wanyu/IteraTeR_full_sent huggingface dataset:
Original:  From this, we observe that white noise and jump noise have a significant effect on the spread of COVID-19 infection . To illustrate this phenomenon, we put some numerical simulations.
Revised:  From this, we observe that white noise and jump noise have a significant effect on the spread of COVID-19 infection , i.e., we can conclude that the stochastic model is more realistic than the deterministic one. Finally, to illustrate this phenomenon, we put some numerical simulations.
Edit intent: meaning-changed
Original:  We propose different update strategies for the grid points , where the approximation is valid to consider the locality of the planar approximation . We experimentally validate the approach by tracking the surface with a robotic manipulator.
Revised:  We propose different update strategies for the grid points , where the approximation is valid to consider the locality of the planar approximation in combination with a projection method. The approach is experimentally validated by tracking the surface with a robotic manipulator.
Edit intent: meaning-changed
Original:  Therefore, we can use this approach to obtain the best framework for modelling and simulating vaccination prioritisation and uptake that will be readily available to inform important policy decisions for the optimal control of the COVID-19 pandemic.
Revised:  Therefore, we can use this approach to obtain the best framework for modelling and simulating vaccination prioritization and uptake that will be readily available to inform important policy decisions for the optimal control of the COVID-19 pandemic.
Edit intent: fluency
Original:  We also derive expressions for some entries in "Eighty New Invariants of N-Periodics in the Elliptic Billiard" (2020), arXiv:2004.12497  .
Revised:  We also check if some invariants listed in "Eighty New Invariants of N-Periodics in the Elliptic Billiard" (2020), arXiv:2004.12497 .
Edit intent: clarity
Original:  We also derive expressions for some entries in "Eighty New Invariants of N-Periodics in the Elliptic Billiard" (2020), arXiv:2004.12497  .
Revised:  We also derive expressions for some entries in "Eighty New Invariants of N-Periodics in the Elliptic Billiard" (2020), arXiv:2004.12497 , remain invariant in the self-intersected case. Toward that end, we derive explicit expressions for many low-N simple and self-intersected cases. We identify two special cases (one simple, one self-intersected) where a quantity prescribed to be invariant is actually variable .
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Original:   We introduce attitude strategies that work with the underactuated planners, controllers, tools,  and remote control interfaces, all while allowing taking advantage of the full actuation.
Revised:  The approach can extend the existing underactuated flight controllers to support the fully-actuated robots, or enhance the existing fully-actuated controllers to support existing underactuated flight stacks. We introduce attitude strategies that work with the underactuated planners, controllers, tools, and remote control interfaces, all while allowing taking advantage of the full actuation.
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Original:  The real experiments on our robots and simulations on several UAV architectures show how the strategies can be utilized . The source code of the PX4 firmware enhanced with the proposed methods and its simulator with our fully-actuated hexarotor model are provided with this paper.
Revised:  The real experiments on our robots and simulations on several UAV architectures show how the strategies can be utilized to extend existing flight controllers for fully-actuated applications. We have provided the source code for the PX4 firmware enhanced with the proposed methods and its simulator with our fully-actuated hexarotor model are provided with this paper.
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Original:  The source code of the PX4 firmware enhanced with the proposed methods and its simulator with our fully-actuated hexarotor model are provided with this paper.
Revised:  The source code of the PX4 firmware enhanced with our proposed methods to showcase an example flight controller for underactuated multirotors that can be modified to seamlessly support fully-actuated hexarotor model are provided with this paper.
Edit intent: meaning-changed
Original:  Since human driving behavior is inherently multimodal, models which allow for multimodal output tend to outperform single-prediction models on standard metrics ; the proposed loss function benefits such models , as all predicted modes must follow the same expected driving rules  .
Revised:  Since human driving behavior is inherently multimodal, models which allow for multimodal output tend to outperform single-prediction models on standard metrics . We propose a loss function which enhances such models by enforcing expected driving rules .
Edit intent: clarity
Original:  we propose a new metric which addresses failure cases of the off-road rate metric by penalizing trajectories that contain driving behavior that opposes the ascribed heading (flow direction) of a driving lane, and we show this metric to be differentiable and therefore suitable as an auxiliary loss function.
Revised:  we propose a new metric which addresses failure cases of the off-road rate metric by penalizing trajectories that oppose the ascribed heading (flow direction) of a driving lane, and we show this metric to be differentiable and therefore suitable as an auxiliary loss function.
Edit intent: clarity
Original:  I focus on a practically relevant situation in which additional covariates are required for identification but the reduced-form and first-stage regressions are possibly misspecified as a result of neglected heterogeneity in the effects of the instrument .
Revised:  I focus on a practically relevant situation in which additional covariates are required for identification while the reduced-form and first-stage regressions are possibly misspecified as a result of neglected heterogeneity in the effects of the instrument .
