wanyu/IteraTeR_v2 huggingface dataset:
Original:  As a second main contribution, we study the tractability frontier of solving RDTPs by considering Hyper Temporal Networks (\HTNs), a strict generalization of \STNs grounded on hypergraphs: on one side, we prove that solving temporal problems having  either only multi-tail or ~ only multi-head hyperarc constraints and Type-2 constraints, it lies in both NP and co-NP and it admits deterministic pseudo-polynomial time algorithms;
Revised:  As a second main contribution, we study the tractability frontier of solving RDTPs by considering Hyper Temporal Networks (\HTNs), a strict generalization of \STNs grounded on hypergraphs: on one side, we prove that solving temporal problems having either only multi-tail or only multi-head hyperarc constraints and Type-2 constraints, it lies in both NP and co-NP and it admits deterministic pseudo-polynomial time algorithms;
Edit intent: fluency
Original:  on the other side, solving problems with  either only multi-tail or only multi-head hyperarc constraints and Type-3 constraints, it turns strongly NP-complete.
Revised:  on the other side, solving problems with either only multi-tail or only multi-head hyperarc constraints turns strongly NP-complete.
Edit intent: coherence
Original: In-memory data management systems, such as key-value store , have become an essential infrastructure in today's big-data processing and cloud computing.
Revised: In-memory data management systems, such as key-value stores , have become an essential infrastructure in today's big-data processing and cloud computing.
Edit intent: fluency
Original:  They rely on efficient index data structures to access data.
Revised:  They rely on efficient index structures to access data.
Edit intent: clarity
Original:  While unordered indexes, such as hash tables, can perform point search in the O(1) time, they cannot be used in many scenarios where range operations are required .
Revised:  While unordered indexes, such as hash tables, can perform point search with O(1) time, they cannot be used in many scenarios where range operations are required .
Edit intent: clarity
Original:  While unordered indexes, such as hash tables, can perform point search in the O(1) time, they cannot be used in many scenarios where range operations are required .
Revised:  While unordered indexes, such as hash tables, can perform point search in the O(1) time, they cannot be used in many scenarios where range queries must be supported .
Edit intent: clarity
Original:  Many ordered indexes, such as B+ tree and skip list, have a O(log N) lookup cost, where N is the number of keys in the index.
Revised:  Many ordered indexes, such as B+ tree and skip list, have a O(log N) lookup cost, where N is number of keys in the index.
Edit intent: fluency
Original:  Many ordered indexes, such as B+ tree and skip list, have a O(log N) lookup cost, where N is the number of keys in the index.
Revised:  Many ordered indexes, such as B+ tree and skip list, have a O(log N) lookup cost, where N is the number of keys in an index.
Edit intent: clarity
Original:  For an ordered index hosting billions of keys, it may take more than 30 key-comparisons for one lookup, which is an order of magnitude more expensive than that in a hash table.
Revised:  For an ordered index hosting billions of keys, it may take more than 30 key-comparisons in a lookup, which is an order of magnitude more expensive than that in a hash table.
Edit intent: clarity
Original:  For an ordered index hosting billions of keys, it may take more than 30 key-comparisons for one lookup, which is an order of magnitude more expensive than that in a hash table.
Revised:  For an ordered index hosting billions of keys, it may take more than 30 key-comparisons for one lookup, which is an order of magnitude more expensive than that on a hash table.
Edit intent: fluency
Original:  With  large memory and fast network in today's data centers, this O(log N) time is taking a big toll on applications that rely on ordered indexes.
Revised:  With availability of large memory and fast network in today's data centers, this O(log N) time is taking a big toll on applications that rely on ordered indexes.
Edit intent: clarity
Original:  With  large memory and fast network in today's data centers, this O(log N) time is taking a big toll on applications that rely on ordered indexes.
Revised:  With large memory and fast network in today's data centers, this O(log N) time is taking a heavy toll on applications that rely on ordered indexes.
