wanyu/IteraTeR_full_sent huggingface dataset:
Original: Complex language modelstrained on huge text corpora have shown unparalleled text generation capabilities, and thanks to transfer learning, are accessible to a greater number. However, despite recent developments, users are not yet able to fully control particular aspects of the text produced. This is why we propose a finetuned OpenAI GPT-2 model for controllable and contextualised text generation specific to novels. By integrating it into a web-service , we would like to enable authors to write and ask for automatic text generation which is consistent with both previous and next paragraphs.
Revised: It is standard procedure these days to solve Information Extraction task by fine-tuning large pre-trained language models. This is not the case for generation task, which relies on a variety of techniques for controlled language generation. In this paper, we describe a system that fine-tunes a natural language generation model for the problem of solving Writer's Block. The fine-tuning changes the conditioning to also include the right context in addition to the left context, as well as an optional list of entities, the size, the genre and a summary of the paragraph that the human author wishes to generate. Our proposed fine-tuning obtains excellent results, even with a small number of epochs and a total cost of USD 150. The system can be accessed as a web-service , we would like to enable authors to write and ask for automatic text generation which is consistent with both previous and next paragraphs.
Edit intent: meaning-changed
Original:  By integrating it into a web-service , we would like to enable authors to write and ask for automatic text generation which is consistent with both previous and next paragraphs. They can specify the genre of their book, the length of the desired text, the entities it should mention and its content via keywords or a short summary . We explore the technical possibilities and limitations around these objectives .
Revised:  By integrating it into a web-service , and all the code is released. A video showcasing the interface and the model is also available .
Edit intent: meaning-changed
Original:  More concretely, we show that the ODE approximation achieves a 2-Wasserstein error of \varepsilon in O\big(d^{2{5}}/\varepsilon^{2{5}}\big) and O\big(d/\varepsilon^{1{3}}\big) steps when Lipschitz continuity is assumed for the Hessian and third derivative of f. By discretizing this ODE using a fourth order splitting method, we  obtain a practical MCMC method that requires just three additional gradient evaluations in each step.
Revised:  More concretely, we show that the ODE approximation achieves a 2-Wasserstein error of \varepsilon in O\big(d^{2{5}}/\varepsilon^{2{5}}\big) and O\big(d/\varepsilon^{1{3}}\big) steps when Lipschitz continuity is assumed for the Hessian and third derivative of f. By discretizing this ODE using a third order Runge-Kutta method, we obtain a practical MCMC method that requires just three additional gradient evaluations in each step.
Edit intent: meaning-changed
Original:  More concretely, we show that the ODE approximation achieves a 2-Wasserstein error of \varepsilon in O\big(d^{2{5}}/\varepsilon^{2{5}}\big) and O\big(d/\varepsilon^{1{3}}\big) steps when Lipschitz continuity is assumed for the Hessian and third derivative of f. By discretizing this ODE using a fourth order splitting method, we  obtain a practical MCMC method that requires just three additional gradient evaluations in each step.
Revised:  More concretely, we show that the ODE approximation achieves a 2-Wasserstein error of \varepsilon in O\big(d^{2{5}}/\varepsilon^{2{5}}\big) and O\big(d/\varepsilon^{1{3}}\big) steps when Lipschitz continuity is assumed for the Hessian and third derivative of f. By discretizing this ODE using a fourth order splitting method, we can obtain a practical MCMC method that requires just three additional gradient evaluations in each step.
Edit intent: fluency
Original:  More concretely, we show that the ODE approximation achieves a 2-Wasserstein error of \varepsilon in O\big(d^{2{5}}/\varepsilon^{2{5}}\big) and O\big(d/\varepsilon^{1{3}}\big) steps when Lipschitz continuity is assumed for the Hessian and third derivative of f. By discretizing this ODE using a fourth order splitting method, we  obtain a practical MCMC method that requires just three additional gradient evaluations in each step.
