wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We use these three properties to define a pseudospherical drawing of G. Our main result is that, for the complete graph, these three properties are equivalent to the same three properties but with " exactly two crossings"  replaced by "at most two crossings".
Revised:  We use these three properties to define a pseudospherical drawing of G. Our main result is that, for the complete graph, Properties (1)--(3) are equivalent to the same three properties but with " exactly two crossings" replaced by "at most two crossings".
Edit intent: meaning-changed
Original:  We use these three properties to define a pseudospherical drawing of G. Our main result is that, for the complete graph, these three properties are equivalent to the same three properties but with " exactly two crossings"  replaced by "at most two crossings".
Revised:  We use these three properties to define a pseudospherical drawing of G. Our main result is that, for the complete graph, these three properties are equivalent to the same three properties but with " precisely two crossings" replaced by "at most two crossings".
Edit intent: fluency
Original:  We use these three properties to define a pseudospherical drawing of G. Our main result is that, for the complete graph, these three properties are equivalent to the same three properties but with " exactly two crossings"  replaced by "at most two crossings".
Revised:  We use these three properties to define a pseudospherical drawing of G. Our main result is that, for the complete graph, these three properties are equivalent to the same three properties but with " exactly two crossings" in (2) replaced by "at most two crossings".
Edit intent: meaning-changed
Original: This article extends the method of synthetic controls to probability measures. The distribution of the synthetic control group is obtained as the optimally weighted barycenter in Wasserstein space of the distributions of the control groups which minimizes the distance to the distribution of the treatment group. It can be applied to settings with disaggregated- or aggregated (functional ) data .
Revised: This article introduces a generalization of the widely-used synthetic controls estimator for evaluating causal effects of policy changes. The proposed method can be applied to settings with disaggregated- or aggregated (functional ) data .
Edit intent: meaning-changed
Original:  It can be applied to settings with disaggregated- or aggregated (functional ) data . The method produces a generically unique counterfactual distribution when the data are continuously distributed. A basic representation of the barycenter provides a computationally efficient implementation via a straightforward tensor-variate regression approach . In addition, identification results are provided that also shed new light on the classical synthetic controls estimator. As an illustration the approach estimates the aggregate effect of the legalization of cannabis on the distribution of household income in Colorado one year after Amendment 64.
Revised:  It can be applied to settings with individual-level- or functional data and provides a geometrically faithful estimate of the entire counterfactual distribution or functional parameter of interest. The technical contribution is the development of a tensor-valued linear regression approach to efficiently compute the estimator in practice. It works as soon as the target distribution is absolutely continuous, but is also applicable in many settings where the target is discrete. The method can be applied to repeated cross-sections or panel data and works with as little as a single pre-treatment period. We introduce novel identification results by showing that any synthetic controls method, classical or our generalization, provides the correct counterfactual for causal models that are essentially affine in the unobserved heterogeneity. We also show that the optimal weights and the whole counterfactual distribution can be consistently estimated from data using this method.
Edit intent: meaning-changed
Original:  While previous approaches have used earlier implementations of BERT to train their Dutch BERT, we used RoBERTa, a robustly optimized BERT approach, to train a Dutch language model called RobBERT.
Revised:  While previous approaches have used earlier implementations of BERT to train a Dutch version of BERT, we used RoBERTa, a robustly optimized BERT approach, to train a Dutch language model called RobBERT.
Edit intent: clarity
Original:  We show that RobBERT improves state of the art results in Dutch-specific language tasks, and also outperforms other existing Dutch BERT-based models in sentiment analysis .
Revised:  We measured its performance on various tasks as well as the importance of the fine-tuning dataset size. We also evaluated the importance of language-specific tokenizers and the model's fairness. We found that RobBERT improves state of the art results in Dutch-specific language tasks, and also outperforms other existing Dutch BERT-based models in sentiment analysis .
