wanyu/IteraTeR_v2 huggingface dataset:
Original:  Finally, we identify two interesting example problems with very different posterior structures, which we use to conduct a large-scale benchmark of the convergence of several Markov Chain Monte Carlo methods that have been developed in recent years for infinite-dimensional settings.
Revised:  Finally, we identify two interesting example problems with very different posterior structures, which we use to conduct a large-scale benchmark of the convergence of several Markov Chain Monte Carlo methods developed in recent years for infinite-dimensional settings.
Edit intent: clarity
Original:  In particular, we demonstrate that two of these algorithms are capable of resolving a posterior with complex , multi-modal structure .
Revised:  Our results indicate that these methods are capable of resolving a posterior with complex , multi-modal structure .
Edit intent: clarity
Original:  In particular, we demonstrate that two of these algorithms are capable of resolving a posterior with complex , multi-modal structure .
Revised:  In particular, we demonstrate that two of these algorithms are capable of resolving complex multimodal posteriors in high dimensions .
Edit intent: clarity
Original: Ubiquitous in eukaryotic microorganisms , the flagellum is a well-studied and highly-functional organelle that is well-known to be responsible for motility in a variety of organisms.
Revised: Ubiquitous in eukaryotic organisms , the flagellum is a well-studied and highly-functional organelle that is well-known to be responsible for motility in a variety of organisms.
Edit intent: clarity
Original: Ubiquitous in eukaryotic microorganisms , the flagellum is a well-studied and highly-functional organelle that is well-known to be responsible for motility in a variety of organisms.
Revised: Ubiquitous in eukaryotic microorganisms , the flagellum is a well-studied organelle that is well-known to be responsible for motility in a variety of organisms.
Edit intent: clarity
Original:  Pertinent to multiple areas of active scientific interest is the understanding of their substructures, mechanical regulation, and beating patterns, with the latter being of particular relevance to the investigation of motile flagellated microorganisms.
Edit intent: clarity
Original:  Here we present a fully-automated method of flagellum identification from videomicroscopy based on the fact that the flagella appear to be of approximately constant width when viewed with typical optics.
Revised:  Here we present a fully-automated method of flagellum identification from videomicroscopy based on the fact that the flagella are of approximately constant width when viewed with typical optics.
Edit intent: clarity
Original: In this paper we provide faster algorithms for approximately solving \infty regression, a fundamental problem prevalent in both combinatorial and continuous optimization.
Revised: We provide faster algorithms for approximately solving \infty regression, a fundamental problem prevalent in both combinatorial and continuous optimization.
Edit intent: clarity
Original:  In particular we provide an accelerated coordinate descent method which converges in k iterations at a O %DIFDELCMD < \left(%%% \frac{1{k}}%DIFDELCMD < \right) %%% rateindependent of the dimension of the problem, and whose iterations can be implemented cheaply for many structured matrices.
Revised:  In particular , we provide accelerated coordinate descent method which converges in k iterations at a O %DIFDELCMD < \left(%%% \frac{1{k}}%DIFDELCMD < \right) %%% rateindependent of the dimension of the problem, and whose iterations can be implemented cheaply for many structured matrices.
Edit intent: fluency
Original:  Our algorithm can be viewed as an alternative approach to the recent breakthrough result of Sherman  which achieves a similar running time improvement over classic algorithmic approaches, i.e. smoothing and gradient descent, which either converge at a O %DIFDELCMD < \left(%%% \frac{1{k}}%DIFDELCMD < \right) %%%  rate or have running times with a worse dependence on problem parameters.
Revised:  Our algorithm can be viewed as an alternative approach to the recent breakthrough result of Sherman which achieves a similar runtime improvement over classic algorithmic approaches, i.e. smoothing and gradient descent, which either converge at a O %DIFDELCMD < \left(%%% \frac{1{k}}%DIFDELCMD < \right) %%% rate or have running times with a worse dependence on problem parameters.
Edit intent: clarity
Original:  We show how to use our algorithm to achieve a runtime of ]  O\left(m + \frac{\sqrt{ns}{\epsilon}} /\epsilon} \right)  to compute an \epsilon-approximate maximum flow , for an undirected graph with m edges , n vertices, and where s is the squared \ell_2 norm of the congestion of any optimal flow.
