wanyu/IteraTeR_v2 huggingface dataset:
Original:  We here investigate the influence of neuron diversity on the dynamical stability , phase space structure , and computational capabilities of inhibitory spiking networks using mixtures of neurons with positive and negative dissipation .
Revised:  Here we investigate the influence of neuron diversity on the dynamical stability , phase space structure , and computational capabilities of inhibitory spiking networks using mixtures of neurons with positive and negative dissipation .
Edit intent: coherence
Original:  We here investigate the influence of neuron diversity on the dynamical stability , phase space structure , and computational capabilities of inhibitory spiking networks using mixtures of neurons with positive and negative dissipation .
Revised:  We here investigate the influence of neuron diversity on the dynamics , phase space structure , and computational capabilities of inhibitory spiking networks using mixtures of neurons with positive and negative dissipation .
Edit intent: clarity
Original:  We here investigate the influence of neuron diversity on the dynamical stability , phase space structure , and computational capabilities of inhibitory spiking networks using mixtures of neurons with positive and negative dissipation .
Revised:  We here investigate the influence of neuron diversity on the dynamical stability , phase space structure and computational capabilities of inhibitory spiking networks using mixtures of neurons with positive and negative dissipation .
Edit intent: fluency
Original:  We here investigate the influence of neuron diversity on the dynamical stability , phase space structure , and computational capabilities of inhibitory spiking networks using mixtures of neurons with positive and negative dissipation .
Revised:  We here investigate the influence of neuron diversity on the dynamical stability , phase space structure , and computational capabilities of spiking neural networks .
Edit intent: clarity
Original:  We find that already a single neuron of a different type may qualitatively change the dynamics of a neural network and that mixed networks can combine the computational capabilities of ones with only a single neuron type.
Revised:  We find that already a single neuron of a different type can qualitatively change the dynamics of a neural network and that mixed networks can combine the computational capabilities of ones with only a single neuron type.
Edit intent: clarity
Original:  We find that already a single neuron of a different type may qualitatively change the dynamics of a neural network and that mixed networks can combine the computational capabilities of ones with only a single neuron type.
Revised:  We find that already a single neuron of a different type may qualitatively change the network dynamics and that mixed networks can combine the computational capabilities of ones with only a single neuron type.
Edit intent: clarity
Original:  We find that already a single neuron of a different type may qualitatively change the dynamics of a neural network and that mixed networks can combine the computational capabilities of ones with only a single neuron type.
Revised:  We find that already a single neuron of a different type may qualitatively change the dynamics of a neural network and that mixed networks may combine the computational capabilities of ones with only a single neuron type.
Edit intent: clarity
Original:  We find that already a single neuron of a different type may qualitatively change the dynamics of a neural network and that mixed networks can combine the computational capabilities of ones with only a single neuron type.
Revised:  We find that already a single neuron of a different type may qualitatively change the dynamics of a neural network and that mixed networks can combine the computational capabilities of ones with a single neuron type.
Edit intent: clarity
Original:   Our results indicate that the performance of CoUD differs depending on the cost assigned per time unit  however the optimal policy remains the same  .
Revised:  Our results indicate that the performance of CoUD differs depending on the cost assigned per time unit , however the optimal policy remains the same .
Edit intent: fluency
Original: The Unbiased Learning-to-Rank framework has been recently introduced as a general approach to systematically remove biases, such as position bias, from learning-to-rank models.
Revised: The Unbiased Learning-to-Rank framework has been recently proposed as a general approach to systematically remove biases, such as position bias, from learning-to-rank models.
Edit intent: clarity
Original:  In this work we propose a novel method to  estimate propensities which does not use any intervention in live search or rely on any ranking features . Rather, we take advantage of the fact that the same query-document pair may naturally change ranks over time.
Revised:  In this work we propose a novel method to estimate propensities which does not use any intervention in live search or rely on modeling relevance . Rather, we take advantage of the fact that the same query-document pair may naturally change ranks over time.