Edit intent: clarity
Original:  In this paper we introduce a new ordered index data structure, named Wormhole, that takes O(log L) worst-case time for looking up a key with a length of L.
Revised:  In this paper we introduce a new ordered index structure, named Wormhole, that takes O(log L) worst-case time for looking up a key with a length of L.
Edit intent: clarity
Original:  The low cost is achieved by simultaneously leveraging strengths of three data structures, namely hash table, prefix tree, and B+ tree, to orchestrate a single fast ordered index.
Revised:  The low cost is achieved by simultaneously leveraging strengths of three indexing structures, namely hash table, prefix tree, and B+ tree, to orchestrate a single fast ordered index.
Edit intent: clarity
Original:  Wormhole's range operations can be performed by linear scanning on a list after an initial lookup.
Revised:  Wormhole's range operations can be performed by a linear scan of a list after an initial lookup.
Edit intent: fluency
Original:  Experiment results show that Wormhole outperforms skip list and B+ tree  by up to 8.4x and 4.9x  in terms of key lookup throughput, respectively .
Revised:  Experiment results show that Wormhole outperforms skip list , B+ tree by up to 8.4x and 4.9x in terms of key lookup throughput, respectively .
Edit intent: fluency
Original:  Experiment results show that Wormhole outperforms skip list and B+ tree  by up to 8.4x and 4.9x  in terms of key lookup throughput, respectively .
Revised:  Experiment results show that Wormhole outperforms skip list and B+ tree by up to 8.4x , 4.9x in terms of key lookup throughput, respectively .
Edit intent: fluency
Original: The roles of different nodes within a network are often inferred via centrality analysis, which aims to quantify the potential for a node to influence, or be influenced by, others by virtue of network connectivity .
Revised: The roles of different nodes within a network are often understood through centrality analysis, which aims to quantify the potential for a node to influence, or be influenced by, others by virtue of network connectivity .
Edit intent: clarity
Original: The roles of different nodes within a network are often inferred via centrality analysis, which aims to quantify the potential for a node to influence, or be influenced by, others by virtue of network connectivity .
Revised: The roles of different nodes within a network are often inferred via centrality analysis, which aims to quantify the capacity of a node to influence, or be influenced by, others by virtue of network connectivity .
Edit intent: clarity
Original: The roles of different nodes within a network are often inferred via centrality analysis, which aims to quantify the potential for a node to influence, or be influenced by, others by virtue of network connectivity .
Revised: The roles of different nodes within a network are often inferred via centrality analysis, which aims to quantify the potential for a node to influence, or be influenced by, other nodes via its connection topology .
Edit intent: clarity
Original:  Many different centrality measures have been proposed, but the degree to which they offer redundant or unique information, or whether it is advantageous to use multiple centrality measures to define node roles, is unclear.
Revised:  Many different centrality measures have been proposed, but the degree to which they offer unique information, or whether it is advantageous to use multiple centrality measures to define node roles, is unclear.
Edit intent: clarity
Original:  Many different centrality measures have been proposed, but the degree to which they offer redundant or unique information, or whether it is advantageous to use multiple centrality measures to define node roles, is unclear.
Revised:  Many different centrality measures have been proposed, but the degree to which they offer redundant or unique information, and such whether it is advantageous to use multiple centrality measures to define node roles, is unclear.
Edit intent: coherence
Original:  Here , we assess the correlations between 15 different centrality measures quantified in 11 networks, examine how these correlations relate to variations in network density and global topology, and clusters according to their centrality profiles to identify distinct node roles .
Revised:  Here , we assess the correlations between 15 different centrality measures quantified in 11 networks, examine how these correlations relate to variations in network density and global topology, and clusters according to their centrality profiles .
