wanyu/IteraTeR_full_sent 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: A first attempt at obtaining market--directional information from a 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.
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 maximizing the number of shares traded per unit time" 1 is presented.
Edit intent: meaning-changed
Original:  We demonstrate that price impact concept is poorly applicable to market dynamics and execution flow I=dV/dt operator with an "impact from the future" term , providing information about not yet executed tradesto be considered instead.
Revised:  We demonstrate that the concept of price impact is poorly applicable to market dynamics and execution flow I=dV/dt operator with an "impact from the future" term , providing information about not yet executed tradesto be considered instead.
Edit intent: fluency
Original:  We demonstrate that price impact concept is poorly applicable to market dynamics and execution flow I=dV/dt operator with an "impact from the future" term , providing information about not yet executed tradesto be considered instead.
Revised:  We demonstrate that price impact concept is poorly applicable to market dynamics . Instead, we consider the execution flow I=dV/dt operator with an "impact from the future" term , providing information about not yet executed tradesto be considered instead.
Edit intent: coherence
Original:  We demonstrate that price impact concept is poorly applicable to market dynamics and execution flow I=dV/dt operator with an "impact from the future" term , providing information about not yet executed tradesto be considered instead.
Revised:  We demonstrate that price impact concept is poorly applicable to market dynamics and execution flow I=dV/dt operator with the "impact from the future" term , providing information about not yet executed tradesto be considered instead.
Edit intent: fluency
Original:  We demonstrate that price impact concept is poorly applicable to market dynamics and execution flow I=dV/dt operator with an "impact from the future" term , providing information about not yet executed tradesto be considered instead.
Revised:  We demonstrate that price impact concept is poorly applicable to market dynamics and execution flow I=dV/dt operator with an "impact from the future" term providing information about not yet executed tradesto be considered instead.
Edit intent: fluency
Original:  We demonstrate that price impact concept is poorly applicable to market dynamics and execution flow I=dV/dt operator with an "impact from the future" term , providing information about not yet executed tradesto be considered instead. An impact from the future  on I can be directly estimated from already executed trades, after that directional information on price can be obtained from experimentally observed fact that  I and p operators to have the same eigenfunctions (  exact result in  dynamic impact approximation p=p(I)).
Revised:  We demonstrate that price impact concept is poorly applicable to market dynamics and execution flow I=dV/dt operator with an "impact from the future" term , providing information about not--yet--executed trades. The " impact from the future on I can be directly estimated from already executed trades, after that directional information on price can be obtained from experimentally observed fact that I and p operators to have the same eigenfunctions ( exact result in dynamic impact approximation p=p(I)).
Edit intent: clarity
Original:  An impact from the future  on I can be directly estimated from already executed trades, after that directional information on price can be obtained from experimentally observed fact that  I and p operators to have the same eigenfunctions (  exact result in  dynamic impact approximation p=p(I)).
Revised:  An impact from the future " on I can be directly estimated from already executed trades, after that directional information on price can be obtained from experimentally observed fact that I and p operators to have the same eigenfunctions ( exact result in dynamic impact approximation p=p(I)).
Edit intent: fluency
Original:  An impact from the future  on I can be directly estimated from already executed trades, after that directional information on price can be obtained from experimentally observed fact that  I and p operators to have the same eigenfunctions (  exact result in  dynamic impact approximation p=p(I)).
Revised:  An impact from the future on I can be directly estimated from the already--executed trades, the directional information on price can be obtained from experimentally observed fact that I and p operators to have the same eigenfunctions ( exact result in dynamic impact approximation p=p(I)).
Edit intent: coherence
Original:  An impact from the future  on I can be directly estimated from already executed trades, after that directional information on price can be obtained from experimentally observed fact that  I and p operators to have the same eigenfunctions (  exact result in  dynamic impact approximation p=p(I)).
Revised:  An impact from the future on I can be directly estimated from already executed trades, after that directional information on price is then obtained from the experimentally observed fact that I and p operators to have the same eigenfunctions ( exact result in dynamic impact approximation p=p(I)).
Edit intent: clarity
Original:  An impact from the future  on I can be directly estimated from already executed trades, after that directional information on price can be obtained from experimentally observed fact that  I and p operators to have the same eigenfunctions (  exact result in  dynamic impact approximation p=p(I)).
