wanyu/IteraTeR_v2 huggingface dataset:
Original:  We connect statistical complexity to the flies' level of conscious arousal, which is manipulated by general anaesthesia (isoflurane).
Revised:  We connect statistical complexity to the flies' level of conscious arousal, which is manipulated by general anesthesia (isoflurane).
Edit intent: fluency
Original:  We show that the complexity of even single channel time series data decreases under anaesthesia .
Revised:  We show that the complexity of even single channel time series data decreases under anesthesia .
Edit intent: fluency
Original:  Specifically, we show that persistent homology detects the curvature of disks from which points have been sampled.
Revised:  Specifically, we prove that persistent homology detects the curvature of disks from which points have been sampled.
Edit intent: clarity
Original:  In the present application, the average persistence landscapes of points sampled from disks of constant curvature produce a path in a Hilbert space which may be learned  .
Revised:  In the present application, the average persistence landscapes of points sampled from disks of constant curvature results in a path in a Hilbert space which may be learned .
Edit intent: clarity
Original:  In the present application, the average persistence landscapes of points sampled from disks of constant curvature produce a path in a Hilbert space which may be learned  .
Revised:  In the present application, the average persistence landscapes of points sampled from disks of constant curvature produce a path in this Hilbert space which may be learned .
Edit intent: clarity
Original:  Standard video CNN architectures have been designed by directly extending architectures devised for image understanding to a third dimension(using a limited number of space-time modules such as 3D convolutions ) or by introducing a handcrafted two-stream design to capture both appearance and motion in videos.
Revised:  Standard video CNN architectures have been designed by directly extending architectures devised for image understanding to include the time dimension, using modules such as 3D convolutions ) or by introducing a handcrafted two-stream design to capture both appearance and motion in videos.
Edit intent: clarity
Original:  Standard video CNN architectures have been designed by directly extending architectures devised for image understanding to a third dimension(using a limited number of space-time modules such as 3D convolutions ) or by introducing a handcrafted two-stream design to capture both appearance and motion in videos.
Revised:  Standard video CNN architectures have been designed by directly extending architectures devised for image understanding to a third dimension(using a limited number of space-time modules such as 3D convolutions , or by using two-stream design to capture both appearance and motion in videos.
Edit intent: clarity
Original: We consider the problem of finding inscribed boxes and axis-aligned inscribed boxes of maximum volume, inside a compact and solid convex set.
Revised: This paper considers the problem of finding inscribed boxes and axis-aligned inscribed boxes of maximum volume, inside a compact and solid convex set.
Edit intent: clarity
Original: We consider the problem of finding inscribed boxes and axis-aligned inscribed boxes of maximum volume, inside a compact and solid convex set.
Revised: We consider the problem of finding maximum volume ( axis-aligned inscribed boxes of maximum volume, inside a compact and solid convex set.
Edit intent: fluency
Original:  Using this exact algorithm as a subroutine, we present an \epsilon-approximation algorithm that computes (1-\epsilon)-approximation to the largest inscribed rectangle with computational complexity of O(\epsilon^{-1 . Finally, we show that how this running time can be improved to O(\epsilon^{-1\log n) with a O(\epsilon^{-1}n) pre-processing time when the convex set is a polygon}  .
Revised:  Using this exact algorithm as a subroutine, we present an \epsilon-approximation algorithm that computes (1-\epsilon)-approximation to the largest inscribed rectangle with computational complexity of O(\epsilon^{-1 . Finally, \log n) with a O(\epsilon^{-1}n) pre-processing time when the convex set is a polygon} .
Edit intent: coherence
Original: The future of high-performance computing, specifically the next generation of Exascale computers, will presumably see memory capacity and bandwidth fail to keep pace with data generation . Current strategies proposed to address this bottleneck entail the omission of large fractions of data, as well as the incorporation of in situ compression algorithms to avoid overuse of memory.
Revised: The future of high-performance computing, specifically on future Exascale computers, will presumably see memory capacity and bandwidth fail to keep pace with data generation . Current strategies proposed to address this bottleneck entail the omission of large fractions of data, as well as the incorporation of in situ compression algorithms to avoid overuse of memory.
Edit intent: clarity
Original:  To ensure that post-processing operations are successful, this must be done in a way that ensures that a sufficiently accurate representation of the solution is stored.
Revised:  To ensure that post-processing operations are successful, this must be done in a way that a sufficiently accurate representation of the solution is stored.
Edit intent: fluency
Original:  Moreover, in situations in which the input/output system becomes a bottleneck in analysis, visualization, etc., the number of passes made over the input data must be minimized.
Revised:  Moreover, in situations where the input/output system becomes a bottleneck in analysis, visualization, etc., the number of passes made over the input data must be minimized.
Edit intent: fluency
Original:  Moreover, in situations in which the input/output system becomes a bottleneck in analysis, visualization, etc., the number of passes made over the input data must be minimized.
Revised:  Moreover, in situations in which the input/output system becomes a bottleneck in analysis, visualization, etc., the number of passes made over the data must be minimized.
Edit intent: fluency
Original:  In the interest of addressing this problem, this work focuses on the application of pass-efficient compressive matrix decompositions to high-dimensional simulation data from turbulent particle-laden flows.
