wanyu/IteraTeR_v2 huggingface dataset:
Original: We address the generalized Nash equilibrium (GNE) problem in a partial-decision information scenario, where each agent can only observe the actions of some neighbors, while its cost function possibly depends on the strategies of other agents.
Revised: We address the generalized Nash equilibrium (GNE) problem in a partial-decision information scenario, where each agent can only exchange information with some neighbors, while its cost function possibly depends on the strategies of other agents.
Edit intent: clarity
Original: We address the generalized Nash equilibrium (GNE) problem in a partial-decision information scenario, where each agent can only observe the actions of some neighbors, while its cost function possibly depends on the strategies of other agents.
Revised: We address the generalized Nash equilibrium (GNE) problem in a partial-decision information scenario, where each agent can only observe the actions of some neighbors, although its cost function possibly depends on the strategies of other agents.
Edit intent: coherence
Original:  As main contribution, we design a fully-distributed , single-layer , fixed-step algorithm to seek a variational GNE, based on a proximal best-response augmented with consensus and constraint-violation penalization terms.
Revised:  As main contribution, we design a fully-distributed single-layer , fixed-step algorithm to seek a variational GNE, based on a proximal best-response augmented with consensus and constraint-violation penalization terms.
Edit intent: fluency
Original:  As main contribution, we design a fully-distributed , single-layer , fixed-step algorithm to seek a variational GNE, based on a proximal best-response augmented with consensus and constraint-violation penalization terms.
Revised:  As main contribution, we design a fully-distributed , single-layer algorithms based on proximal best-response augmented with consensus and constraint-violation penalization terms.
Edit intent: clarity
Original:  This operator-theoretic interpretation proves very powerful.
Revised:  Besides, our operator-theoretic interpretation proves very powerful.
Edit intent: coherence
Original:  Convergence-based error estimates are well studied, with the estimate depending heavily on the eigenvalue gap.
Revised:  Convergence-based error estimates depend heavily on the eigenvalue gap.
Edit intent: clarity
Original:  However, in practice, this gap is often relatively small, resulting in significant overestimates of error.
Revised:  In practice, this gap is often relatively small, resulting in significant overestimates of error.
Edit intent: coherence
Original:  In this work, we prove a number of upper and lower uniform error estimates for the Lanczos method.
Revised:  In this work, we prove explicit upper and lower uniform error estimates for the Lanczos method.
Edit intent: clarity
Original:  These lower bounds imply that the maximum error of m iterations of the Lanczos method over all n \times n symmetric matrices does indeed depend on the dimension n  . The improved upper and lower bounds for extremal eigenvalues translates immediately to error estimates for the condition number of a symmetric positive definite matrix.
Revised:  These lower bounds imply that the maximum error of m iterations of the Lanczos method over all n \times n symmetric matrices does indeed depend on the dimension n . The improved bounds for extremal eigenvalues translates immediately to error estimates for the condition number of a symmetric positive definite matrix.
Edit intent: clarity
Original:  These lower bounds imply that the maximum error of m iterations of the Lanczos method over all n \times n symmetric matrices does indeed depend on the dimension n  . The improved upper and lower bounds for extremal eigenvalues translates immediately to error estimates for the condition number of a symmetric positive definite matrix.
Revised:  These lower bounds imply that the maximum error of m iterations of the Lanczos method over all n \times n symmetric matrices does indeed depend on the dimension n . The improved upper and lower bounds for extremal eigenvalues translate immediately to error estimates for the condition number of a symmetric positive definite matrix.
Edit intent: fluency
Original:  The identification of structures playing important roles in such processes remain an open question, despite recent progresses in the case of static networks.
Revised:  The identification of structures playing important roles in such processes remains largely an open question, despite recent progresses in the case of static networks.
Edit intent: clarity
Original:  The effectiveness of such strategies is assessed in a variety of empirical data sets and against a number of baselines that use only static information on the centrality of nodes and static concepts of coreness  .