Revised:  An impact from the future on I can be directly estimated from already executed trades, after that directional information on price can be obtained from experimentally observed fact that the I and p operators to have the same eigenfunctions ( exact result in dynamic impact approximation p=p(I)).
Edit intent: fluency
Original:  An impact from the future  on I can be directly estimated from already executed trades, after that directional information on price can be obtained from experimentally observed fact that  I and p operators to have the same eigenfunctions (  exact result in  dynamic impact approximation p=p(I)).
Revised:  An impact from the future on I can be directly estimated from already executed trades, after that directional information on price can be obtained from experimentally observed fact that I and p operators have the same eigenfunctions ( exact result in dynamic impact approximation p=p(I)).
Edit intent: clarity
Original:  An impact from the future  on I can be directly estimated from already executed trades, after that directional information on price can be obtained from experimentally observed fact that  I and p operators to have the same eigenfunctions (  exact result in  dynamic impact approximation p=p(I)).
Revised:  An impact from the future on I can be directly estimated from already executed trades, after that directional information on price can be obtained from experimentally observed fact that I and p operators to have the same eigenfunctions ( the exact result in dynamic impact approximation p=p(I)).
Edit intent: clarity
Original:  An impact from the future  on I can be directly estimated from already executed trades, after that directional information on price can be obtained from experimentally observed fact that  I and p operators to have the same eigenfunctions (  exact result in  dynamic impact approximation p=p(I)).
Revised:  An impact from the future on I can be directly estimated from already executed trades, after that directional information on price can be obtained from experimentally observed fact that I and p operators to have the same eigenfunctions ( exact result in the dynamic impact approximation p=p(I)).
Edit intent: fluency
Original:  This work make a substantial progress toward the solution of ultimate market dynamics problem: an evidence of existence (or a proof of non--existence) of an automated trading machine , consistently making positive P L trading on a free market as an autonomous agent , i.e. to decide whether market dynamics equation exist.
Revised:  This work makes a substantial contribution toward solving the ultimate market dynamics problem: an evidence of existence (or a proof of non--existence) of an automated trading machine , consistently making positive P L trading on a free market as an autonomous agent , i.e. to decide whether market dynamics equation exist.
Edit intent: clarity
Original:  This work make a substantial progress toward the solution of ultimate market dynamics problem: an evidence of existence (or a proof of non--existence) of an automated trading machine , consistently making positive P L trading on a free market as an autonomous agent , i.e. to decide whether market dynamics equation exist.
Revised:  This work make a substantial progress toward the solution of ultimate market dynamics problem: find evidence of existence (or a proof of non--existence) of an automated trading machine , consistently making positive P L trading on a free market as an autonomous agent , i.e. to decide whether market dynamics equation exist.
Edit intent: clarity
Original:  This work make a substantial progress toward the solution of ultimate market dynamics problem: an evidence of existence (or a proof of non--existence) of an automated trading machine , consistently making positive P L trading on a free market as an autonomous agent , i.e. to decide whether market dynamics equation exist.
Revised:  This work make a substantial progress toward the solution of ultimate market dynamics problem: an evidence of existence (or proof of non--existence) of an automated trading machine , consistently making positive P L trading on a free market as an autonomous agent , i.e. to decide whether market dynamics equation exist.
Edit intent: fluency
Original:  This work make a substantial progress toward the solution of ultimate market dynamics problem: an evidence of existence (or a proof of non--existence) of an automated trading machine , consistently making positive P L trading on a free market as an autonomous agent , i.e. to decide whether market dynamics equation exist.
Revised:  This work make a substantial progress toward the solution of ultimate market dynamics problem: an evidence of existence (or a proof of non--existence) of an automated trading machine L trading on a free market as an autonomous agent , i.e. to decide whether market dynamics equation exist.
Edit intent: clarity
Original:  This work make a substantial progress toward the solution of ultimate market dynamics problem: an evidence of existence (or a proof of non--existence) of an automated trading machine , consistently making positive P L trading on a free market as an autonomous agent , i.e. to decide whether market dynamics equation exist.
Revised:  This work make a substantial progress toward the solution of ultimate market dynamics problem: an evidence of existence (or a proof of non--existence) of an automated trading machine , consistently making positive P which consistently makes positive P\&L on a free market as an autonomous agent , i.e. to decide whether market dynamics equation exist.
