wanyu/IteraTeR_v2 huggingface dataset:
Original:  Finally, to guide the user in selecting the best variants in ConnectIt for different situations, we provide a detailed analysis of the different strategies in terms of their work and locality .
Revised:  To guide the user in selecting the best variants in ConnectIt for different situations, we provide a detailed analysis of the different strategies in terms of their work and locality .
Edit intent: coherence
Original:  In addition to learning natural language skills, the abstract transformer architecture can generate meaningful moves on a chess board .
Revised:  In addition to learning natural language skills, the abstract transformer architecture can generate meaningful moves on a chessboard .
Edit intent: fluency
Original:  With further fine-tuning, the transformer learns complex game play by training on 2.8 million chess games in Portable Game Notation.
Revised:  With further fine-tuning, the transformer learns complex gameplay by training on 2.8 million chess games in Portable Game Notation.
Edit intent: clarity
Original:  After 30000 training steps, the large transformer called OpenAI's Generative Pre-trained Transformer (GPT-2) optimizes weights for 774 million parameters.
Revised:  After 30000 training steps, OpenAI's Generative Pre-trained Transformer (GPT-2) optimizes weights for 774 million parameters.
Edit intent: clarity
Original:  The chess playing transformer achieves acceptable cross-entropy log loss values (0.2-0.7).
Edit intent: coherence
Original: We study a novel principle for safe and efficient collision avoidance that adopts a mathematically elegant and general framework making as much as possible abstraction of the controlled vehicle's dynamics and of its environment.
Revised: We study a novel principle for safe and efficient collision avoidance that adopts a mathematically elegant and general framework abstracting as much as possible abstraction of the controlled vehicle's dynamics and of its environment.
Edit intent: fluency
Original: We study a novel principle for safe and efficient collision avoidance that adopts a mathematically elegant and general framework making as much as possible abstraction of the controlled vehicle's dynamics and of its environment.
Revised: We study a novel principle for safe and efficient collision avoidance that adopts a mathematically elegant and general framework making as much as possible from the controlled vehicle's dynamics and of its environment.
Edit intent: clarity
Original:  The language allows to describe infinite sets of architectures that share the same pattern, using a set of recursive definitions, similar to the ones used to describe algebraic data types  .
Revised:  The language allows to describe infinite sets of architectures that share the same pattern, using a set of recursive definitions, similar to the ones used to describe algebraic data types or recursive data structures .
Edit intent: clarity
Original:  Further, we give a verification method for the parametric systems described in this language, that relies on the synthesis of structural invariants that allow to prove certain safety properties (mutual exclusion, absence of deadlocks).
Revised:  Further, we give a verification method for the parametric systems described in this language, relying on the automatic synthesis of structural invariants that allow to prove certain safety properties (mutual exclusion, absence of deadlocks).
Edit intent: clarity
Original:  The invariants are defined using the %DIFDELCMD < \kappa%%% \ fragment of the Monadic Second Order (%DIFDELCMD < \mso%%% ) logic, known to be decidable by a classical automata-logic connection.
Revised:  The invariants are defined using the %DIFDELCMD < \kappa%%% \ fragment of the %DIFDELCMD < \mso%%% ) logic, known to be decidable by a classical automata-logic connection.
Edit intent: coherence
Original:  The language allows to describe infinite sets of systems whose coordination between components share the same pattern, using a set of recursive definitions , similar to the ones used to describe algebraic data types or recursive data structures.
Revised:  The language allows to describe infinite sets of systems whose coordination between components share the same pattern, using inductive definitions similar to the ones used to describe algebraic data types or recursive data structures.
Edit intent: clarity
Original:  The invariants are defined using the WSKS fragment of the monadic second order logic, known to be decidable by a classical automata-logic connection.
Revised:  The invariants are defined using the WSkS fragment of the monadic second order logic, known to be decidable by a classical automata-logic connection.
Edit intent: fluency
Original:  This reduces the safety verification problem to checking satisfiability of a WSKS formula.
Revised:  This reduces the safety verification problem to checking satisfiability of a WSkS formula.