Edit intent: clarity
Original:  Finally, we train a simple unbiased learning-to-rank model for eBay search using the estimated propensities and show that it outperforms the baseline model (which does not correct for position bias ) on our offline evaluation metrics .
Revised:  Finally, we train an unbiased learning-to-rank model for eBay search using the estimated propensities and show that it outperforms the baseline model (which does not correct for position bias ) on our offline evaluation metrics .
Edit intent: clarity
Original: This paper introduces a hardware complexity reduction method for successive cancellation list (SCL) decoders.
Revised: This brief introduces a hardware complexity reduction method for successive cancellation list (SCL) decoders.
Edit intent: clarity
Original: Many neural systems display avalanche behavior characterized by uninterrupted sequences of neuronal firing whose distributions of size and durations are heavy-tailed.
Revised: Many neural systems display cascading behavior characterized by uninterrupted sequences of neuronal firing whose distributions of size and durations are heavy-tailed.
Edit intent: clarity
Original:  However, the unknown role of network structure precludes an understanding of how variations in network topology manifest in neural dynamics and either support or impinge upon information processing.
Revised:  However, the unknown role of network structure precludes an understanding of how variations in network structure manifest in neural dynamics and either support or impinge upon information processing.
Edit intent: clarity
Original:  Here, using a generalized spiking model, we develop a mechanistic understanding of how network topology supports information processing through network dynamics .
Revised:  Here, we develop a mechanistic understanding of how network topology supports information processing through network dynamics .
Edit intent: clarity
Original:  Here, using a generalized spiking model, we develop a mechanistic understanding of how network topology supports information processing through network dynamics .
Revised:  Here, using a generalized spiking model, we develop a theoretical understanding of how network topology supports information processing through network dynamics .
Edit intent: clarity
Original:  Here, using a generalized spiking model, we develop a mechanistic understanding of how network topology supports information processing through network dynamics .
Revised:  Here, using a generalized spiking model, we develop a mechanistic understanding of how network structure supports information processing through network dynamics .
Edit intent: clarity
Original:  First, we show how network topology determines network dynamics by analytically and numerically demonstrating that network topology can be designed to propagate stimulus patternsfor long durations.
Revised:  First, we show how network structure can be designed to propagate stimulus patternsfor long durations.
Edit intent: clarity
Original:  Broadly, our results imply that avalanching neural networks could contribute to cognitive faculties that require persistent activation of neuronal patterns, such as working memory or attention.
Revised:  Broadly, our results demonstrate how cascading neural networks could contribute to cognitive faculties that require persistent activation of neuronal patterns, such as working memory or attention.
Edit intent: clarity
Original:  Broadly, our results imply that avalanching neural networks could contribute to cognitive faculties that require persistent activation of neuronal patterns, such as working memory or attention.
Revised:  Broadly, our results imply that avalanching neural networks could contribute to cognitive faculties that require lasting activation of neuronal patterns, such as working memory or attention.
Edit intent: clarity
Original: We present and analyze a  wavelet-Fourier technique for the numerical treatment of multi-dimensional advection-diffusion-reaction equations with periodic boundary conditions . Combining the Petrov-Galerkin technique with the compressed sensing approach, the proposed method is able to approximate the largest coefficients of the solution with respect to a biorthogonal wavelet basis.
Revised: We present and analyze a novel wavelet-Fourier technique for the numerical treatment of multi-dimensional advection-diffusion-reaction equations with periodic boundary conditions . Combining the Petrov-Galerkin technique with the compressed sensing approach, the proposed method is able to approximate the largest coefficients of the solution with respect to a biorthogonal wavelet basis.
Edit intent: clarity
Original: We present and analyze a  wavelet-Fourier technique for the numerical treatment of multi-dimensional advection-diffusion-reaction equations with periodic boundary conditions . Combining the Petrov-Galerkin technique with the compressed sensing approach, the proposed method is able to approximate the largest coefficients of the solution with respect to a biorthogonal wavelet basis.
