wanyu/IteraTeR_full_sent huggingface dataset:
Original:  With the help of  functional networks, neural decoding, and deep learning based multi-voxel pattern analysis (MVPA) of individual cognitive component , we arrived at the conclusion that  core affect is unable to provide varieties of emotions unless coupled with cortical cognitive functions such as autobiographical memory, dmn, self-referential, social, tom and salient event detection.
Revised:  With the help of functional networks, we have decoded cognitive functions for 12 different basic and complex emotion conditions. Using transfer learning in deep neural architecture , we arrived at the conclusion that core affect is unable to provide varieties of emotions unless coupled with cortical cognitive functions such as autobiographical memory, dmn, self-referential, social, tom and salient event detection.
Edit intent: meaning-changed
Original:  With the help of  functional networks, neural decoding, and deep learning based multi-voxel pattern analysis (MVPA) of individual cognitive component , we arrived at the conclusion that  core affect is unable to provide varieties of emotions unless coupled with cortical cognitive functions such as autobiographical memory, dmn, self-referential, social, tom and salient event detection.
Revised:  With the help of functional networks, neural decoding, and deep learning based multi-voxel pattern analysis (MVPA) of individual cognitive component , we arrived at the conclusion that the core affect is unable to provide varieties of emotions unless coupled with cortical cognitive functions such as autobiographical memory, dmn, self-referential, social, tom and salient event detection.
Edit intent: fluency
Original:  In this paper, we present Anteater, an interactive visualization system for tracing and exploring the execution of a program. While existing debugging tools often have visualization components , these components are often added on top of an existing environment.
Revised:  In this paper, we present Anteater, an interactive visualization system for tracing and exploring the execution of Python programs. Existing systems often have visualization components , these components are often added on top of an existing environment.
Edit intent: clarity
Original:  While existing debugging tools often have visualization components , these components are often added on top of an existing environment. In Anteater, in contrast, visualization is a driving concern. We answer the following question: what should a debugging tool look like if it were designed from the ground up to support interactive visualization principles? Anteater automatically instruments source code to capture execution behavior along with variables and expressions specified by the user. After generating the execution trace, Anteater presents the execution information through interactive visualizations . Anteater supports interactions that help with tasks such as discovering important structures in the execution , learning dependencies, and understanding and debugging unexpected behaviors.
Revised:  While existing debugging tools often have visualization components , these components are often added on top of an existing infrastructure. In contrast, URLanization of trace data enables an intermediate representation which can be leveraged to automatically synthesize a variety of visualizations and interactions. These interactive visualizations help with tasks such as discovering important structures in the execution , learning dependencies, and understanding and debugging unexpected behaviors.
Edit intent: clarity
Original:  We derive three novel surprised-based algorithms, one in the family of particle filters, one in the family of variational learning, and the other in the family of message passing, that are biologically plausible, have constant scaling in observation sequence length and particularly simple update dynamics for any distribution in the exponential family.
Revised:  We derive three novel surprised-based algorithms, one in the family of particle filters, one in the family of variational learning, and the other in the family of message passing, that have constant scaling in observation sequence length and particularly simple update dynamics for any distribution in the exponential family.
Edit intent: coherence
Original: We study the system of heterogeneous interbank lending and borrowing based on the relative average of log-capitalization through the linear combination of the average within groups and the ensemble average and describe the evolution of log-capitalization by a system of coupled diffusions.
Revised: We study the system of heterogeneous interbank lending and borrowing based on the relative average of log-capitalization given by the linear combination of the average within groups and the ensemble average and describe the evolution of log-capitalization by a system of coupled diffusions.
Edit intent: clarity
Original:  The model incorporates a game feature with homogeneity within groups and heterogeneity between groups where banks search for the optimal lending or borrowing strategies and intend to minimize the heterogeneous linear quadratic costs in order to remain survival in the system .
Revised:  The model incorporates a game feature with homogeneity within groups and heterogeneity between groups where banks search for the optimal lending or borrowing strategies through minimizing the heterogeneous linear quadratic costs in order to remain survival in the system .
Edit intent: clarity
Original:  The model incorporates a game feature with homogeneity within groups and heterogeneity between groups where banks search for the optimal lending or borrowing strategies and intend to minimize the heterogeneous linear quadratic costs in order to remain survival in the system .
Revised:  The model incorporates a game feature with homogeneity within groups and heterogeneity between groups where banks search for the optimal lending or borrowing strategies and intend to minimize the heterogeneous linear quadratic costs in order to avoid to approach the default barrier .
