wanyu/IteraTeR_v2 huggingface dataset:
Original:  this paper speculates that certain properties of the particular physical processes that entail instances of conscious experience may obey mathematical laws pursuant to which such properties have magnitudes that are numerically defined at most times (and are thus physical properties at such times ), but have magnitudes that are numerically undefined, or "irreducibly abstract," at other times (and can thus, it is argued, be inferred to be phenomenal properties at such times ).
Revised:  this paper speculates that certain properties of the particular physical processes that entail instances of conscious experience may obey mathematical laws pursuant to which such properties have magnitudes that are numerically defined under most circumstances (and can thus be identified with physical properties under such circumstances ), but have magnitudes that are numerically undefined, or "irreducibly abstract," at other times (and can thus, it is argued, be inferred to be phenomenal properties at such times ).
Edit intent: clarity
Original:  this paper speculates that certain properties of the particular physical processes that entail instances of conscious experience may obey mathematical laws pursuant to which such properties have magnitudes that are numerically defined at most times (and are thus physical properties at such times ), but have magnitudes that are numerically undefined, or "irreducibly abstract," at other times (and can thus, it is argued, be inferred to be phenomenal properties at such times ).
Revised:  this paper speculates that certain properties of the particular physical processes that entail instances of conscious experience may obey mathematical laws pursuant to which such properties have magnitudes that are numerically defined at most times (and are thus physical properties at such times ), but have magnitudes that are numerically undefined, or "irreducibly abstract," under other circumstances (and can thus, it is argued, be inferred to be phenomenal properties at such times ).
Edit intent: clarity
Original:  this paper speculates that certain properties of the particular physical processes that entail instances of conscious experience may obey mathematical laws pursuant to which such properties have magnitudes that are numerically defined at most times (and are thus physical properties at such times ), but have magnitudes that are numerically undefined, or "irreducibly abstract," at other times (and can thus, it is argued, be inferred to be phenomenal properties at such times ).
Revised:  this paper speculates that certain properties of the particular physical processes that entail instances of conscious experience may obey mathematical laws pursuant to which such properties have magnitudes that are numerically defined at most times (and are thus physical properties at such times ), but have magnitudes that are numerically undefined, or "irreducibly abstract," at other times (and can thus, it is argued, be inferred to be phenomenal properties under such circumstances ).
Edit intent: clarity
Original:  On this view, a property can be instantiated as a physical property or a phenomenal property depending on whether its mathematical representation is numerically defined or irreducibly abstract , respectively, at a given time.
Revised:  On this view, a property can be instantiated as a physical property or a phenomenal property depending on whether its mathematical representation is numerically defined or irreducibly abstract at a given time.
Edit intent: coherence
Original:  This dynamic forms the basis for a proposed bridge law that may account for the link between the physical and the phenomenal and thus afford an advance concerning the hard problem .
Revised:  This dynamic forms the basis for a proposed bridge law that may explain the relation between the physical and the phenomenal and thus afford an advance concerning the hard problem .
Edit intent: clarity
Original:  This dynamic forms the basis for a proposed bridge law that may account for the link between the physical and the phenomenal and thus afford an advance concerning the hard problem .
Revised:  This dynamic forms the basis for a proposed bridge law that may account for the link between the physical and the phenomenal .
Edit intent: coherence
Original:  It argues that the explanatory gap (Levine, 1983) central to the hard problem of consciousness (Chalmers, 1995) can be bridged via equations featuring singularities that can intuitively explain how objectively unmeasurable properties (identified with qualia) arise from objectively measurable processes (identified with physical processes).
Revised:  It argues that the explanatory gap (Levine, 1983) central to the hard problem of consciousness (Chalmers, 1995) can be bridged via equations featuring singularities that can intuitively explain how objectively unmeasurable aspects (identified with qualia) arise from objectively measurable processes (identified with physical processes).
Edit intent: clarity
Original:  That is to say, this paper proposes that qualia correspond to singularities in the mathematical descriptions of certain physical processes .