Revised:  The effectiveness of such strategies is assessed in a variety of empirical data sets and compared to baselines that use only static information on the centrality of nodes and static concepts of coreness .
Edit intent: clarity
Original:  Our results show that the removal of the most stable and cohesive temporal cores has a strong impact on epidemic processes on temporal networks, and that their nodes are likely to represent influential spreaders.
Revised:  Our results show that the most stable and cohesive temporal cores has a strong impact on epidemic processes on temporal networks, and that their nodes are likely to represent influential spreaders.
Edit intent: clarity
Original:  Our results show that the removal of the most stable and cohesive temporal cores has a strong impact on epidemic processes on temporal networks, and that their nodes are likely to represent influential spreaders.
Revised:  Our results show that the removal of the most stable and cohesive temporal cores play indeed an important role in epidemic processes on temporal networks, and that their nodes are likely to represent influential spreaders.
Edit intent: clarity
Original:  However, the paper itself doesn't attempt to answer the implied question of why Deep Convolutional Neural Networks (DCNNs) can approximate so many of the mappings that they have been trained to model.
Revised:  However, the paper doesn't attempt to answer the implied question of why Deep Convolutional Neural Networks (DCNNs) can approximate so many of the mappings that they have been trained to model.
Edit intent: clarity
Original:  There are detailed mathematical analyses, but this short paper attempts to look at the issue differently, considering the way that these networks are used, the subset of these functions that can be achieved by training (starting from some location in the original function space), as well as the functions that in reality will be modelled .
Revised:  While there are detailed mathematical analyses, but this short paper attempts to look at the issue differently, considering the way that these networks are used, the subset of these functions that can be achieved by training (starting from some location in the original function space), as well as the functions that in reality will be modelled .
Edit intent: fluency
Original:  There are detailed mathematical analyses, but this short paper attempts to look at the issue differently, considering the way that these networks are used, the subset of these functions that can be achieved by training (starting from some location in the original function space), as well as the functions that in reality will be modelled .
Revised:  There are detailed mathematical analyses, this short paper attempts to look at the issue differently, considering the way that these networks are used, the subset of these functions that can be achieved by training (starting from some location in the original function space), as well as the functions that in reality will be modelled .
Edit intent: coherence
Original:  There are detailed mathematical analyses, but this short paper attempts to look at the issue differently, considering the way that these networks are used, the subset of these functions that can be achieved by training (starting from some location in the original function space), as well as the functions that in reality will be modelled .
Revised:  There are detailed mathematical analyses, but this short paper attempts to look at the issue differently, considering the way that these networks are used, the subset of these functions that can be achieved by training (starting from some location in the original function space), as well as the functions to which these networks will actually be applied .
Edit intent: clarity
Original:  We confirm that our approach is easily realizable through a compact prototype implementation which matches our expectations for performance and is shown, both formally and empirically, to possess the desired security characteristics.
Revised:  We confirm that our approach is easily realizable through a compact implementation which matches our expectations for performance and is shown, both formally and empirically, to possess the desired security characteristics.
Edit intent: clarity
Original:  We initiate the study of the message complexity for population protocols, where the state of an agent is divided into an externally-visible message and an internal component, where only the message can be observed by the other agent in an interaction.
Revised:  We initiate the study of the message complexity for population protocols, where the state of an agent is divided into an externally-visible message and an internal component, where only the message can be observed by the other agent in an interaction.
Edit intent: fluency
Original:  We initiate the study of the message complexity for population protocols, where the state of an agent is divided into an externally-visible message and an internal component, where only the message can be observed by the other agent in an interaction.
Revised:  We initiate the study of message complexity for population protocols, where the state of an agent is divided into an externally-visible message and an internal component, where only the message can be observed by the other agent in an interaction.
Edit intent: fluency
Original:  When time is unrestricted, we obtain an exact characterization of the stably computable predicates based on the number of internal states s(n): If s(n) = o(n) then the protocol computes a semilinear predicate (unlike the original model, which can compute non-semilinear predicates with s(n) = O(\log n)), and otherwise it computes a predicate decidable by a nondeterministic O(n \log s(n))-space-bounded Turing machine.