Revised:  Our runtimes match those of ] O\left(m + \frac{\sqrt{ns}{\epsilon}} /\epsilon} \right) to compute an \epsilon-approximate maximum flow , for an undirected graph with m edges , n vertices, and where s is the squared \ell_2 norm of the congestion of any optimal flow.
Edit intent: clarity
Original:  We show how to use our algorithm to achieve a runtime of ]  O\left(m + \frac{\sqrt{ns}{\epsilon}} /\epsilon} \right)  to compute an \epsilon-approximate maximum flow , for an undirected graph with m edges , n vertices, and where s is the squared \ell_2 norm of the congestion of any optimal flow.
Revised:  We show how to use our algorithm to achieve a runtime of ] O\left(m + \frac{\sqrt{ns}{\epsilon}} /\epsilon} \right) to compute an \epsilon-approximate maximum flow for an undirected graph with m edges , n vertices, and where s is the squared \ell_2 norm of the congestion of any optimal flow.
Edit intent: fluency
Original:  We show how to use our algorithm to achieve a runtime of ]  O\left(m + \frac{\sqrt{ns}{\epsilon}} /\epsilon} \right)  to compute an \epsilon-approximate maximum flow , for an undirected graph with m edges , n vertices, and where s is the squared \ell_2 norm of the congestion of any optimal flow.
Revised:  We show how to use our algorithm to achieve a runtime of ] O\left(m + \frac{\sqrt{ns}{\epsilon}} /\epsilon} \right) to compute an \epsilon-approximate maximum flow , for an undirected graph with m edges and n vertices, and where s is the squared \ell_2 norm of the congestion of any optimal flow.
Edit intent: fluency
Original:  As s = O(m) this yields a running time of%DIFDELCMD < \tilde{O}\left(%%% m + \frac{\sqrt{nm}{\epsilon}}%DIFDELCMD < \right)%%% , generically improving upon the previous best known runtime of \tilde{O}\left( \frac{m{\epsilon}}  \right) by Sherman  whenever the graph is slightly dense.
Revised:  As s = O(m) this yields a running time of%DIFDELCMD < \tilde{O}\left(%%% m + \frac{\sqrt{nm}{\epsilon}}%DIFDELCMD < \right)%%% generically improving upon the previous best known runtime of \tilde{O}\left( \frac{m{\epsilon}} \right) by Sherman whenever the graph is slightly dense.
Edit intent: fluency
Original:  As s = O(m) this yields a running time of%DIFDELCMD < \tilde{O}\left(%%% m + \frac{\sqrt{nm}{\epsilon}}%DIFDELCMD < \right)%%% , generically improving upon the previous best known runtime of \tilde{O}\left( \frac{m{\epsilon}}  \right) by Sherman  whenever the graph is slightly dense.
Revised:  As s = O(m) this yields a running time of%DIFDELCMD < \tilde{O}\left(%%% m + \frac{\sqrt{nm}{\epsilon}}%DIFDELCMD < \right)%%% , generically improving upon the previous best known runtime of \tilde{O}\left( {\epsilon}} \right) by Sherman whenever the graph is slightly dense.
Edit intent: clarity
Original:  As s = O(m) this yields a running time of%DIFDELCMD < \tilde{O}\left(%%% m + \frac{\sqrt{nm}{\epsilon}}%DIFDELCMD < \right)%%% , generically improving upon the previous best known runtime of \tilde{O}\left( \frac{m{\epsilon}}  \right) by Sherman  whenever the graph is slightly dense.
Revised:  As s = O(m) this yields a running time of%DIFDELCMD < \tilde{O}\left(%%% m + \frac{\sqrt{nm}{\epsilon}}%DIFDELCMD < \right)%%% , generically improving upon the previous best known runtime of \tilde{O}\left( \frac{m{\epsilon}} \right) in whenever the graph is slightly dense.
Edit intent: clarity
Original:  As s = O(m) this yields a running time of%DIFDELCMD < \tilde{O}\left(%%% m + \frac{\sqrt{nm}{\epsilon}}%DIFDELCMD < \right)%%% , generically improving upon the previous best known runtime of \tilde{O}\left( \frac{m{\epsilon}}  \right) by Sherman  whenever the graph is slightly dense.
