wanyu/IteraTeR_v2 huggingface dataset:
Original:  For piecewise analytic functions, we demonstrate that the convergence rate of the Gegenbauer projection of degree n is the same as that of the best approximation of the same degree when \lambda%DIFDELCMD < \leq1 %%% and the former is slower than the latter by a factor of n  ^{\lambda-1} when \lambda > 1.
Revised:  For piecewise analytic functions, we demonstrate that the convergence rate of the Gegenbauer projection of degree n is the same as that of the best approximation of the same degree when \lambda%DIFDELCMD < \leq1 %%% and the former is slower than the latter by a factor of n ^{\lambda ^{\lambda-1} when \lambda > 1.
Edit intent: fluency
Original: The gradual accumulation of damage and dysregulation during the aging of living organisms is readily quantified.
Revised: The gradual accumulation of damage and dysregulation during the aging of living organisms can be quantified.
Edit intent: clarity
Original:  In this perspective, we outline where we have been, where we are, and where we hope to go in computational models of aging.
Revised:  In this perspective, we outline where we have been, where we are, and where we hope to go with such computational models of aging.
Edit intent: clarity
Original:  To do so, we propose a metric of \emph{community membership consistency , that provides node-level insights in how reliable the placement of that node into a community really is.
Revised:  To do so, we propose a metric of \emph{community membership consistency , that provides node-level insights in how reliable the placement of that node into a community really is.
Edit intent: fluency
Original:  In addition, it enables us to distinguish the community core members of a community.
Revised:  In addition, it enables us to distinguish the community core members of a community.
Edit intent: fluency
Original:  The usefulness  the proposed metrics is demonstrated on corporate board interlock networks, in which weighted links represent shared senior level directors between firms.
Revised:  The usefulness of the proposed metrics is demonstrated on corporate board interlock networks, in which weighted links represent shared senior level directors between firms.
Edit intent: fluency
Original:  Moreover, over-reliance on labeled data when training supervised learning models can lead to unexpected results and open vulnerabilities for adversarial attacks.
Edit intent: coherence
Original: This paper examines Fama's (1970) semi-strong form efficient market hypothesis (EMH) in the prewar Japanese stock market using a new dataset.
Revised: This paper examines Fama's (1970) semi-strong form market efficiency using a new dataset.
Edit intent: clarity
Original:  We particularly focus on the relationship between the prewar Japanese stock market and several government policy interventions to explore whether the semi-strong form stock market efficiency evolves over time.
Revised:  We particularly focus on the relationship between the prewar Japanese financial market and several government policy interventions to explore whether the semi-strong form stock market efficiency evolves over time.
Edit intent: clarity
Original:  We particularly focus on the relationship between the prewar Japanese stock market and several government policy interventions to explore whether the semi-strong form stock market efficiency evolves over time.
Revised:  We particularly focus on the relationship between the prewar Japanese stock market and several government policy interventions to explore whether the semi-strong form market efficiency evolves over time.
Edit intent: fluency
Original:  Therefore, we conclude that Lo's (2004) adaptive market hypothesis is supported in the prewar Japanese stock market even if we consider that the public information affects the stock market.
Revised:  Therefore, we conclude that Lo's (2004) adaptive market hypothesis is supported in the prewar Japanese financial market even if we consider that the public information affects the stock market.
Edit intent: clarity
Original:  An L_2 error bound and a uniform error bound are derived, providing similar information that Tikhonov regularization is able to reduce  operator norm (Lebesgue constants ) and the error term related to the level of noise, both by multiplying a correction factor which is less than one.
Revised:  An L_2 error bound and a uniform error bound are derived, providing similar information that Tikhonov regularization is able to reduce the operator norm (Lebesgue constants ) and the error term related to the level of noise, both by multiplying a correction factor which is less than one.
Edit intent: fluency
Original:  An L_2 error bound and a uniform error bound are derived, providing similar information that Tikhonov regularization is able to reduce  operator norm (Lebesgue constants ) and the error term related to the level of noise, both by multiplying a correction factor which is less than one.
