wanyu/IteraTeR_v2 huggingface dataset:
Original:  to SNNs, which ignore the difference between ANNs and SNNs, thus limiting the performance of the pruned SNNs. Besides, these methods are only suitable for shallow SNNs. In this paper, inspired by synaptogenesis and synapse elimination in the neural system, we propose gradient rewiring (Grad R), a joint learning algorithm of connectivity and weight for SNNs, that enables us to seamlessly optimize network structure without retrain .
Revised:  to SNNs, which ignore the difference between ANNs and SNNs, thus limiting the performance of the pruned SNNs. Besides, these methods are only suitable for shallow SNNs. In this paper, inspired by synaptogenesis and synapse elimination in the neural system, we propose gradient rewiring (Grad R), a joint learning algorithm of connectivity and weight for SNNs, that enables us to seamlessly optimize network structure without retraining .
Edit intent: fluency
Original: 5\% accuracy loss under unprecedented 0.73\% connectivity, which reveals remarkable structure refining capability in SNNs. Our work suggests that there exists extremely high redundancy in deep SNNs. Our codes are available at URL .
Revised: 5\% accuracy loss under unprecedented 0.73\% connectivity, which reveals remarkable structure refining capability in SNNs. Our work suggests that there exists extremely high redundancy in deep SNNs. Our codes are available at URL 
Edit intent: fluency
Original: We develop an efficient algorithm for the  regularization of nonlinear inverse problems based on the discrepancy principle.
Revised: We develop an efficient algorithm for the automatic regularization of nonlinear inverse problems based on the discrepancy principle.
Edit intent: clarity
Original:  We illustrate the robustness and effectiveness of our approach using a number of numerical experiments .
Revised:  We illustrate the behavior of the algorithm using a number of numerical experiments .
Edit intent: clarity
Original:  We consider Talbot-Lau x-ray phase contrast imaging as application .
Revised:  We consider Talbot-Lau X-ray phase contrast imaging as application .
Edit intent: fluency
Original:  We show that the presence of scale-free neuronal avalanches and the associated crackling-noise relation can be explained by the presence of an extrinsic, stochastic-induced mutual information in the system , whereas the intrinsic spatial correlation structure shows the typical features of systems close to their critical point.
Revised:  We show that power-law neuronal avalanches satisfying the crackling-noise relation can be explained by the presence of an extrinsic, stochastic-induced mutual information in the system , whereas the intrinsic spatial correlation structure shows the typical features of systems close to their critical point.
Edit intent: clarity
Original:  An essential requirement for these algorithms is the availability of accurate partial derivatives of the equations of motion with respect to the state and control variables . State of the art methods for calculating the derivatives use analytical differentiation methods based on the chain rule , and although these methods are an improvement over finite-difference in terms of accuracy, they are not always the most efficient.
Revised:  An essential requirement for these algorithms is the ability to quickly and accurately compute partial derivatives of the equations of motion with respect to the state and control variables . State of the art methods for calculating the derivatives use analytical differentiation methods based on the chain rule , and although these methods are an improvement over finite-difference in terms of accuracy, they are not always the most efficient.
Edit intent: clarity
Original:  An essential requirement for these algorithms is the availability of accurate partial derivatives of the equations of motion with respect to the state and control variables . State of the art methods for calculating the derivatives use analytical differentiation methods based on the chain rule , and although these methods are an improvement over finite-difference in terms of accuracy, they are not always the most efficient.
Revised:  An essential requirement for these algorithms is the availability of accurate partial derivatives of the equations of motion . State of the art methods for calculating the derivatives use analytical differentiation methods based on the chain rule , and although these methods are an improvement over finite-difference in terms of accuracy, they are not always the most efficient.
Edit intent: clarity
Original:  An essential requirement for these algorithms is the availability of accurate partial derivatives of the equations of motion with respect to the state and control variables . State of the art methods for calculating the derivatives use analytical differentiation methods based on the chain rule , and although these methods are an improvement over finite-difference in terms of accuracy, they are not always the most efficient.
