wanyu/IteraTeR_full_sent huggingface dataset:
Original:  ' Here, we combine the disease dilemma with the compartmental model used for diseases which do not confer immunity . We prove that if the time scale at which individuals receive information is sufficiently rapid compared to the time scale at which the disease spreads, then cooperation emerges, and the disease can be controlled.
Revised:  ' Here, we combine the disease dilemma with the compartmental model used for diseases which do not confer immunity to recovered individuals, we prove that if the time scale at which individuals receive information is sufficiently rapid compared to the time scale at which the disease spreads, then cooperation emerges, and the disease can be controlled.
Edit intent: meaning-changed
Original:  In the classical prisoner's dilemma, evolutionary game dynamics predict that all individuals evolve to 'defect ,' but when the rate of cooperation within a population is directly linked to the rate of spread of the disease, cooperation evolves under certain conditions.
Revised:  In the classical prisoner's dilemma, evolutionary game dynamics predict that all individuals evolve to 'defect .' We have discovered that when the rate of cooperation within a population is directly linked to the rate of spread of the disease, cooperation evolves under certain conditions.
Edit intent: coherence
Original:  For diseases which do not confer immunity to recovered individuals, we prove that if the time scale at which individuals receive information is sufficiently rapid compared to the time scale at which the disease spreads, then cooperation emerges , and the disease can be controlled .
Revised:  For diseases which do not confer immunity to recovered individuals, if the time scale at which individuals receive information is sufficiently rapid compared to the time scale at which the disease spreads, then cooperation emerges , and the disease can be controlled .
Edit intent: coherence
Original:  For diseases which do not confer immunity to recovered individuals, we prove that if the time scale at which individuals receive information is sufficiently rapid compared to the time scale at which the disease spreads, then cooperation emerges , and the disease can be controlled .
Revised:  For diseases which do not confer immunity to recovered individuals, we prove that if the time scale at which individuals receive information is sufficiently rapid compared to the time scale at which the disease spreads, then cooperation emerges . Moreover, in the limit as mitigation measures become increasingly effective, the disease can be controlled .
Edit intent: meaning-changed
Original:  For diseases which do not confer immunity to recovered individuals, we prove that if the time scale at which individuals receive information is sufficiently rapid compared to the time scale at which the disease spreads, then cooperation emerges , and the disease can be controlled . For non-recurring diseases which do confer immunity to recovered individuals, the dynamics predict that all individuals evolve to 'defect. '
Revised:  For diseases which do not confer immunity to recovered individuals, we prove that if the time scale at which individuals receive information is sufficiently rapid compared to the time scale at which the disease spreads, then cooperation emerges , and the disease can be controlled , and the rate of infections tends to zero. Our model is based on theoretical mathematics and therefore unconstrained to any single context. For example, the disease spreading model considered here could also be used to describe social and group dynamics. In this sense, we may have discovered a fundamental and novel mechanism for the evolution of cooperation in a broad sense.
Edit intent: meaning-changed
Original:  We present a new strong baseline for popularity prediction on Instagram, which is both robust and efficient to compute. The approach expands previous work by a comprehensive ablation study of the predictive power of multiple representations of the visual modality and by detailed use of explainability tools .
Revised:  We present a robust, efficient, and explainable baseline for population-based popularity prediction, achieving strong ranking performance. We employ the latest methods in computer vision to maximize the information extracted from the visual modality .
Edit intent: clarity
Original:  We use transfer learning to extract visual semantics  as concepts, scenes, and objects, which allows us to interpret and explain the trained model and predictions. The study is based in one million posts extracted from Instagram. We approach the problem of popularity prediction as a ranking problem, where we predict the log-normalised number of likes. Through our ablation study design, we can suggest models that outperform a previous state-of-the-art black-box method for multi-modal popularity prediction on Instagram .
Revised:  We use transfer learning to extract visual semantics as concepts, scenes, and objects, allowing a new level of scrutiny in an extensive, explainable ablation study. We inform feature selection towards a robust and scalable model, but also illustrate feature interactions, offering new directions for further inquiry in computational social science. Our strongest models inform a lower limit to population-based predictability of popularity on Instagram. The models are immediately applicable to social media monitoring and influencer identification .
