wanyu/IteraTeR_v2 huggingface dataset:
Original:  Pop. Biol. %DIFDELCMD < {\bf %DIFDELCMD < %%% 65 , 263 (2004)  ] to spatially distributed groups and compare the resulting behavior with their mean field predictions for the coevolving densities of predator and prey strategies.
Revised:  Pop. Biol. %DIFDELCMD < {\bf %DIFDELCMD < %%% 65 , 263 (2004) ] to spatially distributed groups and compare the resulting behavior with their mean-field predictions for the coevolving densities of predator and prey strategies.
Edit intent: fluency
Original:  We show that the coexistence phase in which both strategies for each group are present is stable because of an effective, cyclic dominance behavior similar to a well studied generalizations of the Rock-Paper-Scissors game with four species (without neutral pairs) , a further example of how ubiquitous this mechanism is.
Revised:  We show that the coexistence phase in which both strategies for each group are present is stable because of an effective, cyclic dominance mechanism similar to a well studied generalizations of the Rock-Paper-Scissors game with four species (without neutral pairs) , a further example of how ubiquitous this mechanism is.
Edit intent: clarity
Original:  We show that the coexistence phase in which both strategies for each group are present is stable because of an effective, cyclic dominance behavior similar to a well studied generalizations of the Rock-Paper-Scissors game with four species (without neutral pairs) , a further example of how ubiquitous this mechanism is.
Revised:  We show that the coexistence phase in which both strategies for each group are present is stable because of an effective, cyclic dominance behavior similar to a well-studied generalization of the Rock-Paper-Scissors game with four species (without neutral pairs) , a further example of how ubiquitous this mechanism is.
Edit intent: fluency
Original:  We show that the coexistence phase in which both strategies for each group are present is stable because of an effective, cyclic dominance behavior similar to a well studied generalizations of the Rock-Paper-Scissors game with four species (without neutral pairs) , a further example of how ubiquitous this mechanism is.
Revised:  We show that the coexistence phase in which both strategies for each group are present is stable because of an effective, cyclic dominance behavior similar to a well studied generalizations of the Rock-Paper-Scissors game with four species , a further example of how ubiquitous this mechanism is.
Edit intent: clarity
Original:  Simulations on a 7nm CoMET device show fast, low-energy operation, with a delay/energy of 98ps/ 69aJ for INV and 135ps/85aJ for MAJ3.
Revised:  Simulations on a 7nm CoMET device show fast, low-energy operation, with a delay/energy of 98ps/ 68aJ for INV and 135ps/85aJ for MAJ3.
Edit intent: fluency
Original:  Human interaction tends to be a more burstyprocess , though, having higher probabilities of either extremely short waiting times or long periods of silence rather than the relative regularity of Poisson selection .
Revised:  Human interaction tends to be bursty , though, having higher probabilities of either extremely short waiting times or long periods of silence rather than the relative regularity of Poisson selection .
Edit intent: clarity
Original:  Human interaction tends to be a more burstyprocess , though, having higher probabilities of either extremely short waiting times or long periods of silence rather than the relative regularity of Poisson selection .
Revised:  Human interaction tends to be a more burstyprocess , though, having higher probabilities of either extremely short waiting times or long periods of silence .
Edit intent: clarity
Original:  To quantify the effects this difference may have on the dynamics of social models, we place in competition two groups exhibiting different speakers  waiting-time distributions.
Revised:  To quantify the effects this difference may have on the dynamics of social models, we place in competition two groups exhibiting different speakers ' waiting-time distributions.
Edit intent: fluency
Original:  These competitions are implemented in the binary Naming Game and in the voter model, showing that the relevant aspect of the waiting-time distribution is the density of the head rather than that of the tail.
Revised:  These competitions are implemented in the binary Naming Game , and show that the relevant aspect of the waiting-time distribution is the density of the head rather than that of the tail.
Edit intent: clarity
Original:  In fact, we show that even with identical mean waiting times, a group with a higher density of short waiting times is favored in competition over the group with a less bursty distribution .
Revised:  We show that even with identical mean waiting times, a group with a higher density of short waiting times is favored in competition over the group with a less bursty distribution .
Edit intent: coherence
Original:  In fact, we show that even with identical mean waiting times, a group with a higher density of short waiting times is favored in competition over the group with a less bursty distribution .
Revised:  In fact, we show that even with identical mean waiting times, a group with a higher density of short waiting times is favored in competition over the other group .
Edit intent: clarity
Original:  This effect remains in the presence of nodes holding a single opinion that never changes, as the fraction of such committed individuals necessary for achieving consensus decreases dramatically when their waiting-time distribution has a higher head density than the waiting-time distribution of the nodes holding competing opinions .
