wanyu/IteraTeR_v2 huggingface dataset:
Original:  Integrating these two methods into one network may provide better learning abilities for general tasks.
Revised:  Integrating them into one network may provide better learning abilities for general tasks.
Edit intent: clarity
Original:   Here, we report a hybrid spiking neural network model that integrates the two approaches by introducing a  meta-local module and a two-phase causality modellingmethod.
Revised:  Here, we report a hybrid spiking neural network model that integrates two learning routes by introducing a meta-local module and a two-phase causality modellingmethod.
Edit intent: clarity
Original:  The hybrid model can meta-learn general local plasticity , and receive top-down supervision information for multi-scale learning.
Revised:  The hybrid model can meta-learn local plasticity and receive top-down supervision information for multi-scale learning.
Edit intent: clarity
Original:  We demonstrate that this hybrid model facilitates learning of many general tasks, including fault-tolerance learning, few-shot learningand multiple-task learning .
Revised:  We demonstrate the advantages of this model in multiple different tasks, including fault-tolerance learning, few-shot learningand multiple-task learning .
Edit intent: clarity
Original:  Furthermore, the implementation of the hybrid model on the Tianjic neuromorphic platform proves that it can fully utilize the advantages of neuromorphic hardware architecture and promote energy-efficient on-chip applications .
Revised:  Furthermore, the Tianjic neuromorphic platform proves that it can fully utilize the advantages of neuromorphic hardware architecture and promote energy-efficient on-chip applications .
Edit intent: coherence
Original: Metabolism plays a central role in cell physiology and provides the cellular machinery for building biomolecules essential for growth.
Revised: Metabolism plays a central role in cell physiology as it provides the molecular machinery for growth.
Edit intent: clarity
Original:  Untangling this complexity is key to understand how cells respond to genetic, environmental  or therapeutic perturbations.
Revised:  Untangling this complexity is key to understand how cells respond to genetic, environmental , or therapeutic perturbations.
Edit intent: fluency
Original:  Here we discuss the roles of two complementary strategies for the analysis of genome-scale metabolic models: constraint-based methods, such as flux balance analysis, and network science.
Revised:  Here we discuss the roles of two complementary strategies for the analysis of genome-scale metabolic models: Flux Balance Analysis (FBA) and network science.
Edit intent: clarity
Original:  Whereas constraint-based methods estimate metabolic flux on the basis of an optimization principle, network-theoretic approaches reveal emergent properties of the global metabolic connectivity.
Revised:  While FBA estimates metabolic flux on the basis of an optimization principle, network-theoretic approaches reveal emergent properties of the global metabolic connectivity.
Edit intent: clarity
Original:  Whereas constraint-based methods estimate metabolic flux on the basis of an optimization principle, network-theoretic approaches reveal emergent properties of the global metabolic connectivity.
Revised:  Whereas constraint-based methods estimate metabolic flux on the basis of an optimisation principle, network approaches reveal emergent properties of the global metabolic connectivity.
Edit intent: clarity
Original:  We highlight how the integration of both approaches promises to deliver insights on the structure and function of metabolic systems with wide-ranging implications in basic discovery science, precision medicine and industrial biotechnology.
Revised:  We highlight how the integration of both approaches promises to deliver insights on the structure and function of metabolic systems with wide-ranging implications in discovery science, precision medicine and industrial biotechnology.
Edit intent: clarity
Original: Metabolism plays a central role in cell physiology as it provides the molecular machinery for growth.
Revised: Metabolism plays a central role in cell physiology because it provides the molecular machinery for growth.
Edit intent: coherence
Original: The explosion of disinformation related to the COVID-19 pandemic has overloaded fact-checkers and media worldwide .
Revised: The explosion of disinformation accompanying the COVID-19 pandemic has overloaded fact-checkers and media worldwide .
Edit intent: clarity
Original:  This paper presents: 1) the currently largest available manually annotated COVID-19 disinformation category dataset;
Revised:  This paper presents: 1) a corpus containing what is currently the largest available set of manually annotated COVID-19 disinformation category dataset;
Edit intent: clarity
Original:  Grid firing patterns are suggested to be eigenvectors of a transition matrix reflecting diffusion across states, allowing simple prediction of future state distributions , by replacing matrix multiplication with elementwise multiplication by eigenvalues .
Revised:  Grid firing patterns are suggested to be eigenvectors of a transition matrix reflecting diffusion across states, that allows efficient prediction of future state distributions , by replacing matrix multiplication with elementwise multiplication by eigenvalues .
Edit intent: clarity
Original:  Grid firing patterns are suggested to be eigenvectors of a transition matrix reflecting diffusion across states, allowing simple prediction of future state distributions , by replacing matrix multiplication with elementwise multiplication by eigenvalues .
