wanyu/IteraTeR_v2 huggingface dataset:
Original:  In addition, we present detailed analysis of the multi-level IR design and compiler optimization techniques.
Revised:  In addition, we present detailed analysis on the design of multi-level IR design and compiler optimization techniques.
Edit intent: clarity
Original:  This is the first survey paper focusing on the unique design of DL compiler , which we hope can pave the road for future research towards the DL compiler.
Revised:  This is the first survey paper focusing on the design architecture of DL compilers , which we hope can pave the road for future research towards the DL compiler.
Edit intent: clarity
Original:  This is the first survey paper focusing on the unique design of DL compiler , which we hope can pave the road for future research towards the DL compiler.
Revised:  This is the first survey paper focusing on the unique design of DL compiler , which we hope can pave the road for future research towards DL compiler.
Edit intent: fluency
Original:  Further, by applying the new representation and  properties of the weighted core inverse of the matrix we discuss a few new results related to the reverse order law for these inverses.
Revised:  Further, by applying a new representation and properties of the weighted core inverse of the matrix we discuss a few new results related to the reverse order law for these inverses.
Edit intent: fluency
Original:  Further, by applying the new representation and  properties of the weighted core inverse of the matrix we discuss a few new results related to the reverse order law for these inverses.
Revised:  Further, by applying the new representation and using the properties of the weighted core inverse of the matrix we discuss a few new results related to the reverse order law for these inverses.
Edit intent: coherence
Original:  Further, by applying the new representation and  properties of the weighted core inverse of the matrix we discuss a few new results related to the reverse order law for these inverses.
Revised:  Further, by applying the new representation and properties of the weighted core inverse of a matrix, we discuss a few new results related to the reverse order law for these inverses.
Edit intent: fluency
Original:  However, considering the large number of packets that have to be inspected, the question of computational efficiency arises.
Revised:  However, considering the large number of packets that has to be inspected, the question of computational efficiency arises.
Edit intent: fluency
Original:  Experiments with deep residual networks on CIFAR-10 and the massive-scale benchmark, ImageNet, show that our algorithm generalizes as well as backprop while converging sooner due to weight updates that are parallelizable and computationally less demanding.
Revised:  Experiments with deep residual networks on CIFAR-10 and the large-scale benchmark, ImageNet, show that our algorithm generalizes as well as backprop while converging sooner due to weight updates that are parallelizable and computationally less demanding.
Edit intent: fluency
Original:  Backpropagation (backprop) , the workhorse for training these networks, is an inherently sequential process that is difficult to parallelize.
Revised:  Backpropagation , the workhorse for training these networks, is an inherently sequential process that is difficult to parallelize.
Edit intent: clarity
Original:  Experiments with deep residual networks on CIFAR-10 and the large-scale benchmark, ImageNet, show that our algorithm generalizes as well as backprop while converging sooner due to weight updates that are parallelizable and computationally less demanding.
Revised:  Experiments with residual networks on CIFAR-10 and the large-scale benchmark, ImageNet, show that our algorithm generalizes as well as backprop while converging sooner due to weight updates that are parallelizable and computationally less demanding.
Edit intent: clarity
Original:  Experiments with deep residual networks on CIFAR-10 and the large-scale benchmark, ImageNet, show that our algorithm generalizes as well as backprop while converging sooner due to weight updates that are parallelizable and computationally less demanding.
Revised:  Experiments with deep residual networks on CIFAR-10 and the large benchmark, ImageNet, show that our algorithm generalizes as well as backprop while converging sooner due to weight updates that are parallelizable and computationally less demanding.
Edit intent: clarity
Original: In recent years, social media has increasingly become an important platform for competitive campaigns, especially during political elections.
Revised: In recent years, social media has increasingly become an important platform for political campaigns, especially during political elections.
Edit intent: clarity
Original: In recent years, social media has increasingly become an important platform for competitive campaigns, especially during political elections.