Edit intent: coherence
Original:  We also present a second in-place EREW algorithm  that has linear work and span O(\log n \cdot \log \log n), which is within an O(\log\log n) factor of the optimal span.
Revised:  We also present a second in-place EREW algorithm for the partition problem that has linear work and span O(\log n \cdot \log \log n), which is within an O(\log\log n) factor of the optimal span.
Edit intent: meaning-changed
Original:  Our algorithm runs in time O(nnz(A) + n ^{\alpha_p}poly(k/\epsilon)), where \alpha_p = 1 for p\in [1,2) and \alpha_p = 1 + (\omega-1)(1-2/p) for p>2 and \omega \approx 2.374 is the exponent of matrix multiplication.
Revised:  Our algorithm runs in time O(nnz(A) + mn ^{\alpha_p}poly(k/\epsilon)), where \alpha_p = 1 for p\in [1,2) and \alpha_p = 1 + (\omega-1)(1-2/p) for p>2 and \omega \approx 2.374 is the exponent of matrix multiplication.
Edit intent: fluency
Original:  Our algorithm runs in time O(nnz(A) + n ^{\alpha_p}poly(k/\epsilon)), where \alpha_p = 1 for p\in [1,2) and \alpha_p = 1 + (\omega-1)(1-2/p) for p>2 and \omega \approx 2.374 is the exponent of matrix multiplication.
Revised:  Our algorithm runs in time O(nnz(A) + n ^{\alpha_p}poly(k/\epsilon)), where \alpha_p = 0 for p\in [1,2) and \alpha_p = 1 + (\omega-1)(1-2/p) for p>2 and \omega \approx 2.374 is the exponent of matrix multiplication.
Edit intent: meaning-changed
Original:  Our algorithm runs in time O(nnz(A) + n ^{\alpha_p}poly(k/\epsilon)), where \alpha_p = 1 for p\in [1,2) and \alpha_p = 1 + (\omega-1)(1-2/p) for p>2 and \omega \approx 2.374 is the exponent of matrix multiplication.
Revised:  Our algorithm runs in time O(nnz(A) + n ^{\alpha_p}poly(k/\epsilon)), where \alpha_p = 1 for p\in [1,2) and \alpha_p = (\omega-1)(1-2/p) for p>2 and \omega \approx 2.374 is the exponent of matrix multiplication.
Edit intent: clarity
Original:  For the important case of p = 1, which corresponds to the more "robust" nuclear norm, we obtain O(nnz(A) + n \cdot poly(k/\epsilon)) time, which was previously only known for the Frobenius norm (p = 2).
Revised:  For the important case of p = 1, which corresponds to the more "robust" nuclear norm, we obtain O(nnz(A) + m \cdot poly(k/\epsilon)) time, which was previously only known for the Frobenius norm (p = 2).
Edit intent: meaning-changed
Original:  Moreover, since \alpha_p < \omega  for every p, our algorithm has a better dependence on n than that in the singular value decomposition for every p. Crucial to our analysis is the use of dimensionality reduction for Ky-Fan p-norms.
Revised:  Moreover, since \alpha_p < \omega - 1 for every p, our algorithm has a better dependence on n than that in the singular value decomposition for every p. Crucial to our analysis is the use of dimensionality reduction for Ky-Fan p-norms.
Edit intent: meaning-changed
Original:  Motivated by a stylized heterogeneous firms model of international trade with market entry costs, we propose new bias-corrected dynamic binary choice estimators with three sets of high-dimensional fixed effects .
Revised:  Motivated by a stylized heterogeneous firms model of international trade with market entry costs, we consider dynamic three-way fixed effects binary choice models and study the corresponding incidental parameter problem. The standard maximum likelihood estimator is consistent under asymptotics where all panel dimensions grow at a constant rate, but it has an asymptotic bias in its limiting distribution, invalidating inference even in situations where the bias appears to be small. Thus, we propose two different bias-corrected estimators .