Revised:  Grid firing patterns are suggested to be eigenvectors of a transition matrix reflecting diffusion across states, allowing simple prediction of future state distributions .
Edit intent: clarity
Original:  Here we extend this analysisto any translation-invariant directed transition structure ( displacement and diffusion), showing that a single set of eigenvectors supports prediction via displacement-specific eigenvalues.
Revised:  Here we extend this analysisto any translation-invariant directed transition structures (i.e. displacement and diffusion), showing that a single set of eigenvectors supports prediction via displacement-specific eigenvalues.
Edit intent: clarity
Original:  This unifies the prediction framework with traditional models of grid cells firing driven by self-motion to perform path integration .
Revised:  This unifies the prediction framework with traditional models of grid cell firing driven by self-motion to perform path integration .
Edit intent: fluency
Original:  In this paper, we study a problem of computing distance-generalized core decomposition on a network.
Revised:  In this paper, we study the problem of computing distance-generalized core decomposition on a network.
Edit intent: fluency
Original:  We provide a thorough complexity analysis (NP-hardness proofs and pseudo-polynomial algorithms) for different members of these three classes.
Revised:  We provide a thorough complexity analysis (NP-hardness proofs and (pseudo-)polynomial algorithms) for different members of these three classes.
Edit intent: fluency
Original: The effect of an oscillating electric field generated from music on yeast vacuolar proton-ATPase ( V-ATPase ) activity in its native environment is reported.
Revised: The effect of an oscillating electric field generated from music on yeast vacuolar proton-ATPase ( V- ATPase ) activity in its native environment is reported.
Edit intent: fluency
Original:  Good correlation is found between changes in ATPase activity of the enzyme and the combined intensity of certain frequency bands of the Fourier spectra of the music clips.
Revised:  Good correlation is found between changes in the specific activity of the enzyme and the combined intensity of certain frequency bands of the Fourier spectra of the music clips.
Edit intent: clarity
Original: The effect of an oscillating electric field generated from music on yeast vacuolar proton-ATPase ( V- ATPase ) activity in its native environment is reported.
Revised: The effect of an oscillating electric field generated from music on yeast vacuolar proton-ATPase ( V-ATPase ) activity in its native environment is reported.
Edit intent: clarity
Original:  An oscillating electric field is generated from audio clips of music spanning various genres and played to electrodes that are immersed into a dispersion of yeast vacuolar membrane vesicles natively hosting a high concentration of active V- ATPase .
Revised:  An oscillating electric field is generated by electrodes that are immersed into a dispersion of yeast vacuolar membrane vesicles natively hosting a high concentration of active V- ATPase .
Edit intent: clarity
Original:  An oscillating electric field is generated from audio clips of music spanning various genres and played to electrodes that are immersed into a dispersion of yeast vacuolar membrane vesicles natively hosting a high concentration of active V- ATPase .
Revised:  An oscillating electric field is generated from audio clips of music spanning various genres and played to electrodes that are immersed into a dispersion of yeast vacuolar membrane vesicles natively hosting a high concentration of active V-ATPase .
Edit intent: fluency
Original:  Under the given experimental conditions, the top four music clips that most enhance the specific activity of V-ATPase are in the musical key of D, in a perfect agreement with the Fourier analysis of the clips .
Revised:  These results lead to the conclusion that the oscillating electric field interferes with periodic trans-membrane charge motions in the working enzyme .
Edit intent: clarity
Original: Recommender Systems are giving increasing importance to the beyond accuracyquality measures, and reliability is one of the most important in the Collaborative Filtering context .
Revised: Beyond accuracy, quality measures are gaining importance in modern recommender systems, with reliability being one of the most important in the Collaborative Filtering context .
Edit intent: clarity
Original: Recommender Systems are giving increasing importance to the beyond accuracyquality measures, and reliability is one of the most important in the Collaborative Filtering context .
Revised: Recommender Systems are giving increasing importance to the beyond accuracyquality measures, and reliability is one of the most important indicators in the context of collaborative filtering .
Edit intent: clarity
Original:  This paper proposes Bernoulli Matrix Factorization (BeMF),  a matrix factorization model  to provide both prediction values and reliability ones.
Revised:  This paper proposes Bernoulli Matrix Factorization (BeMF), which is a matrix factorization model to provide both prediction values and reliability ones.
Edit intent: coherence
Original:  This paper proposes Bernoulli Matrix Factorization (BeMF),  a matrix factorization model  to provide both prediction values and reliability ones.
Revised:  This paper proposes Bernoulli Matrix Factorization (BeMF), a matrix factorization model , to provide both prediction values and reliability ones.
Edit intent: fluency
Original:  a) it acts on the model-based Collaborative Filtering, rather than in the memory-based one , b) it does not use external methods or extended architectures for providing reliability such as the existing solutions,  c) it is based on a classification-based model , instead of the usual regression-based ones , and d) the matrix factorization formalism is supported by the Bernoulli distribution , to exploit the binary nature of the designed classification model.
