wanyu/IteraTeR_v2 huggingface dataset:
Original: We examine opinion dynamics in  multi-agent games.
Revised: We examine opinion dynamics in repeated multi-agent games.
Edit intent: clarity
Original:  Each agent forms an opinion describing its preferences among multiple available strategies and exchanges its opinion with other agents.
Revised:  In our model, each agent updates, in continuous time, its opinion about multiple available strategies and exchanges its opinion with other agents.
Edit intent: clarity
Original:  We explain how the model allows the agents to make rational and reciprocal decisions on strategy selection , both of which are key features observed in human decision making  . Using bifurcation analysis, we establish how the agents switch between rational and reciprocal decision making, and we use the results to explain how cooperation emerges in the prisoner's dilemma .
Revised:  We show how the model allows the agents to make rational and reciprocal decisions on strategy selection , both of which are key features observed in human decision making . Using bifurcation analysis, we establish how the agents switch between rational and reciprocal decision making, and we use the results to explain how cooperation emerges in the prisoner's dilemma .
Edit intent: coherence
Original:  We explain how the model allows the agents to make rational and reciprocal decisions on strategy selection , both of which are key features observed in human decision making  . Using bifurcation analysis, we establish how the agents switch between rational and reciprocal decision making, and we use the results to explain how cooperation emerges in the prisoner's dilemma .
Revised:  We explain how the model provides a principled and systematic means to investigate behavior of agents that select strategies using rationality and reciprocity , both of which are key features observed in human decision making . Using bifurcation analysis, we establish how the agents switch between rational and reciprocal decision making, and we use the results to explain how cooperation emerges in the prisoner's dilemma .
Edit intent: clarity
Original: We examine opinion dynamics in repeated multi-agent games .
Revised: We examine the tuning of cooperative behavior in repeated multi-agent games .
Edit intent: clarity
Original:  In our model, each agent updates , in continuous time, its opinion about multiple available strategies, in response to payoffs associated with the game and exchanges of opinions with other agents .
Revised:  In our model, each agent updates , in continuous time, its opinion about multiple available strategies, in response to payoffs and other agent opinions, as observed over a network .
Edit intent: clarity
Original:  We show how the model provides a principled and systematic means to investigate behavior of agents that select strategies using rationality and reciprocity, both of which are key features observed in human decision making in social dilemmas.
Revised:  We show how the model provides a principled and systematic means to investigate behavior of agents that select strategies using rationality and reciprocity, key features of human decision-making in social dilemmas.
Edit intent: clarity
Original:  Using bifurcation analysis, we prove conditions for the multistability of equilibria in two-agent two-strategy social dilemmas.
Revised:  For two-strategy games, we use bifurcation analysis to prove conditions for the multistability of equilibria in two-agent two-strategy social dilemmas.
Edit intent: clarity
Original:  The results are generalizable to games with more agents and more strategies, and to additional feedback dynamics, e.g., those designed to elicit cooperation.
Revised:  The results are generalizable to games with more strategies, heterogeneity, and additional feedback dynamics, e.g., those designed to elicit cooperation.
Edit intent: clarity
Original:  The results are generalizable to games with more agents and more strategies, and to additional feedback dynamics, e.g., those designed to elicit cooperation.
Revised:  The results are generalizable to games with more agents and more strategies, and to additional feedback dynamics, such as those designed to elicit cooperation.
Edit intent: clarity
Original:  These faces can be used to impersonate, with a high probability of success, any user, without having access to any user information .
Revised:  These faces can be used to impersonate, with a high probability of success, any user, without having access to any user-information .
Edit intent: clarity
Original:  An imbalance in the activity of antagonistic laryngeal muscles is hypothesized to play a key role in the alteration of normal vocal fold biomechanics that results in the dysphonia associated with such disorders.
Revised:  Abnormal activity of antagonistic laryngeal muscles is hypothesized to play a key role in the alteration of normal vocal fold biomechanics that results in the dysphonia associated with such disorders.
