wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We propose a theoretical framework for analyzing small sample properties based on a novel approximation of the discontinuous sample moments with a H\"older continuous process . Using this approximation , we derive remainder bounds with nearly-optimal rates for the asymptotic linear expansions of exact and k-step estimators of IVQR models.
Revised:  First, we propose a higher-order analytical framework for comparing competing estimators in small samples and assessing the accuracy of common inference procedures. Our framework is based on a novel approximation of the discontinuous sample moments with a H\"older continuous process . Using this approximation , we derive remainder bounds with nearly-optimal rates for the asymptotic linear expansions of exact and k-step estimators of IVQR models.
Edit intent: meaning-changed
Original:  We propose a theoretical framework for analyzing small sample properties based on a novel approximation of the discontinuous sample moments with a H\"older continuous process . Using this approximation , we derive remainder bounds with nearly-optimal rates for the asymptotic linear expansions of exact and k-step estimators of IVQR models.
Revised:  We propose a theoretical framework for analyzing small sample properties based on a novel approximation of the discontinuous sample moments by a H\"older-continuous process with a negligible error. For any consistent estimator, this approximation leads to asymptotic linear expansions of exact and k-step estimators of IVQR models.
Edit intent: meaning-changed
Original:  We propose a theoretical framework for analyzing small sample properties based on a novel approximation of the discontinuous sample moments with a H\"older continuous process . Using this approximation , we derive remainder bounds with nearly-optimal rates for the asymptotic linear expansions of exact and k-step estimators of IVQR models. Furthermore, we derive a bias formula for exact IVQR estimators up to order O\left(1{n}\right).
Revised:  We propose a theoretical framework for analyzing small sample properties based on a novel approximation of the discontinuous sample moments with a H\"older continuous process . Using this approximation , we derive remainder bounds with nearly-optimal rates for the asymptotic linear expansions with nearly optimal rates. Second, we study the higher-order bias of exact quantile estimators up to order O\left(1{n}\right).
Edit intent: clarity
Original:  To circumvent this problem, we propose a novel 1-step adjustment of the estimator , which admits a feasible bias correction. We suggest using bias-corrected exact estimators, when possible, to achieve the smallest bias. Otherwise, applying 1-step corrections may improve the higher-order bias and MSE of any consistent estimator .
Revised:  To circumvent this problem, we propose a novel 1-step adjustment of the estimator , which admits a feasible implementation. Our simulations confirm the empirical importance of bias correction .
Edit intent: clarity
Original:  Results show an increase of 0.028 standard deviations in test grades, one year after the opening , and are robust to a series of potential problems, including some of the usual concerns in event study models.
Revised:  Results show an average increase of 0.038 standard deviations in test grades, one year after the opening , and are robust to a series of potential problems, including some of the usual concerns in event study models.
Edit intent: meaning-changed
Original:  Results show an increase of 0.028 standard deviations in test grades, one year after the opening , and are robust to a series of potential problems, including some of the usual concerns in event study models.
Revised:  Results show an increase of 0.028 standard deviations in test grades, for the municipality where the university was established , and are robust to a series of potential problems, including some of the usual concerns in event study models.
Edit intent: meaning-changed
Original:  Finally, we derive "efficient robust" forecasts to deal with the problem of first having to estimate the set of forecast distributions and develop a suitable asymptotic optimality theory .
Revised:  Finally, we derive "efficient robust" forecasts to deal with the problem of first having to estimate the set of forecast distributions and develop a suitable asymptotic efficiency theory. Forecasts obtained by replacing nuisance parameters that characterize the set of forecast distributions with efficient first-stage estimators can be strictly dominated by our efficient robust forecasts .
Edit intent: meaning-changed
Original:  Spectral normalization constrains the state-derivatives of the metric to be Lipschitz continuous, and thereby ensures exponential boundedness of the mean squared distance of system trajectories under stochastic disturbances.
