wanyu/IteraTeR_v2 huggingface dataset:
Original:  We define a second-shortest path P_2 to be the shortest path edge-disjoint from P_1, and consider more generally the shortest path P_k edge-disjoint from all earlier paths.
Revised:  Define a second-shortest path P_2 to be the shortest path edge-disjoint from P_1, and consider more generally the shortest path P_k edge-disjoint from all earlier paths.
Edit intent: coherence
Original:  We show that the cost X_k of P_k is asymptotically ( 2k +\ln n) /n . Specifically, X_k / (2k/n +\ln n/n )%DIFDELCMD < \mathrm{p}{\to} %%% 1 uniformly for all k \leq n-1.
Revised:  We show that the cost X_k of P_k is asymptotically ( 2k /n . Specifically, X_k / (2k/n +\ln n/n )%DIFDELCMD < \mathrm{p}{\to} %%% 1 uniformly for all k \leq n-1.
Edit intent: fluency
Original:  We show that the cost X_k of P_k is asymptotically ( 2k +\ln n) /n . Specifically, X_k / (2k/n +\ln n/n )%DIFDELCMD < \mathrm{p}{\to} %%% 1 uniformly for all k \leq n-1.
Revised:  We show that the cost X_k of P_k is asymptotically ( 2k +\ln n) /n +\ln n/n )%DIFDELCMD < \mathrm{p}{\to} %%% 1 uniformly for all k \leq n-1.
Edit intent: clarity
Original:  We show that the cost X_k of P_k is asymptotically ( 2k +\ln n) /n . Specifically, X_k / (2k/n +\ln n/n )%DIFDELCMD < \mathrm{p}{\to} %%% 1 uniformly for all k \leq n-1.
Revised:  We show that the cost X_k of P_k is asymptotically ( 2k +\ln n) /n . Specifically, X_k / (2k/n +\ln n/n %DIFDELCMD < \mathrm{p}{\to} %%% 1 uniformly for all k \leq n-1.
Edit intent: fluency
Original:  We also show an analogous result when the edge weights are drawn from an exponential distribution  .
Revised:  We show analogous results when the edge weights are drawn from an exponential distribution .
Edit intent: clarity
Original:  Due to the distributed nature of a large-scale system, the various hardware, software, and tooling logs are often maintained separately, making it difficult to review the logs jointly for detecting issues.
Revised:  Due to the distributed nature of a large-scale system, the various hardware, software, and tooling logs are often maintained separately, making it difficult to review the logs jointly for understanding production issues.
Edit intent: clarity
Original:  Another challenge in reviewing the logs for identifying issues is the scale - there could easily be millions of entities, each with hundreds of features.
Revised:  Another challenge in reviewing the logs for identifying issues is the scale - there could easily be millions of entities, each described by hundreds of features.
Edit intent: clarity
Original:  We first explore item-sets, i.e. a group of feature values, that could identify groups of samples with sufficient support for the target failures using the Apriori algorithm and a subsequent improvement, FP-Growth.
Revised:  We first explore item-sets, i.e. combinations of feature values, that could identify groups of samples with sufficient support for the target failures using the Apriori algorithm and a subsequent improvement, FP-Growth.
Edit intent: clarity
Original:  With the use of a large-scale real-time database , we propose pre- and post-processing techniques and parallelism to further speed up the analysis  .
Revised:  We propose pre-processing steps with the use of a large-scale real-time database , we propose pre- and post-processing techniques and parallelism to further speed up the analysis .
Edit intent: clarity
Original:  With the use of a large-scale real-time database , we propose pre- and post-processing techniques and parallelism to further speed up the analysis  .
Revised:  With the use of a large-scale real-time database and post-processing techniques and parallelism to further speed up the analysis .
Edit intent: coherence
Original:  We also present the setup and results from multiple production use-cases in this paper.
Revised:  We also present the setup and results from multiple production use cases in this paper.
Edit intent: fluency
Original:  To address these questions computationally, we formalize  Coordination Strategy Inference Problem  .
Revised:  To address these questions computationally, we formalize " Coordination Strategy Inference Problem .
Edit intent: fluency
Original:  To address these questions computationally, we formalize  Coordination Strategy Inference Problem  .
Revised:  To address these questions computationally, we formalize Coordination Strategy Inference Problem " .
