions.
Revised:  In this work, we present algorithms that automatically annotates a PEG with labels, and to build their corresponding recovery expressions.
Edit intent: fluency
Original:  We evaluate these algorithms by using them to generate error recovering parsers for four programming languages: Titan, Pascal, C and Java.
Revised:  We evaluate these algorithms by using them to generate error recovering parsers for four programming languages: Titan, C, Pascal and Java.
Edit intent: fluency
Original:  We generalize their constructionby introducing lifted multiplicity codes , multivariate polynomial codes whose restriction to any line is a codeword of a multiplicity code (Kopparty, Saraf, Yekhanin 2014).
Revised:  We consider a generalization of their construction, which we call lifted multiplicity codes , multivariate polynomial codes whose restriction to any line is a codeword of a multiplicity code (Kopparty, Saraf, Yekhanin 2014).
Edit intent: clarity
Original:  We generalize their constructionby introducing lifted multiplicity codes , multivariate polynomial codes whose restriction to any line is a codeword of a multiplicity code (Kopparty, Saraf, Yekhanin 2014).
Revised:  We generalize their constructionby introducing lifted multiplicity codes . These are multivariate polynomial codes whose restriction to any line is a codeword of a multiplicity code (Kopparty, Saraf, Yekhanin 2014).
Edit intent: coherence
Original:   We find that some graphs perform on par with the unbiased baseline for most genes with a significantly smaller feature set .
Revised:  We find some graphs capture relevant dependencies for most genes with a significantly smaller feature set .
Edit intent: clarity
Original:  The EDSM problem has recently received some attention in the combinatorial pattern matching community, and an O (nm^{1.
Revised:  An O (nm^{1.
Edit intent: coherence
Original:  Our starting point is a conditional lower bound for the EDSMproblem .
Revised:  Our starting point is a conditional lower bound for EDSM .
Edit intent: clarity
Original:  We use the popular combinatorial Boolean matrix multiplication (BMM) conjecture stating that there is no truly subcubic combinatorial algorithm for BMM [Abboud and Williams, FOCS 2014].
Revised:  We use the popular combinatorial Boolean Matrix Multiplication (BMM) conjecture stating that there is no truly subcubic combinatorial algorithm for BMM [Abboud and Williams, FOCS 2014].
Edit intent: fluency
Original:  By designing an appropriate reduction we show that a combinatorial algorithm solving the EDSM problem in \mathcal{O ^{1.5 -\epsilon }+N) time, for any \epsilon >0, refutes this conjecture.
Revised:  By designing an appropriate reduction we show that a combinatorial algorithm solving the EDSM problem in \mathcal{O ^{1.5 -\epsilon }+N) time, for any e >0, refutes this conjecture.
Edit intent: clarity
Original:  Of course, the notion of combinatorial algorithms is not clearly defined, so our reduction should be understood as an indication that decreasing the exponent requires fast matrix multiplication.
Revised:  Our reduction should be understood as an indication that decreasing the exponent requires fast matrix multiplication.
Edit intent: coherence
Original:  Two standard tools used in algorithms on strings are string periodicity and fast Fourier transform  .
Revised:  String periodicity and fast Fourier transform .
Edit intent: clarity
Original:  Our main technical contribution is that we successfully combine these tools with fast matrix multiplication to design a non-combinatorial \mathcal{O \tilde{O} ^{ 1.381 }+N)-time algorithm for EDSM  . To the best of our knowledge, we are the first to do so ] .
Revised:  Our main technical contribution is that we successfully combine these tools with fast matrix multiplication to design a non-combinatorial \tilde{O} ^{ 1.381 }+N)-time algorithm for EDSM . To the best of our knowledge, we are the first to do so ] .
Edit intent: coherence
Original:  It is seen that in this setting, some methods , including all so-called energy stable methods but also some fully implicit methods, require asymptotically more time steps than others.
Revised:  It is seen that in this setting, definite statements about the relative behaviour of time stepping methods can be made. Some methods , including all so-called energy stable methods but also some fully implicit methods, require asymptotically more time steps than others.