Edit intent: meaning-changed
Original:  A reassessment of the most commonly studied determinants of the extensive margin of trade demonstrates that both true state dependence and unobserved heterogeneity contribute strongly to trade persistence and that taking this persistence into account matters significantly in identifying the effects of trade policies on the extensive margin.
Revised:  We apply these estimators in a reassessment of the most commonly studied determinants of the extensive margin of trade demonstrates that both true state dependence and unobserved heterogeneity contribute strongly to trade persistence and that taking this persistence into account matters significantly in identifying the effects of trade policies on the extensive margin.
Edit intent: meaning-changed
Original:  A reassessment of the most commonly studied determinants of the extensive margin of trade demonstrates that both true state dependence and unobserved heterogeneity contribute strongly to trade persistence and that taking this persistence into account matters significantly in identifying the effects of trade policies on the extensive margin.
Revised:  A reassessment of the most commonly studied determinants of the extensive margin of trade . Both true state dependence and unobserved heterogeneity contribute strongly to trade persistence and that taking this persistence into account matters significantly in identifying the effects of trade policies on the extensive margin.
Edit intent: coherence
Original:  A reassessment of the most commonly studied determinants of the extensive margin of trade demonstrates that both true state dependence and unobserved heterogeneity contribute strongly to trade persistence and that taking this persistence into account matters significantly in identifying the effects of trade policies on the extensive margin.
Revised:  A reassessment of the most commonly studied determinants of the extensive margin of trade demonstrates that both true state dependence and unobserved heterogeneity contribute considerably to trade persistence and that taking this persistence into account matters significantly in identifying the effects of trade policies on the extensive margin.
Edit intent: clarity
Original:  A reassessment of the most commonly studied determinants of the extensive margin of trade demonstrates that both true state dependence and unobserved heterogeneity contribute strongly to trade persistence and that taking this persistence into account matters significantly in identifying the effects of trade policies on the extensive margin.
Revised:  A reassessment of the most commonly studied determinants of the extensive margin of trade demonstrates that both true state dependence and unobserved heterogeneity contribute strongly to trade persistence and taking this persistence into account matters significantly in identifying the effects of trade policies on the extensive margin.
Edit intent: fluency
Original:  We demonstrate the effectiveness of our approach by identifying relevant knowledge  from Wikipedia, images, and human-written dialogue utterances, and show that leveraging this retrieved information improves model performance, measured by automatic and human evaluation.
Revised:  We demonstrate the effectiveness of our approach by identifying relevant knowledge required for knowledgeable but engaging dialog from Wikipedia, images, and human-written dialogue utterances, and show that leveraging this retrieved information improves model performance, measured by automatic and human evaluation.
Edit intent: meaning-changed
Original:  We demonstrate the effectiveness of our approach by identifying relevant knowledge  from Wikipedia, images, and human-written dialogue utterances, and show that leveraging this retrieved information improves model performance, measured by automatic and human evaluation.
Revised:  We demonstrate the effectiveness of our approach by identifying relevant knowledge from Wikipedia, images, and human-written dialog utterances, and show that leveraging this retrieved information improves model performance, measured by automatic and human evaluation.
Edit intent: fluency
Original:  In this paper, we use items from psychological scalesand adversarial sample generation to 1) provide a codebook for different types of sexism in theory-driven scales and in social mediatext;
Revised:  In this paper, we outline the different dimensions of sexism by grounding them in their implementation in psychological scales. From the scales, we derive a codebook for different types of sexism in theory-driven scales and in social mediatext;
Edit intent: clarity
Original:  In this paper, we use items from psychological scalesand adversarial sample generation to 1) provide a codebook for different types of sexism in theory-driven scales and in social mediatext; 2) test the performance of different sexism  detection methods across multiple data sets;
Revised:  In this paper, we use items from psychological scalesand adversarial sample generation to 1) provide a codebook for sexism detection methods across multiple data sets;
Edit intent: coherence
Original:  2) test the performance of different sexism  detection methods across multiple data sets;
Revised:  2) test the performance of different sexism in social media, which we use to annotate existing and novel datasets, surfacing their limitations in breadth and validity with respect to the construct of sexism. Next, we leverage the annotated datasets to generate adversarial examples, and test the reliability of sexism detection methods across multiple data sets;
Edit intent: meaning-changed
Original:  2) test the performance of different sexism  detection methods across multiple data sets; 3) provide an overview of strategies employed by humans to remove sexism through minimal changes. Results highlight that current methods seem inadequate in detecting all but the most blatant forms of sexism and do not generalize well to out-of-domain examples.