Edit intent: meaning-changed
Original:  We provide a new perspective in which clusters of strongly interacting countries are identified by means of a specific distance criterion. We refer to the Estrada communicability distance and the vibrational communicability distance, which turn out to be particularly suitable for catching the inner structure of the economic network.
Revised:  In this framework, a specific role is assumed by short and long-range interactions, and hence by the distance, between countries. Therefore, we identify clusters through a new procedure that exploits Estrada communicability distance and the vibrational communicability distance, which turn out to be particularly suitable for catching the inner structure of the economic network.
Edit intent: clarity
Original:  The methodology is based on a varying distance threshold and it is effective from a computational point of view. It also allows an inspection of the intercluster and intracluster properties of the resulting communities.
Revised:  The proposed methodology aims at finding the distance threshold that maximizes a specific modularity function defined for general metric spaces. Main advantages regard the computational efficiency of the procedure as well as the possibility to inspect intercluster and intracluster properties of the resulting communities.
Edit intent: meaning-changed
Original:  Using fluorescence, electron, and atomic force microscopies and hydrodynamic theory, we show that TPX2 on the microtubule URLanizes per the Rayleigh-Plateau instability, like dew drops patterning a spider web.
Revised:  Using fluorescence, electron, and atomic force microscopies and hydrodynamic theory, we show that TPX2 on a microtubule URLanizes according to the Rayleigh-Plateau instability, like dew drops patterning a spider web.
Edit intent: clarity
Original:  Using fluorescence, electron, and atomic force microscopies and hydrodynamic theory, we show that TPX2 on the microtubule URLanizes per the Rayleigh-Plateau instability, like dew drops patterning a spider web.
Revised:  Using fluorescence, electron, and atomic force microscopies and hydrodynamic theory, we show that TPX2 on the microtubule URLanizes per the Rayleigh-Plateau instability, like dew droplets patterning a spider web.
Edit intent: fluency
Original:  Experiments are done in two kind of data: artificial augmented two-speaker data (TIMIT) and real world recording of two-speaker data (MC-WSJ). Six diffident speaker embedding de-mixing architectures are investigated.
Revised:  Experiments are done in two kind of data: artificial augmented two-speaker data (TIMIT) and real world recording of two-speaker data (MC-WSJ). Six different speaker embedding de-mixing architectures are investigated.
Edit intent: fluency
Original:  Comparing with the speaker identification accuracy on the clean speaker embeddings (98.5\%) , the obtained results show that one of the speaker embedding de-mixing architectures obtain close performance, reaching 96.9\% test accuracy on TIMIT when the SNR between the target speaker and interfering speaker is 5 dB.
Revised:  Comparing with the performance on the clean speaker embeddings (98.5\%) , the obtained results show that one of the speaker embedding de-mixing architectures obtain close performance, reaching 96.9\% test accuracy on TIMIT when the SNR between the target speaker and interfering speaker is 5 dB.
Edit intent: clarity
Original:  Comparing with the speaker identification accuracy on the clean speaker embeddings (98.5\%) , the obtained results show that one of the speaker embedding de-mixing architectures obtain close performance, reaching 96.9\% test accuracy on TIMIT when the SNR between the target speaker and interfering speaker is 5 dB.
Revised:  Comparing with the speaker identification accuracy on the clean speaker embeddings , the obtained results show that one of the speaker embedding de-mixing architectures obtain close performance, reaching 96.9\% test accuracy on TIMIT when the SNR between the target speaker and interfering speaker is 5 dB.
Edit intent: coherence
Original:  Comparing with the speaker identification accuracy on the clean speaker embeddings (98.5\%) , the obtained results show that one of the speaker embedding de-mixing architectures obtain close performance, reaching 96.9\% test accuracy on TIMIT when the SNR between the target speaker and interfering speaker is 5 dB.