Edit intent: clarity
Original:  The  temporal second order accuracy for the Navier-Stokes step is achieved via an Artificial Compressibility (AC) scheme with bootstrapping.
Revised:  The temporal second order accuracy is achieved via an Artificial Compressibility (AC) scheme with bootstrapping.
Edit intent: clarity
Original:  The entire scheme is implemented in parallel using a domain decomposition iteration, and  direction splitting approach for the local solves  .
Revised:  The entire scheme is implemented in parallel using a domain decomposition iteration, and a direction splitting approach for the local solves .
Edit intent: fluency
Original: Extreme multi-label  classification (XMC) aims to assign to an instance the most relevant subset of labels from a colossal label set.
Revised: Extreme multi-label classification (XMC) aims to tag each input text with the most relevant subset of labels from a colossal label set.
Edit intent: clarity
Original: Extreme multi-label text classification (XMC) aims to tag each input text with the most relevant labels from an extremely large label set, such as those that arise in product categorization and e-commerce recommendation .
Revised: Extreme multi-label text classification (XMC) concerns tagging input text with the most relevant labels from an extremely large label set, such as those that arise in product categorization and e-commerce recommendation .
Edit intent: clarity
Original: Extreme multi-label text classification (XMC) aims to tag each input text with the most relevant labels from an extremely large label set, such as those that arise in product categorization and e-commerce recommendation .
Revised: Extreme multi-label text classification (XMC) aims to tag each input text with the most relevant labels from an extremely large set .
Edit intent: coherence
Original:  Recently, pretrained language representation models such as BERT achieve remarkable state-of-the-art performance across a wide range of NLP tasks including sentence classification among small label sets (typically fewer than thousands).
Revised:  Recently, pre-trained language representation models such as BERT achieve remarkable state-of-the-art performance across a wide range of NLP tasks including sentence classification among small label sets (typically fewer than thousands).
Edit intent: fluency
Original:  Recently, pretrained language representation models such as BERT achieve remarkable state-of-the-art performance across a wide range of NLP tasks including sentence classification among small label sets (typically fewer than thousands).
Revised:  Recently, pretrained language representation models such as BERT (Bidirectional Encoder Representations from Transformers) have been shown to achieve outstanding performance on many NLP tasks including sentence classification among small label sets (typically fewer than thousands).
Edit intent: clarity
Original:  Recently, pretrained language representation models such as BERT achieve remarkable state-of-the-art performance across a wide range of NLP tasks including sentence classification among small label sets (typically fewer than thousands).
Revised:  Recently, pretrained language representation models such as BERT achieve remarkable state-of-the-art performance across a wide range of NLP tasks including sentence classification with small label sets (typically fewer than thousands).
Edit intent: clarity
Original:  Indeed , there are several challenges in applying BERT to the XMC problem .
Revised:  However , there are several challenges in applying BERT to the XMC problem .
Edit intent: coherence
Original:  Indeed , there are several challenges in applying BERT to the XMC problem .
Revised:  Indeed , there are several challenges in extending BERT to the XMC problem .
Edit intent: clarity
Original:  The main challenges are: (i) the difficulty of capturing dependencies and correlations among labels, whose features may come from heterogeneous sources, and (ii) the tractability to scale to the extreme label setting as the model size can be very large and scale linearly with the size of the output space.
Revised:  The main challenges are: (i) the difficulty of capturing dependencies or correlations among labels, whose features may come from heterogeneous sources, and (ii) the tractability to scale to the extreme label setting as the model size can be very large and scale linearly with the size of the output space.
Edit intent: fluency
Original:  The main challenges are: (i) the difficulty of capturing dependencies and correlations among labels, whose features may come from heterogeneous sources, and (ii) the tractability to scale to the extreme label setting as the model size can be very large and scale linearly with the size of the output space.
Revised:  The main challenges are: (i) the difficulty of capturing dependencies and correlations among labels, whose features may come from heterogeneous sources, and (ii) the tractability to scale to the extreme label setting as the model size can be very large and scale linearly with the output space.
Edit intent: clarity