wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We propose a tunable benchmark suite , Spatter, that allows users to characterize scatter, gather , and related sparse access patterns at a low level across multiple backends, including CUDA, OpenCL, and OpenMP. Spatter also allows users to vary the block size and amount of data that is moved to create a more comprehensive picture of sparse access patterns and to model patternsthat are found in real applications. With Spatter we aim to characterize the performance of memory systems in a novel way by evaluating how the density of accesses compares against real-world effective memory bandwidths (measured by STREAM) and how it can be compared across widely varying architectures including GPUs and x86, ARM, and Power CPUs. We demonstrate how Spatter can be used to generate analysis plots comparing different architectures and show that current GPUsystems achieve up to 65\% of STREAM bandwidth for sparse accesses and are more energy efficient in doing so for several different sparsity patterns.
Revised:  We propose a tunable benchmark suite , Spatter, that allows users to characterize scatter, gather , and related sparse access patterns at a low level across multiple backends, including CUDA, OpenCL, and OpenMP. Spatter also allows users to vary the block size and amount of data that is moved to create a more comprehensive picture of sparse access patterns and experiments show how it can be used to generate analysis plots comparing different architectures and show that current GPUsystems achieve up to 65\% of STREAM bandwidth for sparse accesses and are more energy efficient in doing so for several different sparsity patterns.
Edit intent: coherence
Original:  We demonstrate how Spatter can be used to generate analysis plots comparing different architectures and show that current GPUsystems achieve up to 65\% of STREAM bandwidth for sparse accesses and are more energy efficient in doing so for several different sparsity patterns. Our future plans for the spatter benchmark are to use these results to predict the impact of new memory access primitives on various architectures, develop backends for novel hardware like FPGAs and the Emu Chick, and automate testing so that users can perform their own sparse access studies .
Revised:  We demonstrate how Spatter can be used to evaluate 1) uniform access patterns for CPU and GPU, 2) prefetching regimes for gather/scatter, 3) compiler implementations of vectorization for gather/scatter, and 4) trace-driven "proxy patterns" that reflect the patterns found in multiple applications. The results from Spatter experiments show that GPUs typically outperform CPUs for these operations, and that Spatter can better predict the performance of some cache-dependent mini-apps than traditional STREAM bandwidth measurements .
Edit intent: meaning-changed
Original:  However, many traditional benchmarking tools like STREAM, STRIDE, and GUPS focus on characterizing only uniform stride or fully random accesses despite evidence that modern applications use varied set of more complex access patterns.
Revised:  However, many traditional benchmarking tools like STREAM, STRIDE, and GUPS focus on characterizing only uniform stride or fully random accesses despite evidence that modern applications use varied sets of more complex access patterns.
Edit intent: fluency
Original:  Spatter  provides a tunable and configurable framework to benchmark a variety of indexed access patterns, including variations of gather/scatter that are seen in HPC mini-apps evaluated in this work.
Revised:  Spatter is an open-source benchmark that provides a tunable and configurable framework to benchmark a variety of indexed access patterns, including variations of gather/scatter that are seen in HPC mini-apps evaluated in this work.
Edit intent: meaning-changed
Original:  The results from Spatter experiments show that GPUs typically outperform CPUs for these operations, and that Spatter can better predict the performance of some cache-dependent mini-apps than traditional STREAM bandwidth measurements.
Revised:  The results from Spatter experiments show that GPUs typically outperform CPUs for these operations, and that Spatter can better represent the performance of some cache-dependent mini-apps than traditional STREAM bandwidth measurements.
Edit intent: clarity
Original: We show how to obliviously embed into the reproducing kernel Hilbert spaceassociated with Gaussian kernels, so that distance in this space (the kernel distance) only has (1+\varepsilon)-relative error .
Revised: We introduce a two versions of a new sketch for approximately embedding the Gaussian kernel into Euclidean inner product space. These work by truncating infinite expansions of the Gaussian inner product, and carefully invoking the TensorSketch. After providing concentration and approximation properties of these sketches, we demonstrate them to approximate the kernel distance between points sets. These sketches yield almost (1+\varepsilon)-relative error .