Revised:  2) test the performance of different sexism detection methods . Results indicate that current machine learning models pick up on a very narrow set of linguistic markers of sexism and do not generalize well to out-of-domain examples.
Edit intent: clarity
Original:   By providing a scale-based codebook for sexism and insights into what makes a statement sexist , we hope to contribute to the development of better and broader models for sexism detection, including reflections on theory-driven approaches to data collection.
Revised:  Yet, including diverse data and adversarial examples at training time results in models that generalize better and that are more robust to artifacts of data collection. By providing a scale-based codebook for sexism and insights into what makes a statement sexist , we hope to contribute to the development of better and broader models for sexism detection, including reflections on theory-driven approaches to data collection.
Edit intent: meaning-changed
Original:   By providing a scale-based codebook for sexism and insights into what makes a statement sexist , we hope to contribute to the development of better and broader models for sexism detection, including reflections on theory-driven approaches to data collection.
Revised:  By providing a scale-based codebook and insights regarding the shortcomings of the state-of-the-art , we hope to contribute to the development of better and broader models for sexism detection, including reflections on theory-driven approaches to data collection.
Edit intent: meaning-changed
Original: Automatic humor detection has interesting use cases in modern technologies, such as chatbots and personal assistants. In this paper, we describe a novel approach for detecting humor in short texts  using BERT sentence embedding.
Revised: Automatic humor detection has interesting use cases in modern technologies, such as chatbots and virtual assistants. Based on the general linguistic structure of humor, in this paper, we describe a novel approach for detecting humor in short texts using BERT sentence embedding.
Edit intent: meaning-changed
Original:  Experimental results show an accuracy of 98.1 percent for the proposed method , 2.1 percent improvement compared to the best CNN and RNN models and 1.1 percentbetter than a fine-tuned BERT model. In addition, the combination of RNN-CNN was not successful in this task compared to the CNN model .
Revised:  Experimental results show that our proposed method can determine humor in short texts with accuracy and an F1-score of 98.2 percent. Our 8-layer model with 110M parameters outperforms all baseline models with a large margin, showing the importance of utilizing linguistic structure in machine learning models .
Edit intent: clarity
Original: This paper describes an app URL realized using Shiny, a easy web applications in R from RStudio Inc, URL It is mainly focused on the analysis of the SARS-Cov2 outbreak in Italy at a provincial (i.e. NUTS-3) level. Our choice to focus mainly on Italian provinces, rather than on Italian regions, has been dictated by the fact that the outbreak of SARS-Cov2 in Italy has been so far not homogeneously spread within regions, with many differences from province to province. According to the characteristics of the virus spread, it seems difficult to think of a propagation behavior at the regional level. Even the timing of initial stages of the infection and its dynamics seem to have been very different even among contiguous provinces, as hot-spots of Covid-19 contagion have been often located in specific areas.
Revised: This paper presents an app developed to analyse the outbreak of the Covid-19 contagion have been often located in specific areas.
Edit intent: clarity
Original:  Even the timing of initial stages of the infection and its dynamics seem to have been very different even among contiguous provinces, as hot-spots of Covid-19 contagion have been often located in specific areas. The rules with which the anti-gen tests were made initially depended on the choices of the provincial local health authorities in Italy. Similarly, hospital admissions in the early stages of the emergency depended on the management and absorption capacity of the local health units. Only data on total cases are currently available at a provincial level. We integrated them deriving the provincial Covid-19 deaths from press reports downloaded from regional authorities .
