wanyu/IteraTeR_v2 huggingface dataset:
Original: Consider the following process on a network: Each agent initially holds either opinion emph blue%DIFDELCMD < } %%% orred ;
Revised: Consider the following process on a network: Each agent initially holds either opinion emph %DIFDELCMD < } %%% orred ;
Edit intent: fluency
Original: Consider the following process on a network: Each agent initially holds either opinion emph blue%DIFDELCMD < } %%% orred ;
Revised: Consider the following process on a network: Each agent initially holds either opinion emph blue%DIFDELCMD < } %%% red ;
Edit intent: fluency
Original:  In a nutshell, assume that a densely-connected subset of agents, the core, holds a different opinion from the rest of the network, the periphery .
Revised:  In a nutshell, assume that a densely-connected subset of agents, the core, holds a different opinion from the rest of the network, the periphery .
Edit intent: fluency
Original:  On the one hand, by looking at the 2-Choices dynamics as a simplistic model of competition among opinions in social networks, our theorem sheds light on the influence of the core on the rest of the network, as a function of the core's connectivity towards the latter.
Revised:  On the one hand, by looking at the 2-Choices dynamics as a simplistic model of competition among opinions in social networks, our theorem sheds light on the influence of the core on the rest of the network, as a function of the core's connectivity toward the latter.
Edit intent: fluency
Original:  On the other hand, to the best of our knowledge, we provide the first analytical result which shows a heterogeneous behavior of a simple dynamics as a function of structural parameters of the network.
Revised:  On the other hand, we provide one of the first analytical result which shows a heterogeneous behavior of a simple dynamics as a function of structural parameters of the network.
Edit intent: clarity
Original:  On the other hand, to the best of our knowledge, we provide the first analytical result which shows a heterogeneous behavior of a simple dynamics as a function of structural parameters of the network.
Revised:  On the other hand, to the best of our knowledge, we provide the first analytical results which shows a heterogeneous behavior of a simple dynamics as a function of structural parameters of the network.
Edit intent: fluency
Original: Compromised social media accounts are legitimate user accounts that have been hijacked by a third (malicious ) party and can cause various kinds of damage . Early detection of such compromised accounts is very important in order to control the damage .
Revised: Compromised social media accounts are legitimate user accounts that have been hijacked by a malicious party and can cause various kinds of damage . Early detection of such compromised accounts is very important in order to control the damage .
Edit intent: clarity
Original: Compromised social media accounts are legitimate user accounts that have been hijacked by a third (malicious ) party and can cause various kinds of damage . Early detection of such compromised accounts is very important in order to control the damage .
Revised: Compromised social media accounts are legitimate user accounts that have been hijacked by a third (malicious ) party and can cause various kinds of damage , which makes the detection of these accounts crucial .
Edit intent: clarity
Original:  The framework is built on the observation that users will use language that is measurably different from the language that a hacker (or spammer) would use, when the account is compromised.
Revised:  The framework is built on the observation that users will use language that is measurably different from the language that an attacker would use, when the account is compromised.
Edit intent: clarity
Original:  We use the framework to develop specific algorithms based on language modeling and use the similarity of language models of users and spammers as features in a supervised learning setup to identify compromised accounts.
Revised:  We use the framework to develop specific algorithms based on language modeling and use the similarity of language models of users and attackers as features in a supervised learning setup to identify compromised accounts.
Edit intent: clarity
Original: Compromised social media accounts are legitimate user accounts that have been hijacked by a malicious party and can cause various kinds of damage, which makes the detection of these accounts crucial.
Revised: Compromised accounts on social networks are regular user accounts that have been hijacked by a malicious party and can cause various kinds of damage, which makes the detection of these accounts crucial.
Edit intent: clarity
Original:  The framework is built on the observation that  users will use language that is measurably different from the language that an attacker would use , when the account is compromised.
Revised:  The framework is built on the observation that users will use language that is measurably different from the language that an adversary would use when the account is compromised.