Revised:  An essential requirement for these algorithms is the availability of accurate partial derivatives of the equations of motion with respect to the state and control variables . State of the art approaches to this problem often use analytical methods based on the chain rule , and although these methods are an improvement over finite-difference in terms of accuracy, they are not always the most efficient.
Edit intent: clarity
Original:  An essential requirement for these algorithms is the availability of accurate partial derivatives of the equations of motion with respect to the state and control variables . State of the art methods for calculating the derivatives use analytical differentiation methods based on the chain rule , and although these methods are an improvement over finite-difference in terms of accuracy, they are not always the most efficient.
Revised:  An essential requirement for these algorithms is the availability of accurate partial derivatives of the equations of motion with respect to the state and control variables . State of the art methods for calculating the derivatives use analytical differentiation methods based on the chain rule , and although these methods are an improvement over finite differences in terms of accuracy, they are not always the most efficient.
Edit intent: fluency
Original:  We present a new tool DarkSea, the first tool capable of verifying reachability, termination, and LTL of such lifted binaries.
Revised:  We present a new tool DarkSea, the first tool capable of verifying reachability, termination, and LTL of lifted binaries.
Edit intent: clarity
Original:  ~ 2010 and Regnier et al.
Revised:  2010 and Regnier et al.
Edit intent: coherence
Original:  ~ 1998 showed the generating functions of the distributions of the number of the occurrences of words (distributions of words for short) in finite string in the form of rational functions.
Revised:  1998 showed the generating functions of the distributions of the number of the occurrences of words (distributions of words for short) in finite string in the form of rational functions.
Edit intent: coherence
Original:  Both the proposed algorithm use the crowding distance used in the multiobjective optimization as a metric in order to sort the features.
Revised:  Both the proposed algorithms use the crowding distance used in the multiobjective optimization as a metric in order to sort the features.
Edit intent: fluency
Original:  The former is an individual guarantee, requiring that each agent prefers her own allocation over the allocation of any other;
Revised:  The former is an individual guarantee, requiring that each agent prefers their own allocation over the allocation of any other;
Edit intent: fluency
Original:  We show that in the online setting, the two desired properties (envy-freeness and efficiency) are in direct contention, in that any algorithm achieving additive  envy-freeness up to a factor of L_T necessarily suffers an efficiency loss of at least 1 / L_T. We complement this uncertainty principle with a simple algorithm, HopeGuardrail, which allocates resources based on an adaptive threshold policy .
Revised:  We show that in the online setting, the two desired properties (envy-freeness and efficiency) are in direct contention, in that any algorithm achieving additive envy-freeness up to a factor of L_T necessarily suffers a efficiency loss of at least 1 / L_T. We complement this uncertainty principle with a simple algorithm, HopeGuardrail, which allocates resources based on an adaptive threshold policy .
Edit intent: fluency
Original:  We show that our algorithm is able to achieve any fairness-efficiency point on this frontier , and moreover, in simulation results,  provides allocations close to the optimal fair solution in hindsight .
Revised:  We show that our algorithm is able to achieve any fairness-efficiency point on this frontier . In simulation results, provides allocations close to the optimal fair solution in hindsight .
Edit intent: coherence
Original:  We show that our algorithm is able to achieve any fairness-efficiency point on this frontier , and moreover, in simulation results,  provides allocations close to the optimal fair solution in hindsight .
Revised:  We show that our algorithm is able to achieve any fairness-efficiency point on this frontier , and moreover, in simulation results, our algorithm provides allocations close to the optimal fair solution in hindsight .
Edit intent: coherence
Original:  This motivates its use in practical applications , as the algorithm is able to adapt to any desired fairness efficiency trade-off.
Revised:  This motivates its use in practical applications as the algorithm is able to adapt to any desired fairness efficiency trade-off.
Edit intent: fluency
Original: Graph clustering aiming to obtain a partition of data using the graph information , has received considerable attention in recent years .