Revised:  An L_2 error bound and a uniform error bound are derived, providing similar information that Tikhonov regularization is able to reduce operator norm (Lebesgue constant ) and the error term related to the level of noise, both by multiplying a correction factor which is less than one.
Edit intent: fluency
Original: A simple mathematical model for estimating the risk of airborne transmission of a respiratory infection such as COVID-19  is presented.
Revised: A simple mathematical model for estimating the risk of airborne transmission of a respiratory infection such as COVID-19 , is presented.
Edit intent: fluency
Original: A simple mathematical model for estimating the risk of airborne transmission of a respiratory infection such as COVID-19, is presented.
Revised: A mathematical model for estimating the risk of airborne transmission of a respiratory infection such as COVID-19, is presented.
Edit intent: clarity
Original: Exposed Buffer Architecture addresses network ossification by confronting the virtualization that is inherent to the Internet architecture.
Revised: Exposed Buffer Architecture addresses the problem of creating a programmable service platform for the digital continuum by reexamining the particular form of virtualization that is inherent to the Internet architecture.
Edit intent: clarity
Original:  Aggregating these low level resources in the implementation of IP to implement wide area services serves two different purposes: 1) It virtualizes local services, enabling interoperability through the adoption of a common model, and 2) It hides the topology of local infrastructure.
Revised:  Aggregating these low level resources in the implementation of IP to create wide area services serves two different purposes: 1) It virtualizes local services, enabling interoperability through the adoption of a common model, and 2) It hides the topology of local infrastructure.
Edit intent: clarity
Original:  The premise of Exposed Buffer Architecture is that we can separate these two tasks  .
Revised:  The main premise of ExposedBuffer Architecture is that we can separate these two tasks .
Edit intent: coherence
Original:  They can be used by compilers to make heuristic decisions, by superoptimizers as an minimization objective, or by autotuners to find an optimal configuration of a specific program.
Revised:  They can be used by compilers to make heuristic decisions, by superoptimizers as a minimization objective, or by autotuners to find an optimal configuration of a specific program.
Edit intent: fluency
Original:  They can be used by compilers to make heuristic decisions, by superoptimizers as an minimization objective, or by autotuners to find an optimal configuration of a specific program.
Revised:  They can be used by compilers to make heuristic decisions, by superoptimizers as an minimization objective, or by autotuners to find an optimal configuration for a specific program.
Edit intent: fluency
Original:  However, in order to achieve scalability, existing MARL methods either limit representation expressiveness of their value function classes or relax the IGM consistency, which may  lead to poor policies or even divergence .
Revised:  However, in order to achieve scalability, existing MARL methods either limit representation expressiveness of their value function classes or relax the IGM consistency, which may lead to poor performance .
Edit intent: clarity
Original:  This paper presents a novel MARL approach, called duPLEX dueling multi-agent Q-learning (QPLEX), that takes a duplex dueling network architecture to factorize the joint value function.
Revised:  This paper presents a novel MARL approach, called duPLEX dueling multi-agent Q-learning (QPLEX), which takes a duplex dueling network architecture to factorize the joint value function.
Edit intent: coherence
Original:  This duplex dueling architecture transforms the IGM principle to easily realized constraints on advantage functions and thus enables efficient value function learning.
Revised:  This duplex dueling structure encodes the IGM principle to easily realized constraints on advantage functions and thus enables efficient value function learning.
Edit intent: clarity
Original:  Theoretical analysis shows that QPLEX solves a rich classof tasks . Empirical experiments on StarCraft II unit micromanagement tasks demonstrate that QPLEX significantly outperforms state-of-the-art baselines in both online and offline task settings, and also reveal that QPLEX achieves high sample efficiency and can benefit from offline datasets without additional  exploration.
Revised:  Theoretical analysis shows that QPLEX solves a rich classof tasks . Empirical experiments on StarCraft II micromanagement tasks demonstrate that QPLEX significantly outperforms state-of-the-art baselines in both online and offline task settings, and also reveal that QPLEX achieves high sample efficiency and can benefit from offline datasets without additional exploration.
Edit intent: clarity
Original:  Theoretical analysis shows that QPLEX solves a rich classof tasks . Empirical experiments on StarCraft II unit micromanagement tasks demonstrate that QPLEX significantly outperforms state-of-the-art baselines in both online and offline task settings, and also reveal that QPLEX achieves high sample efficiency and can benefit from offline datasets without additional  exploration.