Edit intent: clarity
Original:  We find that centrality measures are generally positively correlated , but that the strength of these correlations varies across networks and that this variation in related to the modularity and majorization gap of the network . Clustering of nodes based on centrality scores indicates that most networks contain a putative core, comprising nodes that score highly across nearly all measures .
Revised:  We find that centrality measures are generally positively correlated to each other, the strength of these correlations varies across networks and that this variation in related to the modularity and majorization gap of the network . Clustering of nodes based on centrality scores indicates that most networks contain a putative core, comprising nodes that score highly across nearly all measures .
Edit intent: clarity
Original:  We find that centrality measures are generally positively correlated , but that the strength of these correlations varies across networks and that this variation in related to the modularity and majorization gap of the network . Clustering of nodes based on centrality scores indicates that most networks contain a putative core, comprising nodes that score highly across nearly all measures .
Revised:  We find that centrality measures are generally positively correlated , but that the strength of these correlations varies across networks , and network modularity plays a key role in driving these cross-network variations. Data-driven clustering of nodes based on centrality scores indicates that most networks contain a putative core, comprising nodes that score highly across nearly all measures .
Edit intent: clarity
Original:  We find that centrality measures are generally positively correlated , but that the strength of these correlations varies across networks and that this variation in related to the modularity and majorization gap of the network . Clustering of nodes based on centrality scores indicates that most networks contain a putative core, comprising nodes that score highly across nearly all measures .
Revised:  We find that centrality measures are generally positively correlated , but that the strength of these correlations varies across networks and that this variation in related to the modularity and majorization gap of the network . Clustering of nodes based on centrality profiles can distinguish different roles, including topological cores of highly central nodes and peripheries of less central nodes .
Edit intent: clarity
Original:  Our findings shed light on topological constraints that shape the pattern of correlations between centrality measures and demonstrate how a broad, comparative approach to  centrality can inform the interpretation of nodal roles in  networks.
Revised:  Our findings illustrate how network topology shapes the pattern of correlations between centrality measures and demonstrate how a broad, comparative approach to centrality can inform the interpretation of nodal roles in networks.
Edit intent: clarity
Original:  Our findings shed light on topological constraints that shape the pattern of correlations between centrality measures and demonstrate how a broad, comparative approach to  centrality can inform the interpretation of nodal roles in  networks.
Revised:  Our findings shed light on topological constraints that shape the pattern of correlations between centrality measures and demonstrate how a comparative approach to centrality can inform the interpretation of nodal roles in networks.
Edit intent: clarity
Original:  Our findings shed light on topological constraints that shape the pattern of correlations between centrality measures and demonstrate how a broad, comparative approach to  centrality can inform the interpretation of nodal roles in  networks.
Revised:  Our findings shed light on topological constraints that shape the pattern of correlations between centrality measures and demonstrate how a broad, comparative approach to network centrality can inform the interpretation of nodal roles in networks.
Edit intent: fluency
Original:  Our findings shed light on topological constraints that shape the pattern of correlations between centrality measures and demonstrate how a broad, comparative approach to  centrality can inform the interpretation of nodal roles in  networks.
Revised:  Our findings shed light on topological constraints that shape the pattern of correlations between centrality measures and demonstrate how a broad, comparative approach to centrality can inform the interpretation of nodal roles in complex networks.
Edit intent: clarity
Original: Uncovering modular structure in networks is fundamental for advancing the understanding of complex systems in biology, physics, engineering, and technology .
Revised: Uncovering modular structure in networks is fundamental for systems in biology, physics, engineering, and technology .
Edit intent: clarity
Original: Uncovering modular structure in networks is fundamental for advancing the understanding of complex systems in biology, physics, engineering, and technology .
Revised: Uncovering modular structure in networks is fundamental for advancing the understanding of complex systems in biology, physics, and engineering .
Edit intent: clarity
Original:  Community detection provides a way to computationally identify candidate modules as hypotheses, which then need to be experimentally validated .
Revised:  Community detection identifies candidate modules as hypotheses, which then need to be experimentally validated .
