wanyu/IteraTeR_v2 huggingface dataset:
Original: The first attempt to obtain market directional information from non--stationary solution of the dynamic equation 1 "future price tend to the value maximizing the number of shares traded per unit time"  is presented.
Revised: The first attempt to obtain market directional information from non--stationary solution of the dynamic equation 1 "future price tends to the value maximizing the number of shares traded per unit time" is presented.
Edit intent: fluency
Original: The first attempt to obtain market directional information from non--stationary solution of the dynamic equation 1 "future price tend to the value maximizing the number of shares traded per unit time"  is presented.
Revised: The first attempt to obtain market directional information from non--stationary solution of the dynamic equation 1 "future price tend to the value that maximizes the number of shares traded per unit time" is presented.
Edit intent: clarity
Original:  The condition of "no information about the future" is found and directional predictions quality is discussed.
Revised:  The condition for "no information about the future" is found and directional predictions quality is discussed.
Edit intent: fluency
Original:  The condition of "no information about the future" is found and directional predictions quality is discussed.
Revised:  The condition of "no information about the future" is found and directional prediction quality is discussed.
Edit intent: fluency
Original: In this paper, we develop a mathematical framework for modeling  time-variant stochastic channels in diffusive mobile molecular communication (MC ) systems.
Revised: In this paper, we develop a mathematical framework for modeling the time-variant stochastic channels in diffusive mobile molecular communication (MC ) systems.
Edit intent: fluency
Original: In this paper, we develop a mathematical framework for modeling  time-variant stochastic channels in diffusive mobile molecular communication (MC ) systems.
Revised: In this paper, we develop a mathematical framework for modeling time-variant stochastic channels of diffusive mobile MC systems.
Edit intent: clarity
Original:  In particular, we consider a diffusive mobile MC system consisting of a pair of transmitter and receiver nano-machines suspended in a fluid medium with a uniform bulk flow, where we  model the mobility of the nano-machines by Brownian motion.
Revised:  In particular, we consider a diffusive mobile MC system consisting of a pair of transmitter and receiver nano-machines suspended in a fluid medium with a uniform bulk flow, where we model the mobility by Brownian motion.
Edit intent: clarity
Original:  Given the autocorrelation function , we define the coherence time of the time-variant MC channel as a metric for characterization of the variations of the impulse response .
Revised:  Exploiting the ACF , we define the coherence time of the time-variant MC channel as a metric for characterization of the variations of the impulse response .
Edit intent: clarity
Original:  Given this approximation, we derive a simple model for outdated channel state information (CSI).
Revised:  Based on this approximation, we derive a simple model for outdated channel state information (CSI).
Edit intent: coherence
Original: Popular User-Review Social Networks (URSNs) -such as Dianping, Yelp, and Amazon-are often the targets of reputation attacks in which fake reviews are posted in order to boost or diminish the ratings of listed products and services.
Revised: Popular User-Review Social Networks (URSNs) ---such as Dianping, Yelp, and Amazon-are often the targets of reputation attacks in which fake reviews are posted in order to boost or diminish the ratings of listed products and services.
Edit intent: fluency
Original: Popular User-Review Social Networks (URSNs) -such as Dianping, Yelp, and Amazon-are often the targets of reputation attacks in which fake reviews are posted in order to boost or diminish the ratings of listed products and services.
Revised: Popular User-Review Social Networks (URSNs) -such as Dianping, Yelp, and Amazon---are often the targets of reputation attacks in which fake reviews are posted in order to boost or diminish the ratings of listed products and services.
Edit intent: fluency
Original:  In this paper, we introduce the spherical cover number , which is the  number of circles (or spheres) that together cover a  circular-arc drawing in 2D (or 3D).
Revised:  In this paper, we introduce the spherical cover number , which is the number of circles (or spheres) that together cover a circular-arc drawing in 2D (or 3D).
Edit intent: fluency
Original:  bits to Bob when \gamma >2, and O\left(\min\left\{n,\frac{m n}{N_{w}^{2}\log^2 {N_{w}}}\right\}\right) when \gamma = 2. Conversely, under mild restrictions on the communication strategy, we demonstrate that no higher covert throughput is possible for \gamma>2.
