wanyu/IteraTeR_v2 huggingface dataset:
Original:  Furthermore, we demonstrate a faster algorithm without explicit blossom shrinking together with a dual linear programming formulation of the equivalent problem like potential maximization for the unconstrained shortest path problem  .
Revised:  Furthermore, we improve our algorithm so that it does not require explicit blossom shrinking together with a dual linear programming formulation of the equivalent problem like potential maximization for the unconstrained shortest path problem .
Edit intent: clarity
Original:  Furthermore, we demonstrate a faster algorithm without explicit blossom shrinking together with a dual linear programming formulation of the equivalent problem like potential maximization for the unconstrained shortest path problem  .
Revised:  Furthermore, we demonstrate a faster algorithm without explicit blossom shrinking together with a dual linear programming formulation of the equivalent problem based on potential maximization for the unconstrained shortest path problem .
Edit intent: clarity
Original:  The algorithm is based on Dijkstra's algorithm for the unconstrained shortest path problem and Edmonds' blossom shrinking technique in matching algorithms , which is inspired by Derigs' faster algorithm (1985) for the parity-constrained shortest path problem via a reduction to weighted matching.
Revised:  The algorithm is based on Dijkstra's algorithm for the unconstrained shortest path problem and Edmonds' blossom shrinking technique in matching algorithms ; this approach is inspired by Derigs' faster algorithm (1985) for the parity-constrained shortest path problem via a reduction to weighted matching.
Edit intent: clarity
Original: In online debates , as in offline ones, individual utterances or arguments support or attack each other, leading to some subset of arguments winning (potentially from different sides of the debate) .
Revised: In online debates individual arguments support or attack each other, leading to some subset of arguments winning (potentially from different sides of the debate) .
Edit intent: clarity
Original:  However, online conversations are much larger in scale than offline ones, with often hundreds of thousands of users weighing in, and so, readers are often forced to sample a subset of the arguments or arguments being put forth.
Revised:  However, in large discussions readers are often forced to sample a subset of the arguments or arguments being put forth.
Edit intent: clarity
Original:  However, online conversations are much larger in scale than offline ones, with often hundreds of thousands of users weighing in, and so, readers are often forced to sample a subset of the arguments or arguments being put forth.
Revised:  However, online conversations are much larger in scale than offline ones, with often hundreds of thousands of users weighing in, and so, readers are often forced to sample a subset of the arguments being put forth.
Edit intent: coherence
Original:  Since such sampling is rarely done in a principled manner, users may not get all the relevant "winning" arguments to get a full picture of the debate from a sample .
Revised:  Since such sampling is rarely done in a principled manner, users may not read all the relevant "winning" arguments to get a full picture of the debate from a sample .
Edit intent: clarity
Original:  Since such sampling is rarely done in a principled manner, users may not get all the relevant "winning" arguments to get a full picture of the debate from a sample .
Revised:  Since such sampling is rarely done in a principled manner, users may not get all the relevant arguments to get a full picture of the debate from a sample .
Edit intent: clarity
Original:  Since such sampling is rarely done in a principled manner, users may not get all the relevant "winning" arguments to get a full picture of the debate from a sample .
Revised:  Since such sampling is rarely done in a principled manner, users may not get all the relevant "winning" arguments to get a full picture of the debate .
Edit intent: clarity
Original:  This paper is interested in answering the question of how users should sample online conversations to selectively favour winning arguments .
Revised:  This paper is interested in answering the question of how users should sample online conversations to selectively favour the currently justified or accepted positions in the debate .
Edit intent: clarity
Original:  We apply techniques from argumentation theory and complex networks to build a model that predicts the probabilities of the normatively winning arguments given their location in idealised online discussions.
Revised:  We apply techniques from argumentation theory and complex networks to build a model that predicts the probabilities of the normatively justified arguments given their location in idealised online discussions.
Edit intent: clarity
Original:  We apply techniques from argumentation theory and complex networks to build a model that predicts the probabilities of the normatively winning arguments given their location in idealised online discussions.
Revised:  We apply techniques from argumentation theory and complex networks to build a model that predicts the probabilities of the normatively winning arguments given their location in online discussions.
Edit intent: clarity
Original:  Online discussions are modeled as reply networks where nodes represent the comments exchanged and directed edges represent replies that can either be supporting or attacking.
Edit intent: coherence
Original:  Our model shows that the proportion of replies that are supporting in the network, the network's in-degree distribution and the locations of unrebutted arguments ("the last words") all determine the behaviour of the probability that a comment is a winning argumentgiven its location.
Revised:  Our model shows that the proportion of replies that are supporting in the network, the network's in-degree distribution and the locations of un-replied comments all determine the behaviour of the probability that a comment is a winning argumentgiven its location.