Edit intent: coherence
Original:  I focus on a practically relevant situation in which additional covariates are required for identification but the reduced-form and first-stage regressions are possibly misspecified as a result of neglected heterogeneity in the effects of the instrument .
Revised:  I focus on a practically relevant situation in which additional covariates are required for identification but the reduced-form and first-stage regressions implicitly restrict the effects of the instrument .
Edit intent: clarity
Original:  I focus on a practically relevant situation in which additional covariates are required for identification but the reduced-form and first-stage regressions are possibly misspecified as a result of neglected heterogeneity in the effects of the instrument . If we also allow for conditional monotonicity, i. e. the existence of compliers but no defiers at some covariate values and the existence of defiers but no compliers elsewhere, then the weights on some conditional LATEs are negative and the IV estimand is no longer interpretable as a causal effect .
Revised:  I focus on a practically relevant situation in which additional covariates are required for identification but the reduced-form and first-stage regressions are possibly misspecified as a result of neglected heterogeneity in the effects of the instrument to be homogeneous, and are thus possibly misspecified. I show that the weights on some conditional LATEs are negative and the IV estimand is no longer interpretable as a causal effect .
Edit intent: coherence
Original:  If we also allow for conditional monotonicity, i. e. the existence of compliers but no defiers at some covariate values and the existence of defiers but no compliers elsewhere, then the weights on some conditional LATEs are negative and the IV estimand is no longer interpretable as a causal effect .
Revised:  If we also allow for conditional monotonicity, i. e. the existence of compliers but no defiers at some covariate values and the existence of defiers but no compliers elsewhere, then the weights on some conditional LATEs are negative and the IV estimand is no longer interpretable as a causal effect under conditional monotonicity, i.e. when there are compliers but no defiers at some covariate values and defiers but no compliers elsewhere.
Edit intent: clarity
Original:  I show that the weights on some conditional LATEs are negative and the IV estimand is no longer interpretable as a causal effect under conditional monotonicity, i.e. when there are compliers but no defiers at some covariate values and defiers but no compliers elsewhere.
Revised:  I show that the weights on some conditional LATEs are negative and the IV estimand is no longer interpretable as a causal effect under a weaker version of monotonicity, i.e. when there are compliers but no defiers at some covariate values and defiers but no compliers elsewhere.
Edit intent: meaning-changed
Original:  Even if monotonicity holds unconditionally , the IV estimand  is not interpretable as the unconditional LATE parameter unless the groups with different values of the instrument are roughly equal sized  .
Revised:  The problem of negative weights disappears in the overidentified specification of Angrist and Imbens (1995) and in an alternative method, termed "reordered IV," that I also develop. Even if all weights are positive , the IV estimand is not interpretable as the unconditional LATE parameter unless the groups with different values of the instrument are roughly equal sized .
Edit intent: meaning-changed
Original:  Even if monotonicity holds unconditionally , the IV estimand  is not interpretable as the unconditional LATE parameter unless the groups with different values of the instrument are roughly equal sized  .
Revised:  Even if monotonicity holds unconditionally , the IV estimand in the just identified specification is not interpretable as the unconditional LATE parameter unless the groups with different values of the instrument are roughly equal sized .
Edit intent: meaning-changed
Original:  Even if monotonicity holds unconditionally , the IV estimand  is not interpretable as the unconditional LATE parameter unless the groups with different values of the instrument are roughly equal sized  .
Revised:  Even if monotonicity holds unconditionally , the IV estimand is not interpretable as the unconditional LATE parameter unless the groups with different values of the instrument are roughly equal sized . I illustrate my findings in an application to causal effects of college education using the college proximity instrument. The benchmark estimates suggest that college attendance yields earnings gains of about 60 log points, which is well outside the range of estimates in the recent literature. I demonstrate that this result is driven by the existence of defiers and the presence of negative weights. Corrected estimates indicate that attending college causes earnings to be roughly 20\% higher .
Edit intent: meaning-changed
Original:  The results simultaneously demonstrate the good performance of our approach and the fundamental failure of conventionally applied, i.e., linear, weak identification tests in this context. We compare our testing approach to those commonly applied in the literature within two empirical examples: married women labor force participation, and US food aid and civil conflicts.
Revised:  The results simultaneously demonstrate the good performance of our approach and the fundamental failure of conventionally applied, i.e., linear, weak identification tests for linear models in the discrete choice model context. Furthermore, we compare our approach against those commonly applied in the literature within two empirical examples: married women labor force participation, and US food aid and civil conflicts.
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Original: This paperformulates an application of reinforcement learning for an evader in a confinement escape problem . An evader's objective is to attempt escaping a confinement region patrolled by multiple defenders, with minimum use of energy .