Revised:  bits to Bob when \gamma >2, and O\left(\min\left\{n,\frac{m n}{N_{w}^{2}\log^2 {N_{w}}}\right\}\right) when \gamma = 2. Conversely, we demonstrate that no higher covert throughput is possible for \gamma>2.
Edit intent: clarity
Original:  In our framework, we use an adaptation of Trust Region Policy Optimization to learn complex collaborative tasks, such as formation building , building a communication link , and pushing an intruder .
Revised:  In our framework, we use an adaptation of Trust Region Policy Optimization to learn complex collaborative tasks, such as formation building and building a communication link , and pushing an intruder .
Edit intent: coherence
Original:  In our framework, we use an adaptation of Trust Region Policy Optimization to learn complex collaborative tasks, such as formation building , building a communication link , and pushing an intruder .
Revised:  In our framework, we use an adaptation of Trust Region Policy Optimization to learn complex collaborative tasks, such as formation building , building a communication link .
Edit intent: coherence
Original: Social networks and interactions in social media involve both positive and negative relationships . Signed graphs capture both types of relationships: positive edges correspond to pairs of "friends", and negative edges to pairs of "foes".
Revised: Social networks involve both positive and negative relationships . Signed graphs capture both types of relationships: positive edges correspond to pairs of "friends", and negative edges to pairs of "foes".
Edit intent: clarity
Original:  The{\em edge sign prediction problem , that aims to predict whether an interaction between a pair of nodes will be positive or negative , is an important graph mining task for which many heuristicshave recently been proposed Leskovec 2010%DIFDELCMD < ]%%% . We model the edge sign prediction problem as follows : we are allowed to query any pair of nodes whether they belong to the same cluster or not, but the answer to the query is corrupted with some probability 0<q<1{2}.
Revised:  The{\em edge sign prediction problem aims to predict whether an interaction between a pair of nodes will be positive or negative , is an important graph mining task for which many heuristicshave recently been proposed Leskovec 2010%DIFDELCMD < ]%%% . We model the edge sign prediction problem as follows : we are allowed to query any pair of nodes whether they belong to the same cluster or not, but the answer to the query is corrupted with some probability 0<q<1{2}.
Edit intent: coherence
Original:  The{\em edge sign prediction problem , that aims to predict whether an interaction between a pair of nodes will be positive or negative , is an important graph mining task for which many heuristicshave recently been proposed Leskovec 2010%DIFDELCMD < ]%%% . We model the edge sign prediction problem as follows : we are allowed to query any pair of nodes whether they belong to the same cluster or not, but the answer to the query is corrupted with some probability 0<q<1{2}.
Revised:  The{\em edge sign prediction problem , that aims to predict whether an interaction between a pair of nodes will be positive or negative Leskovec 2010%DIFDELCMD < ]%%% . We model the edge sign prediction problem as follows : we are allowed to query any pair of nodes whether they belong to the same cluster or not, but the answer to the query is corrupted with some probability 0<q<1{2}.
Edit intent: clarity
Original:  The{\em edge sign prediction problem , that aims to predict whether an interaction between a pair of nodes will be positive or negative , is an important graph mining task for which many heuristicshave recently been proposed Leskovec 2010%DIFDELCMD < ]%%% . We model the edge sign prediction problem as follows : we are allowed to query any pair of nodes whether they belong to the same cluster or not, but the answer to the query is corrupted with some probability 0<q<1{2}.
Revised:  The{\em edge sign prediction problem , that aims to predict whether an interaction between a pair of nodes will be positive or negative , is an important graph mining task for which many heuristicshave recently been proposed %DIFDELCMD < ]%%% . We model the edge sign prediction problem as follows : we are allowed to query any pair of nodes whether they belong to the same cluster or not, but the answer to the query is corrupted with some probability 0<q<1{2}.
Edit intent: coherence
Original:  We provide an algorithm that recovers all signs correctly with high probability in the presence of noise for any constant gap \delta with O( \frac{n\log n{\delta^4}} {\delta^2}+\log^2 n{\delta^6}} ) queries.