Edit intent: fluency
Original: Pyroptosis is an inflammatory mode of cell death that contributes to the cytokine storm associated with severe cases of coronavirus disease 2019 (COVID-19).
Revised: Pyroptosis is an inflammatory mode of cell death that can contribute to the cytokine storm associated with severe cases of coronavirus disease 2019 (COVID-19).
Edit intent: clarity
Original:  Central to pyroptosis induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the formation of the NLRP3 inflammasome .
Revised:  Central to pyroptosis induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) .
Edit intent: clarity
Original:  One such drug, tranilast, is currently being evaluated as a COVID-19 treatment target in a clinical trial.
Edit intent: coherence
Original:  The model is formulated in terms of a system of ordinary differential equations (ODEs) that describe the dynamics of proteins involved in pyroptosis.
Revised:  The model is formulated in terms of a system of ordinary differential equations (ODEs) that describe the dynamics of the biological components involved in pyroptosis.
Edit intent: clarity
Original:  Integrating a technique called gradient tracking in decentralized stochastic gradient descent (DSGD) , we show that the resulting algorithm, GT-DSGD, exhibits several important characteristics towards minimizing a sum of smooth non-convex functions.
Revised:  Integrating a technique called gradient tracking in decentralized stochastic gradient descent , we show that the resulting algorithm, GT-DSGD, exhibits several important characteristics towards minimizing a sum of smooth non-convex functions.
Edit intent: clarity
Original:  Integrating a technique called gradient tracking in decentralized stochastic gradient descent (DSGD) , we show that the resulting algorithm, GT-DSGD, exhibits several important characteristics towards minimizing a sum of smooth non-convex functions.
Revised:  Integrating a technique called gradient tracking in decentralized stochastic gradient descent (DSGD) , we show that the resulting algorithm, GT-DSGD, enjoys certain desirable characteristics towards minimizing a sum of smooth non-convex functions.
Edit intent: clarity
Original:  The main results of this paper can be divided into two categories: (1) For general smooth non-convex functions, we establish a non-asymptotic characterization of GT-DSGD and derive the conditions under which it achieves network-independent performance and matches centralized minibatch SGD.
Revised:  In particular, for general smooth non-convex functions, we establish a non-asymptotic characterization of GT-DSGD and derive the conditions under which it achieves network-independent performance and matches centralized minibatch SGD.
Edit intent: coherence
Original:  The main results of this paper can be divided into two categories: (1) For general smooth non-convex functions, we establish a non-asymptotic characterization of GT-DSGD and derive the conditions under which it achieves network-independent performance and matches centralized minibatch SGD.
Revised:  The main results of this paper can be divided into two categories: (1) For general smooth non-convex functions, we establish non-asymptotic characterization of GT-DSGD and derive the conditions under which it achieves network-independent performance and matches centralized minibatch SGD.
Edit intent: fluency
Original:  The main results of this paper can be divided into two categories: (1) For general smooth non-convex functions, we establish a non-asymptotic characterization of GT-DSGD and derive the conditions under which it achieves network-independent performance and matches centralized minibatch SGD.
Revised:  The main results of this paper can be divided into two categories: (1) For general smooth non-convex functions, we establish a non-asymptotic characterizations of GT-DSGD and derive the conditions under which it achieves network-independent performance and matches centralized minibatch SGD.
Edit intent: fluency
Original:  The main results of this paper can be divided into two categories: (1) For general smooth non-convex functions, we establish a non-asymptotic characterization of GT-DSGD and derive the conditions under which it achieves network-independent performance and matches centralized minibatch SGD.
Revised:  The main results of this paper can be divided into two categories: (1) For general smooth non-convex functions, we establish a non-asymptotic characterization of GT-DSGD and derive the conditions under which it achieves network-independent performances that match the centralized minibatch SGD.
Edit intent: clarity
Original:  In comparison , the existing results suggest that the performance of GT-DSGD is always network-dependent and is therefore strictly worse than that of centralized minibatch SGD. (2) When the global  function additionally satisfies the Polyak-Lojasiewics  condition, we derive the exponential stability range for GT-DSGD under a constant step-size up to a steady-state error .