Revised:  When time is unrestricted, we obtain an exact characterization of the stably computable predicates based on the number of internal states s(n): If s(n) = o(n) then the protocol computes semilinear predicates (unlike the original model, which can compute non-semilinear predicates with s(n) = O(\log n)), and otherwise it computes a predicate decidable by a nondeterministic O(n \log s(n))-space-bounded Turing machine.
Edit intent: fluency
Original:  We then consider time complexity, introducing novel O(polylog(n)) expected time protocols for junta/leader election and general purpose broadcast correct with high probability, and approximate and exact population size counting correct with probability 1.
Revised:  We then introduce novel O(polylog(n)) expected time protocols for junta/leader election and general purpose broadcast correct with high probability, and approximate and exact population size counting correct with probability 1.
Edit intent: clarity
Original:  Finally, we show that the main constraint on the power of bounded-message-size protocols is the size of the internal states: with unbounded internal states, any computable function can be computed with probability 1 in the limit by a protocol that uses only one-bit messages.
Revised:  Finally, we show that the main constraint on the power of bounded-message-size protocols is the size of the internal states: with unbounded internal states, any computable function can be computed with probability 1 in the limit by a protocol that uses only 1-bit messages.
Edit intent: fluency
Original:  AID combines existing statistical debugging, causal analysis, fault injection, and group testing techniques in a novel way to (1) pinpoint the root-cause of an application's intermittent failure and (2) generate an explanation of how the root-cause triggers the failure.
Revised:  AID combines existing statistical debugging, causal analysis, fault injection, and group testing techniques in a novel way to (1) pinpoint the root cause of an application's intermittent failure and (2) generate an explanation of how the root-cause triggers the failure.
Edit intent: fluency
Original:  AID combines existing statistical debugging, causal analysis, fault injection, and group testing techniques in a novel way to (1) pinpoint the root-cause of an application's intermittent failure and (2) generate an explanation of how the root-cause triggers the failure.
Revised:  AID combines existing statistical debugging, causal analysis, fault injection, and group testing techniques in a novel way to (1) pinpoint the root-cause of an application's intermittent failure and (2) generate an explanation of how the root cause triggers the failure.
Edit intent: fluency
Original:  Finally, it uses  a sequence of runtime interventions of the predicates to discover their true causal relationships.
Revised:  Finally, it uses a sequence of interventions on the predicates and discover their true causal relationships.
Edit intent: clarity
Original:  This enables AID to identify the true root-cause and its causal relationship to the failure.
Revised:  This enables AID to identify the true root cause and its causal relationship to the failure.
Edit intent: fluency
Original:  In each case, AID was able to identify the root-cause and explain how the root-cause triggered the failure, much faster than group testing and more precisely than statistical debugging.
Revised:  In each case, AID was able to identify the root cause and explain how the root-cause triggered the failure, much faster than group testing and more precisely than statistical debugging.
Edit intent: fluency
Original:  In each case, AID was able to identify the root-cause and explain how the root-cause triggered the failure, much faster than group testing and more precisely than statistical debugging.
Revised:  In each case, AID was able to identify the root-cause and explain how the root cause triggered the failure, much faster than group testing and more precisely than statistical debugging.
Edit intent: fluency
Original:  We also evaluate AID with many synthetically generated applications with known root-causes and confirm that the benefits also hold for them.
Revised:  We also evaluate AID with many synthetically generated applications with known root causes and confirm that the benefits also hold for them.
Edit intent: fluency
Original: A comprehensive understanding of data bias is the cornerstone of mitigating biases in social media research.
Revised: A comprehensive understanding of data quality is the cornerstone of mitigating biases in social media research.
Edit intent: clarity
Original: A comprehensive understanding of data bias is the cornerstone of mitigating biases in social media research.
