wanyu/IteraTeR_v2 huggingface dataset:
Original:  Our first result demonstrates that when agents only know local information about the resources they can select, a system operator is forced to manage an inherent trade-off between the  price of anarchy and price of stability , i. e., improving the quality of the worst equilibria comes at the expenses of the best equilibria .
Revised:  Our first result demonstrates that when agents only know local information about the resources they can select, a system operator is forced to manage an inherent trade-off between the price of anarchy and price of stability .
Edit intent: coherence
Original:   Our second result demonstrates that a system operator can move well beyond this price of anarchy / price of stability frontier by designing a communication protocol that provides agents with a limited amount of system-level information beyond these local quantities .
Revised:  Our second results demonstrates how to use an additional piece of system-level information beyond these local quantities .
Edit intent: clarity
Original:   Our second result demonstrates that a system operator can move well beyond this price of anarchy / price of stability frontier by designing a communication protocol that provides agents with a limited amount of system-level information beyond these local quantities .
Revised:  Our second result demonstrates that a system operator can move well beyond this price of anarchy / price of stability frontier by designing a communication protocol that provides agents with a limited amount of system-level information to breach these limitations, thereby improving the system's performance .
Edit intent: clarity
Original:  Our first result demonstrates that any agent-based algorithm relying solely on local information induces a fundamental trade-off between the best and worst case performance guarantees, as measured by the price of anarchy and price of stability  .
Revised:  Our first result demonstrates that any agent-based algorithm relying solely on local information induces a fundamental trade-off between the price of anarchy and price of stability .
Edit intent: clarity
Original:  This result highlights how the information available to the agents translates to constraints on the achievable efficiency guarantees in networked control systems.
Edit intent: coherence
Original:  Our second results demonstrates how to use an additional piece of system-level information  to breach these limitations , thereby improving the system's performance  .
Revised:  Our second results demonstrates how a system-operator could incorporate an additional piece of system-level information to breach these limitations , thereby improving the system's performance .
Edit intent: clarity
Original:  Our second results demonstrates how to use an additional piece of system-level information  to breach these limitations , thereby improving the system's performance  .
Revised:  Our second results demonstrates how to use an additional piece of system-level information to breach these limitations and improve the system's performance .
Edit intent: clarity
Original:  Relational learning algorithms learn the Datalog definition of new relations in terms of the existing relations in the database.
Edit intent: coherence
Original:  As a result, the cloud vendor industry members have lately increased, along with the estimated annual revenue they share.
Revised:  As a result, cloud vendors have lately increased, along with the estimated annual revenue they share.
Edit intent: clarity
Original:  We provide a comparison of their services and sub-services , along with a taxonomy that designates five major service families namely computing, storage, databases, analytics  , and networking.
Revised:  We provide a taxonomy of their services and sub-services , along with a taxonomy that designates five major service families namely computing, storage, databases, analytics , and networking.
Edit intent: clarity
Original:  We provide a comparison of their services and sub-services , along with a taxonomy that designates five major service families namely computing, storage, databases, analytics  , and networking.
Revised:  We provide a comparison of their services and sub-services that designates major service families namely computing, storage, databases, analytics , and networking.
Edit intent: clarity
Original: We reveal a dramatic effect non-demographic noise in the form of uncertainty in the reaction step-size may have on the stability of self-regulating populations.
Revised: We consider non-demographic noise in the form of uncertainty in the reaction step-size may have on the stability of self-regulating populations.
Edit intent: clarity
Original: We reveal a dramatic effect non-demographic noise in the form of uncertainty in the reaction step-size may have on the stability of self-regulating populations.
Revised: We reveal a dramatic effect non-demographic noise in the form of uncertainty in the reaction step size, and reveal a dramatic effect this noise may have on the stability of self-regulating populations.
Edit intent: clarity
Original:  Employing the reaction scheme mA->kA, but allowing  e.g.  the product number k to be a-priori unknown and sampled from a given distribution, we show that such non-demographic noise can greatly increase the population's stability compared to the fixed k case.
Revised:  Employing the reaction scheme mA->kA, but allowing , e.g. the product number k to be a-priori unknown and sampled from a given distribution, we show that such non-demographic noise can greatly increase the population's stability compared to the fixed k case.
Edit intent: fluency
Original:  Employing the reaction scheme mA->kA, but allowing  e.g.  the product number k to be a-priori unknown and sampled from a given distribution, we show that such non-demographic noise can greatly increase the population's stability compared to the fixed k case.
Revised:  Employing the reaction scheme mA->kA, but allowing e.g. , the product number k to be a-priori unknown and sampled from a given distribution, we show that such non-demographic noise can greatly increase the population's stability compared to the fixed k case.