Revised:  As s = O(m) this yields a running time of%DIFDELCMD < \tilde{O}\left(%%% m + \frac{\sqrt{nm}{\epsilon}}%DIFDELCMD < \right)%%% , generically improving upon the previous best known runtime of \tilde{O}\left( \frac{m{\epsilon}} \right) by Sherman She17 whenever the graph is slightly dense.
Edit intent: fluency
Original:  We achieve these results by providing an accelerated coordinate descent method exploiting dynamic measures of coordinate smoothness for smoothed \ell_{\infty .
Revised:  We hope that our work serves as an important step towards achieving even faster maximum flow algorithms .
Edit intent: clarity
Original: Most organisms are exposed to neural damage throughout their lives, which can reduce their ability to carry out core behavioral tasks .
Revised: Most organisms suffer neuronal damage throughout their lives, which can reduce their ability to carry out core behavioral tasks .
Edit intent: clarity
Original: Most organisms are exposed to neural damage throughout their lives, which can reduce their ability to carry out core behavioral tasks .
Revised: Most organisms are exposed to neural damage throughout their lives, which can impair performance of core behaviors .
Edit intent: clarity
Original:  Their neural circuits need to maintain functionality despite injury, which often requires that key readout signals from the system be preserved .
Revised:  Their neural circuits need to maintain function despite injury, which often requires that key readout signals from the system be preserved .
Edit intent: fluency
Original:  Their neural circuits need to maintain functionality despite injury, which often requires that key readout signals from the system be preserved .
Revised:  Their neural circuits need to maintain functionality despite injury, which in particular requires preserving key system outputs .
Edit intent: clarity
Original:  Neuronal impairments are modeled as focal axonal swellings, an axonal pathology observed across all severities of traumatic brain injuries and present in other leading brain disorders.
Revised:  Neuronal impairments are modeled as focal axonal swellings, a ubiquitous form of axonal pathology observed across all severities of traumatic brain injuries and present in other leading brain disorders.
Edit intent: clarity
Original:  Neuronal impairments are modeled as focal axonal swellings, an axonal pathology observed across all severities of traumatic brain injuries and present in other leading brain disorders.
Revised:  Neuronal impairments are modeled as focal axonal swellings, an axonal pathology observed in traumatic brain injuries and present in other leading brain disorders.
Edit intent: clarity
Original:  Neuronal impairments are modeled as focal axonal swellings, an axonal pathology observed across all severities of traumatic brain injuries and present in other leading brain disorders.
Revised:  Neuronal impairments are modeled as focal axonal swellings, an axonal pathology observed across all severities of traumatic brain injuries and other brain disorders.
Edit intent: clarity
Original:  Axonal swellings effectively compromise spike train propagation along the axon and consequently reduce the effective neural firing rate delivered to downstream neurons.
Revised:  Axonal swellings effectively compromise spike train propagation along the axon , reducing the effective neural firing rate delivered to downstream neurons.
Edit intent: coherence
Original:  More generally, these experiments suggest that robustness to injury is a vital design principle to consider when analyzing biological neural systems.
Revised:  More generally, robustness to injury is a vital design principle to consider when analyzing biological neural systems.
Edit intent: clarity
Original:  More generally, these experiments suggest that robustness to injury is a vital design principle to consider when analyzing biological neural systems.
Revised:  More generally, these experiments suggest that robustness to injury is a vital design principle to consider when analyzing neural systems.
Edit intent: clarity
Original:  Indeed, it is possible that some neural structures and mechanisms, including the ability to learn, are best understood as evolutionary solutions to the challenge of maintaining system function despite injury.
Edit intent: coherence
Original:  In this study, we further propose to compose a geared rotationally identical CNN system (GRI-CNN) with a small angle increment by connecting networks of participated processes at the first flatten layer.
Revised:  In this study, we further propose to compose a geared rotationally identical CNN system (GRI-CNN) with a small step angle by connecting networks of participated processes at the first flatten layer.
Edit intent: clarity
Original:  Each of them can produce quantitatively identical output results when a rotation angle of the input vector is evenly divisible by the increment angle of the gear.
Revised:  Each of them can produce quantitatively identical output results when a rotation angle of the input vector is evenly divisible by the step angle of the gear.
Edit intent: clarity
Original:  With an ultra-fine increment angle (e.g., 1 degree or 0.1 degree), a virtually isotropic CNN system can be constructed.
