wanyu/IteraTeR_full_sent huggingface dataset:
Original:  The algorithm removes standard restrictions for path following FoV methods that generally cannot deal with decomposing matrices A due to possible eigencurve crossings for such A . Tests and numerical comparisons are included   .
Revised:  The algorithm removes standard restrictions for path following FoV methods that generally cannot deal with decomposing matrices A due to possible eigencurve crossings for such A . Tests and numerical comparisons are included 0,2\pi{] .
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Original:  We argue that in a setting where  there is imperfect substitutability between money and other measures of wealth (e.g. labor), including two or more payment vehicles may be needed to obtain valid welfare estimates.
Revised:  We argue that in a setting where 1) there is imperfect substitutability between money and other measures of wealth (e.g. labor), including two or more payment vehicles may be needed to obtain valid welfare estimates.
Edit intent: meaning-changed
Original:  We argue that in a setting where  there is imperfect substitutability between money and other measures of wealth (e.g. labor), including two or more payment vehicles may be needed to obtain valid welfare estimates.
Revised:  We argue that in a setting where there is imperfect substitutability between money and other measures of wealth (e.g. labor), and 2) institutions are perceived to be corrupt, including payment vehicles that are currently available to the individual and less pron to corruption may be needed to obtain valid welfare estimates.
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Original: Next generation virtual assistants are envisioned to handle multimodal inputs (e.g., vision, memories of previous interactions, etc., in addition to the user's utterances), and perform multimodal actions (e.g., displaying a route in addition to generating the system's utterance).
Revised: Next generation virtual assistants are envisioned to handle multimodal inputs (e.g., vision, memories of previous interactions, in addition to the user's utterances), and perform multimodal actions (e.g., displaying a route in addition to generating the system's utterance).
Edit intent: coherence
Original: This research quantifies the various South African lockdown regimes, for the SARS-CoV-2 pandemic, in terms of the basic reproduction number, r_0. It further calculates the levels of immunity required in order for these selfsame lockdown regimes to begin to work  .
Revised: This research quantifies the various South African lockdown regimes, for the SARS-CoV-2 pandemic, in terms of the basic reproduction number, r_0. It further calculates the levels of immunity required for these selfsame lockdown regimes to begin to work .
Edit intent: fluency
Original: This research quantifies the various South African lockdown regimes, for the SARS-CoV-2 pandemic, in terms of the basic reproduction number, r_0. It further calculates the levels of immunity required in order for these selfsame lockdown regimes to begin to work  .
Revised: This research quantifies the various South African lockdown regimes, for the SARS-CoV-2 pandemic, in terms of the basic reproduction number, r_0. It further calculates the levels of immunity required in order for these selfsame lockdown regimes to begin to work and predicts perceived values, should infections have been underestimated by a factor of 10. The latter results are compelling .
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Original:  In the appendix, we test the good performance of New Q-Newton's method on various benchmark test functions such as Rastrigin, Askley, Rosenbroch and many other, against algorithms such as Newton's method, BFGS, Adaptive Cubic Regularization, Random damping Newton's method and Inertial Newton's method, as well as Unbounded Two-way Backtracking Gradient Descent.
Revised:  We test the good performance of New Q-Newton's method on various benchmark test functions such as Rastrigin, Askley, Rosenbroch and many other, against algorithms such as Newton's method, BFGS, Adaptive Cubic Regularization, Random damping Newton's method and Inertial Newton's method, as well as Unbounded Two-way Backtracking Gradient Descent.
Edit intent: coherence
Original:  In the appendix, we test the good performance of New Q-Newton's method on various benchmark test functions such as Rastrigin, Askley, Rosenbroch and many other, against algorithms such as Newton's method, BFGS, Adaptive Cubic Regularization, Random damping Newton's method and Inertial Newton's method, as well as Unbounded Two-way Backtracking Gradient Descent.
Revised:  In the appendix, we test the good performance of New Q-Newton's method against algorithms such as Newton's method, BFGS, Adaptive Cubic Regularization, Random damping Newton's method and Inertial Newton's method, as well as Unbounded Two-way Backtracking Gradient Descent.