Revised: In recent years, social media has increasingly become an important platform for competitive campaigns, especially elections.
Edit intent: clarity
Original:  Here we show that the scope of identity with which people feel resonated is key determinant of socio-cognitive biases in forming polarized and segregated network structure, also known as echo chambers.
Revised:  Here we show that the range of political viewpoints individuals are willing to consider is a key determinant in the formation of polarized networks and the emergence of echo chambers.
Edit intent: clarity
Original:  We also find that winning majority support in public discourse is determined not solely by whose voice is louder but also more subtly by the divergence of ideological positioning between opposing campaigns.
Revised:  We also find that winning majority support in public discourse is determined by both the effort exerted by campaigns and the relative ideological positioning of opposing campaigns.
Edit intent: clarity
Original:  Further integrating our mechanistic model with the Twitter discourse data from the presidential debate in the 2016 election reveals the combined effects of absorbing wavering undecided individuals and increasing campaign effort on the unprecedented rise and fall of support rates to respective presidential candidates .
Revised:  Our results demonstrate how public discourse and political polarization can be modeled as an interactive process of shifting individual opinions, evolving social networks, and political campaigns .
Edit intent: clarity
Original: In many real-world settings, a team of cooperative agents must learn to coordinate their behavior with private observations and communication constraints . Deep multiagent reinforcement learning algorithms (Deep-MARL)  have shown superior performance in these realistic and difficult problems but still suffer from challenges.
Revised: In many real-world tasks, multiple agents must learn to coordinate their behavior with private observations and communication constraints . Deep multiagent reinforcement learning algorithms (Deep-MARL) have shown superior performance in these realistic and difficult problems but still suffer from challenges.
Edit intent: clarity
Original: In many real-world settings, a team of cooperative agents must learn to coordinate their behavior with private observations and communication constraints . Deep multiagent reinforcement learning algorithms (Deep-MARL)  have shown superior performance in these realistic and difficult problems but still suffer from challenges.
Revised: In many real-world settings, a team of cooperative agents must learn to coordinate with each other given their private observations and communication constraints . Deep multiagent reinforcement learning algorithms (Deep-MARL) have shown superior performance in these realistic and difficult problems but still suffer from challenges.
Edit intent: clarity
Original: In many real-world settings, a team of cooperative agents must learn to coordinate their behavior with private observations and communication constraints . Deep multiagent reinforcement learning algorithms (Deep-MARL)  have shown superior performance in these realistic and difficult problems but still suffer from challenges.
Revised: In many real-world settings, a team of cooperative agents must learn to coordinate their behavior with private observations and limited communication ability . Deep multiagent reinforcement learning algorithms (Deep-MARL) have shown superior performance in these realistic and difficult problems but still suffer from challenges.
Edit intent: clarity
Original: In many real-world settings, a team of cooperative agents must learn to coordinate their behavior with private observations and communication constraints . Deep multiagent reinforcement learning algorithms (Deep-MARL)  have shown superior performance in these realistic and difficult problems but still suffer from challenges.
Revised: In many real-world settings, a team of cooperative agents must learn to coordinate their behavior with private observations and communication constraints . Deep multiagent reinforcement learning (Deep-MARL) have shown superior performance in these realistic and difficult problems but still suffer from challenges.
Edit intent: clarity
Original: In many real-world settings, a team of cooperative agents must learn to coordinate their behavior with private observations and communication constraints . Deep multiagent reinforcement learning algorithms (Deep-MARL)  have shown superior performance in these realistic and difficult problems but still suffer from challenges.
Revised: In many real-world settings, a team of cooperative agents must learn to coordinate their behavior with private observations and communication constraints . Deep multiagent reinforcement learning algorithms (Deep-MARL) algorithms have shown superior performance in these realistic and difficult problems but still suffer from challenges.
Edit intent: coherence
Original:   In this paper, for the first time, we theoretically derive a linear decomposing formation from Q_{tot multi-head attention mechanism to approximate each term in the decomposing formula with theoretical explanations.
