wanyu/IteraTeR_v2 huggingface dataset:
Original: This paper introduces the key concepts and problems of the new research area of Periodic Geometry and Topology for applications in Materials Science .
Revised: This paper introduces the key concepts and problems in the new research area of Periodic Geometry and Topology for applications in Materials Science .
Edit intent: clarity
Original: This paper introduces the key concepts and problems of the new research area of Periodic Geometry and Topology for applications in Materials Science .
Revised: This paper introduces the key concepts and problems of the new research area of Periodic Geometry and Topology for materials applications .
Edit intent: clarity
Original:  The more practical equivalence is a periodic isotopyin a thickened plane without fixing a lattice basis.
Revised:  The more practical equivalence is a periodic isotopyin a thickened plane without a fixed lattice basis.
Edit intent: fluency
Original:  The scale of the  resulting workflow is such that it is dependent on high performance computing .
Revised:  The scale of the potential resulting workflow is such that it is dependent on high performance computing .
Edit intent: clarity
Original:  The scale of the  resulting workflow is such that it is dependent on high performance computing .
Revised:  The scale of the resulting workflow is such that it is dependent on supercomputing to achieve extremely high throughput .
Edit intent: clarity
Original:  We have demonstrated the applicability of this workflow on four COVID-19 target proteins and our ability to perform the required large-scale calculations to identify lead compounds on a variety of supercomputers.
Revised:  We have demonstrated the viability of this workflow on four COVID-19 target proteins and our ability to perform the required large-scale calculations to identify lead compounds on a variety of supercomputers.
Edit intent: clarity
Original:  In this paper we view the algebraic effect theory of a computation as a variable context , and track the effects directly in computation 's modal type with\emph{  ECMTT, a novel calculus for algebraic effects and handlers.
Revised:  In this paper , we propose to view an algebraic effect theory of a computation as a variable context , and track the effects directly in computation 's modal type with\emph{ ECMTT, a novel calculus for algebraic effects and handlers.
Edit intent: clarity
Original:  In this paper we view the algebraic effect theory of a computation as a variable context , and track the effects directly in computation 's modal type with\emph{  ECMTT, a novel calculus for algebraic effects and handlers.
Revised:  In this paper we view the algebraic effect theory of a computation as a variable context ; consequently, we propose to track algebraic effects of a computation with\emph{ ECMTT, a novel calculus for algebraic effects and handlers.
Edit intent: coherence
Original:  In this paper we view the algebraic effect theory of a computation as a variable context , and track the effects directly in computation 's modal type with\emph{  ECMTT, a novel calculus for algebraic effects and handlers.
Revised:  In this paper we view the algebraic effect theory of a computation as a variable context , and track the effects directly in computation 's modal type with\emph{ . We develop ECMTT, a novel calculus for algebraic effects and handlers.
Edit intent: coherence
Original:  The modal foundation leads to customary logical properties of local soundness and completeness, and determines the operational semantics of ECMTT directly by \beta-reduction .
Revised:  The modal foundation leads to customary logical properties of local soundness and completeness, and determines the operational semantics solely by \beta-reduction .
Edit intent: clarity
Original:  For SpMV we show why the CRS matrix storage format is not a good practical choice on this architecture and how the SELL-C-\sigma format can achieve bandwidth saturation.
Revised:  For SpMV we show why the CRS matrix storage format is not a good practical choice on this architecture and how the SELL-C-sigma format can achieve bandwidth saturation.
Edit intent: fluency
Original:  A typical example that behaves computationally different in subclasses of chordal graph is the Subset Feedback Vertex Set (SFVS) problem: given a  graph G=(V,E) and a set S\subseteq V, SFVS\textsc{  asks for a minimum set of vertices that intersects all cycles containing a vertex of S. SFVS is known to be polynomial-time solvable on interval graphs, whereas SFVS remains \NP-complete on split graphs and, consequently, on chordal graphs.
