wanyu/IteraTeR_v2 huggingface dataset:
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] , the authors exhibit a flexible construction of pseudorandom generators for classes of that satisfy L_1 Fourier 
Edit intent: clarity
Original:  CHHL19%DIFDELCMD < ] %%% show that if a class satisfies such tail bounds at all levels, this implies a PRG through their random walk framework that composes together fractional PRGs that polarize quickly to the Boolean hypercube.
Revised:  %DIFDELCMD < ] %%% show that if a class satisfies such tail bounds at all levels, this implies a PRG through their random walk framework that composes together fractional PRGs that polarize quickly to the Boolean hypercube.
Edit intent: coherence
Original:  CHHL19%DIFDELCMD < ] %%% show that if a class satisfies such tail bounds at all levels, this implies a PRG through their random walk framework that composes together fractional PRGs that polarize quickly to the Boolean hypercube.
Revised:  CHHL19%DIFDELCMD < ] %%% 
Edit intent: coherence
Original:  CHLT19%DIFDELCMD < ] %%% show by derandomizing the analysis of RT19%DIFDELCMD < ] %%% that just level-two Fourier bounds suffice to construct a PRG but naturally obtain exponentially worse dependence on the error in the seed length compared to [CHHL19] . Moreover, this derandomization relies on simulating nearly independent Gaussians for the fractional PRG, which necessitates the polynomial dependence on 1/\epsilon in each fractional step.
Revised:  %DIFDELCMD < ] %%% show by derandomizing the analysis of RT19%DIFDELCMD < ] %%% that just level-two Fourier bounds suffice to construct a PRG but naturally obtain exponentially worse dependence on the error in the seed length compared to [CHHL19] . Moreover, this derandomization relies on simulating nearly independent Gaussians for the fractional PRG, which necessitates the polynomial dependence on 1/\epsilon in each fractional step.
Edit intent: clarity
Original:  CHLT19%DIFDELCMD < ] %%% show by derandomizing the analysis of RT19%DIFDELCMD < ] %%% that just level-two Fourier bounds suffice to construct a PRG but naturally obtain exponentially worse dependence on the error in the seed length compared to [CHHL19] . Moreover, this derandomization relies on simulating nearly independent Gaussians for the fractional PRG, which necessitates the polynomial dependence on 1/\epsilon in each fractional step.
Revised:  CHLT19%DIFDELCMD < ] %%% RT19%DIFDELCMD < ] %%% that just level-two Fourier bounds suffice to construct a PRG but naturally obtain exponentially worse dependence on the error in the seed length compared to [CHHL19] . Moreover, this derandomization relies on simulating nearly independent Gaussians for the fractional PRG, which necessitates the polynomial dependence on 1/\epsilon in each fractional step.
Edit intent: clarity
Original:  CHLT19%DIFDELCMD < ] %%% show by derandomizing the analysis of RT19%DIFDELCMD < ] %%% that just level-two Fourier bounds suffice to construct a PRG but naturally obtain exponentially worse dependence on the error in the seed length compared to [CHHL19] . Moreover, this derandomization relies on simulating nearly independent Gaussians for the fractional PRG, which necessitates the polynomial dependence on 1/\epsilon in each fractional step.
Revised:  CHLT19%DIFDELCMD < ] %%% show by derandomizing the analysis of %DIFDELCMD < ] %%% that just level-two Fourier bounds suffice to construct a PRG but naturally obtain exponentially worse dependence on the error in the seed length compared to [CHHL19] . Moreover, this derandomization relies on simulating nearly independent Gaussians for the fractional PRG, which necessitates the polynomial dependence on 1/\epsilon in each fractional step.
Edit intent: fluency
Original:  CHLT19%DIFDELCMD < ] %%% show by derandomizing the analysis of RT19%DIFDELCMD < ] %%% that just level-two Fourier bounds suffice to construct a PRG but naturally obtain exponentially worse dependence on the error in the seed length compared to [CHHL19] . Moreover, this derandomization relies on simulating nearly independent Gaussians for the fractional PRG, which necessitates the polynomial dependence on 1/\epsilon in each fractional step.