Edit intent: clarity
Original:  Our model shows that the proportion of replies that are supporting in the network, the network's in-degree distribution and the locations of unrebutted arguments ("the last words") all determine the behaviour of the probability that a comment is a winning argumentgiven its location.
Revised:  Our model shows that the proportion of replies that are supporting in the network, the network's in-degree distribution and the locations of unrebutted arguments ("the last words") all determine the probability that a comment is a winning argumentgiven its location.
Edit intent: clarity
Original:  This is also verified with data scraped from the online debating platform Kialo.
Revised:  This is also verified with data obtained from the online debating platform Kialo.
Edit intent: clarity
Original:  In predicting the locations of the winning arguments in reply networks , we can therefore suggest which arguments a reader should sample and read if he or she would like to grasp the winning opinions in such discussions.
Revised:  By predicting the locations of the winning arguments in reply networks , we can therefore suggest which arguments a reader should sample and read if he or she would like to grasp the winning opinions in such discussions.
Edit intent: fluency
Original:  In predicting the locations of the winning arguments in reply networks , we can therefore suggest which arguments a reader should sample and read if he or she would like to grasp the winning opinions in such discussions.
Revised:  In predicting the locations of the justified arguments in reply networks , we can therefore suggest which arguments a reader should sample and read if he or she would like to grasp the winning opinions in such discussions.
Edit intent: clarity
Original:  In predicting the locations of the winning arguments in reply networks , we can therefore suggest which arguments a reader should sample and read if he or she would like to grasp the winning opinions in such discussions.
Revised:  In predicting the locations of the winning arguments in reply trees , we can therefore suggest which arguments a reader should sample and read if he or she would like to grasp the winning opinions in such discussions.
Edit intent: clarity
Original:  In predicting the locations of the winning arguments in reply networks , we can therefore suggest which arguments a reader should sample and read if he or she would like to grasp the winning opinions in such discussions.
Revised:  In predicting the locations of the winning arguments in reply networks , we can suggest which arguments a reader should sample and read if he or she would like to grasp the winning opinions in such discussions.
Edit intent: coherence
Original:  In predicting the locations of the winning arguments in reply networks , we can therefore suggest which arguments a reader should sample and read if he or she would like to grasp the winning opinions in such discussions.
Revised:  In predicting the locations of the winning arguments in reply networks , we can therefore suggest which arguments readers should sample to grasp the winning opinions in such discussions.
Edit intent: clarity
Original:  In predicting the locations of the winning arguments in reply networks , we can therefore suggest which arguments a reader should sample and read if he or she would like to grasp the winning opinions in such discussions.
Revised:  In predicting the locations of the winning arguments in reply networks , we can therefore suggest which arguments a reader should sample and read if he or she would like to grasp the currently accepted opinions in such discussions.
Edit intent: clarity
Original:  Our models have important implications for the design of future online discussion platforms.
Revised:  Our models have important implications for the design of future online debating platforms.
Edit intent: clarity
Original:  In this work, we use insights from complexity theory to classify phases in interacting many-body systems . Specifically, we demonstrate a "complexity phase diagram" for the Bose-Hubbard model with long-range hopping.
Revised:  In this work, we use insights from complexity theory to classify phases in interacting many-body systems . Specifically, we construct a "complexity phase diagram" for the Bose-Hubbard model with long-range hopping.
Edit intent: clarity
Original:  This shows how the complexity of simulating time evolution varies according to various parameters appearing in the problem, such as the evolution time , the particle density, and  the  degree of locality.
Revised:  This shows how the complexity of simulating time evolution varies according to various parameters appearing in the problem, such as the evolution time , the particle density, and the evolution time and the degree of locality.
Edit intent: coherence
Original:  We find that classification of complexity phases is closely related to upper bounds on the spread of quantum correlations , and protocols to transfer quantum information in a controlled manner .
Revised:  We find that the location of the phase transition is intimately related to upper bounds on the spread of quantum correlations , and protocols to transfer quantum information in a controlled manner .
Edit intent: clarity
Original:  We find that classification of complexity phases is closely related to upper bounds on the spread of quantum correlations , and protocols to transfer quantum information in a controlled manner .
Revised:  We find that classification of complexity phases is closely related to upper bounds on the spread of quantum correlations and protocols to transfer quantum information in a controlled manner .
Edit intent: fluency
Original: The class of regular functions from infinite words to infinite words is characterised by MSO-transducers, streaming \omega-string transducers as well as deterministic two-way transducers with look-ahead.
Revised: Regular functions from infinite words to infinite words is characterised by MSO-transducers, streaming \omega-string transducers as well as deterministic two-way transducers with look-ahead.
Edit intent: clarity
Original:  The benefit from the altruistic behavior of a cooperator is implemented by decreasing the death rate of its direct neighbours .
Revised:  The benefit from the altruistic behavior of a cooperator is implemented by decreasing the death rate of its direct neighbors .