Revised:  a) it acts on model-based Collaborative Filtering, rather than in the memory-based one , b) it does not use external methods or extended architectures for providing reliability such as the existing solutions, c) it is based on a classification-based model , instead of the usual regression-based ones , and d) the matrix factorization formalism is supported by the Bernoulli distribution , to exploit the binary nature of the designed classification model.
Edit intent: fluency
Original:  a) it acts on the model-based Collaborative Filtering, rather than in the memory-based one , b) it does not use external methods or extended architectures for providing reliability such as the existing solutions,  c) it is based on a classification-based model , instead of the usual regression-based ones , and d) the matrix factorization formalism is supported by the Bernoulli distribution , to exploit the binary nature of the designed classification model.
Revised:  a) it acts on the model-based collaborative filtering rather than on memory-based one , b) it does not use external methods or extended architectures for providing reliability such as the existing solutions, c) it is based on a classification-based model , instead of the usual regression-based ones , and d) the matrix factorization formalism is supported by the Bernoulli distribution , to exploit the binary nature of the designed classification model.
Edit intent: coherence
Original:  a) it acts on the model-based Collaborative Filtering, rather than in the memory-based one , b) it does not use external methods or extended architectures for providing reliability such as the existing solutions,  c) it is based on a classification-based model , instead of the usual regression-based ones , and d) the matrix factorization formalism is supported by the Bernoulli distribution , to exploit the binary nature of the designed classification model.
Revised:  a) it acts on the model-based Collaborative Filtering, rather than in the memory-based filtering , b) it does not use external methods or extended architectures for providing reliability such as the existing solutions, c) it is based on a classification-based model , instead of the usual regression-based ones , and d) the matrix factorization formalism is supported by the Bernoulli distribution , to exploit the binary nature of the designed classification model.
Edit intent: coherence
Original:  a) it acts on the model-based Collaborative Filtering, rather than in the memory-based one , b) it does not use external methods or extended architectures for providing reliability such as the existing solutions,  c) it is based on a classification-based model , instead of the usual regression-based ones , and d) the matrix factorization formalism is supported by the Bernoulli distribution , to exploit the binary nature of the designed classification model.
Revised:  a) it acts on the model-based Collaborative Filtering, rather than in the memory-based one , b) it does not use external methods or extended architectures , such as existing solutions, c) it is based on a classification-based model , instead of the usual regression-based ones , and d) the matrix factorization formalism is supported by the Bernoulli distribution , to exploit the binary nature of the designed classification model.
Edit intent: clarity
Original:  a) it acts on the model-based Collaborative Filtering, rather than in the memory-based one , b) it does not use external methods or extended architectures for providing reliability such as the existing solutions,  c) it is based on a classification-based model , instead of the usual regression-based ones , and d) the matrix factorization formalism is supported by the Bernoulli distribution , to exploit the binary nature of the designed classification model.
Revised:  a) it acts on the model-based Collaborative Filtering, rather than in the memory-based one , b) it does not use external methods or extended architectures for providing reliability such as the existing solutions, to provide reliability, c) it is based on a classification-based model , instead of the usual regression-based ones , and d) the matrix factorization formalism is supported by the Bernoulli distribution , to exploit the binary nature of the designed classification model.
Edit intent: coherence
Original:  a) it acts on the model-based Collaborative Filtering, rather than in the memory-based one , b) it does not use external methods or extended architectures for providing reliability such as the existing solutions,  c) it is based on a classification-based model , instead of the usual regression-based ones , and d) the matrix factorization formalism is supported by the Bernoulli distribution , to exploit the binary nature of the designed classification model.
Revised:  a) it acts on the model-based Collaborative Filtering, rather than in the memory-based one , b) it does not use external methods or extended architectures for providing reliability such as the existing solutions, c) it is based on a classification-based model instead of traditional regression-based ones , and d) the matrix factorization formalism is supported by the Bernoulli distribution , to exploit the binary nature of the designed classification model.
Edit intent: clarity
Original:  a) it acts on the model-based Collaborative Filtering, rather than in the memory-based one , b) it does not use external methods or extended architectures for providing reliability such as the existing solutions,  c) it is based on a classification-based model , instead of the usual regression-based ones , and d) the matrix factorization formalism is supported by the Bernoulli distribution , to exploit the binary nature of the designed classification model.
Revised:  a) it acts on the model-based Collaborative Filtering, rather than in the memory-based one , b) it does not use external methods or extended architectures for providing reliability such as the existing solutions, c) it is based on a classification-based model , instead of the usual regression-based models , and d) the matrix factorization formalism is supported by the Bernoulli distribution , to exploit the binary nature of the designed classification model.