Revised:  CHLT19%DIFDELCMD < ] %%% show by derandomizing the analysis of RT19%DIFDELCMD < ] %%% that just level-two Fourier bounds suffice to construct a PRG but naturally obtain exponentially worse dependence on the error in the seed length compared to [CHHL19] , or has polynomial dependence on 1/\epsilon in each fractional step.
Edit intent: coherence
Original:  We partially answer ] an open question by [CHLT19] that nearly interpolates between them.
Revised:  We partially answer CHLT19] an open question by [CHLT19] that nearly interpolates between them.
Edit intent: fluency
Original:  We partially answer ] an open question by [CHLT19] that nearly interpolates between them.
Revised:  We partially answer ] an open question in [CHLT19] that nearly interpolates between them.
Edit intent: fluency
Original:  Our analysis shows that for error \epsilon=1/poly(n), one needs control at just level O(\log n)  to recover the seed length of [CHHL19], without assumptions on the entire tail.
Revised:  Our analysis shows that for error \epsilon=1/poly(n), one needs control at just level O(\log n) to recover the seed length in [CHHL19], without assumptions on the entire tail.
Edit intent: fluency
Original:  We avoid this by providing a simple, alternate analysis of their fractional PRG that instead relies on Taylor's theorem and p-biased Fourier analysis to avoid assumptions on the weights of the higher-order terms.
Revised:  We obtain our results by an alternate analysis of their fractional PRG that instead relies on Taylor's theorem and p-biased Fourier analysis to avoid assumptions on the weights of the higher-order terms.
Edit intent: clarity
Original:  We avoid this by providing a simple, alternate analysis of their fractional PRG that instead relies on Taylor's theorem and p-biased Fourier analysis to avoid assumptions on the weights of the higher-order terms.
Revised:  We avoid this by providing a simple, alternate analysis of fractional PRGs using Taylor's theorem and p-biased Fourier analysis to avoid assumptions on the weights of the higher-order terms.
Edit intent: clarity
Original:  This interpolates previous works, which either require Fourier bounds on all levels [CHHL19], or has polynomial dependence on the error parameter in the seed length [ CHLT19 ], and thus answers an open question in [CHLT19].
Revised:  This interpolates previous works, which either require Fourier bounds on all levels [CHHL19], or have polynomial dependence on the error parameter in the seed length [ CHLT19 ], and thus answers an open question in [CHLT19].
Edit intent: fluency
Original:  Interestingly, our analysis relies only on the level-k unsigned Fourier sum , which is potentially a much smaller quantity than the L_1 notion in previous works.
Revised:  Interestingly, our analysis relies only on the level-k unsigned Fourier sum , which is potentially a much smaller quantity than the L_1 notion in previous works.
Edit intent: fluency
Original:  In this paper, we propose CECL (Context Encoding for video retrieval with Contrastive Learning ), a video representation learning framework that aggregates the context information of frame-level descriptors, and a supervised contrastive learning method that performs automatic hard negative mining , and utilizes the memory bank mechanism to increase the capacity of negative samples.
Revised:  In this paper, we propose CECL (Context Encoding for video retrieval with Contrastive Learning ), a video representation learning framework that aggregates the context information of frame-level descriptors, and a supervised contrastive learning method that performs automatic hard negative mining and utilizes the memory bank mechanism to increase the capacity of negative samples.
Edit intent: fluency
Original:  Extensive experiments are conducted on multi video retrieval tasks, such as FIVR, CC_WEB_VIDEO  and EVVE.
Revised:  Extensive experiments are conducted on multiple video retrieval tasks, such as FIVR, CC_WEB_VIDEO and EVVE.
Edit intent: fluency
Original:  Extensive experiments are conducted on multi video retrieval tasks, such as FIVR, CC_WEB_VIDEO  and EVVE.
Revised:  Extensive experiments are conducted on multi video retrieval tasks, such as CC_WEB_VIDEO and EVVE.
Edit intent: clarity
Original:  This inspiration allows  to introduce a dynamical interpretation of spatiotemporal disentanglement.
Revised:  This inspiration allows us to introduce a dynamical interpretation of spatiotemporal disentanglement.