Edit intent: fluency
Original:  Spatial correlations with nearest neighbours only are thus sufficient for sustained cooperation.
Revised:  Spatial correlations with nearest neighbors only are thus sufficient for sustained cooperation.
Edit intent: fluency
Original:  We use variational autoencoders ( VAE ) which explicitly place the most "average" data close to the mean of the Gaussian prior.
Revised:  We use variational autoencoders ( VAEs ) which explicitly place the most "average" data close to the mean of the Gaussian prior.
Edit intent: fluency
Original:  Recently, algorithms based on Direct Coupling Analysis (DCA) pairwise maximum-entropy models have allowed to identify interaction partners among the paralogs of ubiquitous prokaryotic proteins families, starting from sequence data alone.
Revised:  Recently, algorithms based on Direct Coupling Analysis (DCA) pairwise maximum-entropy models have allowed to identify interaction partners among paralogous proteins from sequence data alone.
Edit intent: clarity
Original:  However, interacting proteins often possess similar evolutionary histories , which also gives rise to correlations among their sequences .
Revised:  However, interacting proteins possess similar evolutionary histories , which also gives rise to correlations among their sequences .
Edit intent: clarity
Original:  However, interacting proteins often possess similar evolutionary histories , which also gives rise to correlations among their sequences .
Revised:  However, interacting proteins often possess similar evolutionary histories .
Edit intent: clarity
Original:  To address this question, we employ controlled synthetic data that only involves phylogeny and no interactions or contacts.
Revised:  To address this question, we employ controlled synthetic data that only involve phylogeny and no interactions or contacts.
Edit intent: fluency
Original:  We find that DCA accurately identifies the pairs of synthetic sequences that only share evolutionary history.
Revised:  We find that DCA accurately identifies the pairs of synthetic sequences that share evolutionary history.
Edit intent: clarity
Original:  It performs as well as methods explicitly based on sequence similarity, and even slightly better with large and accurate training sets.
Revised:  It performs as well as phylogenetic methods to this end, and slightly better than them with large and accurate training sets.
Edit intent: clarity
Original:  However, for actually interacting and strongly coevolving proteins, DCA and mutual information outperform sequence similarity .
Revised:  However, for physically interacting and strongly coevolving proteins, DCA and mutual information outperform sequence similarity .
Edit intent: clarity
Original: Gradient decent-based optimization methods underpin the parameter training which results in the impressive results now found when testing neural networks .
Revised: Gradient descent-based optimization methods underpin the parameter training which results in the impressive results now found when testing neural networks .
Edit intent: fluency
Original: Gradient decent-based optimization methods underpin the parameter training which results in the impressive results now found when testing neural networks .
Revised: Gradient decent-based optimization methods underpin the parameter training of neural networks, and hence comprise a significant component in the impressive results now found when testing neural networks .
Edit intent: clarity
Original: Gradient decent-based optimization methods underpin the parameter training which results in the impressive results now found when testing neural networks .
Revised: Gradient decent-based optimization methods underpin the parameter training which results in the impressive test results found in a number of applications .
Edit intent: clarity
Original:  Introducing stochasticity is key to their success in practical problems, and there is some understanding of the role of stochastic gradient decent in this context.
Revised:  Introducing stochasticity is key to their success in practical problems, and there is some understanding of the role of stochastic gradient descent in this context.
Edit intent: fluency
Original:  Momentum modifications of gradient decent such as Polyak's Heavy Ball method (HB) and Nesterov's method of accelerated gradients (NAG), are  widely adopted.
Revised:  Momentum modifications of gradient descent such as Polyak's Heavy Ball method (HB) and Nesterov's method of accelerated gradients (NAG), are widely adopted.
Edit intent: clarity
Original:  Momentum modifications of gradient decent such as Polyak's Heavy Ball method (HB) and Nesterov's method of accelerated gradients (NAG), are  widely adopted.
Revised:  Momentum modifications of gradient decent such as Polyak's Heavy Ball method (HB) and Nesterov's method of accelerated gradients (NAG), are also widely adopted.
Edit intent: coherence
Original:  In this work , our focus is on understanding the role of momentum in the training of neural networks, concentrating on the common situation in which the momentum contribution is fixed at each step of the algorithm ;
Revised:  In this work our focus is on understanding the role of momentum in the training of neural networks, concentrating on the common situation in which the momentum contribution is fixed at each step of the algorithm ;
Edit intent: fluency
Original:  Further we show that the momentum method admits an exponentially attractive invariant manifold on which the dynamic reduces to a gradient flow with respect to a modified loss function , equal to the original one plus a small perturbation .
Revised:  Further we show that the momentum methods admit an exponentially attractive invariant manifold on which the dynamic reduces to a gradient flow with respect to a modified loss function , equal to the original one plus a small perturbation .