Edit intent: meaning-changed
Original: We show how to obliviously embed into the reproducing kernel Hilbert spaceassociated with Gaussian kernels, so that distance in this space (the kernel distance) only has (1+\varepsilon)-relative error . This only holds in comparing any point sets at a kernel distance at least \alpha ; this parameter only shows up as a poly-logarithmic factor of the dimension of an intermediate embedding, but not in the final embedding. The main insight is to effectively modify the well-traveled random Fourier features to be slightly biased and have higher variance, but so they can be defined as a convolution over the function space. This result provides the first guaranteed algorithmic results for LSH of kernel distance on point sets and low-dimensional shapes and distributions, and for relative error bounds on the kernel two-sample test .
Revised: We show how to obliviously embed into the reproducing kernel Hilbert spaceassociated with Gaussian kernels, so that distance in this space (the kernel distance) only has (1+\varepsilon)-relative error , but with a small additive \alpha term. In the first variants the dependence on 1/\alpha is logarithmic, but has a separate exponential dependence on the original dimension d. In the second variant, the dependence on 1/\alpha is still sub-polynomial, but the dependence on d is linear .
Edit intent: meaning-changed
Original:  We propose an extension, Augmented SCM , which uses an outcome model to estimate the bias due to covariate imbalance and then de-biases the original SCM estimate , analogous to bias correction for inexact matching.
Revised:  We propose Augmented SCM to extend SCM to settings where such pre-treatment fit is infeasible. Analogous to bias correction for inexact matching, Augmented SCM uses an outcome model to estimate the bias due to covariate imbalance and then de-biases the original SCM estimate , analogous to bias correction for inexact matching.
Edit intent: meaning-changed
Original:  We propose an extension, Augmented SCM , which uses an outcome model to estimate the bias due to covariate imbalance and then de-biases the original SCM estimate , analogous to bias correction for inexact matching.
Revised:  We propose an extension, Augmented SCM , which uses an outcome model to estimate the bias due to imperfect pre-treatment fit and then de-biases the original SCM estimate , analogous to bias correction for inexact matching.
Edit intent: clarity
Original:  We propose an extension, Augmented SCM , which uses an outcome model to estimate the bias due to covariate imbalance and then de-biases the original SCM estimate , analogous to bias correction for inexact matching. We motivate this approach by showing that SCM is a (regularized) inverse propensity score weighting estimator, with pre-treatment outcomes as covariates and a ridge penalty on the propensity score coefficients.
Revised:  We propose an extension, Augmented SCM , which uses an outcome model to estimate the bias due to covariate imbalance and then de-biases the original SCM estimate . Our main proposal, which uses ridge regression as the outcome model, directly controls pre-treatment outcomes as covariates and a ridge penalty on the propensity score coefficients.
Edit intent: meaning-changed
Original:  We motivate this approach by showing that SCM is a (regularized) inverse propensity score weighting estimator, with pre-treatment outcomes as covariates and a ridge penalty on the propensity score coefficients. We give theoretical guarantees for specific cases and propose a new inference procedure. We demonstrate gains from Augmented SCM with extensive simulation studies and apply this framework to canonical SCM examples .
Revised:  We motivate this approach by showing that SCM is a (regularized) inverse propensity score weighting estimator, with pre-treatment fit while minimizing extrapolation from the convex hull. We bound the bias of this approach under a linear factor model and show how regularization helps to avoid over-fitting to noise. We demonstrate gains from Augmented SCM with extensive simulation studies and apply this framework to canonical SCM examples .
Edit intent: meaning-changed
Original: In this paper we study curve-restricted min-\# simplification of polygonal curves, in which the vertices of the simplified curve can be placed at any place on the input curve, provided that they respect the order along the input curve.
Revised: The goal in the min-\# curve simplification problem is to reduce the number of the vertices of a polygonal curve without changing its shape significantly. We study curve-restricted min-\# simplification of polygonal curves, in which the vertices of the simplified curve can be placed at any place on the input curve, provided that they respect the order along the input curve.