Revised:  This effect remains in the presence of nodes holding a single opinion that never changes, as the fraction of such committed individuals necessary for achieving consensus decreases dramatically when they have a higher head density than the waiting-time distribution of the nodes holding competing opinions .
Edit intent: clarity
Original:  To address this , we revisit the Futamura Projections from a visual perspective by introducing a diagramming schemethat helps the reader navigate the complexity and abstract nature of the Futamura Projections while emphasizing their recurring patterns .
Revised:  To address this , we revisit the Futamura Projections using a diagram scheme. Through these diagrams we emphasize the recurring patterns in the Futamura Projections while emphasizing their recurring patterns .
Edit intent: clarity
Original:  To address this , we revisit the Futamura Projections from a visual perspective by introducing a diagramming schemethat helps the reader navigate the complexity and abstract nature of the Futamura Projections while emphasizing their recurring patterns .
Revised:  To address this , we revisit the Futamura Projections from a visual perspective by introducing a diagramming schemethat helps the reader navigate the complexity and abstract nature of the Futamura Projections while addressing their complexity and abstract nature .
Edit intent: clarity
Original:  Given this broader interest, we revisit the Futamura Projections using a  diagram scheme.
Revised:  Given this broader interest, we revisit the Futamura Projections using a novel diagram scheme.
Edit intent: clarity
Original:  In this short note we investigate the rate that maximizes the expected log-likelihood ratio (i.e. Kullback-Leibler separation) between the four-leaf unresolved (star) tree and a four-leaf binary tree with interior edge length \epsilon.
Revised:  In this note we investigate the rate that maximizes the expected log-likelihood ratio (i.e. Kullback-Leibler separation) between the four-leaf unresolved (star) tree and a four-leaf binary tree with interior edge length \epsilon.
Edit intent: clarity
Original: The reconstruction of phylogenetic trees from discrete character data is typically relies on models that assume the characters evolve under a continuous-time Markov process operating at some overall rate \lambda.
Revised: The reconstruction of phylogenetic trees from discrete character data typically relies on models that assume the characters evolve under a continuous-time Markov process operating at some overall rate \lambda.
Edit intent: fluency
Original:  When \lambda is too high or too low, it becomes difficult to distinguish between a short interior edge from a polytomy (the tree that results from collapsing the edge).
Revised:  When \lambda is too high or too low, it becomes difficult to distinguish a short interior edge from a polytomy (the tree that results from collapsing the edge).
Edit intent: fluency
Original:  In this note  we investigate the rate that maximizes the expected log-likelihood ratio (i.e. Kullback-Leibler separation) between the four-leaf unresolved (star) tree and a four-leaf binary tree with interior edge length \epsilon.
Revised:  In this note , we investigate the rate that maximizes the expected log-likelihood ratio (i.e. Kullback-Leibler separation) between the four-leaf unresolved (star) tree and a four-leaf binary tree with interior edge length \epsilon.
Edit intent: fluency
Original:  In this note  we investigate the rate that maximizes the expected log-likelihood ratio (i.e. Kullback-Leibler separation) between the four-leaf unresolved (star) tree and a four-leaf binary tree with interior edge length \epsilon.
Revised:  In this note we investigate the rate that maximizes the expected log-likelihood ratio (i.e. the Kullback--Leibler separation) between the four-leaf unresolved (star) tree and a four-leaf binary tree with interior edge length \epsilon.
Edit intent: clarity
Original:  For a simple 2-state model we show that as \epsilon converges to 0 the optimal rate also converges to zero when the four pendant edges have equal length.
Revised:  For a simple two-state model, we show that as \epsilon converges to 0 the optimal rate also converges to zero when the four pendant edges have equal length.
Edit intent: fluency
Original:  However, when the four pendant branches have unequal length, two local optima can arise, and it is possible for the the globally optimal rate to converge to a non-zero constant as \epsilon \rightarrow 0. Moreover, in the setting where the four pendant branches have equal length and either (i)
Revised:  However, when the four pendant branches have unequal length, two local optima can arise, and it is possible for the globally optimal rate to converge to a non-zero constant as \epsilon \rightarrow 0. Moreover, in the setting where the four pendant branches have equal length and either (i)
Edit intent: fluency
Original:  However, when the four pendant branches have unequal length, two local optima can arise, and it is possible for the the globally optimal rate to converge to a non-zero constant as \epsilon \rightarrow 0. Moreover, in the setting where the four pendant branches have equal length and either (i)
Revised:  However, when the four pendant branches have unequal length, two local optima can arise, and it is possible for the the globally optimal rate to converge to a non-zero constant as \epsilon \rightarrow 0. Moreover, in the setting where the four pendant branches have equal lengths and either (i)
Edit intent: fluency
Original:  we replace the 2-state model by an infinite state model or (ii) we retain the 2-state model and replace Kullback-Leibler separation by Euclidean distance as the maximization goal  then the optimal rate also converges to a non-zero constant.