Edit intent: coherence
Original: We consider explicit approximations for European put option prices within the stochastic Verhulst model with time-dependent parameters, where the volatility process follows the dynamics dV_t = \kappa_t (\theta_t - V_t) V_t dt + \lambda_t V_t dB_t.
Revised: We consider explicit approximations for European put option prices within the Stochastic Verhulst model with time-dependent parameters, where the volatility process follows the dynamics dV_t = \kappa_t (\theta_t - V_t) V_t dt + \lambda_t V_t dB_t.
Edit intent: fluency
Original:  Furthermore, we perform a numerical sensitivity analysis to investigate the quality of our approximation formula in the stochastic Verhulst model, and show that the errors are well within the acceptable range for application purposes.
Revised:  Furthermore, we perform a numerical sensitivity analysis to investigate the quality of our approximation formula in the Stochastic Verhulst model, and show that the errors are well within the acceptable range for application purposes.
Edit intent: fluency
Original: Recently, we reported an emotion self-regulation study (Zotev et al., 2019 ), in which patients with major depressive disorder (MDD) used simultaneous real-time fMRI and EEG neurofeedback (rtfMRI-EEG-nf) to upregulate two fMRI and two EEG activity measures, relevant to MDD.
Revised: Recently, we reported an emotion self-regulation study (Zotev et al., 2020 ), in which patients with major depressive disorder (MDD) used simultaneous real-time fMRI and EEG neurofeedback (rtfMRI-EEG-nf) to upregulate two fMRI and two EEG activity measures, relevant to MDD.
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Original:  The  analyses reveal significant changes in hemispheric lateralities of upper alpha and high-beta current source densities in the prefrontal regions, consistent with upregulation of the FAA and FBA during the rtfMRI-EEG-nf task.
Revised:  The exploratory analyses reveal significant changes in hemispheric lateralities of upper alpha and high-beta current source densities in the prefrontal regions, consistent with upregulation of the FAA and FBA during the rtfMRI-EEG-nf task.
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Original:   Comparisons with results of previous LORETA studies suggest that the rtfMRI-EEG-nf training is beneficial to MDD patients, and has the ability to correct functional deficiencies associated with anhedonia and comorbid anxiety .
Revised:  Changes in prefrontal high-beta current density are consistent with reduction in comorbid anxiety. Comparisons with results of previous LORETA studies suggest that the rtfMRI-EEG-nf training is beneficial to MDD patients, and has the ability to correct functional deficiencies associated with anhedonia and comorbid anxiety .
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Original:   Comparisons with results of previous LORETA studies suggest that the rtfMRI-EEG-nf training is beneficial to MDD patients, and has the ability to correct functional deficiencies associated with anhedonia and comorbid anxiety .
Revised:  Comparisons with results of previous LORETA studies suggest that the rtfMRI-EEG-nf training is beneficial to MDD patients, and may have the ability to correct functional deficiencies associated with anhedonia and comorbid anxiety .
Edit intent: clarity
Original:   Comparisons with results of previous LORETA studies suggest that the rtfMRI-EEG-nf training is beneficial to MDD patients, and has the ability to correct functional deficiencies associated with anhedonia and comorbid anxiety . Our findings confirm the potential of the rtfMRI-EEG-nf for treatment of major depression .
Revised:  Comparisons with results of previous LORETA studies suggest that the rtfMRI-EEG-nf training is beneficial to MDD patients, and has the ability to correct functional deficiencies associated with anhedonia and comorbid anxiety in MDD .
Edit intent: clarity
Original:  Recently, Sariy\"uce et al. introduced nucleus decomposition, a generalization which uses higher-order structures and can reveal interesting subgraphs that can be missed by core and truss decompositions.
Revised:  Recently, Sariyuce et al. introduced nucleus decomposition, a generalization which uses higher-order structures and can reveal interesting subgraphs that can be missed by core and truss decompositions.