Revised:  With a design of ultra-fine increment angle (e.g., 1 degree or 0.1 degree), a virtually isotropic CNN system can be constructed.
Edit intent: clarity
Original:  With an ultra-fine increment angle (e.g., 1 degree or 0.1 degree), a virtually isotropic CNN system can be constructed.
Revised:  With an ultra-fine gear-tooth step angle (e.g., 1 degree or 0.1 degree), a virtually isotropic CNN system can be constructed.
Edit intent: clarity
Original:  Our study showed when a rotated input vector does not match to a step angle, the GRI-CNN can also produce a highly consistent result.
Revised:  Our study showed when an input vector rotated with an angle does not match to a step angle, the GRI-CNN can also produce a highly consistent result.
Edit intent: clarity
Original:  This simple-to-implement model  ] augments the local model with an anonymous channel that randomly permutes a set of user-supplied messages.
Revised:  This simple-to-implement model ], augments the local model with an anonymous channel that randomly permutes a set of user-supplied messages.
Edit intent: fluency
Original:  For summation queries, we show that this model provides the power of the central model while avoiding the need to trust a central server and the complexity of cryptographic secure function evaluation.
Revised:  For sum queries, we show that this model provides the power of the central model while avoiding the need to trust a central server and the complexity of cryptographic secure function evaluation.
Edit intent: clarity
Original:  More generally, we give evidence that the power of the mixnet model lies strictly between those of the central and local models: for a natural restriction of the model, we show that mixnet protocols for a widely studied selection problem require exponentially higher sample complexity than do central-model protocols.
Revised:  More generally, we give evidence that the power of the mixnet model lies strictly between those of the central and local models: for a natural restriction of the model, we show that shuffled protocols for a widely studied selection problem require exponentially higher sample complexity than do central-model protocols.
Edit intent: clarity
Original: The ability to generate natural language sequences from source code snippets can be used for code summarization, documentation, and retrieval.
Revised: The ability to generate natural language sequences from source code snippets has a variety of applications such as code summarization, documentation, and retrieval.
Edit intent: clarity
Original:  Our model represents a code snippet as the set of  paths in its abstract syntax tree (AST) and uses attention to select the relevant paths during decoding, much like contemporary NMT models .
Revised:  Our model represents a code snippet as the set of paths in its abstract syntax tree (AST) and uses attention to select the relevant paths while decoding .
Edit intent: clarity
Original:  Our model significantly outperforms previous models that were specifically designed for programming languages, as well as general state-of-the-art NMT models.
Revised:  Our model significantly outperforms previous models that were specifically designed for programming languages, as well as state-of-the-art NMT models.
Edit intent: clarity
Original:  We introduce Steady State Reduction (SSR), a method that decomposes a gLV system of many ecological species into two-dimensional (2D) subsystems that each obey gLV dynamics and whose basis vectors are steady states of the high-dimensional model.
Revised:  We introduce Steady State Reduction (SSR), a method that reduces a gLV system of many ecological species into two-dimensional (2D) subsystems that each obey gLV dynamics and whose basis vectors are steady states of the high-dimensional model.
Edit intent: clarity
Original:  These algorithms have two intertwined constituents : one-dimensional linear optimization one one hand, and a combinatorial part closely related to vertex numeration on the other.
Revised:  These algorithms have two intertwined components : one-dimensional linear optimization one one hand, and a combinatorial part closely related to vertex numeration on the other.
Edit intent: fluency
Original:  Their separation provides a deeper insight into Benson's algorithm, and points toward a dual approach different from the one defined by Ehrgott, L\"ohne and Shan .
Revised:  Their separation provides a deeper insight into Benson's algorithm, and points toward a dual approach .
Edit intent: clarity
Original:  On problems with 20 or more objectives the implementation shows a more than 10-fold increase in efficiency compared to Bensolve -- due to the reduced number of iterations and the improved combinatorial handling.
Revised:  On problems with ten or more objectives the implementation shows a more than 10-fold increase in efficiency compared to Bensolve -- due to the reduced number of iterations and the improved combinatorial handling.
Edit intent: fluency
Original:  On problems with 20 or more objectives the implementation shows a more than 10-fold increase in efficiency compared to Bensolve -- due to the reduced number of iterations and the improved combinatorial handling.
Revised:  On problems with 20 or more objectives the implementation shows a more than 10-fold increase in efficiency compared to Bensolve - due to the reduced number of iterations and the improved combinatorial handling.