Edit intent: meaning-changed
Original:  This work make a substantial progress toward the solution of ultimate market dynamics problem: an evidence of existence (or a proof of non--existence) of an automated trading machine , consistently making positive P L trading on a free market as an autonomous agent , i.e. to decide whether market dynamics equation exist.
Revised:  This work make a substantial progress toward the solution of ultimate market dynamics problem: an evidence of existence (or a proof of non--existence) of an automated trading machine , consistently making positive P L trading on a free market as an autonomous agent (aka the existence of the market dynamics equation exist.
Edit intent: clarity
Original:  This work make a substantial progress toward the solution of ultimate market dynamics problem: an evidence of existence (or a proof of non--existence) of an automated trading machine , consistently making positive P L trading on a free market as an autonomous agent , i.e. to decide whether market dynamics equation exist. Software with a reference implementation of the theory is provided.
Revised:  This work make a substantial progress toward the solution of ultimate market dynamics problem: an evidence of existence (or a proof of non--existence) of an automated trading machine , consistently making positive P L trading on a free market as an autonomous agent , i.e. to decide whether market dynamics equation ). The software with a reference implementation of the theory is provided.
Edit intent: coherence
Original: Given a drawing of a graph, its visual complexity is defined as the number of geometrical entities in the drawing, for example, the number of segments in a straight-line drawing or the number of arcs in a circular-arc drawing (in 2D).
Revised: Given a drawing of a graph, its visual complexity is defined as the number of geometrical entities in the drawing, for example, the number of segments in a straight-line drawing or the number of arcs in a circular-arc drawing (in 2D).
Edit intent: fluency
Original:  Recently, Chaplick et al.  introduced a different measure for the visual complexity, the affine cover number , which is the minimum number of lines (or planes) that together cover a  straight-line drawing of a graph G in 2D (3D).
Revised:  Recently, Chaplick et al. GD 2016 introduced a different measure for the visual complexity, the affine cover number , which is the minimum number of lines (or planes) that together cover a straight-line drawing of a graph G in 2D (3D).
Edit intent: meaning-changed
Original:  Recently, Chaplick et al.  introduced a different measure for the visual complexity, the affine cover number , which is the minimum number of lines (or planes) that together cover a  straight-line drawing of a graph G in 2D (3D).
Revised:  Recently, Chaplick et al. introduced a different measure for the visual complexity, the affine cover number , which is the minimum number of lines (or planes) that together cover a straight-line drawing of a graph G in 2D (3D).
Edit intent: fluency
Original:  Recently, Chaplick et al.  introduced a different measure for the visual complexity, the affine cover number , which is the minimum number of lines (or planes) that together cover a  straight-line drawing of a graph G in 2D (3D).
Revised:  Recently, Chaplick et al. introduced a different measure for the visual complexity, the affine cover number , which is the minimum number of lines (or planes) that together cover a crossing-free straight-line drawing of a graph G in 2D (3D).
Edit intent: meaning-changed
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 crossing-free circular-arc drawing in 2D (or 3D).
Edit intent: meaning-changed
Original: Recent studies combining social media data with data from capital markets have mainly focused on the relationship between returnsand activity on social media. In contrast, we study how behavior of different investor categories are associated to Facebook posts and other activity on a company' s Facebook wall. We provide evidence that the decisions of less sophisticated investors---namely, households and URLanizations---to increase or decrease their shareholdings are associated with Facebook data , while the decisions of more sophisticated investors---financial and insurance institutions---are not associated with Facebook data .
Revised: Recent studies combining social media data with data from capital markets have mainly focused on predicting stock returns. Instead of predicting stock price movements, we examine the relation between Facebook data and investors' decision making in stock markets with a unique data on investors' transactions on Nokia. We find that the decisions of less sophisticated investors---namely, households and URLanizations---to increase or decrease their shareholdings are associated with Facebook data , while the decisions of more sophisticated investors---financial and insurance institutions---are not associated with Facebook data .
Edit intent: clarity
Original:  We provide evidence that the decisions of less sophisticated investors---namely, households and URLanizations---to increase or decrease their shareholdings are associated with Facebook data , while the decisions of more sophisticated investors---financial and insurance institutions---are not associated with Facebook data .
Revised:  We provide evidence that the decisions to buy versus sell are associated with Facebook data , while the decisions of more sophisticated investors---financial and insurance institutions---are not associated with Facebook data .