Edit intent: clarity
Original:  We use the framework to develop specific algorithms based on language modeling and use the similarity of language models of users and attackers as features in a supervised learning setup to identify compromised accounts .
Revised:  We use our framework to develop specific algorithms based on language modeling and use the similarity of language models of users and attackers as features in a supervised learning setup to identify compromised accounts .
Edit intent: fluency
Original:  We use the framework to develop specific algorithms based on language modeling and use the similarity of language models of users and attackers as features in a supervised learning setup to identify compromised accounts .
Revised:  We use the framework to develop specific algorithms that use the difference of language models of users and attackers as features in a supervised learning setup to identify compromised accounts .
Edit intent: clarity
Original:  We use the framework to develop specific algorithms based on language modeling and use the similarity of language models of users and attackers as features in a supervised learning setup to identify compromised accounts .
Revised:  We use the framework to develop specific algorithms based on language modeling and use the similarity of language models of users and adversaries as features in a supervised learning setup to identify compromised accounts .
Edit intent: clarity
Original:  We use the framework to develop specific algorithms based on language modeling and use the similarity of language models of users and attackers as features in a supervised learning setup to identify compromised accounts .
Revised:  We use the framework to develop specific algorithms based on language modeling and use the similarity of language models of users and attackers as features in a supervised learning setup .
Edit intent: clarity
Original:  We propose a novel general framework for discovering compromised accounts by semantic analysis of text messages coming out from an account  .
Revised:  We propose a novel general framework for semantic analysis of text messages coming out from an account .
Edit intent: clarity
Original:  We use our framework to develop specific algorithms that use the difference of language models of users and adversaries as features in a supervised learning setup .
Revised:  We propose to use the difference of language models of users and adversaries as features in a supervised learning setup .
Edit intent: clarity
Original:  We } also present a strategy for  computer and a winning strategy for  player in certain conditions.
Revised:  We } also present a strategy for the computer and a winning strategy for player in certain conditions.
Edit intent: fluency
Original:  To our knowledge, this is the first work analyzing the evolutionary causal relationship between the tendency to conform in a culture with tipping points during norm change.
Edit intent: coherence
Original: We present ElPiGraph, a method for approximating data distributions having non-trivial topological features such as the existence of excluded regionsor branching structures.
Revised: Large datasets represented by multidimensional data point clouds often possess non-trivial topological features such as the existence of excluded regionsor branching structures.
Edit intent: clarity
Original: In this paper, we propose a simple neural net that requires only O(nlog_2k) numbers of quantum gates and qubits : Here, n is the number of input parameters, and k is the number of weights applied to these input parameters in the proposed neural net.
Revised: In this paper, we propose a simple neural net that requires only O(nlog_2k) number of qubits and O(nk) quantum gates : Here, n is the number of input parameters, and k is the number of weights applied to these input parameters in the proposed neural net.
Edit intent: clarity
Original: In this paper, we propose a simple neural net that requires only O(nlog_2k) numbers of quantum gates and qubits : Here, n is the number of input parameters, and k is the number of weights applied to these input parameters in the proposed neural net.
Revised: In this paper, we propose a simple neural net that requires only O(nlog_2k) numbers of quantum gates and qubits : Here, n is the number of input parameters, and k is the number of weights applied to these parameters in the proposed neural net.
Edit intent: fluency
Original:  The steps of the gradient descent are described , and then Iris and Breast cancer datasets are used for the numerical simulations.
Revised:  The steps of the gradient descent , and then Iris and Breast cancer datasets are used for the numerical simulations.
Edit intent: clarity
Original:  The steps of the gradient descent are described , and then Iris and Breast cancer datasets are used for the numerical simulations.
Revised:  The steps of the gradient descent are described , and then iris and breast cancer datasets are used for the numerical simulations.
Edit intent: fluency
Original:  The steps of the gradient descent are described , and then Iris and Breast cancer datasets are used for the numerical simulations.