Revised:  Theoretical analysis shows that QPLEX solves a rich classof tasks . Empirical experiments on StarCraft II unit micromanagement tasks demonstrate that QPLEX significantly outperforms state-of-the-art baselines in both online and offline data collection settings, and also reveal that QPLEX achieves high sample efficiency and can benefit from offline datasets without additional exploration.
Edit intent: clarity
Original:  Theoretical analysis shows that QPLEX solves a rich classof tasks . Empirical experiments on StarCraft II unit micromanagement tasks demonstrate that QPLEX significantly outperforms state-of-the-art baselines in both online and offline task settings, and also reveal that QPLEX achieves high sample efficiency and can benefit from offline datasets without additional  exploration.
Revised:  Theoretical analysis shows that QPLEX solves a rich classof tasks . Empirical experiments on StarCraft II unit micromanagement tasks demonstrate that QPLEX significantly outperforms state-of-the-art baselines in both online and offline task settings, and also reveal that QPLEX achieves high sample efficiency and can benefit from offline datasets without additional online exploration.
Edit intent: clarity
Original:  However, in order to achieve scalability, existing MARL methods either limit representation expressiveness of their value function classes or relax the IGM consistency, which may suffer from instability risk or lead to poor performance .
Revised:  However, in order to achieve scalability, existing MARL methods either limit representation expressiveness of their value function classes or relax the IGM consistency, which may suffer from instability risk or may not perform well in complex domains .
Edit intent: clarity
Original:  For this purpose, we adapt HR-Net to octree-based convolutional neural networks for jointly encoding shape and point features with fused multiresolution subnetworks and design a simple-yet-efficient Multiresolution Instance Discrimination (MID) loss for jointly learning the shape and point features.
Revised:  For this purpose, we adapt HR-Net to octree-based convolutional neural networks for jointly encoding shape and point features with fused multiresolution subnetworks and design a simple-yet-efficient Multiresolution Instance Discrimination (MID) loss for jointly learning the shape and point features.
Edit intent: fluency
Original:  The regulation of gene expression is managed through a variety of methods including epigentic processes (e.g., DNA methylation).
Revised:  The regulation of gene expression is managed through a variety of methods including epigenetic processes (e.g., DNA methylation).
Edit intent: clarity
Original:   Beisegel, Chudovsky, Gurvich, Milanic, and Servatius (WADS 2019) conjectured that every graph that contains an induced k-vertex path also contains an avoidable induced path of the same length, and proved the result for k = 2 (the case k = 1 was known before).
Revised:  Beisegel, Chudovsky, Gurvich, Milanic, and Servatius conjectured that every graph that contains an induced k-vertex path also contains an avoidable induced path of the same length, and proved the result for k = 2 (the case k = 1 was known before).
Edit intent: coherence
Original:   Beisegel, Chudovsky, Gurvich, Milanic, and Servatius (WADS 2019) conjectured that every graph that contains an induced k-vertex path also contains an avoidable induced path of the same length, and proved the result for k = 2 (the case k = 1 was known before).
Revised:  Beisegel, Chudovsky, Gurvich, Milanic, and Servatius (WADS 2019) conjectured that every graph that contains an induced k-vertex path also contains an avoidable induced path of the same length, and proved the result for k = 2. The case k = 1 was known before).
Edit intent: coherence
Original:  Here we strengthen their result and show that every induced path can be shifted to an avoidable one  .
Revised:  Here we strengthen their result and show that every induced path can be transformed to an avoidable one .
Edit intent: clarity
Original:  We also prove analogous results for the non-induced case and for the case of walks, and show that the statement cannot be extended to trails or to isometric paths.
Revised:  We also obtain analogous results for the non-induced case and for the case of walks, and show that the statement cannot be extended to trails or to isometric paths.
Edit intent: clarity
Original:  We also prove analogous results for the non-induced case and for the case of walks, and show that the statement cannot be extended to trails or to isometric paths.