Edit intent: fluency
Original:  Although many future Internet architectures and protocols have been proposed to fulfill such needs, ISPs have been reluctant to deploy  these architectures.
Revised:  Although many future Internet architectures and protocols have been proposed to fulfill such needs, ISPs have been reluctant to deploy many of these architectures.
Edit intent: clarity
Original:  What makes a new architecture easier to deploy ?
Revised:  How to enhance the deployability of a new architecture easier to deploy ?
Edit intent: clarity
Original:  What makes a new architecture easier to deploy ?
Revised:  What makes a new architecture ?
Edit intent: clarity
Original:  We also use our model to explain the deploying outcomes of  IPv6, DiffServ, CDN, etc., and  the "Internet flattening phenomenon" . Furthermore, one can use our model to predict the deployability of new architectures such as NDN, XIA, and compare the deployability of competing architectures.
Revised:  We also use our model to explain the deploying outcomes of IPv6, DiffServ, CDN, etc., and shed light on the "Internet flattening phenomenon" . Furthermore, one can use our model to predict the deployability of new architectures such as NDN, XIA, and compare the deployability of competing architectures.
Edit intent: clarity
Original:  We also use our model to explain the deploying outcomes of  IPv6, DiffServ, CDN, etc., and  the "Internet flattening phenomenon" . Furthermore, one can use our model to predict the deployability of new architectures such as NDN, XIA, and compare the deployability of competing architectures.
Revised:  We also use our model to explain the deploying outcomes of IPv6, DiffServ, CDN, etc., and the "Internet flattening phenomenon" ; (3) predict the deployability of new architectures such as NDN, XIA, and compare the deployability of competing architectures.
Edit intent: coherence
Original:  We also use our model to explain the deploying outcomes of  IPv6, DiffServ, CDN, etc., and  the "Internet flattening phenomenon" . Furthermore, one can use our model to predict the deployability of new architectures such as NDN, XIA, and compare the deployability of competing architectures.
Revised:  We also use our model to explain the deploying outcomes of IPv6, DiffServ, CDN, etc., and the "Internet flattening phenomenon" . Furthermore, one can use our model to predict the deployability of a new architecture such as NDN, XIA, and compare the deployability of competing architectures.
Edit intent: fluency
Original:  We also use our model to explain the deploying outcomes of  IPv6, DiffServ, CDN, etc., and  the "Internet flattening phenomenon" . Furthermore, one can use our model to predict the deployability of new architectures such as NDN, XIA, and compare the deployability of competing architectures.
Revised:  We also use our model to explain the deploying outcomes of IPv6, DiffServ, CDN, etc., and the "Internet flattening phenomenon" . Furthermore, one can use our model to predict the deployability of new architectures such as NDN, and compare its deployability with competing architectures.
Edit intent: clarity
Original:  Our study also suggests that the architectures which try to make a fresh start may have a low deployability, unless they have efficient incremental deployment mechanisms or one introduces a centralized coordinator to help the deployment .
Revised:  Our study suggests that the architectures which try to make a fresh start may have a low deployability, unless they have efficient incremental deployment mechanisms or one introduces a centralized coordinator to help the deployment .
Edit intent: clarity
Original:  We focus on four themes:  1) clinical melanoma research,  2) basic melanoma research,  3) clinical dermatology, and  4) basic pigment cell research, with the goal of outlining current highlights, challenges, and frontiers associated with pigmentation and melanocyte biology.
Revised:  We focus on four themes: ( 1) clinical melanoma research, 2) basic melanoma research, 3) clinical dermatology, and 4) basic pigment cell research, with the goal of outlining current highlights, challenges, and frontiers associated with pigmentation and melanocyte biology.
Edit intent: fluency
Original:  We focus on four themes:  1) clinical melanoma research,  2) basic melanoma research,  3) clinical dermatology, and  4) basic pigment cell research, with the goal of outlining current highlights, challenges, and frontiers associated with pigmentation and melanocyte biology.
Revised:  We focus on four themes: 1) clinical melanoma research, ( 2) basic melanoma research, 3) clinical dermatology, and 4) basic pigment cell research, with the goal of outlining current highlights, challenges, and frontiers associated with pigmentation and melanocyte biology.
Edit intent: fluency