Edit intent: fluency
Original:  Given a set of time series that includes coordinated movement and a set of candidate strategies as inputs, we provide the first methodology (to the best of our knowledge) to infer the set of strategies that each individual uses  to achieve movement coordination at the group level.
Revised:  Given a set of time series that includes coordinated movement and a set of candidate strategies as inputs, we provide the first methodology (to the best of our knowledge) to infer whether each individual uses to achieve movement coordination at the group level.
Edit intent: clarity
Original: We describe a Markov chain on redistricting plans that makes relatively global moves .
Revised: We develop a new Markov chain on redistricting plans that makes relatively global moves .
Edit intent: clarity
Original: This note illustrates the limitations of the hyperplane separation bound, a non-combinatorial lower bound on the extension complexity of a polytope.
Revised: We illustrate the limitations of the hyperplane separation bound, a non-combinatorial lower bound on the extension complexity of a polytope.
Edit intent: clarity
Original:  For the canonical slack matrices of the spanning tree polytope and the completion time polytope, we show that the lower bounds produced by the hyperplane separation method are trivial  .
Revised:  For the canonical slack matrices of the spanning tree polytope and the completion time polytope, we show that the lower bounds produced by the hyperplane separation method are trivial .
Edit intent: fluency
Original:  Unfortunately, just like all other biometric systems, ASV is vulnerable to spoofing, also referred to as '' presentation attacks.
Revised:  Unfortunately, just like all other biometric systems, ASV is vulnerable to spoofing, also referred to as " presentation attacks.
Edit intent: fluency
Original:  '' These vulnerabilities are generally unacceptable and call for spoofing countermeasures or "presentation attack detection" systems.
Revised:  " These vulnerabilities are generally unacceptable and call for spoofing countermeasures or "presentation attack detection" systems.
Edit intent: fluency
Original:  Algorithms for this problem fall into three different classes, non-adaptive which always query a fixed set of alternatives, partially-adaptive that query alternatives in a fixed order until they decide to stop and fully-adaptive that choose the next query based on the costs they've seen.
Revised:  Algorithms for this problem fall into three different classes, non-adaptive which always query a fixed set of alternatives, partially-adaptive that query alternatives in a fixed predetermined order but decide when to stop based on the costs they've seen.
Edit intent: clarity
Original:  Our bounds hold for any fixed number of experts and any time-horizon T ;
Revised:  Our bounds hold for any fixed number of experts and any time-horizon ;
Edit intent: clarity
Original:  Our techniques extend in a nonasymptotic setting the recent work of Drenska and Kohn (J. Nonlinear Sci. 2020), which showed that the asymptotically optimal value function is the unique solution of an associated nonlinear PDE.
Edit intent: coherence
Original:  Our bounds hold for any fixed number of experts and any time-horizon ;
Revised:  Our bounds hold for any given number of experts and any time-horizon ;
Edit intent: clarity
Original:  Our bounds hold for any fixed number of experts and any time-horizon ;
Revised:  Our bounds hold for any fixed number of experts and horizon ;
Edit intent: clarity
Original:  For up to three experts, our bounds provide the asymptotically optimal leading order term .
Revised:  For up to three experts, our bounds provide the optimal leading order term .
Edit intent: clarity
Original:  * An O(m \log^2 n{\log\log n} } + n\log ^5 n)-time sequential algorithm: This improves Karger's long-standing O(m \log^3 n) bound{\log\log n} + n\log^6 n) bounds } when the input graph is not extremely sparse  .
Revised:  * An O(m \log^2 n{\log\log n} } + n\log ^5 n)-time sequential algorithm: This improves Karger's O(m \log^3 n) bound{\log\log n} + n\log^6 n) bounds } when the input graph is not extremely sparse .
Edit intent: clarity
Original:  Improvements over Karger's bounds were previously known only under a rather strong assumption that the input graph is %DIFDELCMD < {\em %%% simple (unweighted without parallel edges) [Henzinger , Rao, Wang, SODA'17;
Revised:  Improvements over Karger's bounds were previously known only under a rather strong assumption that the input graph is %DIFDELCMD < {\em %%% simple (unweighted without parallel edges) [Henzinger et al. SODA'17;
Edit intent: clarity
Original:  Ghaffari , Nowicki, Thorup, SODA'20].
Revised:  Ghaffari et al. SODA'20].