Revised:  More concretely, we show that the ODE approximation achieves a 2-Wasserstein error of \varepsilon in O\big(d^{2{5}}/\varepsilon^{2{5}}\big) and O\big(d/\varepsilon^{1{3}}\big) steps when Lipschitz continuity is assumed for the Hessian and third derivative of f. By discretizing this ODE using a fourth order splitting method, we obtain a practical MCMC method that uses just two additional gradient evaluations in each step.
Edit intent: meaning-changed
Original:  More concretely, we show that the ODE approximation achieves a 2-Wasserstein error of \varepsilon in O\big(d^{2{5}}/\varepsilon^{2{5}}\big) and O\big(d/\varepsilon^{1{3}}\big) steps when Lipschitz continuity is assumed for the Hessian and third derivative of f. By discretizing this ODE using a fourth order splitting method, we  obtain a practical MCMC method that requires just three additional gradient evaluations in each step.
Revised:  More concretely, we show that the ODE approximation achieves a 2-Wasserstein error of \varepsilon in O\big(d^{2{5}}/\varepsilon^{2{5}}\big) and O\big(d/\varepsilon^{1{3}}\big) steps when Lipschitz continuity is assumed for the Hessian and third derivative of f. By discretizing this ODE using a fourth order splitting method, we obtain a practical MCMC method that requires just three additional gradient evaluations per step.
Edit intent: clarity
Original: Evolutionary game theory assumes that players replicate a highly scored player's strategy through genetic inheritance  , but in terms of cultural learning , it is often difficult to recognize a strategy just by observing the behaviour.
Revised: Evolutionary game theory assumes that players replicate a highly scored player's strategy through genetic inheritance . However, when learning occurs culturally , but in terms of cultural learning , it is often difficult to recognize a strategy just by observing the behaviour.
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Original:  By examining  best-response relations, we argue that players can escape from full defection into a cooperative equilibrium supported by Win-Stay-Lose-Shift in a self-confirming manner, provided that the cost of cooperation is low and the observational learning supplies sufficiently large uncertainty.
Revised:  By examining the best-response relations, we argue that players can escape from full defection into a cooperative equilibrium supported by Win-Stay-Lose-Shift in a self-confirming manner, provided that the cost of cooperation is low and the observational learning supplies sufficiently large uncertainty.
Edit intent: fluency
Original:  Many real networked systems -- especially social ones -- are characterized by clustered substructures representing either collections of all-to-all pair-wise interactions (cliques) and/or group interactions, involving many of their members at once.
Revised:  Many real networked systems are characterized by clustered substructures representing either collections of all-to-all pair-wise interactions (cliques) and/or group interactions, involving many of their members at once.
Edit intent: clarity
Original:  In this work we focus on interaction structures represented as simplicial complexes, in which a group interaction is identified with a face. We present a microscopic discrete-time  model of complex contagion for which a susceptible-infected-susceptible dynamics is considered .
Revised:  In this work we focus on interaction structures represented as simplicial complexes, we present a discrete-time model of complex contagion for which a susceptible-infected-susceptible dynamics is considered .
Edit intent: clarity
Original:  The mathematical tractability of the model allows for the analytical computation of the epidemic threshold, thus extending to structured populations some primary features of the critical properties of mean-field models. Overall, the model is found in remarkable agreement with numerical simulations .
Revised:  The mathematical tractability of the model allows for the analytical computation of the epidemic threshold, thus extending to structured populations some primary features of the critical properties of mean-field model, the possibility of a bi-stable region is extended to structured populations .
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Original: The verified computing with assistance of computers has proved to be a promising approach to investigate the solution existence to nonlinear equation systems. In this paper, the latest progress about the solution verification for the stationary Navier--Stokes equationover a non-convex 3D domain is reported .
Revised: This paper proposes a computer-assisted solution existence verification method for the stationary Navier-Stokes equation over general 3D domain is reported .