Revised:  we replace the two-state model by an infinite state model or (ii) we retain the 2-state model and replace Kullback-Leibler separation by Euclidean distance as the maximization goal then the optimal rate also converges to a non-zero constant.
Edit intent: fluency
Original:  we replace the 2-state model by an infinite state model or (ii) we retain the 2-state model and replace Kullback-Leibler separation by Euclidean distance as the maximization goal  then the optimal rate also converges to a non-zero constant.
Revised:  we replace the 2-state model by an infinite-state model or (ii) we retain the 2-state model and replace Kullback-Leibler separation by Euclidean distance as the maximization goal then the optimal rate also converges to a non-zero constant.
Edit intent: fluency
Original:  we replace the 2-state model by an infinite state model or (ii) we retain the 2-state model and replace Kullback-Leibler separation by Euclidean distance as the maximization goal  then the optimal rate also converges to a non-zero constant.
Revised:  we replace the 2-state model by an infinite state model or (ii) we retain the two-state model and replace Kullback-Leibler separation by Euclidean distance as the maximization goal then the optimal rate also converges to a non-zero constant.
Edit intent: fluency
Original:  we replace the 2-state model by an infinite state model or (ii) we retain the 2-state model and replace Kullback-Leibler separation by Euclidean distance as the maximization goal  then the optimal rate also converges to a non-zero constant.
Revised:  we replace the 2-state model by an infinite state model or (ii) we retain the 2-state model and replace the Kullback--Leibler separation by Euclidean distance as the maximization goal then the optimal rate also converges to a non-zero constant.
Edit intent: fluency
Original:  we replace the 2-state model by an infinite state model or (ii) we retain the 2-state model and replace Kullback-Leibler separation by Euclidean distance as the maximization goal  then the optimal rate also converges to a non-zero constant.
Revised:  we replace the 2-state model by an infinite state model or (ii) we retain the 2-state model and replace Kullback-Leibler separation by Euclidean distance as the maximization goal , then the optimal rate also converges to a non-zero constant.
Edit intent: fluency
Original:  We define a new edge centrality measure, called bridgeness, to differentiate the importance of a bridge in damaging a network.
Revised:  We define a new edge centrality measure, called bridgeness, to quantify the importance of a bridge in damaging a network.
Edit intent: clarity
Original:  In contrast to previous work that has focused on individual instances as  search target, we propose the first approach to predict categories and attributes of search targets based on gaze data.
Revised:  In contrast to previous work that has focused on individual instances as a search target, we propose the first approach to predict categories and attributes of search targets based on gaze data.
Edit intent: fluency
Original:  However, state of the art models for categorical recognition in general require large amounts of training data, which is prohibitive for gaze data.
Revised:  However, state of the art models for categorical recognition , in general, require large amounts of training data, which is prohibitive for gaze data.
Edit intent: fluency
Original:  We further study how to integrate temporal and spatial gaze information most effectively, and indicate directions for future research in  gaze-based prediction of mental states.
Revised:  We further study how to integrate temporal and spatial gaze information most effectively, and indicate directions for future research in the gaze-based prediction of mental states.
Edit intent: fluency
Original: The fifth generation (5G) of mobile broadband shall be a far more complex system compared to earlier generations due to advancements in radio and network technology, increased densification and heterogeneity of network and user equipment, larger number of operating bands, as well as more stringent performance requirement .
Revised: With the fifth generation (5G) of mobile broadband shall be a far more complex system compared to earlier generations due to advancements in radio and network technology, increased densification and heterogeneity of network and user equipment, larger number of operating bands, as well as more stringent performance requirement .
Edit intent: clarity
Original: The fifth generation (5G) of mobile broadband shall be a far more complex system compared to earlier generations due to advancements in radio and network technology, increased densification and heterogeneity of network and user equipment, larger number of operating bands, as well as more stringent performance requirement .
Revised: The fifth generation (5G) of mobile broadband systems, Radio Resources Management (RRM) will reach unprecedented levels of complexity .
Edit intent: clarity
Original:  To cope with the increased complexity of the Radio Resources Management (RRM ) of 5G systems , this manuscript advocates the need for a clean slate design of the 5G RRM architecture .
Revised:  To cope with the increased complexity of the Radio Resources Management (RRM ) of 5G , this manuscript advocates the need for a clean slate design of the 5G RRM architecture .
Edit intent: clarity
Original:  To cope with the increased complexity of the Radio Resources Management (RRM ) of 5G systems , this manuscript advocates the need for a clean slate design of the 5G RRM architecture .
Revised:  To cope with the increased complexity of the Radio Resources Management (RRM ) of 5G systems , this manuscript presents a lean 5G RRM architecture .
Edit intent: clarity
Original:  We propose to capitalize the large amount of data readily available in the network from measurements and system observations in combination with the most recent advances in the field of machine learning .