Revised:  A typical example that behaves computationally different in subclasses of chordal graphs is the Subset Feedback Vertex Set (SFVS) problem: given a graph G=(V,E) and a set S\subseteq V, SFVS\textsc{ asks for a minimum set of vertices that intersects all cycles containing a vertex of S. SFVS is known to be polynomial-time solvable on interval graphs, whereas SFVS remains \NP-complete on split graphs and, consequently, on chordal graphs.
Edit intent: fluency
Original:  A typical example that behaves computationally different in subclasses of chordal graph is the Subset Feedback Vertex Set (SFVS) problem: given a  graph G=(V,E) and a set S\subseteq V, SFVS\textsc{  asks for a minimum set of vertices that intersects all cycles containing a vertex of S. SFVS is known to be polynomial-time solvable on interval graphs, whereas SFVS remains \NP-complete on split graphs and, consequently, on chordal graphs.
Revised:  A typical example that behaves computationally different in subclasses of chordal graph is the Subset Feedback Vertex Set (SFVS) problem: given a graph G=(V,E) and a set S\subseteq V, the\textsc{ asks for a minimum set of vertices that intersects all cycles containing a vertex of S. SFVS is known to be polynomial-time solvable on interval graphs, whereas SFVS remains \NP-complete on split graphs and, consequently, on chordal graphs.
Edit intent: fluency
Original:  A typical example that behaves computationally different in subclasses of chordal graph is the Subset Feedback Vertex Set (SFVS) problem: given a  graph G=(V,E) and a set S\subseteq V, SFVS\textsc{  asks for a minimum set of vertices that intersects all cycles containing a vertex of S. SFVS is known to be polynomial-time solvable on interval graphs, whereas SFVS remains \NP-complete on split graphs and, consequently, on chordal graphs.
Revised:  A typical example that behaves computationally different in subclasses of chordal graph is the Subset Feedback Vertex Set (SFVS) problem: given a graph G=(V,E) and a set S\subseteq V, SFVS\textsc{ (SFVS) problem asks for a minimum set of vertices that intersects all cycles containing a vertex of S. SFVS is known to be polynomial-time solvable on interval graphs, whereas SFVS remains \NP-complete on split graphs and, consequently, on chordal graphs.
Edit intent: clarity
Original:  A typical example that behaves computationally different in subclasses of chordal graph is the Subset Feedback Vertex Set (SFVS) problem: given a  graph G=(V,E) and a set S\subseteq V, SFVS\textsc{  asks for a minimum set of vertices that intersects all cycles containing a vertex of S. SFVS is known to be polynomial-time solvable on interval graphs, whereas SFVS remains \NP-complete on split graphs and, consequently, on chordal graphs.
Revised:  A typical example that behaves computationally different in subclasses of chordal graph is the Subset Feedback Vertex Set (SFVS) problem: given a graph G=(V,E) and a set S\subseteq V, SFVS\textsc{ asks for a vertex set of minimum weight that intersects all cycles containing a vertex of S. SFVS is known to be polynomial-time solvable on interval graphs, whereas SFVS remains \NP-complete on split graphs and, consequently, on chordal graphs.
Edit intent: clarity
Original: Training machines to understand natural language and interact with humans is an elusive and essential task in the field of artificial intelligence.
Revised: Training machines to understand natural language and interact with humans is an elusive and essential task of artificial intelligence.
Edit intent: clarity
Original:  In recent years, a diversity of dialogue systems has been designed with the rapid development of deep learning researches , especially the recent pre-trained language models  . Among these studies, the fundamental yet challenging part is dialogue comprehension whose role is to teach the machines to read and comprehend the dialogue context before responding.
Revised:  A diversity of dialogue systems has been designed with the rapid development of deep learning researches , especially the recent pre-trained language models . Among these studies, the fundamental yet challenging part is dialogue comprehension whose role is to teach the machines to read and comprehend the dialogue context before responding.
Edit intent: clarity
Original:  In recent years, a diversity of dialogue systems has been designed with the rapid development of deep learning researches , especially the recent pre-trained language models  . Among these studies, the fundamental yet challenging part is dialogue comprehension whose role is to teach the machines to read and comprehend the dialogue context before responding.