Revised: Recently, there has been considerable research interest in graph clustering aimed at data partition using the graph information , has received considerable attention in recent years .
Edit intent: clarity
Original: Graph clustering aiming to obtain a partition of data using the graph information , has received considerable attention in recent years .
Revised: Graph clustering aiming to obtain a partition of data using the graph information .
Edit intent: clarity
Original:  However, noisy edges and nodes in the graph may make the clusteringresults worse.
Revised:  However, one limitation of the most of graph-based methods is that they assume the graph structure to operate is fixed and reliable. And there are inevitably some edges in the graph may make the clusteringresults worse.
Edit intent: clarity
Original:  DGEN is designed as a two-step graph encoder connected by a graph pooling layer , which learns the graph embedding of the selected nodes.
Revised:  DGEN is designed as a two-step graph encoder connected by a graph pooling layer to learn the graph embedding of the selected nodes.
Edit intent: coherence
Original:  This can effectively alleviate the impact of the noise edge to the clustering.
Revised:  This can effectively alleviate the impact of the spurious edges on the clustering.
Edit intent: clarity
Original:  The chance-constraint method can be applied to model the optimi-zation problems of power flow with uncertainty.
Revised:  The chance-constrained method can be applied to model the optimi-zation problems of power flow with uncertainty.
Edit intent: fluency
Original:  The chance-constraint method can be applied to model the optimi-zation problems of power flow with uncertainty.
Revised:  The chance-constraint method can be applied to model the optimization problems of power flow with uncertainty.
Edit intent: fluency
Original:  The chance-constraint method can be applied to model the optimi-zation problems of power flow with uncertainty.
Revised:  The chance-constraint method can be applied to model the optimi-zation problems of power flow under uncertainty.
Edit intent: clarity
Original:  This paper develops a novel solution approach for chance-constrained AC optimal power flow (CCACOPF) problem based on the da-ta-driven convexification of power flow and the fast algorithm for scenario technique (FAST).
Revised:  This paper develops a novel solution approach for chance-constrained AC optimal power flow (CCACOPF) problem based on the data-driven convexification of power flow and the fast algorithm for scenario technique (FAST).
Edit intent: clarity
Original:  This paper develops a novel solution approach for chance-constrained AC optimal power flow (CCACOPF) problem based on the da-ta-driven convexification of power flow and the fast algorithm for scenario technique (FAST).
Revised:  This paper develops a novel solution approach for chance-constrained AC optimal power flow (CCACOPF) problem based on the da-ta-driven convexification of power flow and a fast algorithm for scenario technique (FAST).
Edit intent: fluency
Original:  First, the original nonconvex AC power flow  constraints are approximated by a set of learn-ing-based quadratic convex ones.
Revised:  First, the original nonconvex AC power flow constraints are approximated by a set of learning-based quadratic convex ones.
Edit intent: fluency
Original:  Second, FAST is a more ad-vanced distribution-free scenario-based solution method  using far less scenarios than the conventional one, retaining a high confidence level .
Revised:  Second, FAST is an advanced scenario-based solution method using far less scenarios than the conventional one, retaining a high confidence level .
Edit intent: clarity
Original:  The simulation results on IEEE test cases indicate that 1) the pro-posed solution method can excel the conventional one and ro-bust program in computational efficiency, 2) the data-driven convexification of power flow is effective in approximating original complex AC power flow.
Revised:  The simulation results on IEEE test cases indicate that 1) the proposed solution method can excel the conventional one and ro-bust program in computational efficiency, 2) the data-driven convexification of power flow is effective in approximating original complex AC power flow.
Edit intent: fluency
Original:  The simulation results on IEEE test cases indicate that 1) the pro-posed solution method can excel the conventional one and ro-bust program in computational efficiency, 2) the data-driven convexification of power flow is effective in approximating original complex AC power flow.
Revised:  The simulation results on IEEE test cases indicate that 1) the pro-posed solution method can outperform the conventional SSM in computational efficiency, 2) the data-driven convexification of power flow is effective in approximating original complex AC power flow.