Edit intent: meaning-changed
Original: In this paper we study curve-restricted min-\# simplification of polygonal curves, in which the vertices of the simplified curve can be placed at any place on the input curve, provided that they respect the order along the input curve.
Revised: In this paper we study curve-restricted min-\# simplification of polygonal curves, in which the vertices of the simplified curve can be placed on any point of the input curve, provided that they respect the order along the input curve.
Edit intent: clarity
Original: In this paper we study curve-restricted min-\# simplification of polygonal curves, in which the vertices of the simplified curve can be placed at any place on the input curve, provided that they respect the order along the input curve.
Revised: In this paper we study curve-restricted min-\# simplification of polygonal curves, in which the vertices of the simplified curve can be placed at any place on the input curve, provided that they respect the order along that curve.
Edit intent: clarity
Original:  For local directed Hausdorff distance from the input to the simplified curve  , we present an approximation algorithm that computes a curve whose number of vertices is at most twice the number of the vertices of the curve-restricted simplification with the minimum number of vertices .
Revised:  For local directed Hausdorff distance from the input to the simplified curve in \mathbb{R , we present an approximation algorithm that computes a curve whose number of vertices is at most twice the number of the vertices of the curve-restricted simplification with the minimum number of vertices .
Edit intent: meaning-changed
Original:  For local directed Hausdorff distance from the input to the simplified curve  , we present an approximation algorithm that computes a curve whose number of vertices is at most twice the number of the vertices of the curve-restricted simplification with the minimum number of vertices .
Revised:  For local directed Hausdorff distance from the input to the simplified curve , we present an approximation algorithm that computes a curve whose number of links is at most twice the number of the vertices of the curve-restricted simplification with the minimum number of vertices .
Edit intent: clarity
Original:  For local directed Hausdorff distance from the input to the simplified curve  , we present an approximation algorithm that computes a curve whose number of vertices is at most twice the number of the vertices of the curve-restricted simplification with the minimum number of vertices .
Revised:  For local directed Hausdorff distance from the input to the simplified curve , we present an approximation algorithm that computes a curve whose number of vertices is at most twice the minimum possible .
Edit intent: clarity
Original: Despite strong stability properties, the persistent homology of filtrations classically used in Topological Data Analysis, such as, e.g. th\v{e } or Vietoris-Rips filtrations, are very sensitive to the presence of outliers in the data from which they are computed.
Revised: Despite strong stability properties, the persistent homology of filtrations classically used in Topological Data Analysis, such as, e.g. the } or Vietoris-Rips filtrations, are very sensitive to the presence of outliers in the data from which they are computed.
Edit intent: fluency
Original: Despite strong stability properties, the persistent homology of filtrations classically used in Topological Data Analysis, such as, e.g. th\v{e } or Vietoris-Rips filtrations, are very sensitive to the presence of outliers in the data from which they are computed.
Revised: Despite strong stability properties, the persistent homology of filtrations classically used in Topological Data Analysis, such as, e.g. th\v{e \v C} or Vietoris-Rips filtrations, are very sensitive to the presence of outliers in the data from which they are computed.
Edit intent: meaning-changed
Original: Despite strong stability properties, the persistent homology of filtrations classically used in Topological Data Analysis, such as, e.g. th\v{e } or Vietoris-Rips filtrations, are very sensitive to the presence of outliers in the data from which they are computed.
Revised: Despite strong stability properties, the persistent homology of filtrations classically used in Topological Data Analysis, such as, e.g. th\v{e }ech or Vietoris-Rips filtrations, are very sensitive to the presence of outliers in the data from which they are computed.
Edit intent: fluency
Original: We perform a bidimensional Stokes experiment in an active cellular material: we force a monolayer of Madin-Darby Canine Kidney (MDCK) epithelial cells to migrate around a circular obstacle within a long and narrow channel, involving  cell shape changes and neighbour rearrangements.
Revised: We perform a bidimensional Stokes experiment in an active cellular material: an autonomously migrating monolayer of Madin-Darby Canine Kidney (MDCK) epithelial cells to migrate around a circular obstacle within a long and narrow channel, involving cell shape changes and neighbour rearrangements.