Edit intent: fluency
Original:  Further we show that the momentum method admits an exponentially attractive invariant manifold on which the dynamic reduces to a gradient flow with respect to a modified loss function , equal to the original one plus a small perturbation .
Revised:  Further we show that the momentum method admits an exponentially attractive invariant manifold on which the dynamic reduces to a gradient flow with respect to a modified loss function .
Edit intent: coherence
Original:  Crucially, the dependence on dimension is low , which matters for large-scale applications including PCA and low-rank matrix completion, which both admit natural formulations on manifolds.
Revised:  Crucially, the dependence on dimension is low . This matters for large-scale applications including PCA and low-rank matrix completion, which both admit natural formulations on manifolds.
Edit intent: fluency
Original:  The key technical idea is to generalize PRGD with a distinction between two types of gradient steps: ` steps on the manifold ' and ` perturbed steps in a tangent space of the manifold.
Revised:  The key technical idea is to generalize PRGD with a distinction between two types of gradient steps: " steps on the manifold ' and ` perturbed steps in a tangent space of the manifold.
Edit intent: fluency
Original:  The key technical idea is to generalize PRGD with a distinction between two types of gradient steps: ` steps on the manifold ' and ` perturbed steps in a tangent space of the manifold.
Revised:  The key technical idea is to generalize PRGD with a distinction between two types of gradient steps: ` steps on the manifold " and " perturbed steps in a tangent space of the manifold.
Edit intent: fluency
Original:  ' Ultimately, this distinction makes it possible to extend Jin et al.'s analysis seamlessly.
Revised:  " Ultimately, this distinction makes it possible to extend Jin et al.'s analysis seamlessly.
Edit intent: fluency
Original:  Sub-word units are commonly used in speech recognition yet are generated without the use of acoustic context.
Edit intent: coherence
Original:  Furthermore, we empirically validate that the word-level embeddings we learn contain significant acoustic information, making them more suitable for use in speech recognition.
Edit intent: coherence
Original:  Also, we model the prediction of individuals' mental health as another problem type -- that of node classification (NC) in our HIN, evaluating in the process four node features under logistic regression as a proof-of-concept classifier.
Revised:  Also, we model the prediction of individuals' mental health as another problem type - that of node classification (NC) in our HIN, evaluating in the process four node features under logistic regression as a proof-of-concept classifier.
Edit intent: fluency
Original:  Computing the medoid can be solved exactly in O(n^2) time by computing the distances between all pairs of points.
Revised:  It can be determined exactly in O(n^2) time by computing the distances between all pairs of points.
Edit intent: clarity
Original:  Previous work shows that one can significantly reduce the number of distance computations needed by adaptively querying distances.
Revised:  Previous works show that one can significantly reduce the number of distance computations needed by adaptively querying distances.
Edit intent: fluency
Original:  We relate this game theoretic strategy to earlier neural networks playing unsupervised minimax games . (i) GANs can be formulated as a special case of Adversarial Curiosity (  1990) based on a minimax duel between two networks, one generating data through its probabilistic actions, the other predicting consequences thereof.
Revised:  We relate this game theoretic strategy to earlier neural networks playing unsupervised minimax games . (i) Adversarial Curiosity ( 1990) based on a minimax duel between two networks, one generating data through its probabilistic actions, the other predicting consequences thereof.
Edit intent: clarity
Original:  We relate this game theoretic strategy to earlier neural networks playing unsupervised minimax games . (i) GANs can be formulated as a special case of Adversarial Curiosity (  1990) based on a minimax duel between two networks, one generating data through its probabilistic actions, the other predicting consequences thereof.
Revised:  We relate this game theoretic strategy to earlier neural networks playing unsupervised minimax games . (i) GANs can be formulated as a special case of Adversarial Curiosity ( 1990) is based on two such networks. One network learns to probabilistically generate outputs, the other learns to predict effects of the outputs. Each network minimizes the objective function maximized by the other.
Edit intent: clarity
Original: I review unsupervised or self-supervised neural networks playing minimax games in game-theoretic settings . (i) Adversarial Curiosity (AC, 1990) is based on two such networks.
Revised: I review unsupervised or self-supervised neural networks playing minimax games in game-theoretic settings : (i) Adversarial Curiosity (AC, 1990) is based on two such networks.
Edit intent: fluency
Original: I review unsupervised or self-supervised neural networks playing minimax games in game-theoretic settings . (i) Adversarial Curiosity (AC, 1990) is based on two such networks.
Revised: I review unsupervised or self-supervised neural networks playing minimax games in game-theoretic settings . (i) Artificial Curiosity (AC, 1990) is based on two such networks.
Edit intent: clarity
Original:  One network learns to probabilistically generate outputs, the other learns to predict effects of the outputs.
Revised:  One network learns to generate a probability distribution over outputs, the other learns to predict effects of the outputs.
Edit intent: clarity