Revised:  We propose to capitalize the large amount of data readily available in the network from measurements and system observations .
Edit intent: clarity
Original:  The result is an RRM architecture based on general-purpose learning framework capable of deriving specific RRM control policies directly from data gathered in the network.
Revised:  The result is a general-purpose learning framework capable of deriving specific RRM control policies directly from data gathered in the network.
Edit intent: clarity
Original:  The result is an RRM architecture based on general-purpose learning framework capable of deriving specific RRM control policies directly from data gathered in the network.
Revised:  The result is an RRM architecture based on general-purpose learning framework capable of generating algorithms specialized to RRM functionalities directly from data gathered in the network.
Edit intent: clarity
Original:  The potential of this approach is verified in three case studies and future directions on application of machine learning to RRM are discussed.
Revised:  The potential of this approach is verified in three study cases and future directions on application of machine learning to RRM are discussed.
Edit intent: fluency
Original:  The potential of this approach is verified in three case studies and future directions on application of machine learning to RRM are discussed.
Revised:  The potential of this approach is verified in three case studies and future directions on applications of machine learning to RRM are discussed.
Edit intent: fluency
Original: With the fifth generation (5G) of mobile broadband systems, Radio Resources Management (RRM) will reach unprecedented levels of complexity.
Revised: In the fifth generation (5G) of mobile broadband systems, Radio Resources Management (RRM) will reach unprecedented levels of complexity.
Edit intent: clarity
Original:  To cope with the higher complexity of RRM functionalities , while retaining the fast execution required in 5G, this manuscript presents a lean 5G RRM architecture that capitalizes on the most recent advances in the field of machine learning in combination with the large amount of data readily available in the network from measurements and system observations.
Revised:  To cope with the ever more sophisticated RRM functionalities and with the growing variety of scenarios, while carrying out the prompt decisions required in 5G, this manuscript presents a lean 5G RRM architecture that capitalizes on the most recent advances in the field of machine learning in combination with the large amount of data readily available in the network from measurements and system observations.
Edit intent: clarity
Original:  To cope with the higher complexity of RRM functionalities , while retaining the fast execution required in 5G, this manuscript presents a lean 5G RRM architecture that capitalizes on the most recent advances in the field of machine learning in combination with the large amount of data readily available in the network from measurements and system observations.
Revised:  To cope with the higher complexity of RRM functionalities , while retaining the fast execution required in 5G, this manuscript presents a lean 5G RRM architecture that capitalizes on recent advances in the field of machine learning in combination with the large amount of data readily available in the network from measurements and system observations.
Edit intent: clarity
Original:  The result is a general-purpose learning framework capable of generating algorithms specialized to RRM functionalities directly from data gathered in the network.
Revised:  The architecture relies on a single general-purpose learning framework capable of generating algorithms specialized to RRM functionalities directly from data gathered in the network.
Edit intent: clarity
Original:  The result is a general-purpose learning framework capable of generating algorithms specialized to RRM functionalities directly from data gathered in the network.
Revised:  The result is a general-purpose learning framework conceived for RRM directly using the data gathered in the network.
Edit intent: clarity
Original:  The  potential of this approach is verified in three study cases and future directions on applications of machine learning to RRM are discussed.
Revised:  The potential of this approach is verified in a pair of pertinent scenarios and future directions on applications of machine learning to RRM are discussed.
Edit intent: clarity
Original: Popular approaches to topic modeling often invoke the use of probabilistic generative models , such as Latent Dirichlet Allocation (LDA) . While such models have enjoyed widespread use and proven fruitful , these models or generalizing them to incorporate human input requires detailed and often unrealistic assumptions about the data generating process .
Revised: While generative models such as Latent Dirichlet Allocation (LDA) . While such models have enjoyed widespread use and proven fruitful , these models or generalizing them to incorporate human input requires detailed and often unrealistic assumptions about the data generating process .
Edit intent: clarity
Original: Popular approaches to topic modeling often invoke the use of probabilistic generative models , such as Latent Dirichlet Allocation (LDA) . While such models have enjoyed widespread use and proven fruitful , these models or generalizing them to incorporate human input requires detailed and often unrealistic assumptions about the data generating process .
Revised: Popular approaches to topic modeling often invoke the use of probabilistic generative models , such as Latent Dirichlet Allocation (LDA) . While such models have enjoyed widespread use and proven fruitful , these models or generalizing them to incorporate human input .
Edit intent: clarity
Original:  We introduce a new approach to topic modeling via Correlation Explanation (CorEx), which leverages an information-theoretic framework to bypass typical topic modeling assumptions.
Revised:  We introduce Correlation Explanation (CorEx), which leverages an information-theoretic framework to bypass typical topic modeling assumptions.
Edit intent: clarity