Revised: A comprehensive understanding of data bias is the cornerstone of measurement studies in social media research.
Edit intent: clarity
Original:  This paper presents in-depth measurements of the effects of Twitter data sampling across different timescales and different subjects (entities, networks, and cascades).
Revised:  This paper presents in-depth measurements on the effects of Twitter data sampling across different timescales and different subjects (entities, networks, and cascades).
Edit intent: fluency
Original:  By constructing two complete tweet streams, we show that Twitter rate limit message is an accurate measure for the volume of missing tweets.
Revised:  By constructing complete tweet streams, we show that Twitter rate limit message is an accurate measure for the volume of missing tweets.
Edit intent: clarity
Original:  By constructing two complete tweet streams, we show that Twitter rate limit message is an accurate measure for the volume of missing tweets.
Revised:  By constructing two complete tweet streams, we show that Twitter rate limit message is an accurate indicator for the volume of missing tweets.
Edit intent: clarity
Original:  We identify risks for information diffusion models that rely on tweet inter-arrival times and user influence .
Revised:  We identify risks for information diffusion models that rely on these features .
Edit intent: clarity
Original:  This work calls attention to the social databias caused by data collection, and proposes methods to measure the systematic biases introduced by sampling .
Revised:  This work calls attention to noises and potential biases in social data, and provides a few tools to measure Twitter sampling effects .
Edit intent: clarity
Original: Graph Convolutional Network (GCN) has shown strong effectiveness in graph learning tasks.
Revised: Graph Convolutional Network (GCN) has been widely used in graph learning tasks.
Edit intent: clarity
Original:  Moreover, with the depth of layers increases, the computational and memory cost of GCN grows explosively on account of the recursive neighborhood expansion , which leads to a limitation in processing large graphs .
Revised:  Moreover, with the depth of layers increases, the computational and memory cost of GCNs grow explosively due to the recursive neighborhood expansion , which leads to a limitation in processing large graphs .
Edit intent: clarity
Original:  Moreover, with the depth of layers increases, the computational and memory cost of GCN grows explosively on account of the recursive neighborhood expansion , which leads to a limitation in processing large graphs .
Revised:  Moreover, with the depth of layers increases, the computational and memory cost of GCN grows explosively on account of the recursive neighborhood expansion .
Edit intent: coherence
Original: A total\ coloring \textit{ of a graph G is a map f:V(G) \cup E(G) \rightarrow K, where K is a set of colors, satisfying the following three conditions: 1. f(u) \neq f(v) for any two adjacent vertices u, v \in V(G);
Revised: Total Coloring \textit{ of a graph G is a map f:V(G) \cup E(G) \rightarrow K, where K is a set of colors, satisfying the following three conditions: 1. f(u) \neq f(v) for any two adjacent vertices u, v \in V(G);
Edit intent: fluency
Original:  and 3. f(v) \neq f(e) for any vertex v \in V(G) and any edge e \in E(G) that is incident to  same vertex v. The total\ chromatic\ number , \chi''(G), is the minimum number of colors required for a total\ coloring \textit{ of G. Behzad and Vizing independently conjectured that , for any graph G , \chi''(G)\leq \Delta + 2.
Revised:  and 3. f(v) \neq f(e) for any vertex v \in V(G) and any edge e \in E(G) that is incident to the same vertex v. The total\ chromatic\ number , \chi''(G), is the minimum number of colors required for a total\ coloring \textit{ of G. Behzad and Vizing independently conjectured that , for any graph G , \chi''(G)\leq \Delta + 2.
Edit intent: fluency
Original:  and 3. f(v) \neq f(e) for any vertex v \in V(G) and any edge e \in E(G) that is incident to  same vertex v. The total\ chromatic\ number , \chi''(G), is the minimum number of colors required for a total\ coloring \textit{ of G. Behzad and Vizing independently conjectured that , for any graph G , \chi''(G)\leq \Delta + 2.