Edit intent: fluency
Original:  Employing the reaction scheme mA->kA, but allowing  e.g.  the product number k to be a-priori unknown and sampled from a given distribution, we show that such non-demographic noise can greatly increase the population's stability compared to the fixed k case.
Revised:  Employing the reaction scheme mA->kA, but allowing e.g. the product number k to be a-priori unknown and sampled from a given distribution, we show that such non-demographic noise can greatly increase the population's extinction risk compared to the fixed k case.
Edit intent: clarity
Original:  Such gradients can lead to a number of different characteristic cell shapes, and our first objective is to understand how different distributions of membrane tension influence the shape of cells in vacuo .
Revised:  Such gradients can lead to a number of different characteristic cell shapes, and our first objective is to understand how different distributions of membrane tension influence the shape of cells in a quiescent fluid .
Edit intent: clarity
Original: Recent research has shown that motile cells can adapt their mode of propulsion to the mechanical properties of the environment in which they find themselves - crawling in some environments while swimming in others.
Revised: Recent research has shown that motile cells can adapt their mode of propulsion to the mechanical properties of the environment in which they find themselves--crawling in some environments while swimming in others.
Edit intent: fluency
Original:  The latter can involve movement by blebbing or other cyclic shape changes, and both highly-simplified and more realistic models of these modes have been studied previously.
Revised:  The latter can involve movement by blebbing or other cyclic shape changes, and both highlysimplified and more realistic models of these modes have been studied previously.
Edit intent: fluency
Original:  Such gradients can lead to a number of different characteristic cell shapes, and our first objective is to understand how different distributions of membrane tension influence the shape of cells in a quiescent fluid.
Revised:  Such gradients can lead to a number of different characteristic cell shapes, and our first objective is to understand how different distributions of membrane tension influence the shape of cells in an inviscid quiescent fluid.
Edit intent: clarity
Original:  We also study the effect of fluid-cell interactions and show how tension leads to cell movement, how the balance between tension gradients and a variable bending modulus determine the shape and direction of movement, and how the efficiency of movement depends on the properties of the fluid and the distribution of tension and bending modulus in the membrane.
Revised:  We also study the effect of fluid--cell interactions and show how tension leads to cell movement, how the balance between tension gradients and a variable bending modulus determine the shape and direction of movement, and how the efficiency of movement depends on the properties of the fluid and the distribution of tension and bending modulus in the membrane.
Edit intent: fluency
Original: We propose to estimate mmWave received signal power levels using supervised machine learning and LTE signal measurements in sub-6 GHz bands.
Revised: For a base station that supports cellular communications in sub-6 GHz bands.
Edit intent: clarity
Original:  Simulation results show an improvement of 1.5\% in the handover success rate by the proposed method over the baseline method .
Revised:  Simulation results show improvement in inter-radio access technology handover success rates for the proposed algorithm .
Edit intent: clarity
Original: For a base station that supports cellular communications in sub-6 GHz LTE bands and millimeter (mmWave) bands, we propose a supervised machine learning algorithm to improve the success rate in the handover between the two radio technologies.
Revised: For a base station that supports cellular communications in sub-6 GHz LTE and millimeter (mmWave) bands, we propose a supervised machine learning algorithm to improve the success rate in the handover between the two radio technologies.
Edit intent: fluency
Original:  The proposed algorithm uses sub-6 GHz LTE channel measurements and prior mmWave measurements within a temporal window to estimate mmWave received signal power levels before a handover . Simulation results show improvement in inter-radio access technology handover success rates for the proposed algorithm .
Revised:  The proposed algorithm uses sub-6 GHz LTE channel measurements and prior mmWave measurements within a temporal window to estimate mmWave received signal power levels before a handover . Simulation results show improvement in handover success rates for the proposed algorithm .
Edit intent: clarity
Original:  The proposed algorithm uses sub-6 GHz LTE channel measurements and prior mmWave measurements within a temporal window to estimate mmWave received signal power levels before a handover . Simulation results show improvement in inter-radio access technology handover success rates for the proposed algorithm .
Revised:  The proposed algorithm uses sub-6 GHz LTE channel measurements and prior mmWave measurements within a temporal window to estimate mmWave received signal power levels before a handover . Simulation results show improvement in inter-radio access technology handover success rates for our proposed algorithm compared to standard handover algorithms .
Edit intent: clarity
Original:  The main contributions of our paper are : 1) introduce partially blind handovers, 2) employ machine learning to perform handover success predictions from sub-6 GHz to mmWave frequencies, and 3) show that this machine learning based algorithm combined with partially blind handovers can improve the handover success rate in a realistic network setup of colocated cells.
Revised:  The main contributions of our paper are to 1) introduce partially blind handovers, 2) employ machine learning to perform handover success predictions from sub-6 GHz to mmWave frequencies, and 3) show that this machine learning based algorithm combined with partially blind handovers can improve the handover success rate in a realistic network setup of colocated cells.