Edit intent: clarity
Original: We perform a bidimensional Stokes experiment in an active cellular material: we force a monolayer of Madin-Darby Canine Kidney (MDCK) epithelial cells to migrate around a circular obstacle within a long and narrow channel, involving  cell shape changes and neighbour rearrangements.
Revised: We perform a bidimensional Stokes experiment in an active cellular material: we force a monolayer of Madin-Darby Canine Kidney (MDCK) epithelial cells flows around a circular obstacle within a long and narrow channel, involving cell shape changes and neighbour rearrangements.
Edit intent: clarity
Original: We perform a bidimensional Stokes experiment in an active cellular material: we force a monolayer of Madin-Darby Canine Kidney (MDCK) epithelial cells to migrate around a circular obstacle within a long and narrow channel, involving  cell shape changes and neighbour rearrangements.
Revised: We perform a bidimensional Stokes experiment in an active cellular material: we force a monolayer of Madin-Darby Canine Kidney (MDCK) epithelial cells to migrate around a circular obstacle within a long and narrow channel, involving an interplay between cell shape changes and neighbour rearrangements.
Edit intent: clarity
Original:  We find that the cell deformation and cell rearrangement rate fields correlate strongly, which is compatible with a  viscoelastic liquid behaviour with a relaxation time \tau = 70 \pm 15 min.
Revised:  We find that the cell deformation and rearrangement rate fields correlate strongly, which is compatible with a viscoelastic liquid behaviour with a relaxation time \tau = 70 \pm 15 min.
Edit intent: fluency
Original:  We find that the cell deformation and cell rearrangement rate fields correlate strongly, which is compatible with a  viscoelastic liquid behaviour with a relaxation time \tau = 70 \pm 15 min.
Revised:  We find that the cell deformation and cell rearrangement rate fields correlate strongly, which is compatible with a Maxwell viscoelastic liquid behaviour with a relaxation time \tau = 70 \pm 15 min.
Edit intent: meaning-changed
Original:  We find that the cell deformation and cell rearrangement rate fields correlate strongly, which is compatible with a  viscoelastic liquid behaviour with a relaxation time \tau = 70 \pm 15 min.
Revised:  We find that the cell deformation and cell rearrangement rate fields correlate strongly, which is compatible with a viscoelastic liquid behaviour (and not with a Kelvin-Voigt viscoelastic solid behaviour). The value of the associated relaxation time is measured as \tau = 70 \pm 15 min.
Edit intent: meaning-changed
Original:  We find that the cell deformation and cell rearrangement rate fields correlate strongly, which is compatible with a  viscoelastic liquid behaviour with a relaxation time \tau = 70 \pm 15 min. In our experiment, the monolayer behaves as a flowing material with a Weissenberg number close to one which shows that both elastic and viscous effects can have comparable contributions in the process of collective cell migration.
Revised:  We find that the cell deformation and cell rearrangement rate fields correlate strongly, which is compatible with a viscoelastic liquid behaviour with a relaxation time \tau = 70 \pm 15 ~min, is observed to be independent of obstacle size and division rate, and is increased by inhibiting myosin activity. In this experiment, the monolayer behaves as a flowing material with a Weissenberg number close to one which shows that both elastic and viscous effects can have comparable contributions in the process of collective cell migration.
Edit intent: meaning-changed
Original: We introduce a set-valued generalization of Nash equilibrium, called M equilibrium, which is based on ordinal monotonicity - players' choice probabilities are ranked the same as the expected payoffs based on their beliefs - and ordinal consistency - players' beliefs yield the same ranking of expected payoffs as their choices.
Revised: We introduce a set-valued solution concept, M equilibrium, which is based on ordinal monotonicity - players' choice probabilities are ranked the same as the expected payoffs based on their beliefs - and ordinal consistency - players' beliefs yield the same ranking of expected payoffs as their choices.