Revised:  The steps of the gradient descent are described , and then Iris and Breast cancer datasets are used for the simulations.
Edit intent: clarity
Original: We present a novel natural language query interface, the FactChecker , aimed at text summaries of relational data sets.
Revised: We present a novel natural language query interface, the AggChecker , aimed at text summaries of relational data sets.
Edit intent: fluency
Original:  Similar in spirit to a spell checker, the FactChecker marks up text passages that seem to be inconsistent with the actual data.
Revised:  Similar in spirit to a spell checker, the AggChecker marks up text passages that seem to be inconsistent with the actual data.
Edit intent: fluency
Original:  In fully automated verification, our tool achieves significantly higher recall and precision than baselines from the areas of natural language query interfaces and fact checking .
Revised:  In fully automated verification, our tool achieves significantly higher recall and precision than baselines from the areas of natural language query interfaces and fact-checking .
Edit intent: fluency
Original:  Moreover, in addition to reduce the contention between stations, the use of TWT may also contribute to take full advantage of other novel mechanisms in the the IEEE 802.11 universe, such as multiuser transmissions, multi-AP cooperation, spatial reuse and coexistence in high-density WLAN scenarios.
Revised:  Moreover, in addition to reduce the contention between stations, the use of TWT may also contribute to take full advantage of other novel mechanisms in the IEEE 802.11 universe, such as multiuser transmissions, multi-AP cooperation, spatial reuse and coexistence in high-density WLAN scenarios.
Edit intent: fluency
Original: Shifting computing architectures from von Neumann to event-based spiking neural networks (SNNs) uncovers new opportunities for low-power processing of real-world problems such as vision or sensorimotor control.
Revised: Shifting computing architectures from von Neumann to event-based spiking neural networks (SNNs) uncovers new opportunities for low-power processing of sensory data in applications such as vision or sensorimotor control.
Edit intent: clarity
Original:  Exploring roads toward cognitive on-chip SNNs requires the design of compact, low-power and versatile experimentation platforms with the key requirement of online learning in order to adapt and learn new features in uncontrolled environments.
Revised:  Exploring roads toward cognitive SNNs requires the design of compact, low-power and versatile experimentation platforms with the key requirement of online learning in order to adapt and learn new features in uncontrolled environments.
Edit intent: clarity
Original:  It leverages an efficient  spike-driven synaptic plasticity (SDSP) learning rule implementation that allows to reach a record density with 0.68\mum^2 per synapse with embedded online learning .
Revised:  It leverages an efficient implementation of the spike-driven synaptic plasticity (SDSP) learning rule implementation that allows to reach a record density with 0.68\mum^2 per synapse with embedded online learning .
Edit intent: clarity
Original:  It leverages an efficient  spike-driven synaptic plasticity (SDSP) learning rule implementation that allows to reach a record density with 0.68\mum^2 per synapse with embedded online learning .
Revised:  It leverages an efficient spike-driven synaptic plasticity (SDSP) learning rule for high-density embedded online learning with only 0.68\mum^2 per synapse with embedded online learning .
Edit intent: clarity
Original:  Emphasis here is to outline an algorithm that can be used to minimize dissipation and dispersion errors for various implicit R-K class of methods while retaining, to a large extent, their inherent improved stability and high accuracy virtues.
Revised:  Emphasis here is to outline an algorithm that can be used to design stable implicit R-K class of methods while retaining, to a large extent, their inherent improved stability and high accuracy virtues.
Edit intent: clarity
Original:  Emphasis here is to outline an algorithm that can be used to minimize dissipation and dispersion errors for various implicit R-K class of methods while retaining, to a large extent, their inherent improved stability and high accuracy virtues.
Revised:  Emphasis here is to outline an algorithm that can be used to minimize dissipation and dispersion errors for various implicit R-K methods for suitable time step with better accuracy virtues.