Edit intent: clarity
Original:  Many Hamilton-Jacobi equations have a nonlinear dependency on the gradient of the solution , which gives rise to discontinuities in the gradient of the solution, resulting in kinks in the solution itself .
Revised:  Many Hamilton-Jacobi equations have a nonlinear dependency on the gradient , which gives rise to discontinuities in the gradient of the solution, resulting in kinks in the solution itself .
Edit intent: fluency
Original:  Many Hamilton-Jacobi equations have a nonlinear dependency on the gradient of the solution , which gives rise to discontinuities in the gradient of the solution, resulting in kinks in the solution itself .
Revised:  Many Hamilton-Jacobi equations have a nonlinear dependency on the gradient of the solution , which gives rise to discontinuities in the gradient of the solution, resulting in kinks .
Edit intent: clarity
Original:  The degrees-of-freedom of Hermite methods are tensor-product Taylor polynomials of degree m in each coordinate direction.
Revised:  The degrees-of freedom of Hermite methods are tensor-product Taylor polynomials of degree m in each coordinate direction.
Edit intent: fluency
Original: Recently, several experiments on commercial adaptive cruise control (ACC) vehicles have been conducted worldwide , providing an unprecedented opportunity to study the ACC behaviors .
Revised: Experimental measurements on commercial adaptive cruise control (ACC) vehicles have been conducted worldwide , providing an unprecedented opportunity to study the ACC behaviors .
Edit intent: clarity
Original: Recently, several experiments on commercial adaptive cruise control (ACC) vehicles have been conducted worldwide , providing an unprecedented opportunity to study the ACC behaviors .
Revised: Recently, several experiments on commercial adaptive cruise control (ACC) vehicles have been conducted worldwide , providing an unprecedented opportunity to study the traffic flow characteristics that arise from this technology .
Edit intent: clarity
Original:  This paper has conducted a comprehensive empirical study on the ACC equilibrium behaviors using all available data to date and obtained the ACC fundamental diagrams.
Revised:  This paper has conducted a comprehensive empirical study on the ACC equilibrium behaviors via the resulting fundamental diagrams.
Edit intent: clarity
Original:  We find that  ACC systems display a linear speed-spacing relationship , like human-driven vehicles, but the features of the speed-spacing relationships and the corresponding fundamental diagrams differ from human-driven traffic . ACC generally has very small spacing at minimum headway , resulting in much larger flow (and capacity) than human traffic, but the opposite occurs if maximum headway is used.
Revised:  We find that like human-driven vehicles, ACC systems display a linear speed-spacing relationship , like human-driven vehicles, but the features of the speed-spacing relationships and the corresponding fundamental diagrams differ from human-driven traffic . ACC generally has very small spacing at minimum headway , resulting in much larger flow (and capacity) than human traffic, but the opposite occurs if maximum headway is used.
Edit intent: coherence
Original:  We find that  ACC systems display a linear speed-spacing relationship , like human-driven vehicles, but the features of the speed-spacing relationships and the corresponding fundamental diagrams differ from human-driven traffic . ACC generally has very small spacing at minimum headway , resulting in much larger flow (and capacity) than human traffic, but the opposite occurs if maximum headway is used.
Revised:  We find that ACC systems display a linear speed-spacing relationship (within the range of available data) but the key parameters of these relationships can differ significantly from human-driven traffic . ACC generally has very small spacing at minimum headway , resulting in much larger flow (and capacity) than human traffic, but the opposite occurs if maximum headway is used.
Edit intent: clarity
Original:  Lastly, ACC jam spacing is much larger than  human traffic, translating to much smaller jam density, which will reduce road storage capacity .
Revised:  We also find that ACC jam spacing is much larger than human traffic, translating to much smaller jam density, which will reduce road storage capacity .
Edit intent: coherence
Original:  Lastly, ACC jam spacing is much larger than  human traffic, translating to much smaller jam density, which will reduce road storage capacity .