Edit intent: clarity
Original:  However, validation of detected communities requires expensive and time consuming experimental methods, such as mutagenesis in a wet biological laboratory.
Revised:  However, validation of detected communities requires expensive and time consuming experimental methods, such as mutagenesis in a biological laboratory.
Edit intent: clarity
Original:  As a consequence only a limited number of communities can be experimentally validated, and it is thus important to determine which communities to select for downstream validation and experimentation.
Revised:  Only a few communities can typically be validated, and it is thus important to determine which communities to select for downstream validation and experimentation.
Edit intent: clarity
Original:  As a consequence only a limited number of communities can be experimentally validated, and it is thus important to determine which communities to select for downstream validation and experimentation.
Revised:  As a consequence only a limited number of communities can be experimentally validated, and it is thus important to prioritize which communities to select for downstream validation and experimentation.
Edit intent: clarity
Original:  As a consequence only a limited number of communities can be experimentally validated, and it is thus important to determine which communities to select for downstream validation and experimentation.
Revised:  As a consequence only a limited number of communities can be experimentally validated, and it is thus important to determine which communities to select for downstream experimentation.
Edit intent: clarity
Original:  CRank can be used with any community detection method and scales to large networks .
Revised:  CRank can be used with any community detection method .
Edit intent: clarity
Original:  Experiments on many diverse and important biological networks demonstrate that the proposed approach effectively prioritizes communities, yielding a nearly 50-fold improvement in community prioritization over a baseline ordering of detected communities.
Revised:  Experiments on many large networks show that CRank effectively prioritizes communities, yielding a nearly 50-fold improvement in community prioritization over a baseline ordering of detected communities.
Edit intent: clarity
Original:  The consensus protocol on the unit sphere is the classical one  where agents move toward weighted averages of their neighbors in their respective tangent planes.
Revised:  The consensus protocol on the unit sphere is the classical one , where agents move toward weighted averages of their neighbors in their respective tangent planes.
Edit intent: fluency
Original:  For a large class of consensus protocols defined for switching uniformly quasi-strongly connected time-varying graphs  we show that the consensus manifold is uniformly asymptotically stable relative to closed balls contained in a hemisphere.
Revised:  For a large class of consensus protocols defined for switching uniformly quasi-strongly connected time-varying graphs , we show that the consensus manifold is uniformly asymptotically stable relative to closed balls contained in a hemisphere.
Edit intent: fluency
Original: Prosociality is fundamental to the success of human social life, and, accordingly, much research has attempted to explain human prosocial behavior.
Revised: Prosociality is fundamental to human social life, and, accordingly, much research has attempted to explain human prosocial behavior.
Edit intent: clarity
Original:  Capraro and Rand (  2018) recently advanced the hypothesis that prosocial behavior in anonymous, one-shot interactions  is not driven by outcome-based social preferences for equity or efficiency, as classically assumed , but by a generalized morality preference for "doing the right thing".
Revised:  Capraro and Rand ( 2018) recently provided experimental evidence that prosociality in anonymous, one-shot interactions is not driven by outcome-based social preferences for equity or efficiency, as classically assumed , but by a generalized morality preference for "doing the right thing".
Edit intent: clarity
Original:  Capraro and Rand (  2018) recently advanced the hypothesis that prosocial behavior in anonymous, one-shot interactions  is not driven by outcome-based social preferences for equity or efficiency, as classically assumed , but by a generalized morality preference for "doing the right thing".
Revised:  Capraro and Rand ( 2018) recently advanced the hypothesis that prosocial behavior in anonymous, one-shot interactions is not driven by outcome-based social preferences - as classically assumed , but by a generalized morality preference for "doing the right thing".
Edit intent: clarity
Original:  Capraro and Rand (  2018) recently advanced the hypothesis that prosocial behavior in anonymous, one-shot interactions  is not driven by outcome-based social preferences for equity or efficiency, as classically assumed , but by a generalized morality preference for "doing the right thing".