Edit intent: fluency
Original:  It induces a simple and principled model based on learning disentangled spatial and temporal representations of a phenomenon to accurately predict future observations.
Revised:  It induces a principled model based on learning disentangled spatial and temporal representations of a phenomenon to accurately predict future observations.
Edit intent: clarity
Original:  We evaluated the functionalities and the performance metrics that are critical in context-based visual search and recommender systems using deep-learning embeddings.
Revised:  We evaluated the functionalities and the performance metrics that are critical in content-based visual search and recommender systems using deep-learning embeddings.
Edit intent: clarity
Original:  Our results show that the neuromorphic solution is about 3.2 times more energy-efficient compared with an Intel Core i7 CPU and 12.5 times more energy-efficient compared with Nvidia T4 GPU for inference by a lightweight convolutional neural network without batching , while maintaining the same level of matching accuracy.
Revised:  Our results show that the neuromorphic solution is about 3.2 times more energy-efficient compared with an Intel Core i7 CPU and 12.5 times more energy-efficient compared with NVIDIA T4 GPU for inference by a lightweight convolutional neural network without batching , while maintaining the same level of matching accuracy.
Edit intent: fluency
Original:  Our results show that the neuromorphic solution is about 3.2 times more energy-efficient compared with an Intel Core i7 CPU and 12.5 times more energy-efficient compared with Nvidia T4 GPU for inference by a lightweight convolutional neural network without batching , while maintaining the same level of matching accuracy.
Revised:  Our results show that the neuromorphic solution is about 3.2 times more energy-efficient compared with an Intel Core i7 CPU and 12.5 times more energy-efficient compared with Nvidia T4 GPU for inference by a lightweight convolutional neural network without batching while maintaining the same level of matching accuracy.
Edit intent: fluency
Original:  The study validates the longterm potential of neuromorphic computing in machine learning , as a complementary paradigm to the existing Von Neumann architectures.
Revised:  The study validates the potential of neuromorphic computing in machine learning , as a complementary paradigm to the existing Von Neumann architectures.
Edit intent: clarity
Original:  The study validates the longterm potential of neuromorphic computing in machine learning , as a complementary paradigm to the existing Von Neumann architectures.
Revised:  The study validates the longterm potential of neuromorphic computing in machine learning , as a complementary paradigm to the existing von Neumann architectures.
Edit intent: fluency
Original: A household robot is expected to perform a wide variety of manipulating operations with an understanding of the purpose of the task.
Revised: A household robot is expected to perform various manipulative operations with an understanding of the purpose of the task.
Edit intent: clarity
Original:  To this end, a desirable robotic application should provide an on-site robot teaching framework by non-experts.
Revised:  To this end, robotic applications should provide an on-site robot teaching framework by non-experts.
Edit intent: clarity
Original:  To this end, a desirable robotic application should provide an on-site robot teaching framework by non-experts.
Revised:  To this end, a desirable robotic application should provide an on-site robot teaching framework for non-experts.
Edit intent: fluency
Original:  Here we propose to apply the Learning-from-Observation (LfO) framework to grasp-manipulation-release class household operations  .
Revised:  Here , we propose a Learning-from-Observation (LfO) framework to grasp-manipulation-release class household operations .
Edit intent: coherence
Original:  Here we propose to apply the Learning-from-Observation (LfO) framework to grasp-manipulation-release class household operations  .
Revised:  Here we propose to apply the Learning-from-Observation (LfO) framework for grasp-manipulation-release class household operations .
Edit intent: fluency
Original:  The framework maps a human demonstration to predefined task models through a one-shot demonstration.
Revised:  The framework maps human demonstrations to predefined task models through a one-shot demonstration.
Edit intent: fluency
Original:  The framework maps a human demonstration to predefined task models through a one-shot demonstration.
Revised:  The framework maps a human demonstration to predefined task models through one-shot demonstration.
Edit intent: fluency
Original:  A task model contains both high-level knowledge about the geometric constraints of tasks and low-level knowledge about human postures.
Revised:  A task model contains both high-level knowledge regarding the geometric constraints of tasks and low-level knowledge about human postures.