Revised:  Spectral normalization constrains the state-derivatives of the metric to be Lipschitz continuous, thereby ensuring exponential boundedness of the mean squared distance of system trajectories under stochastic disturbances.
Edit intent: coherence
Original:  This framework allows autonomous agents to approximate optimal stable control and estimation policies in real-time, and outperforms existing nonlinear control and estimation techniques including the state-dependent Riccati equation, iterative LQR, EKF, and  deterministic neural contraction metric method , as illustrated in simulations .
Revised:  The NSCM framework allows autonomous agents to approximate optimal stable control and estimation policies in real-time, and outperforms existing nonlinear control and estimation techniques including the state-dependent Riccati equation, iterative LQR, EKF, and deterministic neural contraction metric method , as illustrated in simulations .
Edit intent: meaning-changed
Original:  This framework allows autonomous agents to approximate optimal stable control and estimation policies in real-time, and outperforms existing nonlinear control and estimation techniques including the state-dependent Riccati equation, iterative LQR, EKF, and  deterministic neural contraction metric method , as illustrated in simulations .
Revised:  This framework allows autonomous agents to approximate optimal stable control and estimation policies in real-time, and outperforms existing nonlinear control and estimation techniques including the state-dependent Riccati equation, iterative LQR, EKF, and the deterministic neural contraction metric method , as illustrated in simulations .
Edit intent: fluency
Original:  This framework allows autonomous agents to approximate optimal stable control and estimation policies in real-time, and outperforms existing nonlinear control and estimation techniques including the state-dependent Riccati equation, iterative LQR, EKF, and  deterministic neural contraction metric method , as illustrated in simulations .
Revised:  This framework allows autonomous agents to approximate optimal stable control and estimation policies in real-time, and outperforms existing nonlinear control and estimation techniques including the state-dependent Riccati equation, iterative LQR, EKF, and deterministic neural contraction metric , as illustrated in simulations .
Edit intent: clarity
Original:  This framework allows autonomous agents to approximate optimal stable control and estimation policies in real-time, and outperforms existing nonlinear control and estimation techniques including the state-dependent Riccati equation, iterative LQR, EKF, and  deterministic neural contraction metric method , as illustrated in simulations .
Revised:  This framework allows autonomous agents to approximate optimal stable control and estimation policies in real-time, and outperforms existing nonlinear control and estimation techniques including the state-dependent Riccati equation, iterative LQR, EKF, and deterministic neural contraction metric method , as illustrated in simulation results .
Edit intent: clarity
Original: When an agent interacts with a complex environment, it receives a stream of percepts in which it may detect entities, such as objects or people. To build up a coherent, low-variance estimate of the underlying state, it is necessary to fuse information from multiple detections over time. To do this fusion, the agent must decide which detections to associate with one another. We address this data-association problem in the setting of an online filter, in which each observation is processed by aggregating into an existing object hypothesis. Classic methods with strong probabilistic foundations exist, but they are computationally expensive and require models that can be difficult to acquire .
Revised: A robot operating in a household makes observations of multiple objects as it moves around over the course of days or weeks. The objects may be moved by inhabitants, but not completely at random. The robot may be called upon later to retrieve objects and will need a long-term object-based memory in order to know how to find them .
Edit intent: coherence
Original:  In this work, we use the deep-learning tools of sparse attention and representation learning to learn a machine that processes a stream of detections and outputs a set of hypothesesabout objects in the world. We evaluate this approach on simple clustering problems, problems with dynamics, and a complex image-based domain. We find that it generalizes well from short to long observation sequences and from a few to many hypotheses, outperforming other learning approaches and classical non-learning methods .
Revised:  In this paper, we combine some aspects of classic techniques for data-association filtering with modern attention-based neural networks to construct object-based memory systems that consume and produce high-dimensional observations and hypotheses. We perform end-to-end learning on labeled observation trajectories to learn both necessary internal transition and observation models. We demonstrate the system's effectiveness on a sequence of problem classes of increasing difficulty and show that it outperforms clustering-based methods, classic filters, and unstructured neural approaches .