Revised:  Comparing with the speaker identification accuracy on the clean speaker embeddings (98.5\%) , the obtained results show that one of the proposed architectures obtained close performance, reaching 96.9\% test accuracy on TIMIT when the SNR between the target speaker and interfering speaker is 5 dB.
Edit intent: clarity
Original:  Comparing with the speaker identification accuracy on the clean speaker embeddings (98.5\%) , the obtained results show that one of the speaker embedding de-mixing architectures obtain close performance, reaching 96.9\% test accuracy on TIMIT when the SNR between the target speaker and interfering speaker is 5 dB. More surprisingly, we found choosing a simple subtraction as the embedding de-mixing function could obtain the second best performance, reaching 95.2\% test accuracy .
Revised:  Comparing with the speaker identification accuracy on the clean speaker embeddings (98.5\%) , the obtained results show that one of the speaker embedding de-mixing architectures obtain close performance, reaching 96.9\% identification accuracy and 0.89 cosine similarity .
Edit intent: meaning-changed
Original:  We also discuss how these errors affect the  similar Friston (2014, URL  The errors call into question the purported interpretation that the internal coordinates of every system with a Markov blanket will appear to engage in Bayesian inference.
Revised:  We also discuss how these errors affect the very similar Friston (2014, URL The errors call into question the purported interpretation that the internal coordinates of every system with a Markov blanket will appear to engage in Bayesian inference.
Edit intent: meaning-changed
Original:  We also discuss how these errors affect the  similar Friston (2014, URL  The errors call into question the purported interpretation that the internal coordinates of every system with a Markov blanket will appear to engage in Bayesian inference.
Revised:  We also discuss how these errors affect the similar Friston (2014, URL and, where appropriate, mention consequences for the newer proposals in Friston (2019, arXiv:1906.10184v1 ) and Parr et al. (2019, URL The errors call into question the purported interpretation that the internal coordinates of every system with a Markov blanket will appear to engage in Bayesian inference.
Edit intent: meaning-changed
Original:  In particular,  we identify three formal errors in the main argument of Friston (2013): The first concerns the rewriting of the equations of motion of systems with Markov blankets which turns out not to be equivalent .
Revised:  In particular, in addition to highlighting the implicit restriction to linear models, we identify three formal errors in the main argument of Friston (2013): The first concerns the rewriting of the equations of motion of systems with Markov blankets which turns out not to be equivalent .
Edit intent: meaning-changed
Original:  In particular,  we identify three formal errors in the main argument of Friston (2013): The first concerns the rewriting of the equations of motion of systems with Markov blankets which turns out not to be equivalent .
Revised:  In particular, we identify three formal errors in the main argument of Friston (2013): The first concerns the rewriting of the equations of motion of systems with Markov blankets which turns out not to be generally correct .
Edit intent: meaning-changed
Original:  The third is the assumption that a non-negative function whose gradient vanishes at some point necessarily has a minimum at that point and that its value at this minimum is zero. However, if the function is constant, which is the case here, its gradient vanishes everywhere, it has no minimum at any point, and its value can be arbitrarily large .
Revised:  The third is the claim that the Free Energy Lemma, when it does hold, implies equality of variational density and ergodic conditional density .
Edit intent: meaning-changed
Original:  The interpretation in terms of Bayesian inference hinges on this point, and we hence conclude that it is unjustified  .
Revised:  The interpretation in terms of Bayesian inference hinges on this point, and we hence conclude that it is unjustified . Additionally, we highlight that the definitions of the Markov blanket in Friston (2013) and Parr et al. (2019) are not equivalent and that the assumptions in Parr et al. (2019) may be too strong to allow for meaningful interpretation .
Edit intent: meaning-changed
Original: We summarize the argument in Friston (2013, URL and highlight some technical errors. We also discuss how these errors affect the very similar Friston (2014, URL and, where appropriate, mention consequences for the newer proposals in Friston (2019, arXiv:1906.10184v1 ) and Parr et al. (2019, URL The errors call into question the purported interpretation that the internal coordinates of every system with a Markov blanketwill appear to engage in Bayesian inference.