Edit intent: clarity
Original:  To address this limitation, a scheme for controlling a self-sustained triangular body-cover model with  intrinsic muscle control is introduced.
Revised:  To address this limitation, a self-sustained triangular body-cover model with intrinsic muscle control is introduced.
Edit intent: clarity
Original:  Pilot simulations of abnormal scenarios illustrated that poorly regulated and elevated muscle activities result in more abducted prephonatory posturing, which lead to inefficient phonation and subglottal pressure compensation to regain loudness .
Revised:  Simulations of vocal fold posturing obtained with distinct antagonistic muscle activation yield clear differences in kinematic, aerodynamic and acoustic measures .
Edit intent: clarity
Original: We study a new challenging problem of efficient deployment for diverse tasks with different resources , where the resource constraint and task of interest corresponding to a group of classes are dynamically specified at testing time.
Revised: In many real-world applications, we often need to handle various deployment scenarios , where the resource constraint and task of interest corresponding to a group of classes are dynamically specified at testing time.
Edit intent: clarity
Original:  Previous NAS approaches seek to design architectures for all classes simultaneously, which may not be optimal for some individual tasks .
Revised:  Previous NAS approaches seek to design architectures for all classes simultaneously, which may not be optimal for some individual superclasses .
Edit intent: clarity
Original:  To this end, we first propose to effectively train the over-parameterized network via a task dropout strategy to disentangle the tasks during training.
Revised:  To this end, we first propose to effectively train an over-parameterized network via a task dropout strategy to disentangle the tasks during training.
Edit intent: fluency
Original:  Based on the well-trained over-parameterized network, we then propose an efficient architecture generator to obtain optimal architectures within a single forward pass.
Revised:  Based on the well-trained over-parameterized network, we then propose an efficient architecture generator to obtain promising architectures within a single forward pass.
Edit intent: clarity
Original:  The observed information simplifies calculation of conditional expectation of outer product of the complete-data score function appeared in the Louis (1982) general matrix formula.
Revised:  The observed information simplifies calculation of conditional expectation of outer product of the complete-data score function appearing in the Louis (1982) general matrix formula.
Edit intent: fluency
Original:   The proposed sandwich estimator takes a different form than the Huber sandwich estimator under model misspecification framework ( Freedman, 2006 and Little and Rubin, 2020).
Revised:  The proposed sandwich estimator takes a different form than the Huber sandwich estimator under model misspecification framework ( Freedman, 2006 ; Little and Rubin, 2020).
Edit intent: coherence
Original:  Moreover, it does not involve the inverse observed Fisher information of incomplete data which therefore notably gives an appealing feature for application.
Revised:  However, in contrast to the latter, the new estimator does not involve the inverse observed Fisher information of incomplete data which therefore notably gives an appealing feature for application.
Edit intent: coherence
Original:  Moreover, it does not involve the inverse observed Fisher information of incomplete data which therefore notably gives an appealing feature for application.
Revised:  Moreover, it does not involve OFI which notably gives an appealing feature for application.
Edit intent: coherence
Original:  Recursive algorithms for the MLE  and the sandwich estimator of covariance matrix are presented.
Revised:  Recursive algorithms for the MLE and the sandwich estimator are presented.
Edit intent: clarity
Original:  Application to parameter estimation of  regime switching conditional Markov jump process is considered to verify the results.
Revised:  Application to parameter estimation of a regime switching conditional Markov jump process is considered to verify the results.
Edit intent: fluency
Original:  The sandwich estimator produces standard errors of the MLE which are closer to their analytic values than those provided by the inverse observed Fisher information .
Revised:  The sandwich estimator produces standard error of the MLE which are closer to their analytic values than those provided by the inverse observed Fisher information .
Edit intent: fluency
Original:  The sandwich estimator produces standard errors of the MLE which are closer to their analytic values than those provided by the inverse observed Fisher information .
Revised:  The sandwich estimator produces standard errors of the MLE close to their analytic values than those provided by the inverse observed Fisher information .
