wanyu/IteraTeR_v2 huggingface dataset:
Original:  We find that for typical rules the effect of making a single swap of adjacent candidates in a single preference order is either that (1) at most one committee member can be replaced, or (2) it is possible that the whole committee can be replaced.
Revised:  We find that for typical rules the effect of making a single swap of adjacent candidates in a single preference order is either that (1) at most one committee member can be replaced, or (2) it is possible that the whole committee will be replaced.
Edit intent: clarity
Original:  Is important to remark that the methodology presented here can be applied to any kind of networks such as protein interaction networks, gene networks or social networks.
Revised:  Our method can also be applied to any kind of networks such as protein interaction networks, gene networks or social networks.
Edit intent: clarity
Original:  Is important to remark that the methodology presented here can be applied to any kind of networks such as protein interaction networks, gene networks or social networks.
Revised:  Is important to remark that the methodology presented here can be applied to other kind of networks such as protein interaction networks, gene networks or social networks.
Edit intent: clarity
Original:  We show that red many of the algorithmic tools that were developed for undirected bounded expansion classes can, with some care, also be applied in their directed counterparts, and thereby we highlight a rich algorithmic structure theory of directed bounded expansion classes.
Revised:  We show that many of the algorithmic tools that were developed for undirected bounded expansion classes can, with some care, also be applied in their directed counterparts, and thereby we highlight a rich algorithmic structure theory of directed bounded expansion classes.
Edit intent: coherence
Original: We derive bounds relating the statistical dimension of linear images of convex cones to Renegar's condition number  . Using results from conic integral geometry, we show that the bounds can be made to depend only on a random projection  to a lower dimensional space, and can still be effective if the linear maps are ill-conditioned.
Revised: We derive bounds relating Renegar's condition number . Using results from conic integral geometry, we show that the bounds can be made to depend only on a random projection to a lower dimensional space, and can still be effective if the linear maps are ill-conditioned.
Edit intent: clarity
Original: We derive bounds relating the statistical dimension of linear images of convex cones to Renegar's condition number  . Using results from conic integral geometry, we show that the bounds can be made to depend only on a random projection  to a lower dimensional space, and can still be effective if the linear maps are ill-conditioned.
Revised: We derive bounds relating the statistical dimension of linear images of convex cones to Renegar's condition number . Using results from conic integral geometry, we show that the bounds can be made to depend only on a random projection to a lower dimensional space, and can still be effective if these operators are ill-conditioned.
Edit intent: clarity
Original: In this paper we investigate the impact of simple text preprocessing decisions (particularly tokenizing, lemmatizing, lowercasing and multiword grouping  on the performance of a state-of-the-art text classifier based on convolutional neural networks.
Revised: In this paper we investigate the impact of simple text preprocessing decisions (particularly tokenizing, lemmatizing, lowercasing and multiword grouping ) on the performance of a state-of-the-art text classifier based on convolutional neural networks.
Edit intent: fluency
Original:  We perform an extensive evaluation in standard benchmarks from text categorization and sentiment analysis.
Revised:  We perform an extensive evaluation on standard benchmarks from text categorization and sentiment analysis.
Edit intent: clarity
Original:  Our results show that a simple tokenization of the input text is often enough, but also highlight the importance of being consistent in the preprocessing of the evaluation set and the corpus used for training word embeddings.
Revised:  While our experiments show that a simple tokenization of the input text is often enough, but also highlight the importance of being consistent in the preprocessing of the evaluation set and the corpus used for training word embeddings.
Edit intent: clarity
Original:  Our results show that a simple tokenization of the input text is often enough, but also highlight the importance of being consistent in the preprocessing of the evaluation set and the corpus used for training word embeddings.
Revised:  Our results show that a simple tokenization of input text is often enough, but also highlight the importance of being consistent in the preprocessing of the evaluation set and the corpus used for training word embeddings.
Edit intent: fluency
Original:  Our results show that a simple tokenization of the input text is often enough, but also highlight the importance of being consistent in the preprocessing of the evaluation set and the corpus used for training word embeddings.
Revised:  Our results show that a simple tokenization of the input text is often enough, but also highlight the importance of paying attention to this usually-overlooked step in the pipeline, particularly when comparing different models. Finally, our evaluation provides insights into the best preprocessing practices for training word embeddings.
Edit intent: clarity
Original:  Finally , we show that when we couple this "pull" effect with individual performance trajectories, we are able to better predict future outcomes when compared to a baseline predictor that relies on individual trajectories alone - providing evidence that the interaction information holds a key to the participants' learning outcomes at an individual level .
Revised:  Finally , we show that the learners' speaking qualities are impacted by the nature of their interactions. This is established by demonstrating that our proposed consensus-based prediction framework outperforms baseline network-agnostic regression models in estimating learning outcomes .