Revised:  In contrast , the existing results suggest that the performance of GT-DSGD is always network-dependent and is therefore strictly worse than that of centralized minibatch SGD. (2) When the global function additionally satisfies the Polyak-Lojasiewics condition, we derive the exponential stability range for GT-DSGD under a constant step-size up to a steady-state error .
Edit intent: fluency
Original:  In comparison , the existing results suggest that the performance of GT-DSGD is always network-dependent and is therefore strictly worse than that of centralized minibatch SGD. (2) When the global  function additionally satisfies the Polyak-Lojasiewics  condition, we derive the exponential stability range for GT-DSGD under a constant step-size up to a steady-state error .
Revised:  In comparison , the existing results suggest that GT-DSGD is always network-dependent and is therefore strictly worse than that of centralized minibatch SGD. (2) When the global function additionally satisfies the Polyak-Lojasiewics condition, we derive the exponential stability range for GT-DSGD under a constant step-size up to a steady-state error .
Edit intent: clarity
Original:  In comparison , the existing results suggest that the performance of GT-DSGD is always network-dependent and is therefore strictly worse than that of centralized minibatch SGD. (2) When the global  function additionally satisfies the Polyak-Lojasiewics  condition, we derive the exponential stability range for GT-DSGD under a constant step-size up to a steady-state error .
Revised:  In comparison , the existing results suggest that the performance of GT-DSGD is always network-dependent and is therefore strictly worse than the centralized minibatch SGD. (2) When the global function additionally satisfies the Polyak-Lojasiewics condition, we derive the exponential stability range for GT-DSGD under a constant step-size up to a steady-state error .
Edit intent: clarity
Original:  In comparison , the existing results suggest that the performance of GT-DSGD is always network-dependent and is therefore strictly worse than that of centralized minibatch SGD. (2) When the global  function additionally satisfies the Polyak-Lojasiewics  condition, we derive the exponential stability range for GT-DSGD under a constant step-size up to a steady-state error .
Revised:  In comparison , the existing results suggest that the performance of GT-DSGD is always network-dependent and is therefore strictly worse than that of centralized minibatch SGD. When the global function additionally satisfies the Polyak-Lojasiewics condition, we derive the exponential stability range for GT-DSGD under a constant step-size up to a steady-state error .
Edit intent: coherence
Original:  In comparison , the existing results suggest that the performance of GT-DSGD is always network-dependent and is therefore strictly worse than that of centralized minibatch SGD. (2) When the global  function additionally satisfies the Polyak-Lojasiewics  condition, we derive the exponential stability range for GT-DSGD under a constant step-size up to a steady-state error .
Revised:  In comparison , the existing results suggest that the performance of GT-DSGD is always network-dependent and is therefore strictly worse than that of centralized minibatch SGD. (2) When the global function additionally satisfies the Polyak-Lojasiewics (PL) condition, we derive the exponential stability range for GT-DSGD under a constant step-size up to a steady-state error .
Edit intent: clarity
Original:  In comparison , the existing results suggest that the performance of GT-DSGD is always network-dependent and is therefore strictly worse than that of centralized minibatch SGD. (2) When the global  function additionally satisfies the Polyak-Lojasiewics  condition, we derive the exponential stability range for GT-DSGD under a constant step-size up to a steady-state error .
Revised:  In comparison , the existing results suggest that the performance of GT-DSGD is always network-dependent and is therefore strictly worse than that of centralized minibatch SGD. (2) When the global function additionally satisfies the Polyak-Lojasiewics condition, we derive the exponential stability range for GT-DSGD up to a steady-state error .
Edit intent: clarity
Original: The variants of sigmoid functions used in artificial neural networks are  , by definition, limited by vanishing gradients.
Revised: The variants of sigmoid functions used in artificial neural networks are inherently , by definition, limited by vanishing gradients.
Edit intent: clarity
Original:  Defining the sigmoid function to become n-times repeated over a finite input-output map can significantly reduce the presence of this limitation.