Edit intent: clarity
Original:  Assuming R < 1, where R is a parameter characterizing the ratio of the nonlinearity to the linear dissipation, this algorithm has complexity T^2poly(\log T, \log n  )/\epsilon, where T is the evolution time and \epsilon is the allowed error in the output quantum state.
Revised:  Assuming R < 1, where R is a parameter characterizing the ratio of the nonlinearity to the linear dissipation, this algorithm has complexity T^2poly(\log T, \log n , \log 1/\epsilon )/\epsilon, where T is the evolution time and \epsilon is the allowed error in the output quantum state.
Edit intent: meaning-changed
Original:  We solve the underlying LP to within a (1+\epsilon) approximation factor in near-linear time via  multiplicative weight update (MWU) techniques.
Revised:  We solve the underlying LP to within a (1+\epsilon) approximation factor in near-linear time via multiplicative weight update (MWU) technique. This yields, in particular, a near-linear time algorithm that outputs an estimate B such that B
Edit intent: meaning-changed
Original: \le \le \lceil \rceil  To round the fractional solution, in our main technical contribution, we describe a fast near-linear time implementation of swap-rounding in the spanning tree polytope of a graph.
Revised: \le B^*\le \lceil \rceil To round the fractional solution, in our main technical contribution, we describe a fast near-linear time implementation of swap-rounding in the spanning tree polytope of a graph.
Edit intent: meaning-changed
Original: \le \le \lceil \rceil  To round the fractional solution, in our main technical contribution, we describe a fast near-linear time implementation of swap-rounding in the spanning tree polytope of a graph.
Revised: \le \le \lceil (1+\epsilon)B\rceil To round the fractional solution, in our main technical contribution, we describe a fast near-linear time implementation of swap-rounding in the spanning tree polytope of a graph.
Edit intent: meaning-changed
Original: \le \le \lceil \rceil  To round the fractional solution, in our main technical contribution, we describe a fast near-linear time implementation of swap-rounding in the spanning tree polytope of a graph.
Revised: \le \le \lceil \rceil +1 where B^* is the minimum-degree of a spanning tree of a given graph. To round the fractional solution, in our main technical contribution, we describe a fast near-linear time implementation of swap-rounding in the spanning tree polytope of a graph.
Edit intent: meaning-changed
Original:  In this paper, we present Mapper Interactive, a web-based framework for the interactive analysis and visualization of high-dimensional point cloud data built upon the mapper algorithm. Different from existing implementations, Mapper Interactive implements the mapper algorithm in an interactive, scalable, and easily extendable way, thus supporting practical data analysis.
Revised:  In this paper, we present Mapper Interactive, a web-based framework for the interactive analysis and visualization of high-dimensional point cloud data . It implements the mapper algorithm in an interactive, scalable, and easily extendable way, thus supporting practical data analysis.
Edit intent: coherence
Original:  It has been conjectured that such a state is best described as a critical dynamical process -- whose nature is still not fully understood -- where scale-free avalanches of activity emerge at the edge of a synchronization phase transition.
Revised:  It has been conjectured that such a state is best described as a critical dynamical process -- whose nature is still not fully understood -- where scale-free avalanches of activity emerge at the edge of a phase transition.
Edit intent: clarity
Original:  Using a simple model of coupled excitable oscillators , we rule out standard phase transitions to explain the emergence of collective oscillations, as they do not suffice to explain current experimental evidence.
Revised:  In particular, some works suggest that this is most likely a synchronization transition, separating synchronous from asynchronous phases. Here, by investigating a simplified model of coupled excitable oscillators , we rule out standard phase transitions to explain the emergence of collective oscillations, as they do not suffice to explain current experimental evidence.