Revised: We summarize the argument in Friston (2013, URL and highlight some technical issues. We discuss how these errors affect the very similar Friston (2014, URL and, where appropriate, mention consequences for the newer proposals in Friston (2019, arXiv:1906.10184v1 ) and Parr et al. (2019, URL The errors call into question the purported interpretation that the internal coordinates of every system with a Markov blanketwill appear to engage in Bayesian inference.
Edit intent: clarity
Original:  We also discuss how these errors affect the very similar Friston (2014, URL and, where appropriate, mention consequences for the newer proposals in Friston (2019, arXiv:1906.10184v1 ) and Parr et al. (2019, URL The errors call into question the purported interpretation that the internal coordinates of every system with a Markov blanketwill appear to engage in Bayesian inference.
Revised:  We also discuss how these issues affect related results involving generalised coordinates and, where appropriate, mention consequences for the newer proposals in Friston (2019, arXiv:1906.10184v1 ) and Parr et al. (2019, URL The errors call into question the purported interpretation that the internal coordinates of every system with a Markov blanketwill appear to engage in Bayesian inference.
Edit intent: meaning-changed
Original:  We also discuss how these errors affect the very similar Friston (2014, URL and, where appropriate, mention consequences for the newer proposals in Friston (2019, arXiv:1906.10184v1 ) and Parr et al. (2019, URL The errors call into question the purported interpretation that the internal coordinates of every system with a Markov blanketwill appear to engage in Bayesian inference. In particular, in addition to highlighting the implicit restriction to linear models, we identify three formal errors in the main argument of Friston (2013): The first concerns the rewriting of the  equations of motion of systems with Markov blankets which turns out not to be generally correct .
Revised:  We also discuss how these errors affect the very similar Friston (2014, URL and, where appropriate, mention consequences for and reveal, up to now unacknowledged, differences to newer formulations of the free energy principle. In particular, we reveal that various definitions of the equations of motion of systems with Markov blankets which turns out not to be generally correct .
Edit intent: meaning-changed
Original:  In particular, in addition to highlighting the implicit restriction to linear models, we identify three formal errors in the main argument of Friston (2013): The first concerns the rewriting of the  equations of motion of systems with Markov blankets which turns out not to be generally correct .
Revised:  In particular, in addition to highlighting the implicit restriction to linear models, we identify three formal errors in the main argument of Friston (2013): The first concerns the rewriting of the "Markov blanket" proposed in different works are not equivalent. We show that crucial steps in the free energy argument which involve rewriting the equations of motion of systems with Markov blankets which turns out not to be generally correct .
Edit intent: meaning-changed
Original:  In particular, in addition to highlighting the implicit restriction to linear models, we identify three formal errors in the main argument of Friston (2013): The first concerns the rewriting of the  equations of motion of systems with Markov blankets which turns out not to be generally correct .
Revised:  In particular, in addition to highlighting the implicit restriction to linear models, we identify three formal errors in the main argument of Friston (2013): The first concerns the rewriting of the equations of motion of systems with Markov blankets , are not generally correct without additional (previously unstated) assumptions .
Edit intent: meaning-changed
Original:  We prove  the non-equivalence with a counterexample that exhibits a Markov blanket but does not satisfy the rewritten equations. Our counterexample also invalidates the corresponding (but more general) rewritten equations in the more recent Friston (2019). The second error concerns the Free Energy Lemma itself, which we prove, by counterexample, to be wrongin general. The third is the claim that the Free Energy Lemma , when it does hold, implies equality of variational density and ergodic conditional density.
Revised:  We prove the original free energy lemma, when taken at face value, is wrong. We show further that this free energy lemma , when it does hold, implies equality of variational density and ergodic conditional density.