Edit intent: meaning-changed
Original:  The existence of the equilibria in the case of the sufficiently large number of banks  is guaranteed by the solvability for the coupled Riccati equations as the number of banks goes to infinity in each group.
Revised:  The existence of the equilibria in the two-group case where the number of banks is guaranteed by the solvability for the coupled Riccati equations as the number of banks goes to infinity in each group.
Edit intent: meaning-changed
Original:  The existence of the equilibria in the case of the sufficiently large number of banks  is guaranteed by the solvability for the coupled Riccati equations as the number of banks goes to infinity in each group.
Revised:  The existence of the equilibria in the case of the sufficiently large number of banks are sufficiently large is guaranteed by the solvability for the coupled Riccati equations as the number of banks goes to infinity in each group.
Edit intent: meaning-changed
Original:  Finally, In the financial implication, we observe the Nash equilibria governed by the mean-reverting term and the linear combination of the ensemble averages of individual groups and study the influence of the relative parameters on the liquidity rate through the numerical analysis.
Revised:  Finally, in the financial implication, we observe the Nash equilibria governed by the mean-reverting term and the linear combination of the ensemble averages of individual groups and study the influence of the relative parameters on the liquidity rate through the numerical analysis.
Edit intent: fluency
Original: The scientific study of consciousness is a new field which has emerged as a response to groundbreaking developments in neuroscience, cognitive psychology and analytic philosophy. Its aim is to develop a scientific account, formulated in terms of formal mathematical laws or regularities, of how conscious experience relates to  the physical domain (e. g. to brain processes).
Revised: In recent years, promising mathematical models have been suggested which aim to the physical domain (e. g. to brain processes).
Edit intent: clarity
Original:  Its aim is to develop a scientific account, formulated in terms of formal mathematical laws or regularities, of how conscious experience relates to  the physical domain (e. g. to brain processes).
Revised:  Its aim is to develop a scientific account, formulated in terms of formal mathematical laws or regularities, of how conscious experience relates to describe conscious experience and its relation to the physical domain (e. g. to brain processes).
Edit intent: meaning-changed
Original:  Its aim is to develop a scientific account, formulated in terms of formal mathematical laws or regularities, of how conscious experience relates to  the physical domain (e. g. to brain processes). Even though several models of consciousness have been proposed in the literature, details of the underlying conceptual terminology and formal framework remain poorly understood. This paper aims to improve this situationby proposing a grounding of the scientific study of consciousness which is based on a concise definition of the object of investigation and gives rise to a clear-cut mathematical framework for models of consciousness . Several examples are studied and an application of this framework is given.
Revised:  Its aim is to develop a scientific account, formulated in terms of formal mathematical laws or regularities, of how conscious experience relates to the physical domain . Whereas the axioms and metaphysical ideas of these theories have been carefully motivated, their mathematical formalism has not. In this article we aim to remedy this situation. We give an account of what warrants mathematical representation of phenomenal experience, derive a general mathematical framework which takes into account consciousness' epistemic context and study which mathematical structures some of the key characteristics of conscious experience imply, showing precisely where mathematical approaches allow to go beyond what the standard methodology can do. The result is a general mathematical framework for models of consciousness . Several examples are studied and an application of this framework is given.
Edit intent: meaning-changed
Original:  This paper aims to improve this situationby proposing a grounding of the scientific study of consciousness which is based on a concise definition of the object of investigation and gives rise to a clear-cut mathematical framework for models of consciousness . Several examples are studied and an application of this framework is given. The underlying definitions are a further development of the grounding of the scientific study of consciousness developed by David Chalmers and Thomas Nagel .
Revised:  This paper aims to improve this situationby proposing a grounding of the scientific study of consciousness which is based on a concise definition of the object of investigation and gives rise to a clear-cut mathematical framework for models of consciousness that can be employed in the theory-building process .
Edit intent: clarity
Original: In this paper, we develop a theory of common decomposition for two correlated Brownian motions, in which, by using change of time method, the correlated Brownian motions are represented by a triple of processes, (X,Y,T), where X and Y are independent Brownian motions.
Revised: In this paper, we develop a theory of common decomposition for two correlated Brownian motions, in which, by using change of time method, the correlated Brownian motions are represented by a triplet of processes, (X,Y,T), where X and Y are independent Brownian motions.
Edit intent: fluency
Original:  Solvable \rho's are given by \rho = - \cos \left( \pi{k} \right), where k \in Z^+ \cup \{ -1 \}.
Revised:  Solvable \rho's are given by \rho = - \cos \left( \pi{k} \right), where k \in Z^+ \cup \{ +\infty \}.