Edit intent: clarity
Original:  In this paper, the latest progress about the solution verification for the stationary Navier--Stokes equationover a non-convex 3D domain is reported .
Revised:  In this paper, the latest progress about the solution verification for the stationary Navier--Stokes equationover a non-convex 3D domains. The proposed method verifies that the exact solution as the fixed point of the Newton iteration exists around the approximate solution through rigorous computation and error estimation. The explicit values of quantities required by applying the fixed point theorem are obtained by utilizing newly developed quantitative error estimation for finite element solutions to boundary value problems and eigenvalue problems of the Stokes equation .
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Original:  We started collecting tweets matching vaccine-related keywords (in Italian) on December 20th 2020 using Twitter APIs, capturing the official start of the Italian vaccination campaign (27th December 2020), and at the time of this writing ( 5th January 2020) we collected over 1.3 M tweets, with over 25k tweets shared on a daily basis.
Revised:  We started collecting tweets matching vaccine-related keywords (in Italian) on December 20th 2020 using Twitter APIs, capturing the Italian vaccine rollout (27th December 2020), and at the time of this writing ( 5th January 2020) we collected over 1.3 M tweets, with over 25k tweets shared on a daily basis.
Edit intent: clarity
Original:  We started collecting tweets matching vaccine-related keywords (in Italian) on December 20th 2020 using Twitter APIs, capturing the official start of the Italian vaccination campaign (27th December 2020), and at the time of this writing ( 5th January 2020) we collected over 1.3 M tweets, with over 25k tweets shared on a daily basis.
Revised:  We started collecting tweets matching vaccine-related keywords (in Italian) on December 20th 2020 using Twitter APIs, capturing the official start of the Italian vaccination campaign (27th December 2020), and at the time of this writing ( 13th January 2020) we collected over 1.3 M tweets, with over 25k tweets shared on a daily basis.
Edit intent: meaning-changed
Original:  We started collecting tweets matching vaccine-related keywords (in Italian) on December 20th 2020 using Twitter APIs, capturing the official start of the Italian vaccination campaign (27th December 2020), and at the time of this writing ( 5th January 2020) we collected over 1.3 M tweets, with over 25k tweets shared on a daily basis.
Revised:  We started collecting tweets matching vaccine-related keywords (in Italian) on December 20th 2020 using Twitter APIs, capturing the official start of the Italian vaccination campaign (27th December 2020), and at the time of this writing ( 5th January 2020) we collected over 1.8 M tweets, with over 25k tweets shared on a daily basis.
Edit intent: meaning-changed
Original:  We started collecting tweets matching vaccine-related keywords (in Italian) on December 20th 2020 using Twitter APIs, capturing the official start of the Italian vaccination campaign (27th December 2020), and at the time of this writing ( 5th January 2020) we collected over 1.3 M tweets, with over 25k tweets shared on a daily basis.
Revised:  We started collecting tweets matching vaccine-related keywords (in Italian) on December 20th 2020 using Twitter APIs, capturing the official start of the Italian vaccination campaign (27th December 2020), and at the time of this writing ( 5th January 2020) we collected over 1.3 M tweets, with an average number of 30k tweets shared on a daily basis.
Edit intent: meaning-changed
Original:  We report a consistent amount of low-credibility information shared on Twitter , whose prevalence is  comparable to high-credibility information with a 1:4 ratio in the number of shared tweets .
Revised:  We report a consistent amount of low-credibility information already circulating on Twitter alongside vaccine-related conversations , whose prevalence is comparable to high-credibility information with a 1:4 ratio in the number of shared tweets .
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Original: We monitor online conversations of Italian users around vaccineson Twitter, and we provide public access to the on-going data collectionwhich will run continuously throughout the vaccination campaign taking place in Italy . We started collecting tweets matching vaccine-related keywords (in Italian) on December 20th 2020 using Twitter APIs, capturing the Italian vaccine rollout (27th December 2020), and at the time of this writing (13th January 2020) we collected over 1.8 M tweets, with an average number of 30k tweets shared on a daily basis. We report a consistent amount of low-credibility information already circulating on Twitter alongside vaccine-related conversations, whose prevalence is smaller yet comparable to high-credibility information.