Edit intent: fluency
Original:  A task model contains both high-level knowledge about the geometric constraints of tasks and low-level knowledge about human postures.
Revised:  A task model contains both high-level knowledge about the geometric constraints of tasks and low-level knowledge related to human postures.
Edit intent: clarity
Original:  The key idea is to design a task model that 1) covers a wide variety of household operations and 2) contains human postures to achieve tasks.
Revised:  The key goal of this study is to design a task model that 1) covers a wide variety of household operations and 2) contains human postures to achieve tasks.
Edit intent: clarity
Original:  The key idea is to design a task model that 1) covers a wide variety of household operations and 2) contains human postures to achieve tasks.
Revised:  The key idea is to design a task model that 1) covers various GMR-operations and 2) contains human postures to achieve tasks.
Edit intent: clarity
Original:  The key idea is to design a task model that 1) covers a wide variety of household operations and 2) contains human postures to achieve tasks.
Revised:  The key idea is to design a task model that 1) covers a wide variety of household operations and 2) includes human postures to achieve tasks.
Edit intent: clarity
Original:  We verified the effectiveness of our framework by testing an implemented system with several operations .
Revised:  We verify the applicability of our framework by testing an implemented system with several operations .
Edit intent: clarity
Original:  In addition, we quantified the coverage of the task model by analyzing Web videos about household operations.
Revised:  In addition, we quantify the coverage of the task model by analyzing Web videos about household operations.
Edit intent: fluency
Original:  In addition, we quantified the coverage of the task model by analyzing Web videos about household operations.
Revised:  In addition, we quantified the coverage of the task model by analyzing online videos of household operations.
Edit intent: fluency
Original:  In the context of one-shot robot teaching, the contributions of the paper is to propose a framework that 1) covers various tasks in grasp-manipulation-release class household operations and 2) mimics human postures during the operations .
Revised:  In the context of one-shot robot teaching, the contributions of the paper is to propose a framework that covers various GMR-operations and mimics human postures during the operations .
Edit intent: clarity
Original:  To this end, robotic applications should provide an on-site robot teaching framework for non-experts.
Revised:  To this end, a desirable robotic application should provide an on-site robot teaching framework for non-experts.
Edit intent: clarity
Original:  Here , we propose a Learning-from-Observation (LfO) framework for grasp-manipulation-release class household operations (GMR-operations).
Revised:  Here we propose a Learning-from-Observation (LfO) framework for grasp-manipulation-release class household operations (GMR-operations).
Edit intent: fluency
Original:  Each task model contains both high-level knowledge regarding the geometric constraints of tasks and low-level knowledge related to human postures.
Revised:  Each task model contains both high-level knowledge regarding the geometric constraints and low-level knowledge related to human postures.
Edit intent: clarity
Original:  The key goal of this study is to design a task model that 1) covers various GMR-operations and 2) includes human postures to achieve tasks.
Revised:  The key idea is to design a task model that 1) covers various GMR-operations and 2) includes human postures to achieve tasks.
Edit intent: clarity
Original:  We verify the applicability of our framework by testing the novel LfO system with a real robot.
Revised:  We verify the applicability of our framework by testing an operational LfO system with a real robot.
Edit intent: clarity
Original:  Within the context of one-shot robot teaching, the contribution of this study is a framework that  covers various GMR-operations and  mimics human postures during operation .
Revised:  In the context of one-shot robot teaching, the contribution of this study is a framework that covers various GMR-operations and mimics human postures during operation .
Edit intent: fluency
Original:  Within the context of one-shot robot teaching, the contribution of this study is a framework that  covers various GMR-operations and  mimics human postures during operation .
Revised:  Within the context of one-shot robot teaching, the contribution of this study is a framework that covers various GMR-operations and 2) mimics human postures during operation .
Edit intent: coherence
Original:  Within the context of one-shot robot teaching, the contribution of this study is a framework that  covers various GMR-operations and  mimics human postures during operation .
Revised:  Within the context of one-shot robot teaching, the contribution of this study is a framework that covers various GMR-operations and mimics human postures during the operations .
