wanyu/IteraTeR_v2 huggingface dataset:
Original: This paper provides statistical theory and intuition for Personalized PageRank (PPR), a popular technique that samples a small community from a massive network.
Revised: The paper provides statistical theory and intuition for Personalized PageRank (PPR), a popular technique that samples a small community from a massive network.
Edit intent: fluency
Original: This paper provides statistical theory and intuition for Personalized PageRank (PPR), a popular technique that samples a small community from a massive network.
Revised: This paper provides statistical theory and intuition for personalized PageRank (called "PPR"): a popular technique that samples a small community from a massive network.
Edit intent: clarity
Original:  We study a setting where the entire network is expensive to thoroughly obtain or maintain, but we can start from a seed node of interest and "crawl" the network to find other nodes through their connections.
Revised:  We study a setting where the entire network is expensive to obtain thoroughly or to maintain, but we can start from a seed node of interest and "crawl" the network to find other nodes through their connections.
Edit intent: fluency
Original:  Using the Degree-Corrected Stochastic Blockmodel , we study whether the PPR vector can select nodes that belong to the same block as the seed node.
Revised:  Using the degree-corrected stochastic block model , we study whether the PPR vector can select nodes that belong to the same block as the seed node.
Edit intent: fluency
Original:  We provide a simple and interpretable form for the PPR vector, highlighting its biases towards high degree nodes outside of the target block.
Revised:  We provide a simple and interpretable form for the PPR vector, highlighting its biases towards high degree nodes outside the target block.
Edit intent: fluency
Original:   We illustrate the method with the  Twitter friendship graph and find that (i) the adjusted and unadjusted PPR techniques are complementary approaches, where the adjustment makes the results particularly localized around the seed node and (ii) the bias adjustment greatly benefits from degree regularization.
Revised:  We illustrate the method with the Twitter friendship graph and find that (i) the adjusted and unadjusted PPR techniques are complementary approaches, where the adjustment makes the results particularly localized around the seed node , and that the bias adjustment greatly benefits from degree regularization.
Edit intent: coherence
Original: We study French-Degroot opinion dynamics in a social network with two polarizing parties.
Revised: We study the French-DeGroot opinion dynamics in a social network with two polarizing parties.
Edit intent: fluency
Original:  This problem generalizes the intensely studied problem of influence maximization.
Edit intent: coherence
Original:  Then, we reduce the problem to a problem of submodular maximization with  submodular knapsack constraint and  additional cardinality constraint , and propose a greedy algorithm with upper bound search to approximate the optimum solution.
Revised:  Then, we reduce the problem to a problem of submodular maximization with a submodular knapsack constraint and additional cardinality constraint , and propose a greedy algorithm with upper bound search to approximate the optimum solution.
Edit intent: fluency
Original:  Then, we reduce the problem to a problem of submodular maximization with  submodular knapsack constraint and  additional cardinality constraint , and propose a greedy algorithm with upper bound search to approximate the optimum solution.
Revised:  Then, we reduce the problem to a problem of submodular maximization with submodular knapsack constraint and an additional cardinality constraint , and propose a greedy algorithm with upper bound search to approximate the optimum solution.
Edit intent: fluency
Original:  Then, we reduce the problem to a problem of submodular maximization with  submodular knapsack constraint and  additional cardinality constraint , and propose a greedy algorithm with upper bound search to approximate the optimum solution.
Revised:  Then, we reduce the problem to a problem of submodular maximization with submodular knapsack constraint and additional cardinality constraint and propose a greedy algorithm with upper bound search to approximate the optimum solution.
Edit intent: fluency
Original:  One major bottleneck for developing automatic depression detection methods lies on the limited data availability.
Revised:  One major bottleneck for developing automatic depression detection methods lies in the limited data availability.
Edit intent: fluency
Original:  This paper proposes DEPA, a self-supervised, Word2Vec like pretrained depression audio embedding method for depression detection.
Revised:  This paper proposes DEPA, a self-supervised, pretrained depression audio embedding method for depression detection.