Edit intent: fluency
Original:  We propose a new long-term declarative memory for Soar that leverages the computational models of analogical reasoning and generalization.
Revised: Architectures that implement the Common Model of Cognition - Soar, ACT-R, and Sigma - have a prominent place in research on cognitive modeling as well as on designing complex intelligent agents. In this paper, we explore how computational models of analogical processing can be brought into these architectures to enable concept acquisition from examples obtained interactively. We propose a new long-term declarative memory for Soar that leverages the computational models of analogical reasoning and generalization.
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Original:  We propose a new long-term declarative memory for Soar that leverages the computational models of analogical reasoning and generalization. We situate our research in interactive task learning (ITL) and embodied language processing (ELP).
Revised:  We propose a new long-term declarative memory for Soar that augments its current system of declarative long-term memories. We frame the problem of concept learning as embedded within the larger context of interactive task learning (ITL) and embodied language processing (ELP).
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Original:  For doing that, we intend to explore how beneficial the information that people manage about a disease is to reduce the risk of an outbreak. In this paper we analyze the interaction between two different processes on multiplex networks: the propagation of an epidemic using the susceptible-infected-susceptible dynamics and the dissemination of information (rumor) about the knowledge of this disease -
Revised:  In this article we study how the spreading of knowledge of a disease affects the propagation of that disease in a population of interacting individuals. For that, we analyze the interaction between two different processes on multiplex networks: the propagation of an epidemic using the susceptible-infected-susceptible dynamics and the dissemination of information (rumor) about the knowledge of this disease -
Edit intent: clarity
Original:  In this paper we analyze the interaction between two different processes on multiplex networks: the propagation of an epidemic using the susceptible-infected-susceptible dynamics and the dissemination of information (rumor) about the knowledge of this disease -
Revised:  In this paper we analyze the interaction between two different processes on multiplex networks: the propagation of an epidemic using the susceptible-infected-susceptible dynamics and the dissemination of information about the disease -
Edit intent: clarity
Original: -and its prevention methods-- using the unaware-aware-unaware dynamics  . Unlike previous related models where disease and information spread at the same time scale, we introduce here a parameter that controls the relative speed between the propagation of the two processes.
Revised: -and its prevention methods-- using the unaware-aware-unaware dynamics , so that informed individuals are less likely to be infected . Unlike previous related models where disease and information spread at the same time scale, we introduce here a parameter that controls the relative speed between the propagation of the two processes.
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Original:  COVID-19 , the disease caused by the coronavirus SARS-CoV-2, has inflicted considerable suffering on the human population. In this paper, we aim to significantly expand the resources available to biological and clinical researchers who are developing therapeutic targets for drug development and repositioning. Taking a genome-scale, systems-level view of virus-host interactions, we adapt and specialize network label propagation methods to prioritize drug targets based on their probability to inhibit host-pathogen interactions or their downstream signaling targets.
Revised:  COVID-19 , we present a genome-scale, systems-level view of virus-host interactions, we adapt and specialize network label propagation methods to prioritize drug targets based on their probability to inhibit host-pathogen interactions or their downstream signaling targets.
Edit intent: coherence
Original:  Taking a genome-scale, systems-level view of virus-host interactions, we adapt and specialize network label propagation methods to prioritize drug targets based on their probability to inhibit host-pathogen interactions or their downstream signaling targets.
Revised:  Taking a genome-scale, systems-level view of virus-host interactions, we adapt and specialize network label propagation methods to prioritize drug targets based on their potential to regulate host-virus interactions or their downstream signaling targets.
Edit intent: clarity
Original:  We discuss cases where our methodology generates promising insights , including the potential role of HSPA5 in viral entry , the connection of HSPA5 and its interactors with anti-clotting drugs, and the role of tubulin proteins involved in ciliary assembly that are targeted by anti-mitotic drugs.
Revised:  We present cases where our methodology generates promising insights , including the potential role of HSPA5 in viral entry , the connection of HSPA5 and its interactors with anti-clotting drugs, and the role of tubulin proteins involved in ciliary assembly that are targeted by anti-mitotic drugs.