Revised:  That is to say, this paper proposes that qualia correspond to singularities in the mathematical descriptions of certain aspects of certain complex physical systems .
Edit intent: clarity
Original: Network alignment (NA) aims to find a node mapping between compared networks in order to uncover highly similar ( i.e., conserved) network regions.
Revised: Network alignment (NA) compares networks with the goal of finding a node mapping between compared networks in order to uncover highly similar ( i.e., conserved) network regions.
Edit intent: clarity
Original: Network alignment (NA) aims to find a node mapping between compared networks in order to uncover highly similar ( i.e., conserved) network regions.
Revised: Network alignment (NA) aims to find a node mapping that uncovers highly similar ( i.e., conserved) network regions.
Edit intent: clarity
Original: Network alignment (NA) aims to find a node mapping between compared networks in order to uncover highly similar ( i.e., conserved) network regions.
Revised: Network alignment (NA) aims to find a node mapping between compared networks in order to uncover highly similar ( conserved) network regions.
Edit intent: coherence
Original:  Instead, we generalize homogeneous graphlets to their heterogeneous counterparts, which we then use to develop a new measure of heterogeneous node similarity.
Revised:  Instead, we extend homogeneous graphlets to their heterogeneous counterparts, which we then use to develop a new measure of heterogeneous node similarity.
Edit intent: clarity
Original:  Also, we generalize S^3, a state-of-the-art measure of edge conservation for homogeneous NA, to its heterogeneous counterpart.
Revised:  Also, we extend S^3, a state-of-the-art measure of edge conservation for homogeneous NA, to its heterogeneous counterpart.
Edit intent: clarity
Original:  Thus, the presence of noise makes sampling set selection a hard combinatorial problem.
Revised:  The presence of noise makes sampling set selection a hard combinatorial problem.
Edit intent: coherence
Original:  Thus, the presence of noise makes sampling set selection a hard combinatorial problem.
Revised:  Thus, the presence of noise makes choosing among these sampling sets a hard combinatorial problem.
Edit intent: clarity
Original:  Although greedy sampling schemes have become ubiquitous in practice, they have no performance guarantee.
Revised:  Although greedy sampling schemes are commonly used in practice, they have no performance guarantee.
Edit intent: clarity
Original: Snapshot Isolation (SI ) is a widely adopted concurrency control mechanism in database systems, which  utilizes timestamps to resolve conflicts between transactions.
Revised: Snapshot Isolation (SI ) is a widely adopted concurrency control mechanism in database systems, which usually utilizes timestamps to resolve conflicts between transactions.
Edit intent: coherence
Original:  As such, PostSI can scale well, rendering it suitable for various multi-core and MPP platforms.
Revised:  As such, PostSI can scale well, rendering it suitable for various multicore and MPP platforms.
Edit intent: fluency
Original: The ability to measure the transcriptome of single-cells has only been feasible for a few years, but is becoming an extremely popular assay.
Revised: The ability to measure the transcriptomes of single cells has only been feasible for a few years, but is becoming an extremely popular assay.
Edit intent: fluency
Original: The ability to measure the transcriptome of single-cells has only been feasible for a few years, but is becoming an extremely popular assay.
Revised: The ability to measure the transcriptome of single-cells has only been feasible for a few years, and is becoming an extremely popular assay.
Edit intent: fluency
Original:  While many types of analysis and questions can be answered using single cell RNA-sequencing, of prime interest is the ability to investigate what cell types occur in nature .
Revised:  While many types of analysis and questions can be answered using single cell RNA-sequencing, a central focus is the ability to investigate what cell types occur in nature .
Edit intent: clarity
Original:  While many types of analysis and questions can be answered using single cell RNA-sequencing, of prime interest is the ability to investigate what cell types occur in nature .
Revised:  While many types of analysis and questions can be answered using single cell RNA-sequencing, of prime interest is the ability to survey the diversity of cell types within a sample .