Edit intent: clarity
Original:  a) it acts on the model-based Collaborative Filtering, rather than in the memory-based one , b) it does not use external methods or extended architectures for providing reliability such as the existing solutions,  c) it is based on a classification-based model , instead of the usual regression-based ones , and d) the matrix factorization formalism is supported by the Bernoulli distribution , to exploit the binary nature of the designed classification model.
Revised:  a) it acts on the model-based Collaborative Filtering, rather than in the memory-based one , b) it does not use external methods or extended architectures for providing reliability such as the existing solutions, c) it is based on a classification-based model , instead of the usual regression-based ones , and d) matrix factorization formalism is supported by the Bernoulli distribution , to exploit the binary nature of the designed classification model.
Edit intent: fluency
Original:  a) it acts on the model-based Collaborative Filtering, rather than in the memory-based one , b) it does not use external methods or extended architectures for providing reliability such as the existing solutions,  c) it is based on a classification-based model , instead of the usual regression-based ones , and d) the matrix factorization formalism is supported by the Bernoulli distribution , to exploit the binary nature of the designed classification model.
Revised:  a) it acts on the model-based Collaborative Filtering, rather than in the memory-based one , b) it does not use external methods or extended architectures for providing reliability such as the existing solutions, c) it is based on a classification-based model , instead of the usual regression-based ones , and d) the matrix factorization formalism is supported by the Bernoulli distribution to exploit the binary nature of the designed classification model.
Edit intent: fluency
Original:  As expected, results show that the more reliable a prediction is, the less liable  to be wrong: recommendation quality has been improved by selecting the most reliable predictions . State-of-the-Art quality measures for reliability have been tested, showing improved results compared to the baseline methods and models.
Revised:  The experimental results show that the more reliable a prediction is, the less liable to be wrong: recommendation quality has been improved by selecting the most reliable predictions . State-of-the-Art quality measures for reliability have been tested, showing improved results compared to the baseline methods and models.
Edit intent: clarity
Original:  As expected, results show that the more reliable a prediction is, the less liable  to be wrong: recommendation quality has been improved by selecting the most reliable predictions . State-of-the-Art quality measures for reliability have been tested, showing improved results compared to the baseline methods and models.
Revised:  As expected, results show that the more reliable a prediction is, the less liable it is to be wrong: recommendation quality has been improved by selecting the most reliable predictions . State-of-the-Art quality measures for reliability have been tested, showing improved results compared to the baseline methods and models.
Edit intent: fluency
Original:  As expected, results show that the more reliable a prediction is, the less liable  to be wrong: recommendation quality has been improved by selecting the most reliable predictions . State-of-the-Art quality measures for reliability have been tested, showing improved results compared to the baseline methods and models.
Revised:  As expected, results show that the more reliable a prediction is, the less liable to be wrong: recommendation quality improves after the most reliable predictions . State-of-the-Art quality measures for reliability have been tested, showing improved results compared to the baseline methods and models.
Edit intent: clarity
Original:  As expected, results show that the more reliable a prediction is, the less liable  to be wrong: recommendation quality has been improved by selecting the most reliable predictions . State-of-the-Art quality measures for reliability have been tested, showing improved results compared to the baseline methods and models.
Revised:  As expected, results show that the more reliable a prediction is, the less liable to be wrong: recommendation quality has been improved by selecting the most reliable predictions are selected. State-of-the-art quality measures for reliability have been tested, showing improved results compared to the baseline methods and models.
Edit intent: clarity
Original: Text editors represent one of the fundamental tools that writers use -- software developers, book authors, mathematicians.
Revised: Text editors represent one of the fundamental tools that writers use - software developers, book authors, mathematicians.
Edit intent: fluency
Original:  A text editor must work as intended in that it allows the users to do their job.
Revised:  A text editor must work as intended in that it should allow the users to do their job.
Edit intent: coherence
Original:  We will start by introducing a small subset of a full-blown text editor -- line editor.
Revised:  We start by introducing a small subset of a full-blown text editor -- line editor.
Edit intent: coherence
Original:  We will start by introducing a small subset of a full-blown text editor -- line editor.
Revised:  We will start by introducing a small subset of a text editor - line editor.
Edit intent: clarity
Original:  Our goal is to obtain factored policies that determine the individual behavior of each agent so that the resulting joint policy is optimal.
Revised:  The goal is to obtain factored policies that determine the individual behavior of each agent so that the resulting joint policy is optimal.
Edit intent: fluency
Original:  Our proposed generator is feed-forward and thus efficient for both training and inference, using a differentiable monotonic interpolation scheme to predict the duration of each input token .
Revised:  Our proposed generator is feed-forward and thus efficient for both training and inference, using a differentiable alignment scheme based on token length prediction .
Edit intent: clarity