Edit intent: coherence
Original:  We introduce a framework called ROC Speak that we have developed towards collecting a novel dataset of six online public speaking learning communities ;
Revised:  We introduce a novel dataset of six online public speaking learning communities ;
Edit intent: coherence
Original: Natural Language Processing (NLP) systems often make use of machine learning techniques that are unfamiliar to end- users who are interested in analyzing clinical records.
Revised: Natural Language Processing (NLP) systems often make use of machine learning techniques that are unfamiliar to end-users who are interested in analyzing clinical records.
Edit intent: fluency
Original:  Al- though NLP has been widely used in extracting information from clinical text, current systems generally do not support model revision based on feedback from domain experts.
Revised:  Although NLP has been widely used in extracting information from clinical text, current systems generally do not support model revision based on feedback from domain experts.
Edit intent: coherence
Original:  We present a prototype tool that allows end users to visual- ize and review the outputs of an NLP system that extracts binary variables from clinical text.
Revised:  We present a prototype tool that allows end users to visualize and review the outputs of an NLP system that extracts binary variables from clinical text.
Edit intent: fluency
Original:  Our tool combines mul- tiple visualizations to help the users understand these results and make any necessary corrections, thus forming a feedback loop and helping improve the accuracy of the NLP models.
Revised:  Our tool combines multiple visualizations to help the users understand these results and make any necessary corrections, thus forming a feedback loop and helping improve the accuracy of the NLP models.
Edit intent: fluency
Original:  Results from semi-structured interviews and a Sys- tem Usability Scale (SUS) analysis show that the users are able to quickly start refining NLP models, despite having very little or no experience with machine learning.
Revised:  Results from semi-structured interviews and a System Usability Scale (SUS) analysis show that the users are able to quickly start refining NLP models, despite having very little or no experience with machine learning.
Edit intent: fluency
Original: The goal of Event Schema Induction ( ESI) is to identify schemas of events from a corpus of documents.
Revised: Relation Schema Induction ( ESI) is to identify schemas of events from a corpus of documents.
Edit intent: clarity
Original:  For example, given documents from the sports domain, we would like to infer that win(WinningPlayer, Trophy, OpponentPlayer, Location) is an important event schema for this domain.
Revised:  For example, in the sports domain, we would like to infer that win(WinningPlayer, Trophy, OpponentPlayer, Location) is an important event schema for this domain.
Edit intent: clarity
Original:  For example, given documents from the sports domain, we would like to infer that win(WinningPlayer, Trophy, OpponentPlayer, Location) is an important event schema for this domain.
Revised:  For example, given documents from the sports domain, inducing a schema win(WinningPlayer, Trophy, OpponentPlayer, Location) is an important event schema for this domain.
Edit intent: clarity
Original:  For example, given documents from the sports domain, we would like to infer that win(WinningPlayer, Trophy, OpponentPlayer, Location) is an important event schema for this domain.
Revised:  For example, given documents from the sports domain, we would like to infer that win(WinningPlayer, OpponentPlayer, Tournament, Location) is an important event schema for this domain.
Edit intent: fluency
Original:  To the best of our knowledge  this is the first application of tensor factorization for the ESI problem.
Revised:  To the best of our knowledge , this is the first application of tensor factorization for the ESI problem.
Edit intent: fluency
Original:  These objects have the interesting feature that they do not have the same intuitive probabilistic behaviour like classical Dyck paths (the typical properties of which are strongly related to Brownian motion theory), and this article quantifies some relations between these two types of paths.
Revised:  These objects have the interesting feature that they do not have the same intuitive probabilistic behaviour as classical Dyck paths (the typical properties of which are strongly related to Brownian motion theory), and this article quantifies some relations between these two types of paths.
Edit intent: fluency
Original:  We give a bijection with some other lattice paths and a link with a continued fraction expansion , and prove several formulae for related combinatorial structures conjectured in the On-line Encyclopedia of Integer Sequences.
Revised:  We give a bijection with some other lattice paths and a link with a continued fraction expansion . Furthermore, we prove several formulae for related combinatorial structures conjectured in the On-line Encyclopedia of Integer Sequences.
Edit intent: coherence
Original:  We give a bijection with some other lattice paths and a link with a continued fraction expansion , and prove several formulae for related combinatorial structures conjectured in the On-line Encyclopedia of Integer Sequences.
Revised:  We give a bijection with some other lattice paths and a link with a continued fraction expansion , and prove several formulae for related combinatorial structures conjectured in the On-Line Encyclopedia of Integer Sequences.
Edit intent: fluency
Original:  Thanks to the kernel method and via analytic combinatorics, we derive the enumeration and limit laws of these "lattice paths with catastrophes" , for any finite set of jumps.
Revised:  Thanks to the kernel method and via analytic combinatorics, we provide the enumeration and limit laws of these "lattice paths with catastrophes" , for any finite set of jumps.