Edit intent: clarity
Original:  Unbiased and reproducible cataloging of distinct cell types require large numbers of cells to be sampled.
Revised:  Unbiased and reproducible cataloging of distinct cell types requires large numbers of cells to be sampled.
Edit intent: fluency
Original:  Technological development and improvement of protocols has exponentially scaled the size of single cell RNA-seq studies, much faster than Moore's Law .
Revised:  Technological development and improvement of protocols has exponentially scaled the size of single cell RNA-seq analyses .
Edit intent: clarity
Original:  In this perspective we will illustrate the steps that made this growth happen, and what that has meant for our ability to define cell types .
Revised:  In this perspective , we will highlight the key technological developments which have enabled this growth in data .
Edit intent: clarity
Original:  This description enables us to carry a graph-theoretic analysis of a convolutional network, with which we demonstrate a direct control over the inductive bias of the deep network via its channel numbers, that are related  min-cut in the underlying graph.
Revised:  This description enables us to carry a graph-theoretic analysis of a convolutional network, with which we demonstrate a direct control over the inductive bias of the deep network via its channel numbers, that are related to the min-cut in the underlying graph.
Edit intent: clarity
Original:  This result is relevant to any practitioner designing a convolutional network for a specific task.
Revised:  This result is relevant to any practitioner designing a network for a specific task.
Edit intent: clarity
Original:  For every setting of the parameters of the model, the computation of the partition function is precisely:  (1) Solvable in polynomial time for every graph, or (2) #P-hard for general graphs but solvable in polynomial time for planar graphs, or (3) #P-hard even for planar graphs.
Revised:  For every setting of the parameters of the model, the computation of the partition function is precisely: Either (1) Solvable in polynomial time for every graph, or (2) #P-hard for general graphs but solvable in polynomial time for planar graphs, or (3) #P-hard even for planar graphs.
Edit intent: coherence
Original:  For every setting of the parameters of the model, the computation of the partition function is precisely:  (1) Solvable in polynomial time for every graph, or (2) #P-hard for general graphs but solvable in polynomial time for planar graphs, or (3) #P-hard even for planar graphs.
Revised:  For every setting of the parameters of the model, the computation of the partition function is precisely: (1) solvable in polynomial time for every graph, or (2) #P-hard for general graphs but solvable in polynomial time for planar graphs, or (3) #P-hard even for planar graphs.
Edit intent: fluency
Original:  For every setting of the parameters of the }  model, the computation of the partition function is precisely: Either (1) solvable in polynomial time for every graph, or (2) #P-hard for general graphs but solvable in polynomial time for planar graphs, or (3) #P-hard even for planar graphs.
Revised:  For every setting of the parameters of the } model, the partition function is precisely: Either (1) solvable in polynomial time for every graph, or (2) #P-hard for general graphs but solvable in polynomial time for planar graphs, or (3) #P-hard even for planar graphs.
Edit intent: clarity
Original:  For every setting of the parameters of the }  model, the computation of the partition function is precisely: Either (1) solvable in polynomial time for every graph, or (2) #P-hard for general graphs but solvable in polynomial time for planar graphs, or (3) #P-hard even for planar graphs.
Revised:  For every setting of the parameters of the } model, the computation of the partition function is either (1) solvable in polynomial time for every graph, or (2) #P-hard for general graphs but solvable in polynomial time for planar graphs, or (3) #P-hard even for planar graphs.
Edit intent: coherence
Original:  For every setting of the parameters of the }  model, the computation of the partition function is precisely: Either (1) solvable in polynomial time for every graph, or (2) #P-hard for general graphs but solvable in polynomial time for planar graphs, or (3) #P-hard even for planar graphs.
Revised:  For every setting of the parameters of the } model, the computation of the partition function is precisely: Either (1) computable in P-time for every graph, or (2) #P-hard for general graphs but solvable in polynomial time for planar graphs, or (3) #P-hard even for planar graphs.