Revised:  In recent years, a diversity of dialogue systems has been designed with the rapid development of deep learning techniques , especially the recent pre-trained language models . Among these studies, the fundamental yet challenging part is dialogue comprehension whose role is to teach the machines to read and comprehend the dialogue context before responding.
Edit intent: clarity
Original:  In recent years, a diversity of dialogue systems has been designed with the rapid development of deep learning researches , especially the recent pre-trained language models  . Among these studies, the fundamental yet challenging part is dialogue comprehension whose role is to teach the machines to read and comprehend the dialogue context before responding.
Revised:  In recent years, a diversity of dialogue systems has been designed with the rapid development of deep learning researches , especially the recent pre-trained language models (PrLMs) . Among these studies, the fundamental yet challenging part is dialogue comprehension whose role is to teach the machines to read and comprehend the dialogue context before responding.
Edit intent: clarity
Original:  In recent years, a diversity of dialogue systems has been designed with the rapid development of deep learning researches , especially the recent pre-trained language models  . Among these studies, the fundamental yet challenging part is dialogue comprehension whose role is to teach the machines to read and comprehend the dialogue context before responding.
Revised:  In recent years, a diversity of dialogue systems has been designed with the rapid development of deep learning researches , especially the recent pre-trained language models . Among these studies, the fundamental yet challenging type of task is dialogue comprehension whose role is to teach the machines to read and comprehend the dialogue context before responding.
Edit intent: clarity
Original:  Then, we discuss three typical patterns of dialogue modeling that are widely-used in dialogue comprehension tasks such as response selection and conversation question-answering, as well as dialogue-related language modeling techniques to enhance PrLMs in dialogue scenarios.
Revised:  Then, we discuss three typical patterns of dialogue modeling that are widely-used in dialogue comprehension tasks such as response selection and conversation question-answering, as well as dialogue-related pre-training techniques which are employed to enhance PrLMs in dialogue scenarios.
Edit intent: clarity
Original:  Finally, we highlight the technical advances in recent years and point out the lessons we can learn from the empirical analysis and the prospects towards a new frontier of researches.
Revised:  Finally, we highlight the technical advances in recent years and point out the lessons from the empirical analysis and the prospects towards a new frontier of researches.
Edit intent: clarity
Original:  This paper introduces the sparse random feature method that learns parsimonious random feature models utilizing techniques from compressive sensing .
Revised:  This paper introduces the sparse random feature method that learns parsimonious random feature models . Specifically, we leverage ideas from compressive sensing .
Edit intent: clarity
Original:  We provide uniform bounds on the approximation error  for functions in a  reproducing kernel Hilbert space  depending on the number of samples and the distribution of features.
Revised:  We provide uniform bounds on the approximation error for functions in a reproducing kernel Hilbert space ) depending on the number of samples and the distribution of features.
Edit intent: fluency
Original:   We show that the sparse random feature method outperforms shallow networks for well-structured functions and applications to scientific machine learning tasks.
Revised:  We show that the sparse random feature expansions outperforms shallow networks for well-structured functions and applications to scientific machine learning tasks.
Edit intent: clarity
Original:   We show that the sparse random feature method outperforms shallow networks for well-structured functions and applications to scientific machine learning tasks.
Revised:  We show that the sparse random feature method outperforms shallow networks in several scientific machine learning tasks.
Edit intent: clarity
Original:  In particular, we provide uniform bounds on the approximation error and generalization bounds for functions in a certain class (that is dense in a reproducing kernel Hilbert space) depending on the number of samples and the distribution of features.
Revised:  In particular, we provide generalization bounds for functions in a certain class (that is dense in a reproducing kernel Hilbert space) depending on the number of samples and the distribution of features.
Edit intent: clarity
Original:  The error bounds improve with additional structural conditions, such as coordinate sparsity, compact clusters of the spectrum, or rapid spectral decay.
Revised:  The generalization bounds improve with additional structural conditions, such as coordinate sparsity, compact clusters of the spectrum, or rapid spectral decay.