Revised:  Lastly, ACC jam spacing is much larger than in human traffic, translating to much smaller jam density, which will reduce road storage capacity .
Edit intent: fluency
Original: Experimental measurements on commercial adaptive cruise control (ACC) vehicles is becoming increasingly available from around the world, providing an unprecedented opportunity to study the traffic flow characteristics that arise from this technology.
Revised: Experimental measurements on commercial adaptive cruise control (ACC) vehicles becoming increasingly available from around the world, providing an unprecedented opportunity to study the traffic flow characteristics that arise from this technology.
Edit intent: coherence
Original:  We find that like human-driven vehicles, ACC systems display a linear speed-spacing relationship (within the range of available data) but the key parameters of these relationships can differ significantly from human-driven traffic depending on input settings: At the minimum headway setting,  capacities in excess of 3500 vehicles per hour are observed, together with an extremely fast congested wave speed of 50 miles per hour on average.
Revised:  We find that like human-driven vehicles, ACC systems display a linear equilibrium spacing-speed relationship (within the range of available data) but the key parameters of these relationships can differ significantly from human-driven traffic depending on input settings: At the minimum headway setting, capacities in excess of 3500 vehicles per hour are observed, together with an extremely fast congested wave speed of 50 miles per hour on average.
Edit intent: clarity
Original:  We find that like human-driven vehicles, ACC systems display a linear speed-spacing relationship (within the range of available data) but the key parameters of these relationships can differ significantly from human-driven traffic depending on input settings: At the minimum headway setting,  capacities in excess of 3500 vehicles per hour are observed, together with an extremely fast congested wave speed of 50 miles per hour on average.
Revised:  We find that like human-driven vehicles, ACC systems display a linear speed-spacing relationship (within the range of available data) but the key parameters of these relationships can differ significantly from human-driven traffic depending on input settings: At the minimum headway setting, capacities in excess of 3500 vehicles per hour are observed, together with an extremely fast equilibrium wave speed of 50 miles per hour on average.
Edit intent: clarity
Original:  These fast waves are unfamiliar to human drivers, and may or may not pose a safety risk.
Revised:  These fast waves are unfamiliar to human drivers, and may pose a safety risk.
Edit intent: clarity
Original:  We also find that ACC jam spacing is much larger than in human traffic, which reduces the network storage capacity .
Revised:  The results also suggest that ACC jam spacing is much larger than in human traffic, which reduces the network storage capacity .
Edit intent: clarity
Original:  We also find that ACC jam spacing is much larger than in human traffic, which reduces the network storage capacity .
Revised:  We also find that ACC jam spacing can be much larger than in human traffic, which reduces the network storage capacity .
Edit intent: clarity
Original:  Different from other approaches, our focus is on the unique characteristics of AI technology and the differences between non-AI computing systems and AI systems.
Revised:  Our review and analysis highlight the new changes introduced by AI technology and the differences between non-AI computing systems and AI systems.
Edit intent: clarity
Original:  Our review and analysis highlight unique issues in developing AI systems which HCI professionals have not encountered in non-AI computing systems.
Revised:  Our review and analysis highlight unique issues in developing AI systems which HCI professionals did not encounter when developing non-AI computing systems.
Edit intent: clarity
Original:  Hyperproperties can express several specifications of interest for cyber-physical systems, such as opacity, robustness, and noninterference, which cannot be expressed using linear time properties.
Revised:  Hyperproperties can express several specifications of interest for cyber-physical systems--such as opacity, robustness, and noninterference, which cannot be expressed using linear time properties.
Edit intent: fluency
Original:  Hyperproperties can express several specifications of interest for cyber-physical systems, such as opacity, robustness, and noninterference, which cannot be expressed using linear time properties.
Revised:  Hyperproperties can express several specifications of interest for cyber-physical systems, such as opacity, robustness, and noninterference--which cannot be expressed using linear time properties.
Edit intent: fluency