Edit intent: coherence
Original:  An encoder-decoder network is used to extract DEPA on sparse-data in-domain (DAIC) and large-data out-domain ( switchboard , Alzheimer's) datasets.
Revised:  An encoder-decoder network is used to extract DEPA on in-domain (DAIC) and large-data out-domain ( switchboard , Alzheimer's) datasets.
Edit intent: clarity
Original:  An encoder-decoder network is used to extract DEPA on sparse-data in-domain (DAIC) and large-data out-domain ( switchboard , Alzheimer's) datasets.
Revised:  An encoder-decoder network is used to extract DEPA on sparse-data in-domain (DAIC) and large-data out-domain ( Switchboard , Alzheimer's) datasets.
Edit intent: fluency
Original:  The problem of extending side-channel analysis to Machine Learning Model extraction  is largely unexplored.
Revised:  Expanding side-channel analysis to Machine Learning Model extraction is largely unexplored.
Edit intent: clarity
Original:  The problem of extending side-channel analysis to Machine Learning Model extraction  is largely unexplored.
Revised:  The problem of extending side-channel analysis to Machine Learning Model extraction , however, is largely unexplored.
Edit intent: coherence
Original:  This paper extends the DPA framework to neural-network classifiers.
Revised:  This paper expands the DPA framework to neural-network classifiers.
Edit intent: fluency
Original:  First, it shows DPA attacks on classifiers that can extract the secret model parameters such as weights and biases of a neural network.
Revised:  First, it shows DPA attacks during inference to extract the secret model parameters such as weights and biases of a neural network.
Edit intent: clarity
Original:  Second, it proposes the first countermeasures against these attacks by augmenting masking .
Revised:  Second, it proposes the first countermeasures against these attacks by augmenting masking .
Edit intent: fluency
Original:  Despite its advantages in data privacy-preserving, Federated Learning (FL) still has challenges in heterogeneity across users ' data and UE's characteristics .
Revised:  Despite its advantages in data privacy-preserving, Federated Learning (FL) still has challenges in heterogeneity across UEs ' data and UE's characteristics .
Edit intent: fluency
Original:  We first address the heterogeneous data challenge by proposing a FL algorithm that can bypass the independent and identically distributed (i.i.d.) UEs' data assumption for strongly convex and smooth problems .
Revised:  We first propose a FL algorithm that can bypass the independent and identically distributed (i.i.d.) UEs' data assumption for strongly convex and smooth problems .
Edit intent: clarity
Original:  We first address the heterogeneous data challenge by proposing a FL algorithm that can bypass the independent and identically distributed (i.i.d.) UEs' data assumption for strongly convex and smooth problems .
Revised:  We first address the heterogeneous data challenge by proposing a FL algorithm which can handle the heterogeneous UEs' data assumption for strongly convex and smooth problems .
Edit intent: clarity
Original:  We provide the convergence rate characterizing the trade-off between local computation rounds of UE to update its local model and global communication rounds to update the  global model.
Revised:  We provide the convergence rate characterizing the trade-off between local computation rounds of UE to update its local model and global communication rounds to update the FL global model.
Edit intent: fluency
Original:  However, existing algorithms only managed to embed the networks into Euclidean spaces, although many features of signed networks reported are more suitable for non-Euclidean space.
Revised:  However, existing algorithms only managed to embed the networks into Euclidean spaces, although many features of signed networks are reported more suitable for non-Euclidean space.
Edit intent: fluency
Original:  Besides , previous works also do not consider the hierarchical organization of networks, which is widely existed in real-world networks.
Revised:  Besides , previous works did not consider the hierarchical organization of networks, which is widely existed in real-world networks.
Edit intent: clarity
Original:  Besides , previous works also do not consider the hierarchical organization of networks, which is widely existed in real-world networks.
Revised:  Besides , previous works also do not consider the hierarchical structures of networks, which is widely existed in real-world networks.
Edit intent: clarity
Original:  Besides , previous works also do not consider the hierarchical organization of networks, which is widely existed in real-world networks.