Edit intent: clarity
Original:  We discuss cases where our methodology generates promising insights , including the potential role of HSPA5 in viral entry , the connection of HSPA5 and its interactors with anti-clotting drugs, and the role of tubulin proteins involved in ciliary assembly that are targeted by anti-mitotic drugs.
Revised:  We discuss cases where our methodology generates promising insights such as the potential role of HSPA5 in viral entry , the connection of HSPA5 and its interactors with anti-clotting drugs, and the role of tubulin proteins involved in ciliary assembly that are targeted by anti-mitotic drugs.
Edit intent: clarity
Original:  We discuss cases where our methodology generates promising insights , including the potential role of HSPA5 in viral entry , the connection of HSPA5 and its interactors with anti-clotting drugs, and the role of tubulin proteins involved in ciliary assembly that are targeted by anti-mitotic drugs.
Revised:  We discuss cases where our methodology generates promising insights , including the potential role of HSPA5 in viral entry . We highlight the connection between endoplasmic reticulum stress, HSPA5 and its interactors with anti-clotting drugs, and the role of tubulin proteins involved in ciliary assembly that are targeted by anti-mitotic drugs.
Edit intent: meaning-changed
Original:  We discuss cases where our methodology generates promising insights , including the potential role of HSPA5 in viral entry , the connection of HSPA5 and its interactors with anti-clotting drugs, and the role of tubulin proteins involved in ciliary assembly that are targeted by anti-mitotic drugs.
Revised:  We discuss cases where our methodology generates promising insights , including the potential role of HSPA5 in viral entry , the connection of HSPA5 , and anti-clotting drugs, and the role of tubulin proteins involved in ciliary assembly that are targeted by anti-mitotic drugs.
Edit intent: clarity
Original:  We discuss cases where our methodology generates promising insights , including the potential role of HSPA5 in viral entry , the connection of HSPA5 and its interactors with anti-clotting drugs, and the role of tubulin proteins involved in ciliary assembly that are targeted by anti-mitotic drugs.
Revised:  We discuss cases where our methodology generates promising insights , including the potential role of HSPA5 in viral entry , the connection of HSPA5 and its interactors with anti-clotting agents. We identify tubulin proteins involved in ciliary assembly that are targeted by anti-mitotic drugs.
Edit intent: clarity
Original:  We make the prioritized list of human proteins and drug targets broadly available as a general resource for repositioning of existing and approved drugs  as anti-COVID-19 agents or for novel drug development .
Revised:  We make the prioritized list of human proteins and drug targets broadly available as a general resource for biological and clinical researchers who are repositioning existing and approved drugs as anti-COVID-19 agents or for novel drug development .
Edit intent: meaning-changed
Original: Sparsification, where the cut values of an input graph are approximately preserved by a sparse graph (called a cut sparsifier) or a succinct data structure (called a cut sketch), has been an influential tool in graph algorithms. But, this tool is restricted to undirected graphs, because some directed graphsare known to not admit sparsification. Such examples, however, are structurally very dissimilar to undirected graphs in that they exhibit highly unbalanced cuts. This motivates us to ask: can we sparsify a balanced digraph? To make this question concrete, we define balance \beta of a digraph as the maximum ratio of the cut value in the two directions (Ene et al., STOC 2016). We show the following results: For-All Sparsification: If all cut values need to be simultaneously preserved (cf.
Revised: In this paper, we consider the problem of designing cut sparsifiers and sketches for directed graphs. To bypass known lower bounds, we allow the sparsifier/sketch to depend on the balance of the input graph, which smoothly interpolates between undirected and directed graphs. We give nearly matching upper and lower bounds for both for-all (cf.