Edit intent: clarity
Original:  For every setting of the parameters of the }  model, the computation of the partition function is precisely: Either (1) solvable in polynomial time for every graph, or (2) #P-hard for general graphs but solvable in polynomial time for planar graphs, or (3) #P-hard even for planar graphs.
Revised:  For every setting of the parameters of the } model, the computation of the partition function is precisely: Either (1) solvable in polynomial time for every graph, or (2) #P-hard for general graphs but computable in P-time for planar graphs, or (3) #P-hard even for planar graphs.
Edit intent: clarity
Original: We propose a novel approach to improve unsupervised hashing.
Revised: We introduce a novel approach to improve unsupervised hashing.
Edit intent: clarity
Original:  One of the main observations on eye movements during scene viewing is the inhomogeneous distribution of fixation locations: While some parts of an image are fixated by almost all observers and are inspected repeatedly by the same observer, other image parts remain unfixated among observers even after long exploration intervals.
Revised:  One of the main observations on eye movements during scene viewing is the inhomogeneous distribution of fixation locations: While some parts of an image are fixated by almost all observers and are inspected repeatedly by the same observer, other image parts remain unfixated by observers even after long exploration intervals.
Edit intent: clarity
Original:  Here, we apply spatial point processes to investigate the correlations between pairs of points.
Revised:  Here, we apply spatial point process methods to investigate the correlations between pairs of points.
Edit intent: clarity
Original:  Here, we apply spatial point processes to investigate the correlations between pairs of points.
Revised:  Here, we apply spatial point processes to investigate the relationship between pairs of points.
Edit intent: clarity
Original:  More technically, the pair correlation function (PCF) is a powerful statistical tool to evaluate how individual scanpathsdeviate from the inhomogeneity observed across participants .
Revised:  More technically, the pair correlation function (PCF) , a powerful statistical tool to evaluate how individual scanpathsdeviate from the inhomogeneity observed across participants .
Edit intent: fluency
Original:  More technically, the pair correlation function (PCF) is a powerful statistical tool to evaluate how individual scanpathsdeviate from the inhomogeneity observed across participants .
Revised:  More technically, the pair correlation function (PCF) is a powerful statistical tool , to evaluate dependencies between fixation locations along individual scanpaths .
Edit intent: clarity
Original:  We demonstrate that aggregation of fixation locations within four degrees is stronger during individual trials than expected by the inhomogeneity of the distribution .
Revised:  We demonstrate that aggregation of fixation locations within four degrees is stronger than expected from chance .
Edit intent: clarity
Original:  It is easy to collect and  domain independent.
Revised:  It is easy to collect and is domain independent.
Edit intent: coherence
Original:  Existing works circumvent this problem by making various assumptions regarding the unconsumed items , which fail to hold when the user did not consume an item because she was unaware of it .
Revised:  Previous work tackles this problem by making various assumptions regarding the unconsumed items , which fail to hold when the user did not consume an item because she was unaware of it .
Edit intent: clarity
Original:  Existing works circumvent this problem by making various assumptions regarding the unconsumed items , which fail to hold when the user did not consume an item because she was unaware of it .
Revised:  Existing works circumvent this problem by assuming that users are not interested or not as much interested in the unconsumed items , which fail to hold when the user did not consume an item because she was unaware of it .
Edit intent: clarity
Original:  In this paper we propose Conformative Filtering (CoF) as a novel method for addressing the lack of negative examples in implicit feedback.
Revised:  In this paper , we propose a novel method called Conformative Filtering (CoF) as a novel method for addressing the lack of negative examples in implicit feedback.
Edit intent: clarity
Original:  The motivation is that if there is a large group of users who share the same taste and none of them  consumed an item  , then it is highly likely that the item is irrelevant to this taste.
Revised:  The motivation is that if there is a large group of users who share the same taste and none of them have consumed an item , then it is highly likely that the item is irrelevant to this taste.