Edit intent: clarity
Original:  } * An algorithm that requires \tilde O(n) %DIFDELCMD < {\em %%% cut queries to compute the min-cut of a weighted graph: This answers an open problem by Rubinstein , Schramm, and Weinberg ITCS'18 , who obtained a similar bound for simple graphs.
Revised:  } * An algorithm requiring \tilde O(n) %DIFDELCMD < {\em %%% cut queries to compute the min-cut of a weighted graph: This answers an open problem by Rubinstein , Schramm, and Weinberg ITCS'18 , who obtained a similar bound for simple graphs.
Edit intent: fluency
Original:  } * An algorithm that requires \tilde O(n) %DIFDELCMD < {\em %%% cut queries to compute the min-cut of a weighted graph: This answers an open problem by Rubinstein , Schramm, and Weinberg ITCS'18 , who obtained a similar bound for simple graphs.
Revised:  } * An algorithm that requires \tilde O(n) %DIFDELCMD < {\em %%% cut queries to compute the min-cut of a weighted graph: This answers an open problem by Rubinstein , Schramm, and Weinberg ITCS'18 , who obtained a similar bound for simple graphs.
Edit intent: fluency
Original:  Our bound is tight up to polylogarithmic factors.
Edit intent: coherence
Original:  * A %DIFDELCMD < {\em %%% streaming algorithm that requires \tilde O(n) space and O(\log n) passes to compute the min-cut: The only previous non-trivial exact min-cut algorithm in this setting is the 2-pass \tilde O(n)-space algorithm on simple graphs [Rubinstein ~et ~ al., ITCS'18] (observed by Assadi , Chen, and Khanna STOC'19 ).
Revised:  * A %DIFDELCMD < {\em %%% streaming algorithm that requires \tilde O(n) space and O(\log n) passes to compute the min-cut: The only previous non-trivial exact min-cut algorithm in this setting is the 2-pass \tilde O(n)-space algorithm on simple graphs [Rubinstein ~et ~ al., ITCS'18] (observed by Assadi , Chen, and Khanna STOC'19 ).
Edit intent: fluency
Original:  * A %DIFDELCMD < {\em %%% streaming algorithm that requires \tilde O(n) space and O(\log n) passes to compute the min-cut: The only previous non-trivial exact min-cut algorithm in this setting is the 2-pass \tilde O(n)-space algorithm on simple graphs [Rubinstein ~et ~ al., ITCS'18] (observed by Assadi , Chen, and Khanna STOC'19 ).
Revised:  * A %DIFDELCMD < {\em %%% streaming algorithm that requires \tilde O(n) space and O(\log n) passes to compute the min-cut: The only previous non-trivial exact min-cut algorithm in this setting is the 2-pass \tilde O(n)-space algorithm on simple graphs [Rubinstein et al., ITCS'18] (observed by Assadi , Chen, and Khanna STOC'19 ).
Edit intent: fluency
Original:  In this work, we employ two real-world binary datasets describing the spontaneous neuronal activity of two laboratory mice over time, and we aim to their efficient low-dimensional representation.
Revised:  In this work, we employ two real-world binary datasets describing the spontaneous neuronal activity of laboratory mice over time, and we aim to their efficient low-dimensional representation.
Edit intent: clarity
Original:  We develop an innovative, robust to noise, dictionary learning algorithm for the identification of patterns with synchronous activity and we also extend it to identify patterns within larger time windows.
Edit intent: coherence
Original: Speaker recognition (SR) is widely used in our daily life as a biometric authentication  mechanism.
Revised: Speaker recognition (SR) is widely used in our daily life as a biometric authentication or identification mechanism.
Edit intent: clarity
Original:  In this paper, we conduct the first comprehensive and systematic study of the adversarial attacks on SR systems (SRSs) to understand their security weakness in the practical black-box setting.
Revised:  In this paper, we conduct the first comprehensive and systematic study of the adversarial attacks on SR systems (SRSs) to understand their security weakness in the practical blackbox setting.
Edit intent: fluency
Original:  For this purpose, we propose an adversarial attack, named FakeBob , to craft adversarial samples.
Revised:  For this purpose, we propose an adversarial attack, named FAKEBOB , to craft adversarial samples.
Edit intent: fluency
Original:  We further demonstrate that FakeBob is also effective (at least 65\% untargeted success rate) on both open-source and commercial systems when playing over the air in the physical world.