Edit intent: clarity
Original:  Our formulation yields remarkably simple expressions for time-declining discount rates which generalize the classic Ramsey formula.
Edit intent: coherence
Original:  Furthermore, with the obvious redefinition of the key parameters of the model, the obtained results are directly applicable for estimations of the expected long-term population growth curve in stochastic environments.
Revised:  Furthermore, with the obvious redefinition of the key parameters of the model, obtained results are directly applicable for estimations of the expected long-term population growth curve in stochastic environments.
Edit intent: fluency
Original:  Furthermore, with the obvious redefinition of the key parameters of the model, the obtained results are directly applicable for estimations of the expected long-term population growth curve in stochastic environments.
Revised:  Furthermore, with the obvious redefinition of the key parameters of the model, the obtained results are directly applicable for description of expected long-term population growth curve in stochastic environments.
Edit intent: clarity
Original:  Furthermore, with the obvious redefinition of the key parameters of the model, the obtained results are directly applicable for estimations of the expected long-term population growth curve in stochastic environments.
Revised:  Furthermore, with the obvious redefinition of the key parameters of the model, the obtained results are directly applicable for estimations of the expected long-term population growth in stochastic environments.
Edit intent: clarity
Original:  In this paper , we propose a new approach for passage re-ranking.
Revised: State of the art approaches for (embedding based) unsupervised semantic search exploits either compositional similarity (of a query and a passage) or pair-wise word (or term) similarity (from the query and the passage). By design, word based approaches do not incorporate similarity in the larger context (query/passage), while compositional similarity based approaches are usually unable to take advantage of the most important cues in the context. In this paper , we propose a new approach for passage re-ranking.
Edit intent: coherence
Original:  In this paper , we propose a new approach for passage re-ranking.
Revised:  In this paper we propose a new approach for passage re-ranking.
Edit intent: fluency
Original:  The experiments reported are conducted on two different datasets in both neural and co-occurrence based distributional semantics settings .
Revised:  The experiments reported are conducted on two different benchmarks .
Edit intent: clarity
Original:  We introduce %DIFDELCMD < {\em %%% self functional maps as a novel surface representation that satisfies these properties, translating the geometric problem of surface classification into an algebraic form of classifying matrices.
Revised:  We introduce %DIFDELCMD < {\em %%% Self Functional Maps as a novel surface representation that satisfies these properties, translating the geometric problem of surface classification into an algebraic form of classifying matrices.
Edit intent: fluency
Original:  Thirdly, we observe the fact that features extracted from only single-level are not robust to handle all challenge factors, thus we suggest to get a multi-level confidence score map with deep features in the continuous spatial domain, and we exploit an implicit interpolation model to extract multi-resolution complementary deep features based on different pre-trained CNNs, including both the deep appearance features and deep motion features of the target.
Revised:  Thirdly, we observe the fact that features extracted from only single-level are not robust to handle all challenge factors, thus we suggest to get a multi-level confidence score map with deep features in the continuous spatial domain, and we exploit an implicit interpolation is applied to convert the multi-resolution complementary deep features based on different pre-trained CNNs, including both the deep appearance features and deep motion features of the target.
Edit intent: clarity
Original:  Our approach obtains an absolute gain of 0.3\% and 0.6\% in mean AUC score compare to the top-ranked method on the OTB-2013 and OTB-2015 benchmarks , respectively, and provides a third-best performance with expected average overlap (EAO) score of 29.8\% on the VOT2017 challenge, while operates at frame-rate .
Revised:  Our approach obtains an absolute gain of 0.3\% and 0.6\% in mean AUC score compare to the top-ranked method on the OTB-2013 and OTB-2015 benchmarks respectively, and provides a third-best performance with expected average overlap (EAO) score of 29.8\% on the VOT2017 challenge, while operates at frame-rate .