Revised: We present and analyze a wavelet-Fourier technique for the numerical treatment of multidimensional advection-diffusion-reaction equations with periodic boundary conditions . Combining the Petrov-Galerkin technique with the compressed sensing approach, the proposed method is able to approximate the largest coefficients of the solution with respect to a biorthogonal wavelet basis.
Edit intent: fluency
Original: A distinguishing feature of living matter is its ability to control force-generating structures that accomplish tasks such as chromosome segregation, intracellular transport, and cell movement.
Revised: Living systems are capable of locomotion, reconfiguration, and replication. To perform these tasks, cells spatiotemporally coordinate the interactions of force-generating structures that accomplish tasks such as chromosome segregation, intracellular transport, and cell movement.
Edit intent: clarity
Original:  Our engineered system consists of  microtubules and light-activatable motor proteins that crosslink and reorganize microtubules upon illumination.
Revised:  Our engineered system consists of microtubules and light-activatable motor proteins that crosslink and organize microtubules into distinct structures upon illumination.
Edit intent: clarity
Original:  We design light patternsthat enable us to create, move, and merge microtubule asters with spatial and temporal precision .
Revised:  We design light patternsthat enable us to create, move, and merge microtubule structures .
Edit intent: clarity
Original:  By composing these basic operations, we  create microtubule networks that can span several hundred microns in length and contract at speeds up to an order of magnitude faster than the speed of an individual motor.
Revised:  By composing these basic operations, we create microtubule networks that span several hundred microns in length and contract at speeds up to an order of magnitude faster than the speed of an individual motor.
Edit intent: clarity
Original:  By scaling the size and speed of contractile networks , we generate and sculpt advective fluid flows.
Revised:  We manipulate these contractile networks to generate and sculpt advective fluid flows.
Edit intent: clarity
Original: Despite the remarkable similarities between deep neural networks ( DNN ) and the human brain as shown in previous studies, the fact that DNNs still fall behind humans in many visual tasks suggests that considerable differences still exist between the two systems.
Revised: Despite the remarkable similarities between deep neural networks ( DNN ) and the human brain , CNNs still fall behind humans in many visual tasks suggests that considerable differences still exist between the two systems.
Edit intent: clarity
Original:  We find that representational similarity between RE and adversarial images in the human brain resembles their perceptual similarity .
Revised:  We find that representational similarity between regular and adversarial images in the human brain resembles their perceptual similarity .
Edit intent: clarity
Original:  We find that representational similarity between RE and adversarial images in the human brain resembles their perceptual similarity .
Revised:  We find that representational similarity between RE and adversarial images largely echoes their perceptual similarity .
Edit intent: clarity
Original:  Furthermore, forward encoding modeling reveals that the DNN-brain hierarchical correspondence proposed in previous studies only holds when the two systems process RE and AI images but not AN images.
Revised:  Furthermore, we show that voxel-encoding models trained on regular images can successfully generalize to the neural responses to AI images but not AN images.
Edit intent: clarity
Original: In this paper, we construct several energy stable schemes based on the idea of the semi-implicit scheme (SIS), invariant energy quadratization (IEQ) and scalar auxiliary variable (SAV) methods for the incommensurate multi-length-scale  phase-field crystal model , which is able to describe the phase behavior of aperiodic structures.
Revised: This article focuses on the development of high-order energy stable schemes for the multi-length-scale phase-field crystal model , which is able to describe the phase behavior of aperiodic structures.
Edit intent: clarity
Original: In this paper, we construct several energy stable schemes based on the idea of the semi-implicit scheme (SIS), invariant energy quadratization (IEQ) and scalar auxiliary variable (SAV) methods for the incommensurate multi-length-scale  phase-field crystal model , which is able to describe the phase behavior of aperiodic structures.
Revised: In this paper, we construct several energy stable schemes based on the idea of the semi-implicit scheme (SIS), invariant energy quadratization (IEQ) and scalar auxiliary variable (SAV) methods for the incommensurate multi-length-scale phase-field crystal model which is able to describe the phase behavior of aperiodic structures.