Revised: This paperformulates an application of reinforcement learning for an evader in a confinement escape problem (CEP). In CEP, an evader's objective is to attempt escaping a confinement region patrolled by multiple defenders, with minimum use of energy .
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Original:  Meanwhile, the defenders aim to reach and capture the evader without any communication between them. The problem formulation uses the actor-critic approach for the defender.
Revised:  Meanwhile, the defenders aim to reach and capture the evader . The inverse solution for pursuers to try and capture has been extensively studied in the literature. However, the problem of evaders escaping from the region is still an open issue. The SR2L employs an actor-critic approach for the defender.
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Original:  The problem formulation uses the actor-critic approach for the defender. In this paper, the novel Scaffolding Reflection in Reinforcement Learning ( SR2L ) framework is proposed, using a potential field method as a scaffold to assist the actor's action-reflection.
Revised:  The problem formulation uses the actor-critic framework to enable the evader to escape the confinement region. A time-varying state representation and reward function have been developed for proper convergence. The formulation uses the sensor information about the observable environment and prior knowledge of the confinement boundary. The conventional Independent Actor-Critic (IAC) method fails to converge due to sparseness in the reward. The effect becomes evident when operating in such a dynamic environment with a large area. In SR2L, along with the developed reward function, we use the scaffolding reflection method to improve the convergence significantly while increasing its efficiency. In SR2L ) framework is proposed, using a potential field method as a scaffold to assist the actor's action-reflection.
Edit intent: meaning-changed
Original:  In this paper, the novel Scaffolding Reflection in Reinforcement Learning ( SR2L ) framework is proposed, using a potential field method as a scaffold to assist the actor's action-reflection. Through the user's clearly articulated intent, the action-reflection enables the actor to learn by observing the probable actions and their values based on experience.
Revised:  In this paper, the novel Scaffolding Reflection in Reinforcement Learning ( SR2L ) framework is proposed, using a potential field method as a scaffold for the actor-critic network to observe, compare and learn the action-reward pair. It enables the evader to achieve the required objective while using lesser resources and time. Convergence studies show that SR2L learns faster and converges to higher rewards as compared to IAC.
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Original: We present an iterative method for solving the system arisen from finite element discretization of a distributed optimal control problem with time-periodic parabolic equations.
Revised: We present a stationary iteration method, namely Alternating Symmetric positive definite and Scaled symmetric positive semidefinite Splitting (ASSS), for solving the system arisen from finite element discretization of a distributed optimal control problem with time-periodic parabolic equations.
Edit intent: meaning-changed
Original: We present a stationary iteration method, namely Alternating Symmetric positive definite and Scaled symmetric positive semidefinite Splitting (ASSS), for solving the system arisen from finite element discretization of a distributed optimal control problem  with time-periodic parabolic equations.
Revised: We present a stationary iteration method, namely Alternating Symmetric positive definite and Scaled symmetric positive semidefinite Splitting (ASSS), for solving the system of linear equations obtained by using finite element discretization of a distributed optimal control problem with time-periodic parabolic equations.
Edit intent: meaning-changed
Original: We present a stationary iteration method, namely Alternating Symmetric positive definite and Scaled symmetric positive semidefinite Splitting (ASSS), for solving the system arisen from finite element discretization of a distributed optimal control problem  with time-periodic parabolic equations.
Revised: We present a stationary iteration method, namely Alternating Symmetric positive definite and Scaled symmetric positive semidefinite Splitting (ASSS), for solving the system arisen from finite element discretization of a distributed optimal control problem together with time-periodic parabolic equations.
Edit intent: coherence
Original:  We evaluated our approach in various environments using two different robots, i.e., a HSR by Toyota and a \mbox{Care-O-Bot-4 . As the experimental results demonstrate, our system is able to generate maps that are close to the ground truth and outperforms an existing approach in terms of intersection over union, different distance metrics, and the number of correct object mappings.
Revised:  We evaluated our approach in various environments using two different robots, i.e., a Toyota HSR and a Fraunhofer Care-O-Bot-4 . As the experimental results demonstrate, our system is able to generate maps that are close to the ground truth and outperforms an existing approach in terms of intersection over union, different distance metrics, and the number of correct object mappings.
Edit intent: meaning-changed
Original:  The main idea is to reduce the stiffness of the problem by subtracting to the standard stiffness bilinear form a least-squares penalty on the gradient jumps across the mesh interfaces  .
Revised:  The main idea is to reduce the stiffness of the problem by subtracting to the standard stiffness bilinear form a least-squares penalty on the gradient jumps across the mesh interfaces from the standard stiffness bilinear form .