Revised:  and 3. f(v) \neq f(e) for any vertex v \in V(G) and any edge e \in E(G) that is incident to same vertex v. The total chromatic number , \chi''(G), is the minimum number of colors required for a total\ coloring \textit{ of G. Behzad and Vizing independently conjectured that , for any graph G , \chi''(G)\leq \Delta + 2.
Edit intent: fluency
Original:  and 3. f(v) \neq f(e) for any vertex v \in V(G) and any edge e \in E(G) that is incident to  same vertex v. The total\ chromatic\ number , \chi''(G), is the minimum number of colors required for a total\ coloring \textit{ of G. Behzad and Vizing independently conjectured that , for any graph G , \chi''(G)\leq \Delta + 2.
Revised:  and 3. f(v) \neq f(e) for any vertex v \in V(G) and any edge e \in E(G) that is incident to same vertex v. The total\ chromatic\ number , \chi''(G), is the minimum number of colors required for a total\ coloring \textit{ of G. Behzad and Vizing independently conjectured that , for any graph G \chi''(G)\leq \Delta + 2.
Edit intent: fluency
Original:  This  is one of the classic mathematical unsolved problems.
Revised:  This is one of the classic unsolved mathematical problems.
Edit intent: fluency
Original:  In this paper, we settle this classical conjecture by proving that the total\ chromatic\ number \chi''(G) of a graph is indeed bounded above by \Delta+2.
Revised:  In this paper, we settle this classical conjecture by proving that the total chromatic number \chi''(G) of a graph is indeed bounded above by \Delta+2.
Edit intent: fluency
Original:  Our novel approach involves algebraic settings over  finite field \mathbb{Z}_p and application of combinatorial nullstellensatz .
Revised:  Our novel approach involves algebraic settings over a finite field \mathbb{Z}_p and application of combinatorial nullstellensatz .
Edit intent: fluency
Original: Predictive power allocation is conceived for power-efficient video streaming over mobile networks using deep reinforcement learning.
Revised: Predictive power allocation is conceived for energy-efficient video streaming over mobile networks using deep reinforcement learning.
Edit intent: clarity
Original:  The goal is to minimize the accumulated energy consumption  over a complete video streaming session for a mobile user under the quality of service constraint that avoids video playback interruptions.
Revised:  The goal is to minimize the accumulated energy consumption over a complete video streaming session under the constraint that avoids video playback interruptions.
Edit intent: clarity
Original:  In contrast to previous predictive resource policies that first predict future information with historical data and then optimize the policy based on the predicted information, the proposed policy operates in an on-line and end-to-end manner.
Revised:  In contrast to previous predictive power allocation policies that first predict future information with historical data and then optimize the policy based on the predicted information, the proposed policy operates in an on-line and end-to-end manner.
Edit intent: clarity
Original:  In contrast to previous predictive resource policies that first predict future information with historical data and then optimize the policy based on the predicted information, the proposed policy operates in an on-line and end-to-end manner.
Revised:  In contrast to previous predictive resource policies that first predict future information with historical data and then optimize the power allocation based on the predicted information, the proposed policy operates in an on-line and end-to-end manner.
Edit intent: clarity
Original:  By judiciously designing the action and state that only depend on slowly-varying average channel gains,  the signaling overhead between the edge server and the base stations can be reduced, and the dynamics of the system can be learned effortlessly.
Revised:  By judiciously designing the action and state that only depend on slowly-varying average channel gains, we reduce the signaling overhead between the edge server and the base stations can be reduced, and the dynamics of the system can be learned effortlessly.
Edit intent: clarity
Original:  To improve the robustness of streaming and accelerate learning , we further exploit the partially known dynamics of the system  by integrating the concepts of safer layer, post-decision state, and virtual experience into the basic DDPG algorithm.
Revised:  To improve the robustness of streaming and accelerate learning , we further exploit the partially known model of the system by integrating the concepts of safer layer, post-decision state, and virtual experience into the basic DDPG algorithm.
Edit intent: clarity