Edit intent: clarity
Original:  The motivation is that if there is a large group of users who share the same taste and none of them  consumed an item  , then it is highly likely that the item is irrelevant to this taste.
Revised:  The motivation is that if there is a large group of users who share the same taste and none of them consumed an item before , then it is highly likely that the item is irrelevant to this taste.
Edit intent: clarity
Original:  The motivation is that if there is a large group of users who share the same taste and none of them  consumed an item  , then it is highly likely that the item is irrelevant to this taste.
Revised:  The motivation is that if there is a large group of users who share the same taste and none of them consumed an item , then it is likely that the item is irrelevant to this taste.
Edit intent: clarity
Original:  We use Hierarchical Latent Tree Analysis (HLTA) to identify taste-based user groups, and make recommendations for a user based on her memberships in the groups  . Experiments on  real-world datasets from different domains show that CoF has superior performance compared to other baselinesand more than 10\% improvement in Recall@5 and Recall@10 is observed .
Revised:  We use Hierarchical Latent Tree Analysis (HLTA) to identify user `tastes' groups and make recommendations for a user based on her memberships in the groups . Experiments on real-world datasets from different domains show that CoF has superior performance compared to other baselinesand more than 10\% improvement in Recall@5 and Recall@10 is observed .
Edit intent: clarity
Original:  We use Hierarchical Latent Tree Analysis (HLTA) to identify taste-based user groups, and make recommendations for a user based on her memberships in the groups  . Experiments on  real-world datasets from different domains show that CoF has superior performance compared to other baselinesand more than 10\% improvement in Recall@5 and Recall@10 is observed .
Revised:  We use Hierarchical Latent Tree Analysis (HLTA) to identify taste-based user groups, and make recommendations for a user based on her memberships in the groups . Experiments on real-world datasets from different domains show that CoF has superior performance compared to several common baselines .
Edit intent: clarity
Original:  One of the most intriguing open problems up to date is to understand the power of budget-balanced and separable cost sharing protocols in order to induce low-cost Steiner forests.
Revised:  One of the most intriguing open problems to date is to understand the power of budget-balanced and separable cost sharing protocols in order to induce low-cost Steiner forests.
Edit intent: clarity
Original:  As our main result, we give a complete characterization of efficient undirected graphs for two-player network design games: an undirected graph is efficient if and only if it does not not contain at least one out of few forbidden subgraphs.
Revised:  As our main result, we give a complete characterization of efficient undirected graphs for two-player network design games: an undirected graph is efficient if and only if it does not contain (at least) one out of few forbidden subgraphs.
Edit intent: fluency
Original:  We demonstrate our approach on five graph frameworks : GraphMat, the Graph500, the Graph Algorithm Platform  , GraphBIG, and PowerGraph using synthetic and real-world datasets.
Revised:  We demonstrate our approach on five graph processing packages : GraphMat, the Graph500, the Graph Algorithm Platform , GraphBIG, and PowerGraph using synthetic and real-world datasets.
Edit intent: clarity
Original: The brain must robustly store a large number of memories, corresponding to the many events and scenes a person encounters over a lifetime.
Revised: The brain must robustly store a large number of memories, corresponding to the many events encountered over a lifetime.
Edit intent: clarity
Original:  However, the number of memory states in existing neural network models either grows weakly with network size or recall performance fails catastrophically with vanishingly little noise.
Revised:  However, the number of memory states in existing neural network models either grows weakly with network size or recall fails catastrophically with vanishingly little noise.
Edit intent: clarity
Original:  Here we show that it is possible to construct an associative content-addressable memory (ACAM) with exponentially many stable states and robust error-correction.
Revised:  We construct an associative content-addressable memory (ACAM) with exponentially many stable states and robust error-correction.
Edit intent: coherence
Original:  Here we show that it is possible to construct an associative content-addressable memory (ACAM) with exponentially many stable states and robust error-correction.
Revised:  Here we show that it is possible to construct an associative content-addressable memory with exponentially many stable states and robust error-correction.
Edit intent: clarity