Revised:  Besides , previous works also do not consider the hierarchical organization of networks, which is widely witnessed in real-world networks.
Edit intent: clarity
Original:  In this work, we investigate the problem of whether the hyperbolic space is a better choice to represent signed networks .
Revised:  In this work, we answer an open question that whether the hyperbolic space is a better choice to represent signed networks .
Edit intent: clarity
Original:  Our method embeds signed networks into a Poincar\'e ball , which is a hyperbolic space can be seen as a continuous tree.
Revised:  Our method embeds signed networks into a Poincar\'e ball in a hyperbolic space can be seen as a continuous tree.
Edit intent: clarity
Original:  We study a bipartite Euclidean matching in order to study how incorporating geometric frustration leads to variation in the statistics of the meta distribution of the signal-to-interference ratio compared to these simplified models , comparing with the bipolar or downlink cellular networks studied by Haenggi and others .
Revised:  We study a bipartite Euclidean matching in order to study how incorporating geometric frustration leads to variation in the statistics of the meta distribution , comparing with the bipolar or downlink cellular networks studied by Haenggi and others .
Edit intent: clarity
Original: Generative adversarial networks conditioned on simple textual image descriptions are capable of generating realistic-looking images.
Revised: Generative adversarial networks conditioned on textual image descriptions are capable of generating realistic-looking images.
Edit intent: clarity
Original:  Furthermore, quantitatively evaluating these text-to-image synthesis models is still challenging, as most evaluation metrics only judge image quality but not the conformity between the image and its caption.
Revised:  Furthermore, quantitatively evaluating these text-to-image models is challenging, as most evaluation metrics only judge image quality but not the conformity between the image and its caption.
Edit intent: clarity
Original:  To address the aforementioned challenges we introduce both a new model that explicitly models individual objects within an image and a new evaluation metric called Semantic Object Accuracy (SOA) that specifically evaluates images given an image caption.
Revised:  To address these challenges we introduce both a new model that explicitly models individual objects within an image and a new evaluation metric called Semantic Object Accuracy (SOA) that specifically evaluates images given an image caption.
Edit intent: clarity
Original:  To address the aforementioned challenges we introduce both a new model that explicitly models individual objects within an image and a new evaluation metric called Semantic Object Accuracy (SOA) that specifically evaluates images given an image caption.
Revised:  To address the aforementioned challenges we introduce a new model that explicitly models individual objects within an image and a new evaluation metric called Semantic Object Accuracy (SOA) that specifically evaluates images given an image caption.
Edit intent: clarity
Original:  Our model adds an object pathway to both the generator and the discriminator to explicitly learn features of individual objects.
Edit intent: coherence
Original:  The SOA uses a pre-trained object detector to evaluate if a generated image contains objects that are specifically mentioned in the image caption, e.g. whether an image generated from "a car driving down the street" contains a car.
Revised:  The SOA uses a pre-trained object detector to evaluate if a generated image contains objects that are mentioned in the image caption, e.g. whether an image generated from "a car driving down the street" contains a car.
Edit intent: clarity
Original:  Our evaluation shows that models which explicitly model individual objects outperform models which only model global image characteristics .
Revised:  Our evaluation shows that models which explicitly model objects outperform models which only model global image characteristics .
Edit intent: clarity
Original: Universal probabilistic programming systems (PPSs) provide a powerful and expressive framework for specifying rich and complex probabilistic models.
Revised: Universal probabilistic programming systems (PPSs) provide a powerful framework for specifying rich and complex probabilistic models.
Edit intent: clarity
Original:  However, this expressiveness comes at the cost of substantially complicating the process of drawing inferences from the model.
Revised:  They further attempt to automate the process of drawing inferences from the model.
Edit intent: clarity
Original:  Though general-purpose inference engines have been designed to operate in such settings, they are typically highly inefficient, often relying on proposing from the prior to make transitions .
Revised:  Though general-purpose inference engines have been designed to operate in such settings, they are typically highly inefficient, often relying on proposing from the prior .