Revised: We present VaccinItaly, a project which monitors Italian online conversations around vaccines, on Twitter and Facebook. We describe the ongoing data collection, which follows the SARS-CoV-2 vaccination campaign roll-out in Italy and we provide public access to the data collected. We show results from a preliminary analysis of the spread of low- and high-credibility information.
Edit intent: meaning-changed
Original:  We report a consistent amount of low-credibility information already circulating on Twitter alongside vaccine-related conversations, whose prevalence is smaller yet comparable to high-credibility information. We believe that our data will allow researchers to understand the interplay between  public discourse on online social media and the evolution of the on-going vaccination campaign against SARS-CoV-2 taking place in Italy .
Revised:  We report a consistent amount of low-credibility information already circulating on Twitter alongside vaccine-related conversations, whose prevalence is smaller yet comparable to high-credibility news shared alongside vaccine-related conversations on both social media platforms. We also investigate the content of most popular YouTube videos and encounter several cases of harmful and misleading content about vaccines. Finally, we geolocate Twitter users who discuss vaccines and correlate their activity with open data statistics on vaccine uptake. We make up-to-date results available to the public through an interactive online dashboard associated with the project. The goal of our project is to gain further understanding of the interplay between public discourse on online social media and the evolution of the on-going vaccination campaign against SARS-CoV-2 taking place in Italy .
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Original:  We believe that our data will allow researchers to understand the interplay between  public discourse on online social media and the evolution of the on-going vaccination campaign against SARS-CoV-2 taking place in Italy .
Revised:  We believe that our data will allow researchers to understand the interplay between the public discourse on online social media and the evolution of the on-going vaccination campaign against SARS-CoV-2 taking place in Italy .
Edit intent: fluency
Original:  Thus, topology and quality of the original mesh are preserved, enabling application of POD-based reduced order modeling techniques, and avoiding the necessity to additional meshing steps  .
Revised:  Thus, topology and quality of the original mesh are preserved, enabling application of POD-based reduced order modeling techniques, and avoiding the necessity to additional meshing steps . Model order reduction is performed coupling POD and Gaussian process regression (GPR) in a data-driven fashion .
Edit intent: meaning-changed
Original: We developed a model and an instrument for stochastic simulations of spreading of COVID-19 and other similar infectious diseases, that takes into account both contact network structures and geographical distribution of population density, detailed up to a level of location of individuals.
Revised: We developed a model and a software package for stochastic simulations of spreading of COVID-19 and other similar infectious diseases, that takes into account both contact network structures and geographical distribution of population density, detailed up to a level of location of individuals.
Edit intent: clarity
Original: We developed a model and an instrument for stochastic simulations of spreading of COVID-19 and other similar infectious diseases, that takes into account both contact network structures and geographical distribution of population density, detailed up to a level of location of individuals.
Revised: We developed a model and an instrument for stochastic simulations of transmission of COVID-19 and other similar infectious diseases, that takes into account both contact network structures and geographical distribution of population density, detailed up to a level of location of individuals.
Edit intent: clarity
Original: We developed a model and an instrument for stochastic simulations of spreading of COVID-19 and other similar infectious diseases, that takes into account both contact network structures and geographical distribution of population density, detailed up to a level of location of individuals.
Revised: We developed a model and an instrument for stochastic simulations of spreading of COVID-19 and other similar infectious diseases, that takes into account contact network structures and geographical distribution of population density, detailed up to a level of location of individuals.
Edit intent: clarity
Original:  This set of instruments (the model, the simulation code, and the optimizer) can be a useful tool for policymakers and epidemic response teams who can use it to forecast epidemic development scenarios in local environments (on the scale from towns to large countries) and design optimal response strategies.