Revised:  In this paper, we theoretically derive a linear decomposing formation from Q_{tot multi-head attention mechanism to approximate each term in the decomposing formula with theoretical explanations.
Edit intent: coherence
Original:  Experiments show that our method outperforms state-of-the-art MARL methods on the widely adopted StarCraft benchmarks across different scenarios, and attention analysis is also investigated with sights .
Revised:  Experiments show that our method outperforms state-of-the-art MARL methods on the widely adopted StarCraft benchmark across different scenarios, and attention analysis is also investigated with sights .
Edit intent: fluency
Original:  Experiments show that our method outperforms state-of-the-art MARL methods on the widely adopted StarCraft benchmarks across different scenarios, and attention analysis is also investigated with sights .
Revised:  Experiments show that our method outperforms state-of-the-art MARL methods on the widely adopted StarCraft benchmarks across different scenarios, and attention analysis is further conducted with valuable insights .
Edit intent: clarity
Original:  Although epithelial monolayers are often modeled as two-dimensional (2D) elastic surfaces, they distinguish themselves from conventional thin elastic plates in three important ways : the presence of an apical-basal polarity, spatial control and variability of cellular thickness, and their nonequilibrium active nature.
Revised:  Although epithelial monolayers are often modeled as two-dimensional (2D) elastic surfaces, they distinguish themselves from conventional thin elastic plates in three important ways - the presence of an apical-basal polarity, spatial control and variability of cellular thickness, and their nonequilibrium active nature.
Edit intent: fluency
Original:  Although epithelial monolayers are often modeled as two-dimensional (2D) elastic surfaces, they distinguish themselves from conventional thin elastic plates in three important ways : the presence of an apical-basal polarity, spatial control and variability of cellular thickness, and their nonequilibrium active nature.
Revised:  Although epithelial monolayers are often modeled as two-dimensional (2D) elastic surfaces, they distinguish themselves from conventional thin elastic plates in three important ways : the presence of an apical-basal polarity, spatial variability of cellular thickness, and their nonequilibrium active nature.
Edit intent: clarity
Original:  We start from a full three-dimensional (3D)description of the tissue and derive an effective 2D model that captures  both the apical-basal asymmetry and the spatial geometry of the tissue , through the curvature of the apical surface .
Revised:  We start from a full three-dimensional (3D)description of the tissue and derive an effective 2D model that captures , through the curvature of the apical surface, both the apical-basal asymmetry and the spatial geometry of the tissue , through the curvature of the apical surface .
Edit intent: fluency
Original:  By identifying four distinct sources of activity, we find that bulk active stresses arising from actomyosin contractility and growth compete with boundary active tensions due to localized actomyosin cables and lamellipodial activity , to generate the various states spanning the morphospace of a planar epithelium.
Revised:  By identifying four distinct sources of activity, we find that bulk active stresses arising from actomyosin contractility and growth compete with boundary active tensions due to localized actomyosin cables and lamellipodial activity to generate the various states spanning the morphospace of a planar epithelium.
Edit intent: fluency
Original:  Our treatment hence unifies elastic dewetting and 3D shape deformations  of substrate-adhered tissues.
Revised:  Our treatment hence unifies 3D shape deformations of substrate-adhered tissues.
Edit intent: clarity
Original: The basic reproductive number --- R_0 --- is one of the most common and most commonly misapplied numbers in public health.
Revised: The basic reproductive number -- R_0 -- is one of the most common and most commonly misapplied numbers in public health.
Edit intent: fluency
Original:  Nevertheless, estimating R_0 for every transmissible pathogen, emerging or endemic, remains a priority for epidemiologists the world over.
Edit intent: clarity
Original:  Further, we show how this framework is robust in the face of the typically limited amount of data for emerging pathogens.