Edit intent: fluency
Original: In this paper, we construct several energy stable schemes based on the idea of the semi-implicit scheme (SIS), invariant energy quadratization (IEQ) and scalar auxiliary variable (SAV) methods for the incommensurate multi-length-scale  phase-field crystal model , which is able to describe the phase behavior of aperiodic structures.
Revised: In this paper, we construct several energy stable schemes based on the idea of the semi-implicit scheme (SIS), invariant energy quadratization (IEQ) and scalar auxiliary variable (SAV) methods for the incommensurate multi-length-scale phase-field crystal model , which is able to study the phase behavior of aperiodic structures.
Edit intent: clarity
Original: Motivated by fundamental applications in databases and relational machine learning, we formulate and study the problem of answering Functional Aggregate Queries (FAQ) in which some of the input factors are defined by a collection of Additive Inequalities between variables.
Revised: Motivated by fundamental applications in databases and relational machine learning, we formulate and study the problem of answering functional aggregate queries (FAQ) in which some of the input factors are defined by a collection of Additive Inequalities between variables.
Edit intent: fluency
Original: Motivated by fundamental applications in databases and relational machine learning, we formulate and study the problem of answering Functional Aggregate Queries (FAQ) in which some of the input factors are defined by a collection of Additive Inequalities between variables.
Revised: Motivated by fundamental applications in databases and relational machine learning, we formulate and study the problem of answering Functional Aggregate Queries (FAQ) in which some of the input factors are defined by a collection of additive inequalities between variables.
Edit intent: fluency
Original:  To answer FAQ-AI in the Boolean semiring, we define "relaxed " tree decompositions and "relaxed " submodular and fractional hypertree width parameters.
Revised:  To answer FAQ-AI in the Boolean semiring, we define relaxed tree decompositions and "relaxed " submodular and fractional hypertree width parameters.
Edit intent: fluency
Original:  To answer FAQ-AI in the Boolean semiring, we define "relaxed " tree decompositions and "relaxed " submodular and fractional hypertree width parameters.
Revised:  To answer FAQ-AI in the Boolean semiring, we define "relaxed " tree decompositions and relaxed submodular and fractional hypertree width parameters.
Edit intent: fluency
Original:  Our second contribution is a relaxation of the set of polymatroids that gives rise to the counting version of the submodular width, denoted by " #subw " . This new width is sandwiched between the submodular and the fractional hypertree widths.
Revised:  Our second contribution is a relaxation of the set of polymatroids that gives rise to the counting version of the submodular width, denoted by #subw " . This new width is sandwiched between the submodular and the fractional hypertree widths.
Edit intent: fluency
Original:  Our second contribution is a relaxation of the set of polymatroids that gives rise to the counting version of the submodular width, denoted by " #subw " . This new width is sandwiched between the submodular and the fractional hypertree widths.
Revised:  Our second contribution is a relaxation of the set of polymatroids that gives rise to the counting version of the submodular width, denoted by " #subw . This new width is sandwiched between the submodular and the fractional hypertree widths.
Edit intent: fluency
Original:  In particular, three previously studied strategies emerge as special limits of our model:
Revised:  In particular, three previously studied strategies emerge as special cases of our model:
Edit intent: clarity
Original:   when environmental cues are accurate, organisms rely on the cue to express the favorable phenotype in each environmental condition ("tracking strategy"), when cues are noisy, organisms either express a same phenotype in all environments ("unvarying strategy ") or, remarkably, use the uninformative cue as a source of randomness to diversify into subpopulations of different phenotypes ("bet-hedging strategy").
Revised:  when environmental cues are accurate, whereas when cues are noisy, organisms either express a same phenotype in all environments ("unvarying strategy ") or, remarkably, use the uninformative cue as a source of randomness to diversify into subpopulations of different phenotypes ("bet-hedging strategy").