Edit intent: clarity
Original: Establishing the authorship of online texts is a fundamental issue to combat several cybercrimes.
Revised: Establishing authorship of online texts is a fundamental issue to combat several cybercrimes.
Edit intent: fluency
Original: Establishing the authorship of online texts is a fundamental issue to combat several cybercrimes.
Revised: Establishing the authorship of online texts is fundamental to combat cybercrimes.
Edit intent: clarity
Original:  Unfortunately, some platforms limit the length of the text , making the challenge harder.
Revised:  Unfortunately, text length is limited on some platforms , making the challenge harder.
Edit intent: clarity
Original:  Here, we aim at identifying the author of Twitter messages limited to 140 characters.
Revised:  We aim at identifying the author of Twitter messages limited to 140 characters.
Edit intent: coherence
Original:  Here, we aim at identifying the author of Twitter messages limited to 140 characters.
Revised:  Here, we aim at identifying the authorship of Twitter messages limited to 140 characters.
Edit intent: fluency
Original:  We evaluate popular stylometric features, widely used in traditional literary analysis, which capture the writing style at different levels (character, word, and sentence) .
Revised:  We evaluate popular stylometric features, widely used in literary analysis, which capture the writing style at different levels (character, word, and sentence) .
Edit intent: clarity
Original:  We use a public database of 93 users, containing 1142 to 3209 Tweets per user.
Revised:  We use two databases with 93 users, containing 1142 to 3209 Tweets per user.
Edit intent: clarity
Original: With the prevalence of publicly available source code repositories to train deep neural network models, neural program analyzers can do well in source code analysis tasks such as predicting method names in given programs that cannot be easily done by traditional program analyzers .
Revised: With the prevalence of publicly available source code repositories to train deep neural network models, neural program models can do well in source code analysis tasks such as predicting method names in given programs that cannot be easily done by traditional program analyzers .
Edit intent: clarity
Original: With the prevalence of publicly available source code repositories to train deep neural network models, neural program analyzers can do well in source code analysis tasks such as predicting method names in given programs that cannot be easily done by traditional program analyzers .
Revised: With the prevalence of publicly available source code repositories to train deep neural network models, neural program analyzers can do well in source code analysis tasks such as predicting method names in given programs that cannot be easily done by traditional program analysis techniques .
Edit intent: clarity
Original:  Although such analyzers have been tested on various existing datasets, the extent in which they generalize to unforeseen source code is largely unknown.
Revised:  Although such neural program models have been tested on various existing datasets, the extent in which they generalize to unforeseen source code is largely unknown.
Edit intent: clarity
Original:  Although such analyzers have been tested on various existing datasets, the extent in which they generalize to unforeseen source code is largely unknown.
Revised:  Although such analyzers have been tested on various existing datasets, the extent to which they generalize to unforeseen source code is largely unknown.
Edit intent: clarity
Original:  Since it is impossible to test neural program analyzers on all unforeseen programs, in this paper, we propose to evaluate the generalizability of neural program analyzers with respect to semantic-preserving transformations: a generalizable neural program analyzer should perform equally well on programs that are of the same semantics but of different lexical appearances and syntactical structures.
Revised:  Since it is very challenging to test neural program analyzers on all unforeseen programs, in this paper, we propose to evaluate the generalizability of neural program analyzers with respect to semantic-preserving transformations: a generalizable neural program analyzer should perform equally well on programs that are of the same semantics but of different lexical appearances and syntactical structures.
Edit intent: clarity
Original:  Since it is impossible to test neural program analyzers on all unforeseen programs, in this paper, we propose to evaluate the generalizability of neural program analyzers with respect to semantic-preserving transformations: a generalizable neural program analyzer should perform equally well on programs that are of the same semantics but of different lexical appearances and syntactical structures.
Revised:  Since it is impossible to test neural program models on all unforeseen programs, in this paper, we propose to evaluate the generalizability of neural program analyzers with respect to semantic-preserving transformations: a generalizable neural program analyzer should perform equally well on programs that are of the same semantics but of different lexical appearances and syntactical structures.
Edit intent: clarity