Revised:  We provide an algorithm that recovers all signs correctly with high probability in the presence of noise with O( \frac{n\log n{\delta^4}} {\delta^2}+\log^2 n{\delta^6}} ) queries.
Edit intent: clarity
Original:  We provide an algorithm that recovers all signs correctly with high probability in the presence of noise for any constant gap \delta with O( \frac{n\log n{\delta^4}} {\delta^2}+\log^2 n{\delta^6}} ) queries.
Revised:  We provide an algorithm that recovers all signs correctly with high probability in the presence of noise for any constant gap \delta with O( \frac{n\log n{\delta^4}} \frac{n\log n{\delta^2}+\log^2 n{\delta^6}} ) queries.
Edit intent: fluency
Original:  Our findings suggest that the use of  paths improves the classification accuracy, especially for pairs of nodes with no common neighbors.
Revised:  Empirical findings suggest that the use of paths improves the classification accuracy, especially for pairs of nodes with no common neighbors.
Edit intent: clarity
Original:  Our findings suggest that the use of  paths improves the classification accuracy, especially for pairs of nodes with no common neighbors.
Revised:  Our findings suggest that the use of such paths improves the classification accuracy, especially for pairs of nodes with no common neighbors.
Edit intent: clarity
Original:  Models are adapted to recent history via a gradient descent based mechanism, allowing them to assign higher probabilities to re-occurring sequential patterns.
Revised:  Models are adapted to recent history via a gradient descent based mechanism, causing them to assign higher probabilities to re-occurring sequential patterns.
Edit intent: coherence
Original:  Dynamic evaluation is demonstrated to compare favourably with existing adaptation approaches for language modelling.
Revised:  Dynamic evaluation outperforms existing adaptation approaches for language modelling.
Edit intent: clarity
Original:  We apply dynamic evaluation to improve the state of the art word-level perplexities on the Penn Treebank and WikiText-2 datasets to 51.1 and 44.3 respectively, and the state of the art character-level cross-entropy on the Hutter prize dataset to 1.17 bits/ character .
Revised:  We apply dynamic evaluation to improve the state of the art word-level perplexities on the Penn Treebank and WikiText-2 datasets to 51.1 and 44.3 respectively, and the state-of-the-art character-level cross-entropy on the Hutter prize dataset to 1.17 bits/ character .
Edit intent: fluency
Original: This paper presents a method for the evaluation of a posteriori (historical) multi-variate multi-stage optimal trading under transaction costs and a diversification constraint.
Revised: This paper presents a simple method for a posteriori (historical) multi-variate multi-stage optimal trading under transaction costs and a diversification constraint.
Edit intent: clarity
Original:  Variants are discussed, such as unconstrained trading frequency, a fixed number of total admissable trades, and the waiting of a specific time-period after every executed trade until the next trade.
Revised:  Variants are discussed, including unconstrained trading frequency, a fixed number of total admissable trades, and the waiting of a specific time-period after every executed trade until the next trade.
Edit intent: fluency
Original:  Mathematical aspects are the modeling of transition dynamics as a Markov Decision Process (MDP), efficient graph generation and consequent graph search .
Revised:  The developed methods are based on efficient graph generation and consequent graph search .
Edit intent: clarity
Original:  In order to provide a prediction curve, a Takagi-Sugeno based model trained using ANFISis provided .
Revised:  In order to provide a prediction curve, we implemented an adaptative neuro fuzzy inference system (ANFIS) .
Edit intent: clarity
Original:  In order to provide a prediction curve, we implemented an adaptative neuro fuzzy inference system (ANFIS).
Edit intent: coherence
Original:  Moreover, compared to a state-of-the-art cache contention detector, AutoCon detected more anomalies .
Revised:  Moreover, compared to a state-of-the-art approach .
Edit intent: clarity
Original: In this paper, we present AutoPerf, a generalized software performance anomaly detection system.
Revised: We present AutoPerf, a generalized software performance anomaly detection system.