Edit intent: clarity
Original:  Thanks to the kernel method and via analytic combinatorics, we derive the enumeration and limit laws of these "lattice paths with catastrophes" , for any finite set of jumps.
Revised:  Thanks to the kernel method and via analytic combinatorics, we derive the enumeration and limit laws of these "lattice paths with catastrophes" for any finite set of jumps.
Edit intent: fluency
Original: This paperproposes the use of Multirate Partial Differential Equations (MPDEs)  for the efficient solution of low-frequency applications with pulsed excitation.
Revised: In this paper, Multirate Partial Differential Equations (MPDEs) for the efficient solution of low-frequency applications with pulsed excitation.
Edit intent: clarity
Original: This paperproposes the use of Multirate Partial Differential Equations (MPDEs)  for the efficient solution of low-frequency applications with pulsed excitation.
Revised: This paperproposes the use of Multirate Partial Differential Equations (MPDEs) are used for the efficient solution of low-frequency applications with pulsed excitation.
Edit intent: clarity
Original: The system of differential equations describing the application is reformulated as MPDEs which are solved by a Galerkin approach and time discretization.
Revised: The system of differential equations describing the problem are reformulated as MPDEs which are solved by a Galerkin approach and time discretization.
Edit intent: clarity
Original:  The  method is applied to the example of a simplified buck converter.
Revised:  The new method is applied to the example of a simplified buck converter.
Edit intent: clarity
Original:  The  method is applied to the example of a simplified buck converter.
Revised:  The method is applied to the example of a buck converter.
Edit intent: clarity
Original:  We compare with existing static and dynamic tools for loop invariant inference, and show that LoopInvGen enables a less onerous and more expressive form of inference .
Revised:  Compared to existing static and dynamic tools for loop invariant inference, and show that LoopInvGen enables a less onerous and more expressive form of inference .
Edit intent: coherence
Original:  We compare with existing static and dynamic tools for loop invariant inference, and show that LoopInvGen enables a less onerous and more expressive form of inference .
Revised:  We compare with existing static and dynamic techniques for loop invariant inference, and show that LoopInvGen enables a less onerous and more expressive form of inference .
Edit intent: clarity
Original:  We compare with existing static and dynamic tools for loop invariant inference, and show that LoopInvGen enables a less onerous and more expressive form of inference .
Revised:  We compare with existing static and dynamic tools for loop invariant inference, not only does LoopInvGen enable a less onerous and more expressive form of inference .
Edit intent: coherence
Original: We present LoopInvGen , a tool for generating loop invariants that can provably guarantee correctness of a program with respect to a given specification.
Revised: We describe the LoopInvGen tool for generating loop invariants that can provably guarantee correctness of a program with respect to a given specification.
Edit intent: clarity
Original:  In contrast to existing data-driven techniques, LoopInvGen is not restricted to a fixed set of features -- atomic predicates that are composed together to build complex loop invariants.
Revised:  In contrast to existing techniques, LoopInvGen is not restricted to a fixed set of features -- atomic predicates that are composed together to build complex loop invariants.
Edit intent: clarity
Original:  Compared to existing static and dynamic techniques for loop invariant inference, not only does LoopInvGen enable a less onerous and more expressive approach, but is also significantly faster over the SyGuS-INV ( 2017 ) benchmarks .
Revised:  This not only enables a less onerous and more expressive approach, but is also significantly faster over the SyGuS-INV ( 2017 ) benchmarks .
Edit intent: clarity
Original:  Compared to existing static and dynamic techniques for loop invariant inference, not only does LoopInvGen enable a less onerous and more expressive approach, but is also significantly faster over the SyGuS-INV ( 2017 ) benchmarks .
Revised:  Compared to existing static and dynamic techniques for loop invariant inference, not only does LoopInvGen enable a less onerous and more expressive approach, but also appears to be significantly faster than the existing tools over the SyGuS-COMP 2017 ) benchmarks .
Edit intent: clarity
Original: We provide characterization of the strong termination property of the CCV (complete call-by-value) lambda-mu calculus introduced in the first part of the series of the paper.
Revised: We provide characterization of the strong termination property of the CCV (complete call-by-value) lambda-mu calculus introduced in the first part of this series of the paper.
Edit intent: clarity
Original:  This paper presents a new modular framework for the analysis of finite-precision computations which computes sound roundoff error bounds fully automatically.
Revised:  This paper presents a formally verified and modular tool which fully automatically checks the correctness of finite-precision computations which computes sound roundoff error bounds fully automatically.
Edit intent: clarity
Original:  This paper presents a new modular framework for the analysis of finite-precision computations which computes sound roundoff error bounds fully automatically.
Revised:  This paper presents a new modular framework for the analysis of finite-precision roundoff error bounds fully automatically.