Revised:  Defining the sigmoid function to become n-times repeated over a finite input-output mapping can significantly reduce the presence of this limitation.
Edit intent: fluency
Original:  This function mapping as proposed in this paper is the nlogistic-sigmoid function  .
Revised:  Here we propose the nlogistic-sigmoid function .
Edit intent: clarity
Original:  To illustrate the underlying mechanism of our enhanced algorithm, we start by describing a test problem -- the orienteering problem -- used to demonstrate the efficacy of ML-ACO . In this problem, the objective is to find a route that visits a subset of vertices in a graph within a time budget to maximize the collected score.
Revised:  To illustrate the underlying mechanism of our ML-ACO algorithm, we start by describing a test problem -- the orienteering problem -- used to demonstrate the efficacy of ML-ACO . In this problem, the objective is to find a route that visits a subset of vertices in a graph within a time budget to maximize the collected score.
Edit intent: clarity
Original:  To illustrate the underlying mechanism of our enhanced algorithm, we start by describing a test problem -- the orienteering problem -- used to demonstrate the efficacy of ML-ACO . In this problem, the objective is to find a route that visits a subset of vertices in a graph within a time budget to maximize the collected score.
Revised:  To illustrate the underlying mechanism of our enhanced algorithm, we start by describing a test problem , the orienteering problem -- used to demonstrate the efficacy of ML-ACO . In this problem, the objective is to find a route that visits a subset of vertices in a graph within a time budget to maximize the collected score.
Edit intent: fluency
Original:  To illustrate the underlying mechanism of our enhanced algorithm, we start by describing a test problem -- the orienteering problem -- used to demonstrate the efficacy of ML-ACO . In this problem, the objective is to find a route that visits a subset of vertices in a graph within a time budget to maximize the collected score.
Revised:  To illustrate the underlying mechanism of our enhanced algorithm, we start by describing a test problem -- the orienteering problem . In this problem, the objective is to find a route that visits a subset of vertices in a graph within a time budget to maximize the collected score.
Edit intent: clarity
Original:  We have tested several classification models including graph neural networks, logistic regression and support vector machines.
Edit intent: coherence
Original:  Furthermore, we show our algorithm is robust in the sense that (a) its overall performance is not sensitive to any particular classification model , and (b) it generalizes well to large  and real-world problem instances.
Revised:  Furthermore, we show our algorithm is robust in the sense that (a) its overall performance is not sensitive to any particular classification model , and (b) it generalizes well to large and real-world instances.
Edit intent: clarity
Original:  Our approach integrating ML with a meta-heuristic is generic and can be applied to a wide range of combinatorial optimization problems.
Revised:  Our approach integrating ML with a meta-heuristic is generic and can be applied to a wide range of optimization problems.
Edit intent: clarity
Original: In this paper we revisit the approaches to the solution of parity games based on progress measures and show how the notion of quasi dominions can be integrated with those approaches.
Revised: We revisit the approaches to the solution of parity games based on progress measures and show how the notion of quasi dominions can be integrated with those approaches.
Edit intent: coherence
Original:  To accommodate quasi dominions, however, a non trivial refinement of the approach is necessary.
Revised:  To accommodate quasi dominions, however, non trivial refinements of the approach is necessary.
Edit intent: fluency
Original:  To accommodate quasi dominions, however, a non trivial refinement of the approach is necessary.
Revised:  To accommodate quasi dominions, however, a non trivial refinement of the approach are necessary.
Edit intent: fluency
Original:  In particular, we need to introduce a novel notion of measure and a new approach to prove correctness of the resulting solution technique.
Revised:  In particular, we need to introduce a novel notion of measure and a new method to prove correctness of the resulting solution technique.
Edit intent: clarity
Original:  importantly, the oscillators are particularly effective in dense graphs with the Max-Cut being optimal in 7 out of 9 measured graphs with edge density 0.8.
Revised:  importantly, the oscillators are particularly effective in dense graphs with the Max-Cut being optimal in seven out of nine measured graphs with edge density 0.8.