Edit intent: fluency
Original: The visual recognition of transitive actions comprising human-object interactions is a key component enabling artificial systems to operate in natural environments.
Revised: The visual recognition of transitive actions comprising human-object interactions is a key component for artificial systems operating in natural environments.
Edit intent: clarity
Original:  This challenging task requires , in addition to the recognition of articulated body actions , the extraction of semantic elements from the scene such as the identity of the manipulated objects.
Revised:  This challenging task requires jointly the recognition of articulated body actions , the extraction of semantic elements from the scene such as the identity of the manipulated objects.
Edit intent: clarity
Original:  This challenging task requires , in addition to the recognition of articulated body actions , the extraction of semantic elements from the scene such as the identity of the manipulated objects.
Revised:  This challenging task requires , in addition to the recognition of articulated body actions as well as the extraction of semantic elements from the scene such as the identity of the manipulated objects.
Edit intent: clarity
Original:  Our model consists of a hierarchy of Grow When Required (GWR) networks which learn prototypical representations of body motion patterns and objects, also accounting for the development of action-object mappings in an unsupervised fashion.
Revised:  Our model consists of a hierarchy of Grow-When-Required (GWR) networks which learn prototypical representations of body motion patterns and objects, also accounting for the development of action-object mappings in an unsupervised fashion.
Edit intent: fluency
Original:  Our model consists of a hierarchy of Grow When Required (GWR) networks which learn prototypical representations of body motion patterns and objects, also accounting for the development of action-object mappings in an unsupervised fashion.
Revised:  Our model consists of a hierarchy of Grow When Required (GWR) networks that learn prototypical representations of body motion patterns and objects, also accounting for the development of action-object mappings in an unsupervised fashion.
Edit intent: clarity
Original:  Our model consists of a hierarchy of Grow When Required (GWR) networks which learn prototypical representations of body motion patterns and objects, also accounting for the development of action-object mappings in an unsupervised fashion.
Revised:  Our model consists of a hierarchy of Grow When Required (GWR) networks which learn prototypical representations of body motion patterns and objects, accounting for the development of action-object mappings in an unsupervised fashion.
Edit intent: coherence
Original:  To demonstrate this ability, we report experimental results on a dataset of daily activities collected for the purpose of this study as well as on a publicly available benchmark dataset.
Revised:  We report experimental results on a dataset of daily activities collected for the purpose of this study as well as on a publicly available benchmark dataset.
Edit intent: clarity
Original:  In line with neurophysiological studies, our self-organizing architecture shows higher neural activation for congruent action-object pairs learned during training sessions with respect to artificially created incongruent ones.
Revised:  In line with neurophysiological studies, our self-organizing architecture exhibits higher neural activation for congruent action-object pairs learned during training sessions with respect to artificially created incongruent ones.
Edit intent: fluency
Original:  In line with neurophysiological studies, our self-organizing architecture shows higher neural activation for congruent action-object pairs learned during training sessions with respect to artificially created incongruent ones.
Revised:  In line with neurophysiological studies, our self-organizing architecture shows higher neural activation for congruent action-object pairs learned during training sessions with respect to synthetically created incongruent ones.
Edit intent: fluency
Original:  We show that our model achieves good classification accuracy on the benchmark dataset in an unsupervised fashion, showing competitive performance with respect to strictly supervised state-of-the-art approaches.
Revised:  We show that our unsupervised model shows competitive classification results on the benchmark dataset in an unsupervised fashion, showing competitive performance with respect to strictly supervised state-of-the-art approaches.
Edit intent: clarity
Original:  We show that our model achieves good classification accuracy on the benchmark dataset in an unsupervised fashion, showing competitive performance with respect to strictly supervised state-of-the-art approaches.
Revised:  We show that our model achieves good classification accuracy on the benchmark dataset with respect to strictly supervised state-of-the-art approaches.
Edit intent: clarity
Original:  We show that our model achieves good classification accuracy on the benchmark dataset in an unsupervised fashion, showing competitive performance with respect to strictly supervised state-of-the-art approaches.
Revised:  We show that our model achieves good classification accuracy on the benchmark dataset in an unsupervised fashion, showing competitive performance with respect to strictly supervised approaches.
Edit intent: clarity
Original: In this paper we give a characterization of both Boolean and arithmetic circuit classes of logarithmic depth in the vein of descriptive complexity theory, i.e., the Boolean classes NC^1, SAC^1 and AC^1 as well as their arithmetic counterparts  NC^1,  SAC^1 and  AC^1.
Revised: In this paper we give a characterization of both Boolean and arithmetic circuit classes of logarithmic depth in the vein of descriptive complexity theory, i.e., the Boolean classes NC^1, SAC^1 and AC^1 as well as their arithmetic counterparts \# NC^1, SAC^1 and AC^1.