Revised:  This set of instruments (the model, the simulation code, and the optimizer) is a useful tool for policymakers and epidemic response teams who can use it to forecast epidemic development scenarios in local environments (on the scale from towns to large countries) and design optimal response strategies.
Edit intent: clarity
Original: Remote photoplethysmography (rPPG) is a known family of techniques for monitoring blood volume changes from a camera. It may be especially useful for widespread contact-less health monitoring when used to analyze face video from consumer-grade visible-light cameras.
Revised: Remote photoplethysmography (rPPG) is a known family of techniques for monitoring blood volume changes , may be especially useful for widespread contact-less health monitoring when used to analyze face video from consumer-grade visible-light cameras.
Edit intent: fluency
Original:  We found that occlusions from face masks affect face video-based rPPG as the mean absolute error of blood volume estimation is nearly doubled when the face is partially occluded by protective masks. To our knowledge, this paper is the first to analyse the impact of face masks on the accuracy of blood volume pulse estimation and offers several novel elements: (a) two publicly available pulse estimation datasets acquired from 86 unmasked and 61 masked subjects, (b) evaluations of handcrafted algorithms and a 3D convolutional neural network trained on videos of full (unmasked) faces and synthetically generated masks, and (c) data augmentation method (a generator adding a synthetic mask to a face video). Our findings help identify how face masks degrade accuracy of face video analysis, and we discuss paths toward more robust pulse estimation in their presence. The datasets and source codes of all proposed methods are available along with this paper.
Revised:  We found that occlusions from face masks affect face video-based rPPG as the mean absolute error of heart rate estimation by more than 80
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Original:  We illustrate our method on a small universe of 18 ETFs, using four well known and publicly available market variables to construct 10000 market conditions, and show that it performs well out of sample.
Revised:  We illustrate our method on a small universe of 18 ETFs, using three well known and publicly available market variables to construct 10000 market conditions, and show that it performs well out of sample.
Edit intent: meaning-changed
Original:  We illustrate our method on a small universe of 18 ETFs, using four well known and publicly available market variables to construct 10000 market conditions, and show that it performs well out of sample.
Revised:  We illustrate our method on a small universe of 18 ETFs, using four well known and publicly available market variables to construct 1000 market conditions, and show that it performs well out of sample.
Edit intent: meaning-changed
Original:  In this paper, we emit the backpropagation-based recollection hypothesis as follows: weak and fast fading retrograde signals following the post to pre-synaptic backward pathways with highest pre-synaptic weights , mediate explicit cue-based memory recall.
Revised:  In this paper, we emit the backpropagation-based recollection hypothesis as follows: weak and fast fading Action Potentials following the (highest weight) post to pre-synaptic backward pathways with highest pre-synaptic weights , mediate explicit cue-based memory recall.
Edit intent: meaning-changed
Original:  In this paper, we emit the backpropagation-based recollection hypothesis as follows: weak and fast fading retrograde signals following the post to pre-synaptic backward pathways with highest pre-synaptic weights , mediate explicit cue-based memory recall.
Revised:  In this paper, we emit the backpropagation-based recollection hypothesis as follows: weak and fast fading retrograde signals following the post to pre-synaptic backward pathways , mediate explicit cue-based memory recall.
Edit intent: meaning-changed
Original:  These signals originate in highly invariant neurons, which uniquely respond to some specific stimuli , e.g. image of a cat , and travel backwards to reactivate the same populations of neurons that usually uniquely activate in the actual presence of such specific stimuli , thus creating offline an experience that is similar.
Revised:  These signals originate in highly invariant neurons, which uniquely respond to some specific stimuli ( e.g. image of a cat , and travel backwards to reactivate the same populations of neurons that usually uniquely activate in the actual presence of such specific stimuli , thus creating offline an experience that is similar.
Edit intent: fluency