Revised:  We also prove analogous results for not necessarily induced paths and for walks. In contrast, the statement cannot be extended to trails or to isometric paths.
Edit intent: coherence
Original: We present the Surrogate-gradient Online Error-triggered Learning (SOEL) system for online few-shot learningon neuromorphic processors.
Revised: We present the Surrogate-gradient Online Error-triggered Learning (SOEL) system for online few-shot learning on neuromorphic processors.
Edit intent: fluency
Original:  The SOEL learning system usesa combination of transfer learning and principles of computa-tional neuroscience and deep learning.
Revised:  The SOEL learning system uses a combination of transfer learning and principles of computa-tional neuroscience and deep learning.
Edit intent: fluency
Original:  The SOEL learning system usesa combination of transfer learning and principles of computa-tional neuroscience and deep learning.
Revised:  The SOEL learning system usesa combination of transfer learning and principles of computational neuroscience and deep learning.
Edit intent: fluency
Original:  We show that partiallytrained deep Spiking Neural Networks (SNNs) implemented onneuromorphic hardware can rapidly adapt online to new classesof data within a domain.
Revised:  We show that partially trained deep Spiking Neural Networks (SNNs) implemented onneuromorphic hardware can rapidly adapt online to new classesof data within a domain.
Edit intent: fluency
Original:  We show that partiallytrained deep Spiking Neural Networks (SNNs) implemented onneuromorphic hardware can rapidly adapt online to new classesof data within a domain.
Revised:  We show that partiallytrained deep Spiking Neural Networks (SNNs) implemented on neuromorphic hardware can rapidly adapt online to new classesof data within a domain.
Edit intent: fluency
Original:  We show that partiallytrained deep Spiking Neural Networks (SNNs) implemented onneuromorphic hardware can rapidly adapt online to new classesof data within a domain.
Revised:  We show that partiallytrained deep Spiking Neural Networks (SNNs) implemented onneuromorphic hardware can rapidly adapt online to new classes of data within a domain.
Edit intent: fluency
Original:  SOEL updates trigger when an erroroccurs , enabling faster learning with fewer updates.
Revised:  SOEL updates trigger when an error occurs , enabling faster learning with fewer updates.
Edit intent: fluency
Original:  Using gesturerecognition as a case study, we show SOEL can be used for onlinefew-shot learning of new classes of pre-recorded gesture data andrapid online learning of new gestures from data streamed livefrom a Dynamic Active-pixel Vision Sensor to an Intel Loihineuromorphic research processor.
Revised:  Using gesture recognition as a case study, we show SOEL can be used for onlinefew-shot learning of new classes of pre-recorded gesture data andrapid online learning of new gestures from data streamed livefrom a Dynamic Active-pixel Vision Sensor to an Intel Loihineuromorphic research processor.
Edit intent: fluency
Original:  Using gesturerecognition as a case study, we show SOEL can be used for onlinefew-shot learning of new classes of pre-recorded gesture data andrapid online learning of new gestures from data streamed livefrom a Dynamic Active-pixel Vision Sensor to an Intel Loihineuromorphic research processor.
Revised:  Using gesturerecognition as a case study, we show SOEL can be used for online few-shot learning of new classes of pre-recorded gesture data andrapid online learning of new gestures from data streamed livefrom a Dynamic Active-pixel Vision Sensor to an Intel Loihineuromorphic research processor.
Edit intent: fluency
Original:  Using gesturerecognition as a case study, we show SOEL can be used for onlinefew-shot learning of new classes of pre-recorded gesture data andrapid online learning of new gestures from data streamed livefrom a Dynamic Active-pixel Vision Sensor to an Intel Loihineuromorphic research processor.
Revised:  Using gesturerecognition as a case study, we show SOEL can be used for onlinefew-shot learning of new classes of pre-recorded gesture data and rapid online learning of new gestures from data streamed livefrom a Dynamic Active-pixel Vision Sensor to an Intel Loihineuromorphic research processor.
Edit intent: fluency
Original:  Using gesturerecognition as a case study, we show SOEL can be used for onlinefew-shot learning of new classes of pre-recorded gesture data andrapid online learning of new gestures from data streamed livefrom a Dynamic Active-pixel Vision Sensor to an Intel Loihineuromorphic research processor.