Revised:  Even the timing of initial stages of the infection and its dynamics seem to have been very different even among contiguous provinces, as hot-spots of Covid-19 infection in Italy considering daily NUTS-3 data on positive cases provided by the Italian Ministry of Health and on deaths derived from Italian regional authorities' official press conferences. Descriptive time series plots are provided together with a map describing the spatial distribution of province cumulative cases and rates. A section on a proposed time-dependent adjusted SIRD model for NUTS-3 regions is also provided in the app .
Edit intent: meaning-changed
Original: This paper presents an app developed to analyse the outbreak of the Covid-19 infection in Italy considering daily NUTS-3 data on positive cases provided by the Italian Ministry of Health and on deaths derived from Italian regional authorities' official press conferences.
Revised: This paper presents an dashboard developed to analyse the outbreak of the Covid-19 infection in Italy considering daily NUTS-3 data on positive cases provided by the Italian Ministry of Health and on deaths derived from Italian regional authorities' official press conferences.
Edit intent: fluency
Original:  Always returning the shorter path compared with the Euclidean approximation yielded by Anya, Spherical Anya is additionally shown to be faster than Anya for the majority of routes, due to the wider field of vision provided by cone projections in Spherical geometry .
Revised:  Always returning the shorter path compared with the Euclidean approximation yielded by Anya, Spherical Anya is shown to be faster than Anya for the majority of routes, due to the wider field of vision provided by cone projections in Spherical geometry .
Edit intent: clarity
Original:  Always returning the shorter path compared with the Euclidean approximation yielded by Anya, Spherical Anya is additionally shown to be faster than Anya for the majority of routes, due to the wider field of vision provided by cone projections in Spherical geometry .
Revised:  Always returning the shorter path compared with the Euclidean approximation yielded by Anya, Spherical Anya is additionally shown to be faster than Anya for the majority of sea routes and slower for Game Maps and Random Maps .
Edit intent: meaning-changed
Original:  We examine the explicit representation and the numerical schemes for the limit case of the fractional order \alpha %DIFDELCMD < \uparrow1%%% , corresponding to the well-known ordinary SIS model, and we analyse the effects of the fractional derivatives by comparing the two models.
Revised:  A comparison with the limit case when the fractional order \alpha %DIFDELCMD < \uparrow1%%% , corresponding to the well-known ordinary SIS model, and we analyse the effects of the fractional derivatives by comparing the two models.
Edit intent: clarity
Original:  We examine the explicit representation and the numerical schemes for the limit case of the fractional order \alpha %DIFDELCMD < \uparrow1%%% , corresponding to the well-known ordinary SIS model, and we analyse the effects of the fractional derivatives by comparing the two models.
Revised:  We examine the explicit representation and the numerical schemes for the limit case of the fractional order \alpha %DIFDELCMD < \uparrow1%%% \uparrow 1 (the SIS model) is also given. We analyse the effects of the fractional derivatives by comparing the two models.
Edit intent: meaning-changed
Original:  We examine the explicit representation and the numerical schemes for the limit case of the fractional order \alpha %DIFDELCMD < \uparrow1%%% , corresponding to the well-known ordinary SIS model, and we analyse the effects of the fractional derivatives by comparing the two models.
Revised:  We examine the explicit representation and the numerical schemes for the limit case of the fractional order \alpha %DIFDELCMD < \uparrow1%%% , corresponding to the well-known ordinary SIS model, and we analyse the effects of the fractional derivatives by comparing the SIS and the \alpha-SIS models.
Edit intent: meaning-changed
Original:  We introduce a " Markov chains of Markov chains " model such that with probably (1-\omega) \in[0,1]  random walkers remain in the same layer and follow (layer-specific) intralayer Markov chains , whereas with probability \omega they move to different layers following (node-specific) interlayer Markov chains .
Revised:  We introduce a novel `` Markov chains of Markov chains " model such that with probably (1-\omega) \in[0,1] random walkers remain in the same layer and follow (layer-specific) intralayer Markov chains , whereas with probability \omega they move to different layers following (node-specific) interlayer Markov chains .
Edit intent: clarity