Edit intent: clarity
Original:  This penalty bilinear form is similar to the known technique used to stabilize finite element approximations in various contexts , but it brings here a negative contribution. Since it reduces the stiffness of the problem , the resulting approximation technique is called softFEM . The two key advantages of softFEM over the standard Galerkin FEM are to improve the approximation of the eigenvalues in the upper part of the discrete spectrum and to reduce the condition number of the stiffness matrix.
Revised:  This penalty bilinear form is similar to the known technique used to stabilize finite element approximations in various contexts . The penalty term is designed to dampen the high frequencies in the spectrum and so it is weighted here by a negative coefficient. The resulting approximation technique is called softFEM since it reduces the stiffness of the problem , the resulting approximation technique is called softFEM . The two key advantages of softFEM over the standard Galerkin FEM are to improve the approximation of the eigenvalues in the upper part of the discrete spectrum and to reduce the condition number of the stiffness matrix.
Edit intent: clarity
Original:  Since it reduces the stiffness of the problem , the resulting approximation technique is called softFEM . The two key advantages of softFEM over the standard Galerkin FEM are to improve the approximation of the eigenvalues in the upper part of the discrete spectrum and to reduce the condition number of the stiffness matrix.
Revised:  Since it reduces the stiffness of the problem . The two key advantages of softFEM over the standard Galerkin FEM are to improve the approximation of the eigenvalues in the upper part of the discrete spectrum and to reduce the condition number of the stiffness matrix.
Edit intent: clarity
Original:  We evaluate our proposed Efficient Scene Analysis Network (ESANet) on the common indoor datasets NYUv2 and SUNRGB-D and show that it reaches state-of-the-art performance when considering both segmentation performance and runtime .
Revised:  We evaluate our proposed Efficient Scene Analysis Network (ESANet) on the common indoor datasets NYUv2 and SUNRGB-D and show that we reach state-of-the-art performance when considering both segmentation performance and runtime .
Edit intent: fluency
Original:  We evaluate our proposed Efficient Scene Analysis Network (ESANet) on the common indoor datasets NYUv2 and SUNRGB-D and show that it reaches state-of-the-art performance when considering both segmentation performance and runtime .
Revised:  We evaluate our proposed Efficient Scene Analysis Network (ESANet) on the common indoor datasets NYUv2 and SUNRGB-D and show that it reaches state-of-the-art performance while enabling faster inference .
Edit intent: clarity
Original: Current state-of-the-art approaches for named entity recognition (NER) using BERT-style transformers typically use one of two different approaches: (1) The first fine-tunes the transformer itself on the NER task and adds only a simple linear layer for word-level predictions. (2) The second uses the transformer only to provide featuresto a standard LSTM-CRF sequence labeling architecture and thus performs no fine-tuning .
Revised: Current state-of-the-art approaches for named entity recognition (NER) typically consider text at the sentence-level and thus do not model information that crosses sentence boundaries. However, the use of transformer-based models for NER offers natural options for capturing document-level features .
Edit intent: clarity
Original:  In this paper, we perform a comparative analysis of both approaches in a variety of settings currently considered in the literature . In particular, we evaluate how well they work when document-level features are leveraged. Our evaluation on the classic CoNLL benchmark datasets for 4 languages shows that document-level features significantly improve NER quality and that fine-tuning generally outperforms the feature-based approaches .
Revised:  In this paper, we perform a comparative analysis of both approaches in a variety of settings currently considered in the literature , namely " fine-tuning generally outperforms the feature-based approaches .
Edit intent: coherence
Original:  Our evaluation on the classic CoNLL benchmark datasets for 4 languages shows that document-level features significantly improve NER quality and that fine-tuning generally outperforms the feature-based approaches .
Revised:  Our evaluation on the classic CoNLL benchmark datasets for 4 languages shows that document-level features significantly improve NER quality and that fine-tuning generally outperforms the feature-based LSTM-CRF". We evaluate different hyperparameters for document-level features such as context window size and enforcing document-locality .
Edit intent: meaning-changed
Original: This paper shows how to use a randomized saturation experimental design to identify and estimate causal effects in the presence of social interactions--one person's treatment may affect another's outcome--and one-sided non-compliance--subjects can only be offered treatment, not compelled to take it up.
Revised: This paper shows how to use a randomized saturation experimental design to identify and estimate causal effects in the presence of spillovers--one person's treatment may affect another's outcome--and one-sided non-compliance--subjects can only be offered treatment, not compelled to take it up.
Edit intent: clarity
Original:  We go on to propose a feasible estimator that is consistent and asymptotically normal as the number and size of groups increases  .
Revised:  We go on to propose a feasible estimator that is consistent and asymptotically normal as the number and size of groups increases . We apply our estimator to data from a large-scale job placement services experiment, and find negative indirect treatment effects on the likelihood of employment for those willing to take up the program. These negative spillovers are offset by positive direct treatment effects from own take-up .
Edit intent: meaning-changed