Edit intent: clarity
Original:  AutoPerf uses autoencoders, an unsupervised learning technique, and hardware performance counters to learn the performance signatures of parallel programs .
Revised:  AutoPerf uses autoencoders, an unsupervised learning technique, and hardware performance counters to learn the performance signatures of a program .
Edit intent: clarity
Original:  It then uses this knowledge to identify when newer versions of the program suffer performance penalties , while simultaneously providing root cause analysis to help programmers debug the program's performance.
Revised:  It then uses this knowledge to identify when newer versions of the program suffer from performance regressions , while simultaneously providing root cause analysis to help programmers debug the program's performance.
Edit intent: clarity
Original:  AutoPerf has only 3.7\% profiling overhead (on average) and detects more anomalies than the prior state-of-the-art approach .
Revised:  On average, AutoPerf exhibits only 3.7\% profiling overhead (on average) and detects more anomalies than the prior state-of-the-art approach .
Edit intent: clarity
Original:  AutoPerf has only 3.7\% profiling overhead (on average) and detects more anomalies than the prior state-of-the-art approach .
Revised:  AutoPerf has only 3.7\% profiling overhead and diagnoses more regressions than prior state-of-the-art approach .
Edit intent: clarity
Original:  AutoPerf has only 3.7\% profiling overhead (on average) and detects more anomalies than the prior state-of-the-art approach .
Revised:  AutoPerf has only 3.7\% profiling overhead (on average) and detects more anomalies than the prior state-of-the-art approaches .
Edit intent: fluency
Original: We analyse multimodal time-series data corresponding to weight, sleep and steps measurements , derived from a dataset spanning 15000 users, collected across a range of consumer-grade health devices by Nokia Digital Health - Withings .
Revised: We analyse multimodal time-series data corresponding to weight, sleep and steps measurements .
Edit intent: coherence
Original:  For this, we design several deep long short-term memory (LSTM) architectures, including a novel cross-modal LSTM (X-LSTM), and demonstrate their superiority over several baseline approaches.
Revised:  For this, we design several deep long short-term memory (LSTM) architectures, including a novel cross-modal LSTM (X-LSTM), and demonstrate their superiority over baseline approaches.
Edit intent: clarity
Original:  The X-LSTM improves parameter efficiency of the feature extraction by separately processing each modality , while also allowing for information flow between modalities by way of recurrent cross-connections.
Revised:  The X-LSTM improves parameter efficiency by processing each modality , while also allowing for information flow between modalities by way of recurrent cross-connections.
Edit intent: clarity
Original:  The X-LSTM improves parameter efficiency of the feature extraction by separately processing each modality , while also allowing for information flow between modalities by way of recurrent cross-connections.
Revised:  The X-LSTM improves parameter efficiency of the feature extraction by separately processing each modality separately and allowing for information flow between modalities by way of recurrent cross-connections.
Edit intent: coherence
Original:  The X-LSTM improves parameter efficiency of the feature extraction by separately processing each modality , while also allowing for information flow between modalities by way of recurrent cross-connections.
Revised:  The X-LSTM improves parameter efficiency of the feature extraction by separately processing each modality , while also allowing for information flow between them by way of recurrent cross-connections.
Edit intent: clarity
Original:  Finally, we visualise the X-LSTM classification models, revealing interesting potential implications about latent variables in this task.
Revised:  Finally, we visualise the model's predictions, revealing implications about latent variables in this task.
Edit intent: clarity
Original: The calibration of local volatility models from observable option prices has always been an important problem in quantitative finance.
Revised: The calibration of volatility models from observable option prices has always been an important problem in quantitative finance.
Edit intent: clarity
Original: The calibration of local volatility models from observable option prices has always been an important problem in quantitative finance.
Revised: The calibration of local volatility models from observable option prices is a fundamental problem in quantitative finance.
Edit intent: clarity
Original:  However, the evidence for spike-based computation being in any way superior to non-spiking alternatives remains scarce.
Revised:  However, the evidence for spike-based computation beiung in any way superior to non-spiking alternatives remains scarce.