Edit intent: meaning-changed
Original:  We provide evidence that the decisions of less sophisticated investors---namely, households and URLanizations---to increase or decrease their shareholdings are associated with Facebook data , while the decisions of more sophisticated investors---financial and insurance institutions---are not associated with Facebook data .
Revised:  We provide evidence that the decisions of less sophisticated investors---namely, households and URLanizations---to increase or decrease their shareholdings are associated with Facebook data especially for passive households and also for URLanizations. At the same time, it seems that more sophisticated investors---financial and insurance institutions---are not associated with Facebook data .
Edit intent: meaning-changed
Original:  We provide evidence that the decisions of less sophisticated investors---namely, households and URLanizations---to increase or decrease their shareholdings are associated with Facebook data , while the decisions of more sophisticated investors---financial and insurance institutions---are not associated with Facebook data .
Revised:  We provide evidence that the decisions of less sophisticated investors---namely, households and URLanizations---to increase or decrease their shareholdings are associated with Facebook data , while the decisions of more sophisticated investors---financial and insurance institutions---are behaving independently from Facebook activities .
Edit intent: clarity
Original:  Starting from a given amount of money in some currency, we analyze the stage-wise optimal allocation over a time horizon with potential investments in multiple currencies and various assets , such as, for example, assets emulating stock indices. 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:  Starting from a given amount of money in some currency, we analyze the stage-wise optimal allocation over a time horizon with potential investments in multiple currencies and various assets . Three 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.
Edit intent: clarity
Original:  Mathematical aspects are the modeling of transition dynamics as a Markov Decision Process (MDP), efficient graph generation and consequent graph search . The developed strategies are evaluated on recent real-world data dating back one year.
Revised:  Mathematical aspects are the modeling of transition dynamics as a Markov Decision Process (MDP), efficient graph generation and consequent graph search , and are evaluated quantitatively on real-world data dating back one year.
Edit intent: clarity
Original: Cache contention is an important type of performance anomaly in this multi-core and many-core era. It can cause a significant slowdown in parallel programs. However, it is hard to detect and often, not visible in the source code. As software changes over time, modifications in code can introduce cache contention anomalies. One way to detect such anomalies, is to use performance regression testing. Prior approaches for cache contention detection are either not suitable for performance regression testing or requires knowledge about specific type of contention behavior. To remedy these shortcomings, we propose AutoCon. It works by finding the modified functions and collecting hardware performance counter profiles for them. It uses an unsupervised learning technique, called Autoencoder, to learn the contention behavior implied by the profiles (collected from the older version of code).
Revised: In this paper, we present AutoPerf, a generalized software performance anomaly detection system. AutoPerf uses autoencoders, an unsupervised learning technique, called Autoencoder, to learn the contention behavior implied by the profiles (collected from the older version of code).
Edit intent: coherence
Original:  It uses an unsupervised learning technique, called Autoencoder, to learn the contention behavior implied by the profiles (collected from the older version of code). Then, it checks the profiles collected from the newer version of code to determine whether the contention pattern (implied by the profiles) is anomalous. If so, AutoCon reports a cache contention anomaly. Finally, it performs root cause analysis to provide detailed debugging information.
Revised:  It uses an unsupervised learning technique, called Autoencoder, to learn the performance signatures of parallel programs. It then uses this knowledge to identify when newer versions of the program suffer performance penalties, while simultaneously providing root cause analysis to provide detailed debugging information.
Edit intent: clarity
Original:  AutoCon is the first learning based cache contention detectorthat does not require any positive example of contention anomalies. We evaluated AutoCon with 13 real world cache contentionanomalies as well as 7 open source programs.
Revised:  AutoCon is the first zero-positive learning performance anomaly detector, a system that trains entirely in the negative (non-anomalous) space to learn positive (anomalous) behaviors. We demonstrate AutoPerf's generality against three different types of performance anomalies: (i) true sharing cache contention, (ii) false sharing cache contention, and (iii) NUMA latencies across 15 real world performance anomalies and 7 open source programs.
Edit intent: meaning-changed
Original:  AutoCon detected all types of cache contention anomalies with only 3.7\% profiling overhead (on average) . Moreover, compared to a state-of-the-art cache contention detector, AutoCon detected more anomalies .
Revised:  AutoCon detected all types of cache contention anomalies with only 3.7\% profiling overhead (on average) and detects more anomalies than the prior state-of-the-art cache contention detector, AutoCon detected more anomalies .
Edit intent: coherence