Revised:  We further demonstrate that FAKEBOB is also effective (at least 65\% untargeted success rate) on both open-source and commercial systems when playing over the air in the physical world.
Edit intent: fluency
Original:  We further demonstrate that FakeBob is also effective (at least 65\% untargeted success rate) on both open-source and commercial systems when playing over the air in the physical world.
Revised:  We further demonstrate that FakeBob is also effective on both open-source and commercial systems when playing over the air in the physical world.
Edit intent: coherence
Original:  Last but not least, we show that three promising defense methods for adversarial attack from the speech recognition domain become ineffective on SRSs against FakeBob , which calls for more effective defense methods.
Revised:  Last but not least, we show that three promising defense methods for adversarial attack from the speech recognition domain become ineffective on SRSs against FAKEBOB , which calls for more effective defense methods.
Edit intent: fluency
Original: Recurrent neural networks (RNNs) have been applied to a broad range of application areas such as natural language processing, drug discovery, and video recognition.
Revised: Recurrent neural networks (RNNs) have been applied to a broad range of applications such as natural language processing, drug discovery, and video recognition.
Edit intent: clarity
Original:  This paper develops a coverage-guided test framework, including three test metrics and a mutation-based test case generation method, for the validation of a major class of RNNs , i.e., long short-term memory networks (LSTMs).
Revised:  This paper develops a coverage-guided testing approach for a major class of RNNs , i.e., long short-term memory networks (LSTMs).
Edit intent: clarity
Original:  This paper develops a coverage-guided test framework, including three test metrics and a mutation-based test case generation method, for the validation of a major class of RNNs , i.e., long short-term memory networks (LSTMs).
Revised:  This paper develops a coverage-guided test framework, including three test metrics and a mutation-based test case generation method, for the validation of a major class of RNNs -- long short-term memory networks (LSTMs).
Edit intent: coherence
Original:  The test metrics are designed with respect to the internal structures of the LSTM layers to quantify the information of the forget gate, the one-step information change of an aggregate hidden state, and the multi-step information evolution of positive and negative aggregate hidden state, respectively.
Revised:  We start from defining a family of three test metrics that are designed to quantify not only the values but also the temporal relations (including both step-wise and negative aggregate hidden state, respectively.
Edit intent: clarity
Original: Recurrent neural networks (RNNs) have been applied to a broad range of applications such as natural language processing, drug discovery, and video recognition.
Revised: Recurrent neural networks (RNNs) have been applied to a broad range of applications , including natural language processing, drug discovery, and video recognition.
Edit intent: clarity
Original:  We start from defining a family of three test metrics that are designed to quantify not only the values but also the temporal relations (including both step-wise and bounded-length) learned through LSTM 's internal structures.
Revised:  We start from defining a family of three test metrics are designed to quantify not only the values but also the temporal relations (including both step-wise and bounded-length) learned through LSTM 's internal structures.
Edit intent: fluency
Original:  Also, we show that testRNN effectively captures erroneous behaviours in RNNs. Furthermore, meaningful information can be collected from testRNN for users to understand what the testing results represent.
Revised:  Also, we show that testRNN effectively captures erroneous behaviours in RNNs. Furthermore, meaningful information can be collected from testRNN for users to understand the testing results represent.
Edit intent: coherence
Original:  As a test case , we consider the problem of community detection in a distribution of random regular graphs we'll call the Degree Regular Block Model, wherein the vertices are partitioned into k communities, and a graph is sampled conditional on a prescribed number of inter- and intra-community edges.
Revised:  As a test case , we consider the problem of community detection in block models. The vertices are partitioned into k communities, and a graph is sampled conditional on a prescribed number of inter- and intra-community edges.
Edit intent: clarity
Original:  The problem of detection , where we are to decide with high probability whether a graph was drawn from this model or the uniform distribution on regular graphs, is conjectured to undergo a computational phase transition at a point called the Kesten-Stigum (KS)
Revised:  The problem of detection , where we are to decide with high probability whether a graph was drawn from this model or the uniform distribution on regular graphs, is conjectured to undergo a computational phase transition at a point called the Kesten-Stigum (KS)
Edit intent: fluency
Original:  threshold , and we show (i) that sufficiently high constant levels of our hierarchy can perform detection arbitrarily close to this point, (ii) that our algorithm is robust to o(n) adversarial edge perturbations , and (iii)that below Kesten-Stigum no level constant level can do so.