Edit intent: clarity
Original: We introduce a set-valued generalization of Nash equilibrium, called M equilibrium, which is based on ordinal monotonicity - players' choice probabilities are ranked the same as the expected payoffs based on their beliefs - and ordinal consistency - players' beliefs yield the same ranking of expected payoffs as their choices. Using results from semi-algebraic geometry, we prove there exist a finite number of M equilibria, each consisting of a finite number of connected components. Generically, M-equilibria can be "color coded" by their ranks in the sense that choices and beliefs belonging to the same M equilibrium have the same color. We show that colorable M equilibria are behaviorally stable, a concept that strengthens strategic stability. Furthermore, set-valued and parameter-free M equilibrium envelopes various parametric models based on fixed-points, including QRE as well as a new andcomputationally simpler class of models called \mu%DIFDELCMD < } %%% Equilibrium .
Revised: We introduce a set-valued generalization of Nash equilibrium, called M equilibrium, to capture empirical regularities from over half a century of game-theory experiments. We show M equilibrium serves as a meta theory for various models that hitherto were considered unrelated. M equilibrium is empirically robust and, despite being set-valued and parameter-free M equilibrium envelopes various parametric models based on fixed-points, including QRE as well as a new andcomputationally simpler class of models called \mu%DIFDELCMD < } %%% Equilibrium .
Edit intent: meaning-changed
Original:  Furthermore, set-valued and parameter-free M equilibrium envelopes various parametric models based on fixed-points, including QRE as well as a new andcomputationally simpler class of models called \mu%DIFDELCMD < } %%% Equilibrium .
Revised:  Furthermore, set-valued and parameter-free M equilibrium envelopes various parametric models based on fixed-points, including QRE as well as a new andcomputationally simpler class of models called %DIFDELCMD < } %%% Equilibrium .
Edit intent: fluency
Original:  Furthermore, set-valued and parameter-free M equilibrium envelopes various parametric models based on fixed-points, including QRE as well as a new andcomputationally simpler class of models called \mu%DIFDELCMD < } %%% Equilibrium .
Revised:  Furthermore, set-valued and parameter-free M equilibrium envelopes various parametric models based on fixed-points, including QRE as well as a new andcomputationally simpler class of models called \mu%DIFDELCMD < } %%% , falsifiable .
Edit intent: meaning-changed
Original:  We report the results of several experiments designed to contrast M equilibrium predictions with those of existing behavioral game-theory models . A first experiment considers five variations of an asymmetric-matching pennies game that leave the predictions of Nash, various versions of QRE, and level-k unaltered. However, observed choice frequencies differ substantially and significantly across games as do players' beliefs. Moreover, beliefs and choices are heterogeneous and beliefs do not match choices in any of the games. These findings contradict existing behavioral game-theory models but accord well with the unique M equilibrium. Follow up experiments employ 3 by 3 games with a unique pure-strategy Nash equilibrium and multiple M equilibria .
Revised:  We report results from a series of experiments comparing M equilibrium to leading behavioral-game-theory models and demonstrate its virtues in predicting observed choices and stated beliefs. Data from experimental games with a unique pure-strategy Nash equilibrium and multiple M equilibria .
Edit intent: clarity
Original:  Follow up experiments employ 3 by 3 games with a unique pure-strategy Nash equilibrium and multiple M equilibria . The belief and choice data exhibit coordination problems that could not be anticipated through the lens of existing behavioral game-theory models.
Revised:  Follow up experiments employ 3 by 3 games with a unique pure-strategy Nash equilibrium and multiple M equilibria exhibit coordination problems that could not be anticipated through the lens of existing behavioral game-theory models.
Edit intent: coherence
Original:  We have obtained a general relation allowing calculating exactly the probability density function ( pdf ) p(t) of output interspike intervals (ISI) values for a neuronwith feedback based on known pdf p^0(t) for the same neuron without feedback, intensity of the input stream \lambda and the properties of the feedback line.
Revised:  We have obtained a general relation allowing calculating exactly the probability density function ( PDF ) p(t) of output interspike intervals (ISI) values for a neuronwith feedback based on known pdf p^0(t) for the same neuron without feedback, intensity of the input stream \lambda and the properties of the feedback line.
Edit intent: fluency