Edit intent: meaning-changed
Original:  After reading the paper, the audience will understand seven benchmarking principles, generally know that differential characteristics of mainstream AI devices, qualitatively compare deep learning hardware through our 12-metric approach for benchmarking hardware, and read benchmarking results of 16 deep learning frameworks via our 7-metric set for benchmarking frameworks.
Revised:  Because MLPerf is a URLanization working with industry and academia, and offering deep learning benchmarks that evaluate training and inference on deep learning hardware devices, the survey also mentions MLPerf benchmark results, benchmark metrics, datasets, deep learning frameworks and algorithms. We summarize seven benchmarking principles, generally know that differential characteristics of mainstream AI devices, qualitatively compare deep learning hardware through our 12-metric approach for benchmarking hardware, and read benchmarking results of 16 deep learning frameworks via our 7-metric set for benchmarking frameworks.
Edit intent: meaning-changed
Original:  After reading the paper, the audience will understand seven benchmarking principles, generally know that differential characteristics of mainstream AI devices, qualitatively compare deep learning hardware through our 12-metric approach for benchmarking hardware, and read benchmarking results of 16 deep learning frameworks via our 7-metric set for benchmarking frameworks.
Revised:  After reading the paper, the audience will understand seven benchmarking principles, differential characteristics of mainstream AI devices, qualitatively compare deep learning hardware through our 12-metric approach for benchmarking hardware, and read benchmarking results of 16 deep learning frameworks via our 7-metric set for benchmarking frameworks.
Edit intent: coherence
Original:  After reading the paper, the audience will understand seven benchmarking principles, generally know that differential characteristics of mainstream AI devices, qualitatively compare deep learning hardware through our 12-metric approach for benchmarking hardware, and read benchmarking results of 16 deep learning frameworks via our 7-metric set for benchmarking frameworks.
Revised:  After reading the paper, the audience will understand seven benchmarking principles, generally know that differential characteristics of mainstream AI devices, and qualitative comparison of deep learning hardware and frameworks.
Edit intent: clarity
Original: We provide a mathematical analysis of an election system proposed by the eminent logician Gottlob Frege (1848--1925) . His proposal was written presumably in 1918, was (re)discovered around the turn of the millennium, and published for the first time in the original German in 2000. A remarkable feature of Frege's proposal is its concern for the representation of minorities and its sensitivity to past election results.
Revised: We provide a mathematical analysis of an election system proposed by the eminent logician Gottlob Frege (1848--1925) was rediscovered in the Th\"uringer Universit\"ats- und Landesbibliothek in Jena, Germany. Frege's proposal is its concern for the representation of minorities and its sensitivity to past election results.
Edit intent: coherence
Original:  A remarkable feature of Frege's proposal is its concern for the representation of minorities and its sensitivity to past election results. Frege's proposal is based on some highly original and relevant ideas; his core idea is that the votes of unelected candidates are carried over to the next election .
Revised:  A remarkable feature of Frege's proposal is its concern for the representation of minorities . Its core idea is that the votes of unelected candidates are carried over to the next election .
Edit intent: coherence
Original:  his core idea is that the votes of unelected candidates are carried over to the next election . All candidates thus accumulate votes over time and eventually each candidate is elected at some point. We provide a mathematical formulation of Frege's election system and investigate how well it achieves its aim of a fair representation of all political opinions in a community over time.
Revised:  his core idea is that the votes of unelected candidates are carried over to the next election , while the elected candidates incur a cost of winning. We prove that this sensitivity to past elections guarantees a proportional representation of political opinions over time.
Edit intent: meaning-changed
Original:  We can prove that this goal is fulfilled remarkably well. However, we also show that, in other aspects, it falls short of Frege's high ambition that no voter's vote be lost. We propose a slight modification of his voting rule, the modified Frege method, that remedies these shortcomings.
Revised:  We find that through a slight modification of his voting rule, the modified Frege method, that remedies these shortcomings.
Edit intent: clarity
Original:  We propose a slight modification of his voting rule, the modified Frege method, that remedies these shortcomings. We analyse both methods from the perspective of modern social choice and apportionment theory, and can show that they are novel contributions with noteworthy proportionality properties over time .
Revised:  We propose a slight modification of the original voting method even stronger forms of proportionality can be achieved. This modified version of Frege's method can also be seen as providing a novel solution to the apportionment problem. We prove that it is distinct from all of the best-known apportionment methods, while it still possesses noteworthy proportionality properties over time .
Edit intent: meaning-changed
Original:  This modified version of Frege's method can also be seen as providing a novel solution to the apportionment problem . We prove that it is distinct from all of the best-known apportionment methods, while it still possesses noteworthy proportionality properties.