Revised:  threshold , and we show (i) that sufficiently high constant levels of our hierarchy can perform detection arbitrarily close to this point, (ii) that our algorithm is robust to o(n) adversarial edge perturbations , and (iii)that below Kesten-Stigum threshold no constant level can do so.
Edit intent: clarity
Original:  In the more-studied case of the (irregular) Stochastic Block Model, it is known that efficient algorithms exist all the way down to this threshold, although none are robust to  adversarial perturbations of the graph when the average degree is small.
Revised:  In the case of the (irregular) Stochastic Block Model, it is known that efficient algorithms exist all the way down to this threshold, although none are robust to adversarial perturbations of the graph when the average degree is small.
Edit intent: clarity
Original:  More importantly, there is little complexity-theoretic evidence that detection is hard below Kesten-Stigum .
Revised:  More importantly, there is little complexity-theoretic evidence that detection is hard below the threshold .
Edit intent: clarity
Original: Getting solution near singular point of any non-linear BVP is always tough because solution blows up near singularity .
Revised: Capturing solution near the singular point of any non-linear BVP is always tough because solution blows up near singularity .
Edit intent: clarity
Original: Getting solution near singular point of any non-linear BVP is always tough because solution blows up near singularity .
Revised: Getting solution near singular point of any nonlinear SBVPs is challenging because coefficients involved in the differential equation blow up near singularities .
Edit intent: clarity
Original:  In this article our goal is to construct a general method based on orthogonal polynomial and then use different orthogonal polynomials as particular wavelets.
Revised:  In this article , we aim to construct a general method based on orthogonal polynomial and then use different orthogonal polynomials as particular wavelets.
Edit intent: clarity
Original:  In this work we discuss multiresolution analysis for wavelets generated by orthogonal polynomials, e.g.,  Legendre, Chebyshev, Lagurre, Gegenbauer.
Revised:  In this work we discuss multiresolution analysis for wavelets generated by orthogonal polynomials, e.g., Legendre, Chebyshev, Laguerre, and Gegenbauer.
Edit intent: clarity
Original:  Wavelets are able to deal with singularity easily and efficiently  .
Revised:  These wavelets can deal with singularities easily and efficiently .
Edit intent: clarity
Original:  PNS can be used to mitigate a class of attacks known as  code-reuse attacks by significantly reducing the success probability of an exploit payload .
Revised:  PNS can be used to mitigate a class of attacks known as code-reuse .
Edit intent: clarity
Original:  If an attacker causes any of the PC-relative addresses to be different from the one chosen during the fetch, the  program will crash.
Revised:  If an attacker causes any of the instruction addresses to be different from the one chosen during the fetch, the program will crash.
Edit intent: clarity
Original:  If an attacker causes any of the PC-relative addresses to be different from the one chosen during the fetch, the  program will crash.
Revised:  If an attacker causes any of the PC-relative addresses to be different from the one chosen during a fetch, the program will crash.
Edit intent: fluency
Original:  If an attacker causes any of the PC-relative addresses to be different from the one chosen during the fetch, the  program will crash.
Revised:  If an attacker causes any of the PC-relative addresses to be different from the one chosen during the fetch, the exploited program will crash.
Edit intent: clarity
Original:  PNS provides a new security feature that requires minor microarchitectural adjustments, and can be combined with other security features to enhance their strength . Lastly, we show that our performance is better than commercially-available  state-of-the-art hardware primitives, e.g., cryptographic CFI, by a significant margin .
Revised:  PNS provides a new security feature that requires minor microarchitectural adjustments, and can be combined with other security features to enhance their strength . Lastly, we show that our performance is better than commercially-available , state-of-the-art hardware primitives, e.g., cryptographic CFI, by a significant margin .
Edit intent: fluency
Original:  PNS provides a new security feature that requires minor microarchitectural adjustments, and can be combined with other security features to enhance their strength . Lastly, we show that our performance is better than commercially-available  state-of-the-art hardware primitives, e.g., cryptographic CFI, by a significant margin .
Revised:  PNS provides a new security feature that requires minor microarchitectural adjustments, and can be combined with other security features to enhance their strength . Lastly, we show that our performance is better than commercially-available state-of-the-art , hardware-based protections .
Edit intent: clarity