Edit intent: fluency
Original:  However, the evidence for spike-based computation beiung in any way superior to non-spiking alternatives remains scarce.
Revised:  However, the evidence for spike-based computation being in any way superior to non-spiking alternatives remains scarce.
Edit intent: fluency
Original: This work studies the labeled multi-robot path and motion planning problem in continuous domains, in the absence of static obstacles . Given n robots which may be arbitrarily close to each otherand assuming random start and goal configurations for the robots, we derived an O(n^3) , complete algorithm that produces solutions with constant-factor optimality guarantees on both makespan and distance optimality, in expectation .
Revised: We study the labeled multi-robot path and motion planning problem in continuous domains, in the absence of static obstacles . Given n robots which may be arbitrarily close to each otherand assuming random start and goal configurations for the robots, we derived an O(n^3) , complete algorithm that produces solutions with constant-factor optimality guarantees on both makespan and distance optimality, in expectation .
Edit intent: clarity
Original: This work studies the labeled multi-robot path and motion planning problem in continuous domains, in the absence of static obstacles . Given n robots which may be arbitrarily close to each otherand assuming random start and goal configurations for the robots, we derived an O(n^3) , complete algorithm that produces solutions with constant-factor optimality guarantees on both makespan and distance optimality, in expectation .
Revised: This work studies the labeled multi-robot path planning problem in continuous domains, in the absence of static obstacles . Given n robots which may be arbitrarily close to each otherand assuming random start and goal configurations for the robots, we derived an O(n^3) , complete algorithm that produces solutions with constant-factor optimality guarantees on both makespan and distance optimality, in expectation .
Edit intent: clarity
Original: This work studies the labeled multi-robot path and motion planning problem in continuous domains, in the absence of static obstacles . Given n robots which may be arbitrarily close to each otherand assuming random start and goal configurations for the robots, we derived an O(n^3) , complete algorithm that produces solutions with constant-factor optimality guarantees on both makespan and distance optimality, in expectation .
Revised: This work studies the labeled multi-robot path and motion planning problem in continuous domains, in the absence of obstacles where robots must not collide with each other. For an arbitrary number of robots in arbitrary initial and goal arrangements, we derive a polynomial time , complete algorithm that produces solutions with constant-factor optimality guarantees on both makespan and distance optimality, in expectation .
Edit intent: clarity
Original:  Beyond the baseline solution , adapting an effective (but non-polynomial time) robot routing subroutine, we also provide a highly efficient implementation that quickly computes near-optimal solutions.
Revised:  In addition to the baseline implementation , adapting an effective (but non-polynomial time) robot routing subroutine, we also provide a highly efficient implementation that quickly computes near-optimal solutions.
Edit intent: clarity
Original:  Beyond the baseline solution , adapting an effective (but non-polynomial time) robot routing subroutine, we also provide a highly efficient implementation that quickly computes near-optimal solutions.
Revised:  Beyond the baseline solution , adapting an effective (but non-polynomial time) routing subroutine, we also provide a highly efficient implementation that quickly computes near-optimal solutions.
Edit intent: clarity
Original:  Hardware experiments on  microMVP platform composed of non-holonomic robots confirms the practical applicability of our algorithmic pipeline.
Revised:  Hardware experiments on the microMVP platform composed of non-holonomic robots confirms the practical applicability of our algorithmic pipeline.
Edit intent: fluency
Original: We study the problem of continuous objects dissemination---given a large number of users and continuously arriving new objects, deliver an object to all users who prefer the object.
Revised: We study the problem of continuous object dissemination---given a large number of users and continuously arriving new objects, deliver an object to all users who prefer the object.
Edit intent: fluency
Original:  Many real world applications analyze users' preferences for effective objects dissemination.
Revised:  Many real world applications analyze users' preferences for effective object dissemination.
Edit intent: fluency
Original: Segregation  discovery consists of finding contexts of segregation of social groups distributed across units or communities.
Revised: Segregation discovery consists of finding contexts of segregation . In the modern digital society, discovering segregation is challenging, due to the large amount and the variety of social data. We present a tool in support of segregation discovery from relational and graph data.
Edit intent: coherence