Edit intent: clarity
Original:  The global action is mainly performed by a small set of scholarly monographs, reference works or primary sources, while the rest of the core, and especially most journal articles, acts mostly locally.
Revised:  In our study, the global action is mainly performed by a small set of scholarly monographs, reference works or primary sources, while the rest of the core, and especially most journal articles, acts mostly locally.
Edit intent: coherence
Original:  The global action is mainly performed by a small set of scholarly monographs, reference works or primary sources, while the rest of the core, and especially most journal articles, acts mostly locally.
Revised:  The global action is mainly performed by small sets of scholarly monographs, reference works or primary sources, while the rest of the core, and especially most journal articles, acts mostly locally.
Edit intent: fluency
Original:  The global action is mainly performed by a small set of scholarly monographs, reference works or primary sources, while the rest of the core, and especially most journal articles, acts mostly locally.
Revised:  The global action is mainly performed by a small set of scholarly monographs, reference works and primary sources, while the rest of the core, and especially most journal articles, acts mostly locally.
Edit intent: fluency
Original:  Stellar decompositions are general in that they can compactly represent and efficiently traverse arbitrary complexes with a manifold or non-manifold domain  They are scalable to complexes in high dimension and of large size, and they enable users to easily construct tailored application-dependent data structures using a fraction of the memory required by the corresponding topological data structure on the global complex.
Revised:  Stellar decompositions are general in that they can compactly represent and efficiently traverse arbitrary complexes with a manifold or non-manifold domain . They are scalable to complexes in high dimension and of large size, and they enable users to easily construct tailored application-dependent data structures using a fraction of the memory required by the corresponding topological data structure on the global complex.
Edit intent: fluency
Original:  Stellar decompositions are general in that they can compactly represent and efficiently traverse arbitrary complexes with a manifold or non-manifold domain  They are scalable to complexes in high dimension and of large size, and they enable users to easily construct tailored application-dependent data structures using a fraction of the memory required by the corresponding topological data structure on the global complex.
Revised:  Stellar decompositions are general in that they can compactly represent and efficiently traverse arbitrary complexes with a manifold or non-manifold domain They are scalable to complexes in high dimension and of large size, and they enable users to easily construct tailored application-dependent data structures using a fraction of the memory required by a corresponding global topological data structure on the global complex.
Edit intent: clarity
Original:  Stellar decompositions are general in that they can compactly represent and efficiently traverse arbitrary complexes with a manifold or non-manifold domain  They are scalable to complexes in high dimension and of large size, and they enable users to easily construct tailored application-dependent data structures using a fraction of the memory required by the corresponding topological data structure on the global complex.
Revised:  Stellar decompositions are general in that they can compactly represent and efficiently traverse arbitrary complexes with a manifold or non-manifold domain They are scalable to complexes in high dimension and of large size, and they enable users to easily construct tailored application-dependent data structures using a fraction of the memory required by the corresponding topological data structure on the complex.
Edit intent: clarity
Original:  Stellar trees are competitive with state-of-the-art topological data structures for manifold simplicial complexes and offer significant improvements for cell complexes and non-manifold simplicial complexes.
Revised:  Stellar trees are competitive with state-ofthe-art topological data structures for manifold simplicial complexes and offer significant improvements for cell complexes and non-manifold simplicial complexes.
Edit intent: fluency
Original:  In this paper, we use the deep-Q reinforcement learning models to arrive at optimal sequences of actions to improve the cellular network SINR value from a starting to a feasible target value.
Revised:  In this paper, we use the deep reinforcement learning model to arrive at optimal sequences of actions to improve the cellular network SINR value from a starting to a feasible target value.
Edit intent: clarity
Original: We propose a method to improve the DL SINR for a single cell indoor base station operating in the millimeter wave frequency range using deep reinforcement learning .
Revised: We propose a method to improve the radio link performance in a wireless network using a deep Q-Learning based algorithm .
Edit intent: clarity
Original:  In this paper, we use the deep reinforcement learning model to arrive at optimal sequences of actions to improve the cellular networkSINR value from a starting to a feasible target value.
Revised:  In this paper, we use this reinforcement learning model to arrive at optimal sequences of actions to improve the cellular networkSINR value from a starting to a feasible target value.
Edit intent: clarity
Original:  The main contributions of this paper are : 1) introduce a radio performance tuning algorithm that self-organizing networks can implement in a polynomial runtime , 2) employ deep reinforcement learning to perform fault management, and 3) show that this fault management method can improve the radio link performance in a realistic network setup.
Revised:  The main contributions of this paper are to 1) introduce a radio performance tuning algorithm that self-organizing networks can implement in a polynomial runtime , 2) employ deep reinforcement learning to perform fault management, and 3) show that this fault management method can improve the radio link performance in a realistic network setup.
Edit intent: fluency