Edit intent: clarity
Original: Biological systems understand the world by simultaneously processing high-dimensional inputs from modalities as diverse as vision, audition, touch, proprioception, etc.
Revised: Biological systems perceive the world by simultaneously processing high-dimensional inputs from modalities as diverse as vision, audition, touch, proprioception, etc.
Edit intent: clarity
Original:  We show that this architecture performs competitively or beyond strong, specialized models on classification tasks across various modalities: images, point clouds, audio, video  and video+audio.
Revised:  We show that this architecture is competitive with or outperforms strong, specialized models on classification tasks across various modalities: images, point clouds, audio, video and video+audio.
Edit intent: clarity
Original:  We show that this architecture performs competitively or beyond strong, specialized models on classification tasks across various modalities: images, point clouds, audio, video  and video+audio.
Revised:  We show that this architecture performs competitively or beyond strong, specialized models on classification tasks across various modalities: images, point clouds, audio, video , and video+audio.
Edit intent: fluency
Original:  It also surpasses state-of-the-art results for all modalities in AudioSet.
Revised:  It is also competitive in all modalities in AudioSet.
Edit intent: clarity
Original:  To overcome these limitations, we propose Message Passing Simplicial Networks (MPSNs), a class of models that perform message passing on simplicial complexes (SCs) - topological objects generalising graphs to higher dimensions .
Revised:  To overcome these limitations, we propose Message Passing Simplicial Networks (MPSNs), a class of models that perform message passing on simplicial complexes (SCs) .
Edit intent: coherence
Original:  However, a recurring issue with this approach is the existence of trivial constant representations .
Revised:  However, a recurring issue with this approach is the existence of trivial constant solutions .
Edit intent: clarity
Original:  Most current methods avoid such collapsed solutions by careful implementation details.
Revised:  Most current methods avoid such solutions by careful implementation details.
Edit intent: clarity
Original:  A successful approach to SSL is to learn representations which are invariant to distortions of the input sample.
Revised:  A successful approach to SSL is to learn embeddings which are invariant to distortions of the input sample.
Edit intent: clarity
Original:  This causes the representation vectors of distorted versions of a sample to be similar, while minimizing the redundancy between the components of these vectors.
Revised:  This causes the embedding vectors of distorted versions of a sample to be similar, while minimizing the redundancy between the components of these vectors.
Edit intent: clarity
Original:  It allows the use of very high-dimensional output vectors.
Revised:  Intriguingly it benefits from very high-dimensional output vectors.
Edit intent: coherence
Original:  Signaling games, which are often used in existing works, are built on the implicit premise that the player 's belief is public information.
Revised:  Signaling games, which are often used in existing works, are built on the implicit premise that the receiver 's belief is public information.
Edit intent: clarity
Original:  For  precise evaluation of risks arising from cognitive gaps, this paper proposes epistemic signaling games based on the Mertens-Zamir model, which explicitly quantifies players' asymmetric recognition.
Revised:  For a precise evaluation of risks arising from cognitive gaps, this paper proposes epistemic signaling games based on the Mertens-Zamir model, which explicitly quantifies players' asymmetric recognition.
Edit intent: fluency
Original:  We use the peeling algorithm as a tool to compare the performance of random topologies as well as to aid in the synthesis of topologies robust to deadlocks.
Revised:  We use the peeling algorithm as a tool to compare the performance of different topologies as well as to aid in the synthesis of topologies robust to deadlocks.
Edit intent: clarity
Original:  Here we propose simple autoregressive models as highly accurate but computationally extremely efficient generative sequence models.
Revised:  Here we propose simple autoregressive models as highly accurate but computationally efficient generative sequence models.
Edit intent: clarity
Original:  Using these models, we can easily estimate both the model probability of a given sequence, and the size of the functional sequence space related to a specific protein family.
Revised:  Within these models, we can easily estimate both the model probability of a given sequence, and the size of the functional sequence space related to a specific protein family.
Edit intent: coherence
Original:  Using these models, we can easily estimate both the model probability of a given sequence, and the size of the functional sequence space related to a specific protein family.