Edit intent: coherence
Original:  Bencz\'ur and Karger, STOC 1996) , then we show that the size of the sparsifier (or even cut sketch) must scale linearly with \beta. The upper bound is a simple extension of sparsification of undirected graphs (formally stated recently in Ikeda and Tanigawa (WAOA 2018)), so our main contribution here is to show a matching lower bound. For-Each Sparsification: If each cut value needs to be individually preserved ( Andoni et al., ITCS 2016) , then the situation is more interesting.
Revised:  Bencz\'ur and Karger, STOC 1996) and for-each ( Andoni et al., ITCS 2016) , then the situation is more interesting.
Edit intent: coherence
Original:  For-Each Sparsification: If each cut value needs to be individually preserved ( Andoni et al., ITCS 2016) , then the situation is more interesting. Here, we give a cut sketch whose size scales with \sqrt{\beta We also show that this result is tight by exhibiting a matching lower bound of \sqrt{\beta .
Revised:  For-Each Sparsification: If each cut value needs to be individually preserved ( Andoni et al., ITCS 2016) cut sparsifiers/sketches as a function of cut balance, defined the maximum ratio of the cut value in the two directions of a directed graph (Ene et al., STOC 2016). We also show that this result is tight by exhibiting a matching lower bound of \sqrt{\beta .
Edit intent: meaning-changed
Original:  Here, we give a cut sketch whose size scales with \sqrt{\beta We also show that this result is tight by exhibiting a matching lower bound of \sqrt{\beta .
Revised:  Here, we give a cut sketch whose size scales with \sqrt{\beta We also show an interesting application of digraph sparsification via cut balance by using it to give a very short proof of a celebrated maximum flow result of Karger and Levine (STOC 2002) .
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Original:  For this problem class, the algorithm Sequential Manifold Planning (SMP*) is developed that searches for optimal intersection points between manifolds by using RRT* in an inner loop with a novel steering strategy.
Revised:  For this problem class, we develop the algorithm Planning on Sequenced Manifolds (PSM*) which searches for optimal intersection points between manifolds by using RRT* in an inner loop with a novel steering strategy.
Edit intent: meaning-changed
Original: The Quasi-Maximum Likelihood (QML) procedure is widely used for statistical inference due to its robustness against overdisper-sion. However, while there are extensive references on non-recursive QML estimation , recursive QML estimation has attracted little attention until recently.
Revised: The Quasi-Maximum Likelihood (QML) procedure is widely used for statistical inference . While there are extensive references on non-recursive QML estimation , recursive QML estimation has attracted little attention until recently.
Edit intent: coherence
Original:  In this paper, we investigate the convergence properties of the QML procedure in a general conditionally heteroscedastic time series model , extending the classical offline optimization routines to recursive approximation. We propose an adaptive recursive estimation routine for GARCH models using the technique of Variance Targeting Estimation (VTE) to alleviate the convergence difficulties encountered in the usual QML estimation .
Revised:  In this paper, we investigate the convergence properties of the QML procedure in a general conditionally heteroscedastic time series model is conducted, and the classical batch optimization routines extended to the framework of streaming and large-scale problems. An adaptive recursive estimation routine for GARCH models using the technique of Variance Targeting Estimation (VTE) to alleviate the convergence difficulties encountered in the usual QML estimation .
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Original:  We propose an adaptive recursive estimation routine for GARCH models using the technique of Variance Targeting Estimation (VTE) to alleviate the convergence difficulties encountered in the usual QML estimation .
Revised:  We propose an adaptive recursive estimation routine for GARCH models named AdaVol is presented. The AdaVol procedure relies on stochastic approximations combined with the technique of Variance Targeting Estimation (VTE) to alleviate the convergence difficulties encountered in the usual QML estimation .
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Original:  We propose an adaptive recursive estimation routine for GARCH models using the technique of Variance Targeting Estimation (VTE) to alleviate the convergence difficulties encountered in the usual QML estimation .
Revised:  We propose an adaptive recursive estimation routine for GARCH models using the technique of Variance Targeting Estimation (VTE) . This recursive method has computationally efficient properties, while VTE alleviates some convergence difficulties encountered in the usual QML estimation .
Edit intent: meaning-changed