Edit intent: meaning-changed
Original:  Using a simple model of coupled excitable oscillators , we rule out standard phase transitions to explain the emergence of collective oscillations, as they do not suffice to explain current experimental evidence. Conversely, we uncover a novel hybrid-type of synchronization transition displaying a very-rich dynamical repertoire supporting all key empirical observations, including scale-free avalanches , marginal coherence, and bistability .
Revised:  Using a simple model of coupled excitable oscillators describing the cortex dynamics at a mesoscopic level, we investigate the possible nature of such a synchronization phase transition. Within our modeling approach, we conclude that -- in order to reproduce all key empirical observations, including scale-free avalanches , marginal coherence, and bistability .
Edit intent: meaning-changed
Original:  Conversely, we uncover a novel hybrid-type of synchronization transition displaying a very-rich dynamical repertoire supporting all key empirical observations, including scale-free avalanches , marginal coherence, and bistability .
Revised:  Conversely, we uncover a novel hybrid-type of synchronization transition displaying a very-rich dynamical repertoire supporting all key empirical observations, such as scale-free avalanches , marginal coherence, and bistability .
Edit intent: coherence
Original:  Conversely, we uncover a novel hybrid-type of synchronization transition displaying a very-rich dynamical repertoire supporting all key empirical observations, including scale-free avalanches , marginal coherence, and bistability .
Revised:  Conversely, we uncover a novel hybrid-type of synchronization transition displaying a very-rich dynamical repertoire supporting all key empirical observations, including scale-free avalanches and bistability, on which fundamental functional advantages rely -- the transition to collective oscillatory behavior needs to be of an unconventional hybrid type, with mixed features of type-I and type-II excitability, opening the possibility for a particularly rich dynamical repertoire .
Edit intent: meaning-changed
Original: The surprising finding reported in Deyugina and Molitor (2020) that a hurricane as devastating as Katrina reduced the mortality of  residents of New Orleans merits close scrutiny because it is inconsistent with intuition, theory and prior evidence (e. g., Laditka et al. 2010;
Revised: In a recent article in the American Economic Review, Tatyana Deryugina and David Molitor (DM) analyzed the effect of Hurricane Katrina on the mortality of residents of New Orleans merits close scrutiny because it is inconsistent with intuition, theory and prior evidence (e. g., Laditka et al. 2010;
Edit intent: meaning-changed
Original: The surprising finding reported in Deyugina and Molitor (2020) that a hurricane as devastating as Katrina reduced the mortality of  residents of New Orleans merits close scrutiny because it is inconsistent with intuition, theory and prior evidence (e. g., Laditka et al. 2010;
Revised: The surprising finding reported in Deyugina and Molitor (2020) that a hurricane as devastating as Katrina reduced the mortality of elderly and disabled residents of New Orleans merits close scrutiny because it is inconsistent with intuition, theory and prior evidence (e. g., Laditka et al. 2010;
Edit intent: meaning-changed
Original: The surprising finding reported in Deyugina and Molitor (2020) that a hurricane as devastating as Katrina reduced the mortality of  residents of New Orleans merits close scrutiny because it is inconsistent with intuition, theory and prior evidence (e. g., Laditka et al. 2010; Rhodes et al. 2010; Fussel and Lowe 2014; Calvo et al. 2015).
Revised: The surprising finding reported in Deyugina and Molitor (2020) that a hurricane as devastating as Katrina reduced the mortality of residents of New Orleans . The authors concluded that Hurricane Katrina improved the eight-year survival rate of elderly and disabled residents of New Orleans by 3\% and that most of this decline in mortality was due to declines in mortality among those who moved to places with lower mortality.
Edit intent: meaning-changed
Original:  I find the evidence wanting .
Revised:  There are three main problems. First, DM generally fail to account for the fact that people of different ages, races or sex will have different probabilities of dying as time goes by, and when they do allow for this, results change markedly. Second, DM do not account for the fact that residents in New Orleans are likely to be selected non-randomly on the basis of health because of the relatively high mortality rate in New Orleans compared to the rest of the country. Third, there is considerable evidence that among those who moved from New Orleans, the destination chosen was non-random. Finally, DM never directly assessed changes in mortality of those who moved, or stayed, in New Orleans before and after Hurricane Katrina. These problems lead me to conclude that the evidence presented by DM does not support their inferences .