Revised:  Using these models, we can easily estimate both the probability of a given sequence, and the size of the functional sequence space related to a specific protein family.
Edit intent: clarity
Original:  In the case of response regulators, we find a huge number of ca.  10^{68}  sequences, which nevertheless constitute only the astronomically small fraction 10^{-80} of all amino-acid sequences of the same length.
Revised:  In the example of response regulators, we find a huge number of ca. 10^{68} sequences, which nevertheless constitute only the astronomically small fraction 10^{-80} of all amino-acid sequences of the same length.
Edit intent: clarity
Original:  In the case of response regulators, we find a huge number of ca.  10^{68}  sequences, which nevertheless constitute only the astronomically small fraction 10^{-80} of all amino-acid sequences of the same length.
Revised:  In the case of response regulators, we find a huge number of ca. ~ 10^{68} sequences, which nevertheless constitute only the astronomically small fraction 10^{-80} of all amino-acid sequences of the same length.
Edit intent: clarity
Original:  In the case of response regulators, we find a huge number of ca.  10^{68}  sequences, which nevertheless constitute only the astronomically small fraction 10^{-80} of all amino-acid sequences of the same length.
Revised:  In the case of response regulators, we find a huge number of ca. 10^{68} possible sequences, which nevertheless constitute only the astronomically small fraction 10^{-80} of all amino-acid sequences of the same length.
Edit intent: clarity
Original:  ~ 10^{68} possible sequences, which nevertheless constitute only the astronomically small fraction 10^{-80} of all amino-acid sequences of the same length.
Revised:  10^{68} possible sequences, which nevertheless constitute only the astronomically small fraction 10^{-80} of all amino-acid sequences of the same length.
Edit intent: fluency
Original: Since the 1950s, citation impact has been the dominant metric by which science is quantitatively evaluated.
Revised: Since the 1950s, citation number or "impact" has been the dominant metric by which science is quantitatively evaluated.
Edit intent: clarity
Original:  2) novel papers are more likely to become "sleeping beauties" and accumulate citation impact over the long run ;
Revised:  2) novel papers are more likely to become "sleeping beauties" , accumulating surprising attention and citation impact over the long run ;
Edit intent: clarity
Original:  3) novelty can be reformulated as distance in journal embedding spaces to map the moving frontier of science .
Revised:  3) novelty can be reformulated as the combination of ideas across knowledge space to reveal the combinatorial nature of advance .
Edit intent: clarity
Original:  The evolution of embedding spaces over time reveals how yesterday's novelty forms today's scientific conventions, which condition the novelty--and surprise--of tomorrow's breakthroughs.
Revised:  The evolution of knowledge space over time characterizes how yesterday's novelty forms today's scientific conventions, which condition the novelty--and surprise--of tomorrow's breakthroughs.
Edit intent: clarity
Original:  The evolution of embedding spaces over time reveals how yesterday's novelty forms today's scientific conventions, which condition the novelty--and surprise--of tomorrow's breakthroughs.
Revised:  The evolution of embedding spaces over time reveals how yesterday's novelty forms today's scientific conventions, which condition the novelty-and surprise-of tomorrow's breakthroughs.
Edit intent: fluency
Original:  The evolution of knowledge space over time characterizes how yesterday's novelty forms today's scientific conventions, which condition the novelty-and surprise-of tomorrow's breakthroughs  .
Revised:  The evolution of this knowledge space characterizes how yesterday's novelty forms today's scientific conventions, which condition the novelty-and surprise-of tomorrow's breakthroughs .
Edit intent: clarity
Original:  The evolution of knowledge space over time characterizes how yesterday's novelty forms today's scientific conventions, which condition the novelty-and surprise-of tomorrow's breakthroughs  .
Revised:  The evolution of knowledge space over time characterizes how yesterday's novelty forms today's scientific conventions, which condition the novelty--and surprise--of tomorrow's breakthroughs .
Edit intent: fluency
Original: Science is built upon scholarship consensus that changes over time.
Revised: Science is built on the scholarly consensus that shifts with time.
Edit intent: clarity