Revised:  Using gesturerecognition as a case study, we show SOEL can be used for onlinefew-shot learning of new classes of pre-recorded gesture data andrapid online learning of new gestures from data streamed live from a Dynamic Active-pixel Vision Sensor to an Intel Loihineuromorphic research processor.
Edit intent: fluency
Original:  Using gesturerecognition as a case study, we show SOEL can be used for onlinefew-shot learning of new classes of pre-recorded gesture data andrapid online learning of new gestures from data streamed livefrom a Dynamic Active-pixel Vision Sensor to an Intel Loihineuromorphic research processor.
Revised:  Using gesturerecognition as a case study, we show SOEL can be used for onlinefew-shot learning of new classes of pre-recorded gesture data andrapid online learning of new gestures from data streamed livefrom a Dynamic Active-pixel Vision Sensor to an Intel Loihi neuromorphic research processor.
Edit intent: fluency
Original:  The task is to model students  mastery level of knowledge  based on their responses to the questions in the past, as well as predict the probabilities that they correctly answer subsequent questions in the future.
Revised:  The task is to model students ' mastery level of knowledge based on their responses to the questions in the past, as well as predict the probabilities that they correctly answer subsequent questions in the future.
Edit intent: fluency
Original:  The forgetting curve theorystates that human memory retention declines over time, therefore knowledge states should be mostly affected by the recent questions . Based on this observation , we propose a Convolutional Knowledge Tracing ( CKT ) model in this paper.
Revised:  The forgetting curve theorystates that human memory retention declines over time, therefore knowledge states should be mostly affected by the recent questions . Based on this theory , we propose a Convolutional Knowledge Tracing ( CKT ) model in this paper.
Edit intent: clarity
Original:  The forgetting curve theorystates that human memory retention declines over time, therefore knowledge states should be mostly affected by the recent questions . Based on this observation , we propose a Convolutional Knowledge Tracing ( CKT ) model in this paper.
Revised:  The forgetting curve theorystates that human memory retention declines over time, therefore knowledge states should be mostly affected by the recent questions . Based on this observation , we propose a Convolution-Augmented Knowledge Tracing ( CKT ) model in this paper.
Edit intent: clarity
Original:  The forgetting curve theorystates that human memory retention declines over time, therefore knowledge states should be mostly affected by the recent questions . Based on this observation , we propose a Convolutional Knowledge Tracing ( CKT ) model in this paper.
Revised:  The forgetting curve theorystates that human memory retention declines over time, therefore knowledge states should be mostly affected by the recent questions . Based on this observation , we propose a Convolutional Knowledge Tracing ( CAKT ) model in this paper.
Edit intent: fluency
Original:  Extensive experiments show that CKT achieves the new state-of-the-art  in predicting students performance compared with existing models.
Revised:  Extensive experiments show that CKT achieves the new state-of-the-art performance in predicting students performance compared with existing models.
Edit intent: clarity
Original:  Extensive experiments show that CKT achieves the new state-of-the-art  in predicting students performance compared with existing models.
Revised:  Extensive experiments show that CKT achieves the new state-of-the-art in predicting students ' responses compared with existing models.
Edit intent: clarity
Original:  This result establishes the first rigorous link between a definition of curvature applicable to random graphs and a traditional definition of curvature of smooth space .
Revised:  This result establishes the first rigorous link between a definition of curvature applicable to random graphs and a traditional definition of curvature of smooth spaces .
Edit intent: fluency
Original:  In particular, the Russian-backed Internet Research Agency (IRA) has been identified as a key source of misinformation spread on Twitter prior to the 2016  presidential election.
Revised:  In particular, the Russian-backed Internet Research Agency (IRA) has been identified as a key source of misinformation spread on Twitter prior to the 2016 U.S. presidential election.
Edit intent: clarity
Original: In recent work by [CHHL19,CHLT19] , the authors exhibit a flexible construction of pseudorandom generators for classes of that satisfy L_1 Fourier bounds.
Revised: In recent work by [CHHL19,CHLT19] that exploit L_1 Fourier bounds.
Edit intent: clarity