Revised:  This modified version of Frege's method can also be seen as providing a novel solution to the apportionment problem , which is distinct from all of the best-known apportionment methods, while it still possesses noteworthy proportionality properties.
Edit intent: coherence
Original:  This study formulates a portfolio trading process as a Markov decision process in which the agent can learn about the financial market environment, and it identifies a deep neural network structure as an approximation of the Q-function. To ensure applicability to real-world trading , we devise three novel techniques that are both reasonable and implementable. First, the agent's action space is modeled as a combinatorial action space of trading directions with prespecified trading sizes for each asset . Second, we introduce a mapping function that can replace an initially-determined action that may be infeasible with a feasible action that is reasonably close to the original, ideal action.
Revised:  This study formulates a portfolio trading process as a Markov decision process model for the portfolio trading process, and the model adopts a discrete combinatorial action space of trading directions with prespecified trading sizes for each asset . Second, we introduce a mapping function that can replace an initially-determined action that may be infeasible with a feasible action that is reasonably close to the original, ideal action.
Edit intent: clarity
Original:  First, the agent's action space is modeled as a combinatorial action space of trading directions with prespecified trading sizes for each asset . Second, we introduce a mapping function that can replace an initially-determined action that may be infeasible with a feasible action that is reasonably close to the original, ideal action.
Revised:  First, the agent's action space is modeled as a combinatorial action space , determining the trading direction at prespecified trading size for each asset . Second, we introduce a mapping function that can replace an initially-determined action that may be infeasible with a feasible action that is reasonably close to the original, ideal action.
Edit intent: clarity
Original:  First, the agent's action space is modeled as a combinatorial action space of trading directions with prespecified trading sizes for each asset . Second, we introduce a mapping function that can replace an initially-determined action that may be infeasible with a feasible action that is reasonably close to the original, ideal action.
Revised:  First, the agent's action space is modeled as a combinatorial action space of trading directions with prespecified trading sizes for each asset , to ensure practical applicability. Our novel portfolio trading strategy takes advantage of three features to outperform in real-world trading. First, a mapping function that can replace an initially-determined action that may be infeasible with a feasible action that is reasonably close to the original, ideal action.
Edit intent: meaning-changed
Original:  First, the agent's action space is modeled as a combinatorial action space of trading directions with prespecified trading sizes for each asset . Second, we introduce a mapping function that can replace an initially-determined action that may be infeasible with a feasible action that is reasonably close to the original, ideal action.
Revised:  First, the agent's action space is modeled as a combinatorial action space of trading directions with prespecified trading sizes for each asset . Second, we introduce a mapping function is devised to handle and transform an initially found but infeasible action into a feasible action that is reasonably close to the original, ideal action.
Edit intent: meaning-changed
Original:  First, the agent's action space is modeled as a combinatorial action space of trading directions with prespecified trading sizes for each asset . Second, we introduce a mapping function that can replace an initially-determined action that may be infeasible with a feasible action that is reasonably close to the original, ideal action.
Revised:  First, the agent's action space is modeled as a combinatorial action space of trading directions with prespecified trading sizes for each asset . Second, we introduce a mapping function that can replace an initially-determined action that may be infeasible with a feasible action closest to the originally proposed ideal action.
Edit intent: clarity
Original:  Last, we introduce a technique by which an agent simulates all feasible actions in each state and learns about these experiences to derive a multi-asset trading strategy that best reflects financial data .
Revised:  Second, by overcoming the dimensionality problem, this study establishes models of agent and Q-network for deriving a multi-asset trading strategy in the predefined action space. Last, this study introduces a technique that has the advantage of deriving a well-fitted multi-asset trading strategy by designing an agent to simulate all feasible actions in each state and learns about these experiences to derive a multi-asset trading strategy that best reflects financial data .
Edit intent: meaning-changed
Original: We propose an aggregation scheme for methods that control the false discovery rate (FDR). Our scheme retains the underlying methods' FDR guarantees in theory and can decrease FDR and increase power in practice .
Revised: Recent discoveries suggest that our gut microbiome plays an important role in our health and wellbeing. However, the gut microbiome data are intricate; for example, the microbial diversity in the gut makes the data high-dimensional. While there are dedicated high-dimensional methods, such as the lasso estimator, they always come with the risk of false discoveries. Knockoffs are a recent approach to control the number of false discoveries. In this paper, we show that knockoffs can be aggregated to increase power while retaining sharp control over the false discoveries. We support our method both in theory and can decrease FDR and increase power in practice .
Edit intent: meaning-changed