Revised:  Capraro and Rand ( 2018) recently advanced the hypothesis that prosocial behavior in anonymous, one-shot interactions is not driven by outcome-based social preferences for equity or efficiency, as classically assumed - but by a generalized morality preference for "doing the right thing".
Edit intent: fluency
Original:  Consistent with this hypothesis and the results of Capraro and Rand (2018) , our findings indicate that prosocial behavior in anonymous, one-shot interactions is driven by a preference for doing the morally right thing.
Revised:  Consistent with this hypothesis , our findings indicate that prosocial behavior in anonymous, one-shot interactions is driven by a preference for doing the morally right thing.
Edit intent: clarity
Original:  Consistent with this hypothesis and the results of Capraro and Rand (2018) , our findings indicate that prosocial behavior in anonymous, one-shot interactions is driven by a preference for doing the morally right thing.
Revised:  Consistent with this hypothesis and the results of Capraro and Rand (2018) , our findings indicate that prosociality in the anonymous, one-shot interactions is driven by a preference for doing the morally right thing.
Edit intent: clarity
Original:  Consistent with this hypothesis and the results of Capraro and Rand (2018) , our findings indicate that prosocial behavior in anonymous, one-shot interactions is driven by a preference for doing the morally right thing.
Revised:  Consistent with this hypothesis and the results of Capraro and Rand (2018) , our findings indicate that prosocial behavior in anonymous, one-shot interactions is driven by preferences for doing the morally right thing.
Edit intent: fluency
Original:  Inconsistent with influential psychological theory, however, our results suggest the preference to do "good" is as potent as the preference to avoid doing "bad" in prosocial choice .
Revised:  Inconsistent with influential psychological theory, however, our results suggest the preference to do "good" was as potent as the preference to avoid doing "bad" in prosocial choice .
Edit intent: fluency
Original:  Inconsistent with influential psychological theory, however, our results suggest the preference to do "good" is as potent as the preference to avoid doing "bad" in prosocial choice .
Revised:  Inconsistent with influential psychological theory, however, our results suggest the preference to do "good" is as potent as the preference to avoid doing "bad" in this case .
Edit intent: clarity
Original: We show that an American put option with delivery lags  can be decomposed as a European put option and another American-style derivative.
Revised: We show that an American put option with delivery lags . We show that its put option can be decomposed as a European put option and another American-style derivative.
Edit intent: clarity
Original:  Based on the this decomposition , we further show that the associated optimal exercise boundary exists , and is a strictly increasing and smooth curve .
Revised:  Based on the this decomposition , we further show that the associated optimal exercise boundary exists and is a strictly increasing and smooth curve .
Edit intent: fluency
Original:  We also analyze its asymptotic behavior for both large maturity and small time lag using the free-boundary method .
Revised:  We also analyze its asymptotic behavior for both large maturity and small time lag .
Edit intent: clarity
Original:  In this paper we present a flaw in the original proof and give another, different , and shorter proof of this result.
Revised:  However the original proof and give another, different , and shorter proof of this result.
Edit intent: coherence
Original:  In this paper we present a flaw in the original proof and give another, different , and shorter proof of this result.
Revised:  In this paper we present a flaw in the original proof has a flaw. We give a different and shorter proof of this result.
Edit intent: clarity
Original: Modelling user-item interaction patterns is an important task for personalized recommendations.
Revised: Modeling user-item interaction patterns is an important task for personalized recommendations.
Edit intent: fluency
Original:  Many recommender systems are based on the assumption that there exists a linear relationship between users and items , while neglecting the intricacy and non-linearity of real-life historical interactions.
Revised:  Many recommender systems are based on the assumption that there exists a linear relationship between users and items while neglecting the intricacy and non-linearity of real-life historical interactions.
Edit intent: fluency