Edit intent: meaning-changed
Original: This paper presents a non-linear optimization method for trajectory planning in a marsupial robot configuration . Particularly, the paper addresses the planning problem of an unmanned aerial vehicle (UAV) linked to an unmanned ground vehicle (UGV) by means of a tether.
Revised: This paper presents a non-linear optimization method for trajectory planning of tethered aerial robots . Particularly, the paper addresses the planning problem of an unmanned aerial vehicle (UAV) linked to an unmanned ground vehicle (UGV) by means of a tether.
Edit intent: clarity
Original: We prove that the alpha-expansion algorithm for MAP inference always returns a globally optimal assignment for Markov Random Fields with Potts pairwise potentials, with a catch: the returned assignment is only guaranteed to be optimal in a small perturbation of the original problem instance.
Revised: We prove that the \alpha-expansion algorithm for MAP inference always returns a globally optimal assignment for Markov Random Fields with Potts pairwise potentials, with a catch: the returned assignment is only guaranteed to be optimal in a small perturbation of the original problem instance.
Edit intent: fluency
Original: We prove that the alpha-expansion algorithm for MAP inference always returns a globally optimal assignment for Markov Random Fields with Potts pairwise potentials, with a catch: the returned assignment is only guaranteed to be optimal in a small perturbation of the original problem instance.
Revised: We prove that the alpha-expansion algorithm for MAP inference always returns a globally optimal assignment for Markov Random Fields with Potts pairwise potentials, with a catch: the returned assignment is only guaranteed to be optimal for an instance within a small perturbation of the original problem instance.
Edit intent: clarity
Original: This paper is concerned with a new Timoshenko beam model with thermal, mass diffusion and viscoelastic effects . First, by the C0-semigroup theory, we prove the well posedness of the considered problemwith Dirichlet boundary conditions. An exponential decay is obtained by construction of the Lyuponov functional. Finally, a numerical study is done based on P_1-finite element approximation for space discretization and implicit Euler scheme for time discretization , where we study the stability of the scheme, analysis of the error and obtained some numerical simulations  .
Revised: This paper is concerned with a new Timoshenko beam model with thermal, mass diffusion and theormoelastic effects is studied. We state and prove the well-posedness of problem. The global existence and uniqueness of the solution is proved by using the classical Faedo-Galerkin approximations along with two a priori estimates. We prove an exponential stability estimate for problem under an unusual assumption, and by using a multiplier technique in two different cases, with frictional damping in the angular rotation and with frictional damping in the vertical displacement. In numerical parts, we first obtained a numerical scheme for problem by P_1-finite element approximation for space discretization and implicit Euler scheme for time discretization , where we study the stability of the scheme, analysis of the error and obtained some numerical simulations .
Edit intent: meaning-changed
Original:  Finally, a numerical study is done based on P_1-finite element approximation for space discretization and implicit Euler scheme for time discretization , where we study the stability of the scheme, analysis of the error and obtained some numerical simulations  .
Revised:  Finally, a numerical study is done based on P_1-finite element method for space discretization and implicit Euler scheme for time discretization , where we study the stability of the scheme, analysis of the error and obtained some numerical simulations .
Edit intent: clarity
Original:  Finally, a numerical study is done based on P_1-finite element approximation for space discretization and implicit Euler scheme for time discretization , where we study the stability of the scheme, analysis of the error and obtained some numerical simulations  .
Revised:  Finally, a numerical study is done based on P_1-finite element approximation for space discretization and implicit Euler scheme for time discretization . Then, we showed that the discrete energy decays, later a priori error estimates are established. Finally , some numerical simulations .
Edit intent: meaning-changed