Edit intent: fluency
Original:  Design and implementation of the Sustainable Infrastructure Planning Game provides a prototypical co-design platform that leverages the High Level Architecture co-simulation standard.
Revised:  Design and implementation of the Sustainable Infrastructure Planning Game provides a prototypical co-design artifact that leverages the High Level Architecture co-simulation standard.
Edit intent: clarity
Original:  An observational human subject study conducts 15 co-design sessions to understand how information system features influence design outcomes.
Revised:  An observational study conducts 15 co-design sessions to understand how information system features influence design outcomes.
Edit intent: clarity
Original:  An observational human subject study conducts 15 co-design sessions to understand how information system features influence design outcomes.
Revised:  An observational human subject study conducts 15 co-design sessions to understand underlying dynamics between actors and how co-simulation capabilities influence design outcomes.
Edit intent: clarity
Original:  Results show co-simulation facilitates information exchange critical for discovering and addressing interdependencies across role-specific objectives and frequent data exchangeis correlated with achieving joint objectives, highlighting the role of co-simulation in co-design settings . Conclusions reflect on the opportunities and challenges presented by co-simulation in co-design settings to address engineering problems for infrastructure systems and more broadly .
Revised:  Results show co-simulation facilitates information exchange critical for discovering and addressing interdependencies across role-specific objectives and frequent data exchangeis correlated with achieving joint objectives, highlighting the role of co-simulation in co-design settings . Conclusions reflect on the opportunities and challenges presented by co-simulation in co-design settings to address engineering systems problems .
Edit intent: clarity
Original:  While our proposed Directional Laplacian Centrality may be applied to any graph , we study its effectiveness in identifying important Internet Protocol addresses in network flow data.
Revised:  While our proposed Directional Laplacian Centrality may be applied to any graph , we study its effectiveness in identifying important IP addresses in network flow data.
Edit intent: clarity
Original:  As a corollary, we obtain similar bounds on space and approximation ratio for Vertex Cover and several graph deletion problems.
Revised:  As a corollary, we obtain similar bounds for Vertex Cover and several graph deletion problems.
Edit intent: clarity
Original:  We give a factor-2 approximation algorithm for Vertex Cover which runs in time n^{O(\Delta)} and uses O(\Delta log n) bits of space.
Revised:  We devise a factor-2 approximation algorithm for Vertex Cover which runs in time n^{O(\Delta)} and uses O(\Delta log n) bits of space.
Edit intent: clarity
Original:  We give a factor-2 approximation algorithm for Vertex Cover which runs in time n^{O(\Delta)} and uses O(\Delta log n) bits of space.
Revised:  We give a factor-2 approximation algorithm for Vertex Cover which runs in time n^{O(\Delta)} and use O(\Delta log n) bits of space.
Edit intent: fluency
Original:  We focus on the real-time Hot Search List (HSL), which provides the ranking of the most popular 50 hashtags based on the amount of Sina Weibo searches on them .
Revised:  We focus on the real-time Hot Search List (HSL), which provides the ranking of the most popular 50 hashtags based on the amount of Sina Weibo searches .
Edit intent: clarity
Original:  Then very rapidly a situation was reached , where the participation of the COVID-related hashtags occupied 30-70\% of the HSL, however, with changing content.
Revised:  Then very rapidly a situation was reached where COVID-related hashtags occupied 30-70\% of the HSL, however, with changing content.
Edit intent: clarity
Original:  in period 3, we see  potential of clustering while not as strong as in period 1.
Revised:  in period 3, we see a potential of clustering while not as strong as in period 1.
Edit intent: fluency
Original:  To quantify the dynamics of HSL we measured the lifetimes of hashtags on the list and the rank diversity at given ranks.
Revised:  We further explore the dynamics of HSL we measured the lifetimes of hashtags on the list and the rank diversity at given ranks.
Edit intent: clarity
Original:  To quantify the dynamics of HSL we measured the lifetimes of hashtags on the list and the rank diversity at given ranks.
Revised:  To quantify the dynamics of HSL by measuring the ranking dynamics and the lifetimes of hashtags on the list and the rank diversity at given ranks.
Edit intent: clarity