Edit intent: fluency
Original:  Our approach obtains an absolute gain of 0.3\% and 0.6\% in mean AUC score compare to the top-ranked method on the OTB-2013 and OTB-2015 benchmarks , respectively, and provides a third-best performance with expected average overlap (EAO) score of 29.8\% on the VOT2017 challenge, while operates at frame-rate .
Revised:  Our approach obtains an absolute gain of 0.3\% and 0.6\% in mean AUC score compare to the top-ranked method on the OTB-2013 and OTB-2015 benchmarks , respectively, and obtains a third-best performance with expected average overlap (EAO) score of 29.8\% on the VOT2017 challenge, while operates at frame-rate .
Edit intent: clarity
Original:  Our approach obtains an absolute gain of 0.3\% and 0.6\% in mean AUC score compare to the top-ranked method on the OTB-2013 and OTB-2015 benchmarks , respectively, and provides a third-best performance with expected average overlap (EAO) score of 29.8\% on the VOT2017 challenge, while operates at frame-rate .
Revised:  Our approach obtains an absolute gain of 0.3\% and 0.6\% in mean AUC score compare to the top-ranked method on the OTB-2013 and OTB-2015 benchmarks , respectively, and provides a third-best expected average overlap (EAO) score of 29.8\% on the VOT2017 challenge, while operates at frame-rate .
Edit intent: clarity
Original:  Our approach obtains an absolute gain of 0.3\% and 0.6\% in mean AUC score compare to the top-ranked method on the OTB-2013 and OTB-2015 benchmarks , respectively, and provides a third-best performance with expected average overlap (EAO) score of 29.8\% on the VOT2017 challenge, while operates at frame-rate .
Revised:  Our approach obtains an absolute gain of 0.3\% and 0.6\% in mean AUC score compare to the top-ranked method on the OTB-2013 and OTB-2015 benchmarks , respectively, and provides a third-best performance with expected average overlap (EAO) score of 29.8\% on the VOT-2017 benchmark .
Edit intent: clarity
Original: In this paper , we propose a distributed iterated hard thresholding algorithm termed DiFIGHT over a network that is built on the diffusion mechanism and also propose a modification of the proposed algorithm  termed MoDiFIGHT, that has low complexity in terms of communication in the network.
Revised: In this paper we propose a distributed iterated hard thresholding algorithm termed DiFIGHT over a network that is built on the diffusion mechanism and also propose a modification of the proposed algorithm termed MoDiFIGHT, that has low complexity in terms of communication in the network.
Edit intent: fluency
Original: In this paper , we propose a distributed iterated hard thresholding algorithm termed DiFIGHT over a network that is built on the diffusion mechanism and also propose a modification of the proposed algorithm  termed MoDiFIGHT, that has low complexity in terms of communication in the network.
Revised: In this paper , we propose a distributed iterated hard thresholding algorithm termed DiFIGHT over a network that is built on the diffusion mechanism and also propose a modification of the proposed algorithm , termed MoDiFIGHT, that has low complexity in terms of communication in the network.
Edit intent: fluency
Original:  Also, we present an analysis of the two proposed algorithms and provide provable bounds on their recovery performance with or without using the random node selection strategies.
Revised:  Also, we present analysis of the two proposed algorithms and provide provable bounds on their recovery performance with or without using the random node selection strategies.
Edit intent: fluency
Original:  Finally , we use numerical studies to show that both when the random strategies are used as well as when they are not used, the proposed algorithms display performances far superior to distributed IHT algorithm using consensus mechanism .
Revised:  Finally we use numerical studies to show that both when the random strategies are used as well as when they are not used, the proposed algorithms display performances far superior to distributed IHT algorithm using consensus mechanism .
Edit intent: coherence
Original: We envision a mobile edge computing (MEC) framework for machine learning (ML) technologies, which leverages distributed client data and computation resources for training high-performance ML models while preserving a client privacy.
Revised: We envision a mobile edge computing (MEC) framework for machine learning (ML) technologies, which leverages distributed client data and computation resources for training high-performance ML models while preserving client privacy.
Edit intent: fluency