Revised:  Further, we show the different ways in which this framework can be implemented in the data-scarce reality of emerging pathogens.
Edit intent: clarity
Original:  Taken  together, our work highlights the critical need for contact tracing during emerging infectious disease outbreaks and the need to look beyond R_0 when predicting epidemic size.
Revised:  Taken . Taken together, our work highlights the critical need for contact tracing during emerging infectious disease outbreaks and the need to look beyond R_0 when predicting epidemic size.
Edit intent: fluency
Original:  We distinguish between two types of substructure counting: matching-count and containment-count, and establish mostly negative answers for a wide class of GNN architectures.
Revised:  We distinguish between two types of substructure counting: matching-count and containment-count, and establish mostly negative answers for popular GNN architectures.
Edit intent: clarity
Original:  Specifically, we prove that Message Passing Neural Networks (MPNNs), Weisfeiler-Lehman (WL ) and 2-Invariant Graph Networks (2-IGNs) cannot perform matching-count of substructures consisting of 3 or more nodes, while they can perform containment-count of star-shaped substructures.
Revised:  Specifically, we prove that Message Passing Neural Networks (MPNNs), 2-Weisfeiler-Lehman (2-WL ) and 2-Invariant Graph Networks (2-IGNs) cannot perform matching-count of substructures consisting of 3 or more nodes, while they can perform containment-count of star-shaped substructures.
Edit intent: fluency
Original:  We also provide partial results for k-WL and k-IGNs  . We then conduct experiments that support several of the theoretical results  , and demonstrate that local relational pooling strategies inspired by Murphy et al. (2019) are more effective for substructure counting.
Revised:  We also prove positive results for k-WL and k-IGNs . We then conduct experiments that support several of the theoretical results , and demonstrate that local relational pooling strategies inspired by Murphy et al. (2019) are more effective for substructure counting.
Edit intent: clarity
Original:  We also provide partial results for k-WL and k-IGNs  . We then conduct experiments that support several of the theoretical results  , and demonstrate that local relational pooling strategies inspired by Murphy et al. (2019) are more effective for substructure counting.
Revised:  We also provide partial results for k-WL and k-IGNs . We then conduct experiments that support the theoretical results , and demonstrate that local relational pooling strategies inspired by Murphy et al. (2019) are more effective for substructure counting.
Edit intent: clarity
Original:  In addition,  we prove that WL and 2-IGNs are equivalent in distinguishing non-isomorphic graphs, partly answering an open problem raised in Maron et al. (2019).
Revised:  In addition, we prove that 2-WL and 2-IGNs are equivalent in distinguishing non-isomorphic graphs, partly answering an open problem raised in Maron et al. (2019).
Edit intent: coherence
Original:   We also prove positive results for k-WL and k-IGNs as well as negative results for k-WL with limited number of iterations.
Revised:  We also prove positive results for k-WL and k-IGNs as well as negative results for k-WL with a finite number of iterations.
Edit intent: clarity
Original:  We then conduct experiments that support the theoretical results for MPNNs and 2-IGNs , and demonstrate that local relational pooling strategies inspired by Murphy et al. (2019) are more effective for substructure counting .
Revised:  We then conduct experiments that support the theoretical results for MPNNs and 2-IGNs , and demonstrate that local relational pooling approach with inspirations from Murphy et al. (2019) are more effective for substructure counting .
Edit intent: clarity
Original:  Moreover, motivated by substructure counting , we propose a local relational pooling approach with inspirations from Murphy et al. (2019)  and demonstrate that it is not only effective for substructure counting but also able to achieve competitive performance on real-world tasks.
Revised:  Moreover, motivated by substructure counting and inspired by Murphy et al. (2019) and demonstrate that it is not only effective for substructure counting but also able to achieve competitive performance on real-world tasks.
Edit intent: coherence
Original:  Moreover, motivated by substructure counting , we propose a local relational pooling approach with inspirations from Murphy et al. (2019)  and demonstrate that it is not only effective for substructure counting but also able to achieve competitive performance on real-world tasks.