Edit intent: coherence
Original:  Additionally, we highlight that the definitions of the Markov blanket in Friston (2013) and Parr et al. (2019) are not equivalent and that the assumptions in Parr et al. (2019) may be too strong to allow for meaningful interpretation .
Revised:  Additionally, we highlight that the variational densities presented in newer formulations of the free energy principle and lemma are parameterised by different variables than in older works, leading to a substantially different interpretation of the theory. Note that we only highlight some specific problems in the discussed publications. These problems do not rule out conclusively that the general ideas behind the free energy principle are worth pursuing .
Edit intent: meaning-changed
Original: The sub-fractional Brownian motion (sfBm) could be considered as the intermediate step between the standard Brownian motion (Bm) and the fractional Brownian motion (fBm).
Revised: The sub-fractional Brownian motion is a stochastic process, characterized by non-stationarity in their increments and long-range dependency, considered as an intermediate step between the standard Brownian motion (Bm) and the fractional Brownian motion (fBm).
Edit intent: meaning-changed
Original:  By the way, subfractional diffusion is a candidate to describe stochastic processes with long-range dependence and non-stationarity in their increments .
Revised:  The mixed process, a linear combination between a Bm and an independent sfBm, called mixed sub-fractional Brownian motion (msfBm), keeps the features of the sfBm adding the semi-martingale property for H>3/4, is a suitable candidate to use in price fluctuation modeling, in particular for option pricing .
Edit intent: meaning-changed
Original:  In particular, we extend the results provided by Araneda Axel A. Araneda. The fractional and mixed-fractional CEV model. Journal of Computational and Applied Mathematics, 363:106-123, 2020%DIFDELCMD < ] %%% arriving at the option pricing under the sub-fractional CEVmodel .
Revised:  In particular, we extend the results provided by Araneda %DIFDELCMD < ] %%% arriving at the option pricing under the sub-fractional CEVmodel .
Edit intent: coherence
Original:  Journal of Computational and Applied Mathematics, 363:106-123, 2020%DIFDELCMD < ] %%% arriving at the option pricing under the sub-fractional CEVmodel .
Revised:  Journal of Computational and Applied Mathematics, 363:106-123, 2020%DIFDELCMD < ] %%% arrive at the European Call price under the consider the Constant Elasticity of Variance (CEV) model driven by a mixed sub-fractional Brownian motion .
Edit intent: meaning-changed
Original: The sub-fractional Brownian motion  is a stochastic process, characterized by non-stationarity in their increments and long-range dependency, considered as an intermediate step between the standard Brownian motion (Bm) and the fractional Brownian motion (fBm).
Revised: The sub-fractional Brownian motion (sfBm) is a stochastic process, characterized by non-stationarity in their increments and long-range dependency, considered as an intermediate step between the standard Brownian motion (Bm) and the fractional Brownian motion (fBm).
Edit intent: meaning-changed
Original:  In this note, we arrive at the European Call price under the consider the Constant Elasticity of Variance (CEV) model driven by a mixed sub-fractional Brownian motion  .
Revised:  In this note, we arrive at the European Call price under the consider the Constant Elasticity of Variance (CEV) model driven by a mixed sub-fractional Brownian motion . Empirical tests show the capacity of the proposed model to capture the temporal structure of option prices across different maturities .
Edit intent: meaning-changed
Original:  We have proposed to weigh these dynamic interactions by including the concept of homophily , that is a human-related factor related to the similarity and frequency of interactions on the multiplex network. We have modeled the evolutionary dynamics of sensing behaviours by defining a mathematical framework based on multiplex EGT, quantifying the impact of homophily, network heterogeneity and various social dilemmas.
Revised:  We have proposed to weigh these dynamic interactions by including the concept of homophily and we have modelled the evolutionary dynamics of sensing behaviours by defining a mathematical framework based on multiplex EGT, quantifying the impact of homophily, network heterogeneity and various social dilemmas.
Edit intent: coherence