Edit intent: clarity
Original:  The sandwich estimator produces standard errors of the MLE which are closer to their analytic values than those provided by the inverse observed Fisher information .
Revised:  The sandwich estimator produces standard errors of the MLE which are closer to their analytic values compared to those overestimated by the OFI .
Edit intent: clarity
Original: Fault tolerance of a blockchain is often characterized by the fraction f of ``adversarial power'' that it can tolerate in the system.
Revised: Fault tolerance of a blockchain is often characterized by the fraction f of "adversarial power" that it can tolerate in the system.
Edit intent: fluency
Original:  We first note that the well-known impossibility of {\em byzantine consensus} under f%DIFDELCMD < \ge %%% \frac{1 does not carry over to blockchains.
Revised:  We first note that the well-known impossibility of {\em byzantine consensus} %DIFDELCMD < \ge %%% \frac{1 does not carry over to blockchains.
Edit intent: clarity
Original:  To address the second issue, we devise an instance-based transformer module to exploit the dependencies between different text instances and a pixel-based transformer module to exploit the global context from the shared background, which are able to collaboratively learn more discriminative text feature representations .
Revised:  To address the second issue, we devise an instance-based transformer module to exploit the dependencies between different text instances and a global context module to exploit the global context from the shared background, which are able to collaboratively learn more discriminative text feature representations .
Edit intent: clarity
Original:  To address the second issue, we devise an instance-based transformer module to exploit the dependencies between different text instances and a pixel-based transformer module to exploit the global context from the shared background, which are able to collaboratively learn more discriminative text feature representations .
Revised:  To address the second issue, we devise an instance-based transformer module to exploit the dependencies between different text instances and a pixel-based transformer module to exploit the global context from the shared background, which are able to collaboratively learn more discriminative text feature representation .
Edit intent: fluency
Original:  Experimental results show that the proposed I3CL sets new state-of-the-art performances on three challenging public benchmarks, i.e., an F-measure of 76.4 \% on ICDAR2019-ArT, 86.2 \% on Total-Text, and 85.8 \% on CTW-1500.
Revised:  Experimental results show that the proposed I3CL sets new state-of-the-art results on three challenging public benchmarks, i.e., an F-measure of 76.4 \% on ICDAR2019-ArT, 86.2 \% on Total-Text, and 85.8 \% on CTW-1500.
Edit intent: clarity
Original:  Experimental results show that the proposed I3CL sets new state-of-the-art performances on three challenging public benchmarks, i.e., an F-measure of 76.4 \% on ICDAR2019-ArT, 86.2 \% on Total-Text, and 85.8 \% on CTW-1500.
Revised:  Experimental results show that the proposed I3CL sets new state-of-the-art performances on three challenging public benchmarks, i.e., an F-measure of 76.4 \% on ICDAR2019-ArT, 86.2 \% on Total-Text, and 86.4 \% on CTW-1500.
Edit intent: clarity
Original:  Besides, I3CL with  ResNeSt-101 backbone ranked 1st place on the ICDAR2019-ArT leaderboard.
Revised:  Notably, our I3CL with ResNeSt-101 backbone ranked 1st place on the ICDAR2019-ArT leaderboard.
Edit intent: clarity
Original:  Besides, I3CL with  ResNeSt-101 backbone ranked 1st place on the ICDAR2019-ArT leaderboard.
Revised:  Besides, I3CL with the ResNeSt-101 backbone ranked 1st place on the ICDAR2019-ArT leaderboard.
Edit intent: fluency
Original: Vision transformers have recently received explosive popularity, but  huge computational cost is still a severe issue.
Revised: Vision transformers have recently received explosive popularity, but the huge computational cost is still a severe issue.
Edit intent: fluency
Original:  However, rough token pruning breaks the spatial structure that is indispensable for local spatial prior.
Revised:  However, token pruning breaks the spatial structure that is indispensable for local spatial prior.