Edit intent: clarity
Original:  This proves that MAJ\circ MAJ_t cannot break the \log n barrier ( in the simultaneous model) when t is constant.
Revised:  This proves that MAJ\circ MAJ_t to break the \log n barrier ( in the simultaneous model) when t is constant.
Edit intent: clarity
Original:  This proves that MAJ\circ MAJ_t cannot break the \log n barrier ( in the simultaneous model) when t is constant.
Revised:  This proves that MAJ\circ MAJ_t cannot break the \log n barrier in the simultaneous model) when t is constant.
Edit intent: fluency
Original:  In medical applications and military zones , for example, change in behaviors should be detected in near real-time, to avoid potential loss of life.
Revised:  In medical applications and emergency response settings , for example, change in behaviors should be detected in near real-time, to avoid potential loss of life.
Edit intent: clarity
Original:  In medical applications and military zones , for example, change in behaviors should be detected in near real-time, to avoid potential loss of life.
Revised:  In medical applications and military zones , for example, change in behaviours should be detected in near real-time, to avoid potential loss of life.
Edit intent: fluency
Original: We used neural networks in ~ 3,000 sleep recordings from over 10 locations to automate sleep stage scoring, producing a probability distribution called an hypnodensity graph . Accuracy was validated in 70 subjects scored by six technicians (gold standard).
Revised: We used neural networks in approximately 3,000 sleep recordings from over 10 locations to automate sleep stage scoring, producing a probability distribution called an hypnodensity graph . Accuracy was validated in 70 subjects scored by six technicians (gold standard).
Edit intent: clarity
Original:  Using sequencing and genetic engineering we reveal the genetic basis for this reduction in phenotypic fluctuations.
Revised:  Using sequencing and genetic engineering we study the genetic basis for this reduction in phenotypic fluctuations.
Edit intent: clarity
Original:  We offer one interpretation for this reduction by developing a simple, abstracted,  simulation model of the evolution of phenotypic fluctuations subject to constraints.
Revised:  We study the generality of this reduction by developing a simple, abstracted, simulation model of the evolution of phenotypic fluctuations subject to constraints.
Edit intent: clarity
Original:  P-Tucker performs an alternating least squares with a gradient-based update rule in a fully parallel way, which significantly reduces memory requirements for updating factor matrices.
Revised:  P-Tucker performs alternating least squares with a gradient-based update rule in a fully parallel way, which significantly reduces memory requirements for updating factor matrices.
Edit intent: fluency
Original:  Furthermore, we offer two variants of P-Tucker: a caching algorithm P-Tucker-CACHE and an approximation algorithm P-Tucker-APPROX , both of which accelerate the update process.
Revised:  Furthermore, we offer two variants of P-Tucker: a caching algorithm P-Tucker-Cache and an approximation algorithm P-Tucker-APPROX , both of which accelerate the update process.
Edit intent: fluency
Original:  Furthermore, we offer two variants of P-Tucker: a caching algorithm P-Tucker-CACHE and an approximation algorithm P-Tucker-APPROX , both of which accelerate the update process.
Revised:  Furthermore, we offer two variants of P-Tucker: a caching algorithm P-Tucker-CACHE and an approximation algorithm P-Tucker-Approx , both of which accelerate the update process.
Edit intent: fluency
Original:  In the first phase of our algorithm we propose PhraseType , a probabilistic generative model which exploits textual features and limited POS tags to broadly segment text snippets into aspect-typed phrases.
Revised:  In the first phase of our algorithm we propose PhraseType , a probabilistic generative model which exploits textual features and limited POS tags to broadly segment text snippets into aspect-typed phrases.
Edit intent: fluency
Original: Rumor spreading has been studied for decades, but its underlying mechanism is still under debate, especially for those ones based on internet .
Revised: Information spreading has been studied for decades, but its underlying mechanism is still under debate, especially for those ones based on internet .
Edit intent: clarity
Original:  By focusing on the  spreading data of six typical events on Sina Weibo, we surprisingly find that the spreading of modern news shows some new features, i.e. either explosively fast or slow, depending on the individual events.
Revised:  By focusing on the information spreading data of six typical events on Sina Weibo, we surprisingly find that the spreading of modern news shows some new features, i.e. either explosively fast or slow, depending on the individual events.
Edit intent: clarity
Original:  By focusing on the  spreading data of six typical events on Sina Weibo, we surprisingly find that the spreading of modern news shows some new features, i.e. either explosively fast or slow, depending on the individual events.
Revised:  By focusing on the spreading data of six typical events on Sina Weibo, we surprisingly find that the spreading of modern information shows some new features, i.e. either explosively fast or slow, depending on the individual events.
Edit intent: clarity