Edit intent: clarity
Original:   when environmental cues are accurate, organisms rely on the cue to express the favorable phenotype in each environmental condition ("tracking strategy"), when cues are noisy, organisms either express a same phenotype in all environments ("unvarying strategy ") or, remarkably, use the uninformative cue as a source of randomness to diversify into subpopulations of different phenotypes ("bet-hedging strategy").
Revised:  when environmental cues are accurate, organisms rely on the cue to express the favorable phenotype in each environmental condition ("tracking strategy"), when cues are noisy, organisms can either use an unvarying strategy or, remarkably, use the uninformative cue as a source of randomness to diversify into subpopulations of different phenotypes ("bet-hedging strategy").
Edit intent: clarity
Original:  In particular, these include functions of the asymptotic form f(\nu\to0)\sim\nu^a and f(|\nu|\to\infty)\sim\nu^b with arbitrary real a>b.
Revised:  In particular, these include cases of the asymptotic form f(\nu\to0)\sim\nu^a and f(|\nu|\to\infty)\sim\nu^b with arbitrary real a>b.
Edit intent: clarity
Original:  For example, we show that the solution tensor X \in C^{n \times n \times n} of a discretized Poisson equation -\nabla^2 u =1 on [-1,1]^3 with zero Dirichlet conditions can be approximated to a relative accuracy of \epsilon by a tensor-train decomposition of rank ((n (\log n)^2 (\log(} 1 ,s_1,s_2,1), where s_1=s_2=O( \log n \log (1/\epsilon)) and 0 < \epsilon < 1.
Revised:  For example, we show that the solution tensor X \in C^{n \times n \times n} of a discretized Poisson equation -\nabla^2 u =1 on [-1,1]^3 with zero Dirichlet conditions can be approximated to a relative accuracy of \epsilon by a tensor-train decomposition of rank ((n (\log n)^2 (\log(} 1 ,s_1,s_2,1), where s_1=s_2=O( \log (1/\epsilon)) and 0 < \epsilon < 1.
Edit intent: fluency
Original:  That simple Zipf's law pattern also arises among the population sizes of cities, the sizes of corporations, and other patterns of abundance.
Revised:  That simple Zipf's law pattern also arises in the population sizes of cities, the sizes of corporations, and other patterns of abundance.
Edit intent: clarity
Original:  We novelly propose a plug-and-play relation reasoning module injected with the relation embeddings to enhance image encoder . Specifically, we design upgraded Graph Convolutional Networks (GCN) to utilize the information of relation embeddings and relation directionality between objects for generating relation-aware image representations.
Revised:  We novelly propose a plug-and-play relation reasoning module injected with the relation embeddings to enhance image encoder . 
Edit intent: coherence
Original:  Extensive experiments are conducted on VQA 2.0 and CMPlaces datasets and superior performance is reported when comparing with state-of-the-art work .
Revised:  Extensive experiments are conducted on VQA 2.0 dataset, remarkably achieving state-of-the-art work .
Edit intent: clarity
Original:  In comparison with existing acceleration regularization methods, FAR is an accelerated method without saturation.
Edit intent: coherence
Original:  We consider a threshold contagion on a network whose nodes are embedded in a manifold and which has both `geometric edges', which respect the geometry of the underlying manifold, and `non-geometric edges' that are not constrained by that geometry.
Revised:  We consider a threshold contagion on a network whose nodes are embedded in a manifold and where the network has both `geometric edges', which respect the geometry of the underlying manifold, and `non-geometric edges' that are not constrained by that geometry.
Edit intent: clarity
Original:  We consider different probability distributions for constructing non-geometric edges --- reflecting different decay rates with respect to the distance between nodes in the underlying manifold --- and examine how qualitative spreading dynamics are affected by these choices .
Revised:  We consider different probability distributions for constructing non-geometric edges --- reflecting different decay rates with respect to the distance between nodes in the underlying manifold --- and examine the effect of such choices on the qualitative properties of the spreading dynamics .
Edit intent: clarity