Edit intent: clarity
Original:  To take advantage of both two pipelines, this work seeks to dynamically identify uninformative tokens for each instance and trim down both the training and inference complexity while maintain complete spatial structure and information flow.
Revised:  To take advantage of both two pipelines, this work seeks to dynamically identify uninformative tokens for each instance and trim down both the training and inference complexity while maintaining complete spatial structure and information flow.
Edit intent: fluency
Original:  Then, we propose to update information tokens and placeholder tokens that contribute little to the final prediction with different computational properties , namely, slow-fast updating.
Revised:  Then, we propose to update informative tokens and placeholder tokens that contribute little to the final prediction with different computational properties , namely, slow-fast updating.
Edit intent: fluency
Original:  Then, we propose to update information tokens and placeholder tokens that contribute little to the final prediction with different computational properties , namely, slow-fast updating.
Revised:  Then, we propose to update information tokens and placeholder tokens that contribute little to the final prediction with different computational priorities , namely, slow-fast updating.
Edit intent: clarity
Original:  For example, our method accelerates DeiT-S by over 60\% throughput while only sacrificing 0.4\% top-1 accuracy.
Revised:  For example, our method accelerates DeiTS by over 60\% throughput while only sacrificing 0.4\% top-1 accuracy.
Edit intent: fluency
Original: Vision transformers  have recently received explosive popularity, but the huge computational cost is still a severe issue.
Revised: Vision transformers (ViTs) have recently received explosive popularity, but the huge computational cost is still a severe issue.
Edit intent: clarity
Original:  To achieve this goal, we propose Evo-ViT, a self-motivated slow-fast token evolution method for vision transformers.
Revised:  To achieve this goal, we propose Evo-ViT, a self-motivated slow-fast token evolution approach for vision transformers.
Edit intent: clarity
Original:  Specifically, we conduct unstructured instance-wise token selection by taking advantage of the  global class attention that is unique to vision transformers.
Revised:  Specifically, we conduct unstructured instance-wise token selection by taking advantage of the global class attention that is native to vision transformers.
Edit intent: clarity
Original:  Then, we propose to update  informative tokens and placeholder tokens that contribute little to the final prediction with different computational priorities , namely, slow-fast updating.
Revised:  Then, we propose to update informative tokens and uninformative tokens with different computation paths , namely, slow-fast updating.
Edit intent: clarity
Original:  Thanks to the slow-fast updating mechanism that guarantees information flow and spatial structure , our Evo-ViT can accelerate vanilla transformers of both flat and deep-narrow structures from the very beginning of the training process.
Revised:  Since slow-fast updating mechanism that guarantees information flow and spatial structure , our Evo-ViT can accelerate vanilla transformers of both flat and deep-narrow structures from the very beginning of the training process.
Edit intent: coherence
Original:  Thanks to the slow-fast updating mechanism that guarantees information flow and spatial structure , our Evo-ViT can accelerate vanilla transformers of both flat and deep-narrow structures from the very beginning of the training process.
Revised:  Thanks to the slow-fast updating mechanism maintains the spatial structure and information flow, Evo-ViT can accelerate vanilla transformers of both flat and deep-narrow structures from the very beginning of the training process.
Edit intent: clarity
Original:  Experimental results demonstrate that the proposed method can significantly reduce the computational costs of vision transformers while maintaining comparable performance on image classification .
Revised:  Experimental results demonstrate that our method significantly reduces the computational cost of vision transformers while maintaining comparable performance on image classification .
Edit intent: clarity
Original:  In contrast to existing software packagessuch as HTML2text, jusText and Lynx, Inscriptis (i) provides a layout-aware conversion of HTML that more closely resembles the rendering obtained from standard Web browsers and, therefore, better preserves the spatial arrangement of text elements.
Revised:  In contrast to related software packages, Inscriptis (i) provides a layout-aware conversion of HTML that more closely resembles the rendering obtained from standard Web browsers and, therefore, better preserves the spatial arrangement of text elements.