Edit intent: clarity
Original:  We show how DCC can be implemented as an automated and general-purpose PPS inference engine , and empirically confirm that it can provide substantial performance improvements over previous approaches .
Revised:  We show how DCC can be implemented as an automated and general-purpose PPS inference engine . We empirically demonstrate substantial performance improvements over previous approaches .
Edit intent: clarity
Original: Universal probabilistic programming systems (PPSs) provide a powerful framework for specifying rich and complex probabilistic models.
Revised: Universal probabilistic programming systems (PPSs) provide a powerful framework for specifying rich probabilistic models.
Edit intent: clarity
Original:  In particular, we show  they produce surprisingly unsatisfactory performance for models where the support may vary between executions, often doing no better than importance sampling from the prior.
Revised:  In particular, we show that they produce surprisingly unsatisfactory performance for models where the support may vary between executions, often doing no better than importance sampling from the prior.
Edit intent: fluency
Original:  In particular, we show  they produce surprisingly unsatisfactory performance for models where the support may vary between executions, often doing no better than importance sampling from the prior.
Revised:  In particular, we show they produce surprisingly unsatisfactory performance for models where the support varies between executions, often doing no better than importance sampling from the prior.
Edit intent: clarity
Original:  To address this, we introduce a new inference framework: Divide, Conquer, and Combine, which remains efficient for such models, and show how it can be implemented as an automated and general-purpose PPS inference engine.
Revised:  To address this, we introduce a new inference framework: Divide, Conquer, and Combine, which remains efficient for such models, and show how it can be implemented as an automated and generic PPS inference engine.
Edit intent: clarity
Original:  This question was already studied in the plane, our contribution is to extend the planar results to higher dimensions .
Revised:  This question was extensively studied in the plane, our contribution is to extend the planar results to higher dimensions .
Edit intent: clarity
Original: MRI signal acquisition with multiple coils in a phased array is nowadays a standard setting .
Revised: MRI signal acquisition with multiple coils in a phased array is nowadays commonplace .
Edit intent: clarity
Original:  This easily implies various heretofore difficult results  in probabilistic combinatorics, e.g. thresholds for perfect hypergraph matchings ( Johansson-Kahn-Vu)and bounded-degree spanning trees (Montgomery)  .
Revised:  This easily implies several heretofore difficult results in probabilistic combinatorics, e.g. thresholds for perfect hypergraph matchings ( Johansson-Kahn-Vu)and bounded-degree spanning trees (Montgomery) .
Edit intent: fluency
Original:  This easily implies various heretofore difficult results  in probabilistic combinatorics, e.g. thresholds for perfect hypergraph matchings ( Johansson-Kahn-Vu)and bounded-degree spanning trees (Montgomery)  .
Revised:  This easily implies various heretofore difficult results in probabilistic combinatorics, including thresholds for perfect hypergraph matchings ( Johansson-Kahn-Vu)and bounded-degree spanning trees (Montgomery) .
Edit intent: clarity
Original:  This easily implies various heretofore difficult results  in probabilistic combinatorics, e.g. thresholds for perfect hypergraph matchings ( Johansson-Kahn-Vu)and bounded-degree spanning trees (Montgomery)  .
Revised:  This easily implies various heretofore difficult results in probabilistic combinatorics, e.g. thresholds for perfect hypergraph matchings ( Johansson--Kahn--Vu), bounded-degree spanning trees (Montgomery) .
Edit intent: fluency
Original:  We also resolve (and vastly extend) one version of the ' random multi-dimensional assignment ' problem of Frieze and Sorkin .
Revised:  We also resolve (and vastly extend) one version of the random multi-dimensional assignment ' problem of Frieze and Sorkin .
Edit intent: fluency
Original:  Our approach builds on recent breakthrough work of Alweiss, Lovett, Wu and Zhang on the Erdo s-Rado 'sunflower'conjecture .
Revised:  Our approach builds on a recent breakthrough of Alweiss, Lovett, Wu and Zhang on the Erdo s-Rado 'sunflower'conjecture .