Revised:  Moreover, motivated by substructure counting , we propose a local relational pooling approach with inspirations from Murphy et al. (2019) and demonstrate that it is not only effective for substructure counting but also able to achieve competitive performance on molecular prediction tasks.
Edit intent: clarity
Original:  We also propose an analog of Van der Waerden's conjecture for HPSD matrices, where the polynomial optimization problem is interpreted as a relaxation of the permanent.
Revised:  We also propose an analog of van der Waerden's conjecture for HPSD matrices, where the polynomial optimization problem is interpreted as a relaxation of the permanent.
Edit intent: fluency
Original: We report results of a comparison of the accuracy of crowdworkers and seven NaturalLanguage Processing (NLP) toolkits in solving two important NLP tasks, named-entity recognition (NER) and entity-level sentiment (ELS) analysis.
Revised: We report results of a comparison of the accuracy of crowdworkers and seven Natural Language Processing (NLP) toolkits in solving two important NLP tasks, named-entity recognition (NER) and entity-level sentiment (ELS) analysis.
Edit intent: fluency
Original:   This paper presents an algorithm called Enhanced Population-Based Training (EPBT) that interleaves the training of a DNN's weights with the metalearning of optimal hyperparameters and loss functions.
Revised:  This paper presents an algorithm called Enhanced Population-Based Training (EPBT) that interleaves the training of a DNN's weights with the metalearning of loss functions.
Edit intent: clarity
Original:  Loss functions use a TaylorGLO parameterization, based on multivariate Taylor expansions , that EPBT can directly optimize.
Revised:  They are parameterized using multivariate Taylor expansions , that EPBT can directly optimize.
Edit intent: clarity
Original:  Loss functions use a TaylorGLO parameterization, based on multivariate Taylor expansions , that EPBT can directly optimize.
Revised:  Loss functions use a TaylorGLO parameterization, based on multivariate Taylor expansions that EPBT can directly optimize.
Edit intent: fluency
Original:   On the CIFAR-10 and SVHN image classification benchmarks, EPBT discovers loss function schedules that enable faster, more accurate learning.
Revised:  On the CIFAR-10 and SVHN image classification benchmarks, EPBT results in faster, more accurate learning.
Edit intent: clarity
Original:  The discovered functions adapt to the training process and serve to regularize the learning task by discouraging overfitting to the labels.
Revised:  The discovered hyperparameters adapt to the training process and serve to regularize the learning task by discouraging overfitting to the labels.
Edit intent: clarity
Original:  EPBT thus demonstrates a promising synergy of simultaneous training and metalearning .
Revised:  EPBT thus demonstrates a practical instantiation of regularization metalearning based on simultaneous training .
Edit intent: clarity
Original:  Suppose P is a causal model on a set V of n observable variables with respect to a given causal graph G with observable distribution P.
Revised:  Suppose P is a causal model on a set of n observable variables with respect to a given causal graph G with observable distribution P.
Edit intent: clarity
Original:  We show that assuming that G has bounded in-degree, bounded c-components  , and that the observational distribution is identifiable and satisfies certain strong positivity condition : 1. Evaluation%DIFDELCMD < ] %%% There is an algorithm that outputs with probability 2/3 an evaluator for a distribution P' that satisfies d_{tv(P_x, P') \leq \epsilon using }  m=O(n\epsilon^{-2}) samples from P and O(mn) time .
Revised:  Assuming that G has bounded in-degree, bounded c-components , and that the observational distribution is identifiable and satisfies certain strong positivity condition : 1. Evaluation%DIFDELCMD < ] %%% There is an algorithm that outputs with probability 2/3 an evaluator for a distribution P' that satisfies d_{tv(P_x, P') \leq \epsilon using } m=O(n\epsilon^{-2}) samples from P and O(mn) time .
Edit intent: coherence