Edit intent: clarity
Original:  In addition, it (ii) supports annotation rules, i.e., user-provided mappings that allow for annotating the extracted text based on structural and semantic information encoded in HTML tags and attributes used for controlling structure and layout in the original HTML document .
Revised:  In addition, it (ii) supports annotation rules, i.e., user-provided mappings that allow for annotating the extracted text based on structural and semantic information encoded in HTML tags and attributes .
Edit intent: coherence
Original:  These unique features ensure that downstream knowledge extraction components can operate on accurate text representations, and may even use information on the semantics and structure of the original HTML document , if annotation support has been enabled .
Revised:  These unique features ensure that downstream knowledge extraction components can operate on accurate text representations, and may even use information on the semantics and structure of the original HTML document .
Edit intent: coherence
Original:  In this work, sparse coding has been integrated into an existing hierarchical V2 model (Hosoya and Hyv\"arinen, 2015), but replacing the Independent Component Analysis (ICA) with an explicit sparse coding in which the degree of sparsity can be controlled.
Revised:  In this work, sparse coding has been integrated into an existing hierarchical V2 model (Hosoya and Hyv\"arinen, 2015), but replacing its independent component analysis (ICA) with an explicit sparse coding in which the degree of sparsity can be controlled.
Edit intent: clarity
Original:  The contributions of the models were assessed with image classification tasks, including object classification, and tasks associated with mid-level vision including figure-ground classification, texture classification, and angle prediction between two line stimuli.
Revised:  The contributions of the models were assessed with image classification tasks, specifically tasks associated with mid-level vision including figure-ground classification, texture classification, and angle prediction between two line stimuli.
Edit intent: clarity
Original: We propose a numerical scheme based on Random Projection Neural Networks (RPNN) for the solution of  Ordinary Differential Equations (ODEs) with a focus on stiff problems.
Revised: We propose a numerical method based on physics-informed Random Projection Neural Networks (RPNN) for the solution of Ordinary Differential Equations (ODEs) with a focus on stiff problems.
Edit intent: clarity
Original: We propose a numerical scheme based on Random Projection Neural Networks (RPNN) for the solution of  Ordinary Differential Equations (ODEs) with a focus on stiff problems.
Revised: We propose a numerical scheme based on Random Projection Neural Networks for the solution of Ordinary Differential Equations (ODEs) with a focus on stiff problems.
Edit intent: clarity
Original:  In particular, we use an Extreme Learning Machine , a single-hidden layer Feedforward Neural Network with Radial Basis Functions which widths are uniformly distributed random variables, while the values of the weights between the input and the hidden layer are set equal to one.
Revised:  We address an Extreme Learning Machine , a single-hidden layer Feedforward Neural Network with Radial Basis Functions which widths are uniformly distributed random variables, while the values of the weights between the input and the hidden layer are set equal to one.
Edit intent: coherence
Original:  In particular, we use an Extreme Learning Machine , a single-hidden layer Feedforward Neural Network with Radial Basis Functions which widths are uniformly distributed random variables, while the values of the weights between the input and the hidden layer are set equal to one.
Revised:  In particular, we use an Extreme Learning Machine with a single hidden layer with radial basis functions having as widths uniformly distributed random variables, while the values of the weights between the input and the hidden layer are set equal to one.
Edit intent: clarity
Original:  The numerical solution  is obtained by constructing a system of nonlinear algebraic equations, which is solved with respect to the output weights using the Gauss-Newton method .
Revised:  The numerical solution is obtained by constructing a system of nonlinear algebraic equations, which is solved with respect to the output weights by the Gauss-Newton method .
Edit intent: coherence
Original:  We show that our proposed scheme yields good numerical approximation accuracywithout being affected by the stiffness , thus outperforming in same cases the \texttt{ode45} and \texttt{ode15s} functions.
Revised:  We show that the proposed scheme yields good numerical approximation accuracywithout being affected by the stiffness , thus outperforming in same cases the \texttt{ode45} and \texttt{ode15s} functions.
Edit intent: fluency