Edit intent: clarity
Original:  Our approach builds on recent breakthrough work of Alweiss, Lovett, Wu and Zhang on the Erdo s-Rado 'sunflower'conjecture .
Revised:  Our approach builds on recent breakthrough work of Alweiss, Lovett, Wu and Zhang on the Erdo s--Rado 'Sunflower Conjecture' .
Edit intent: fluency
Original:  MEDO views preferences as selective processes influencing the likelihood of particular outcomes , which are more or less consistent with the dynamics underlying those influences .
Revised:  MEDO views preferences as selective pressures influencing the likelihood of particular outcomes , which are more or less consistent with the dynamics underlying those influences .
Edit intent: clarity
Original:  MEDO views preferences as selective processes influencing the likelihood of particular outcomes , which are more or less consistent with the dynamics underlying those influences .
Revised:  MEDO views preferences as selective processes influencing the likelihood of particular outcomes .
Edit intent: clarity
Original:  In this way, MEDO uses economic decision theory to explain goal-oriented behaviors as well as the interacting evolutionary optimization processes from which they emerge. 
Revised:  In this way, MEDO uses economic decision theory to describe goal-oriented behaviors as well as the interacting evolutionary optimization processes from which they emerge. 
Edit intent: clarity
Original: We study the uncertainty quantification for a Boltzmann-Poisson system that models electron transport in semiconductors and the physical collision mechanisms over the charges.
Revised: We study uncertainty quantification for a Boltzmann-Poisson system that models electron transport in semiconductors and the physical collision mechanisms over the charges.
Edit intent: fluency
Original:  We use the stochastic Galerkin method in order to handle the randomness associated to the problem.
Revised:  We use the stochastic Galerkin method in order to handle the randomness associated with the problem.
Edit intent: fluency
Original:  The main uncertainty in the Boltzmann equation is knowing the initial condition for a large number of particles, which is why the problem is formulated in terms of a probability density in phase space.
Revised:  The main uncertainty in the Boltzmann equation concerns the initial conditions for a large number of particles, which is why the problem is formulated in terms of a probability density in phase space.
Edit intent: clarity
Original:  The second source of uncertainty, directly related to the quantum nature of the problem, is the collision operator, as its structure in this semi-classical model comes from the quantum scattering matrices operating on the wave function associated to the electron probability density.
Revised:  The second source of uncertainty, directly related to the quantum nature of the problem, is the collision operator, as its structure in this semiclassical model comes from the quantum scattering matrices operating on the wave function associated to the electron probability density.
Edit intent: clarity
Original:  Then we choose the lattice temperature as a random variable, as it defines the value of the collision operator terms in the case of electron - phonon scattering by being a parameter of the phonon distribution.
Revised:  Then we choose the lattice temperature as a random variable, since it defines the value of the collision operator terms in the case of electron - phonon scattering by being a parameter of the phonon distribution.
Edit intent: fluency
Original:  Then we choose the lattice temperature as a random variable, as it defines the value of the collision operator terms in the case of electron - phonon scattering by being a parameter of the phonon distribution.
Revised:  Then we choose the lattice temperature as a random variable, as it defines the value of the collision operator terms in the case of electron-phonon scattering by being a parameter of the phonon distribution.
Edit intent: fluency
Original:  We present our numerical simulations for this last case .
Revised:  Finally, we present our numerical simulations for this last case .
Edit intent: coherence
Original:  A variety of mechanical forces act on these complexes in the cartilage extracellular matrix, motivating the need for a quantitative description of their structure and mechanical response.
Revised:  A variety of mechanical forces act on these complexes in the cartilage extracellular matrix, motivating the need for a quantitative description which links their structure and mechanical response.
Edit intent: clarity
Original:  Theory of polymer brushes and models of side-chain-induced internal tension show our data are consistent with a polydisperse aggrecan population, attributable to varying degrees of glycosylation  .
Revised:  Theory of polymer brushes and models of side-chain-induced internal tension show our data are consistent with a polydisperse aggrecan population, likely caused by varying degrees of glycosylation .
Edit intent: clarity