Revised:  In the interest of addressing this problem, this work focuses on the utility of pass-efficient compressive matrix decompositions to high-dimensional simulation data from turbulent particle-laden flows.
Edit intent: clarity
Original:  It also includes the presentation of a novel single-pass matrix decomposition algorithm for computing interpolative decompositions .
Revised:  It also includes the presentation of a novel single-pass matrix decomposition algorithm for computing the so-called interpolative decomposition .
Edit intent: clarity
Original:  In the unladen channel flow case, compression factors exceeding 400 are achieved while maintaining accuracy with respect to first- and second-order flow statistics.
Revised:  In the first (unladen) channel flow case, compression factors exceeding 400 are achieved while maintaining accuracy with respect to first- and second-order flow statistics.
Edit intent: fluency
Original:  In the particle-laden case, compression factors between 10 and 150 with relative reconstruction errors of%DIFDELCMD < {\cal %%% O (10^{-3) are achieved .
Revised:  In the particle-laden case, compression factors between 10 and %DIFDELCMD < {\cal %%% O (10^{-3) are achieved .
Edit intent: clarity
Original:  In the particle-laden case, compression factors between 10 and 150 with relative reconstruction errors of%DIFDELCMD < {\cal %%% O (10^{-3) are achieved .
Revised:  In the particle-laden case, compression factors between 10 and 150 with relative reconstruction errors of%DIFDELCMD < {\cal %%% (10^{-3) are achieved .
Edit intent: clarity
Original:  These algorithms are easily parallelized and can be incorporated directly into solvers, which will allow for effective }\textit{in situ compression of large-scale simulation data .
Revised:  These algorithms are easily parallelized and can be incorporated directly into solvers, which will allow for effective }\textit{ compression of large-scale simulation data .
Edit intent: clarity
Original:  One problem is that current deep learning research datasets either have very little hierarchical structure or are too complex for their structureto be analyzed, impeding precise predictions of hierarchical representations .
Revised:  One problem is that current deep learning research datasets either have little hierarchical or compositional structure, or the structure is not known. This gap impedes precise analysis of a network's representations and thus hinders development of new methods that can learn such properties .
Edit intent: clarity
Original:  To address this gap, we present a benchmark dataset with known hierarchical and compositional structure and a set of methods for performing hypothesis-driven data analysis using DNs . The Hangul Fonts Dataset is composed of 35 fonts  , each with 11,172 written syllablesconsisting of 19 initial consonants, 21 medial vowels, and 28 final consonants.
Revised:  To address this gap, we developed a new benchmark dataset with known hierarchical and compositional structure and a set of methods for performing hypothesis-driven data analysis using DNs . The Hangul Fonts Dataset is composed of 35 fonts , each with 11,172 written syllablesconsisting of 19 initial consonants, 21 medial vowels, and 28 final consonants.
Edit intent: clarity
Original:  To address this gap, we present a benchmark dataset with known hierarchical and compositional structure and a set of methods for performing hypothesis-driven data analysis using DNs . The Hangul Fonts Dataset is composed of 35 fonts  , each with 11,172 written syllablesconsisting of 19 initial consonants, 21 medial vowels, and 28 final consonants.
Revised:  To address this gap, we present a benchmark dataset with known hierarchical and compositional structure . The Hangul Fonts Dataset is composed of 35 fonts , each with 11,172 written syllablesconsisting of 19 initial consonants, 21 medial vowels, and 28 final consonants.
Edit intent: clarity
Original:  To address this gap, we present a benchmark dataset with known hierarchical and compositional structure and a set of methods for performing hypothesis-driven data analysis using DNs . The Hangul Fonts Dataset is composed of 35 fonts  , each with 11,172 written syllablesconsisting of 19 initial consonants, 21 medial vowels, and 28 final consonants.
Revised:  To address this gap, we present a benchmark dataset with known hierarchical and compositional structure and a set of methods for performing hypothesis-driven data analysis using DNs . The Hangul Fonts Dataset (HFD) is comprised of 35 fonts , each with 11,172 written syllablesconsisting of 19 initial consonants, 21 medial vowels, and 28 final consonants.
Edit intent: clarity
Original:  These videos provide important and useful information for reconstructing the events.
Edit intent: coherence
Original:  It provides a web interface for human-in-the-loop verification to ensure accurate estimations.
Revised:  It provides a web interface that enables human-in-the-loop verification to ensure accurate estimations.
Edit intent: clarity
Original:  We present the results of estimating the shooter's location of the Las Vegas Shooting in 2017 and show that DAISY is able to get accurate location using only the first few shots .
Revised:  We present the results of estimating the shooter's location of the Las Vegas Shooting in 2017 and show that DAISY is able to get accurate location using only the first few gunshots .
Edit intent: fluency
Original:  We then point out future directions that can help improve the system and further reduces human labor in the process.
Revised:  We then point out future directions that can help improve the system and further reduce unnecessary human labor in the process.
Edit intent: clarity
Original:  All  relevant source code, including the web interface and machine learning models, are freely available in Github.
Revised:  All relevant source code, including the web interface and machine learning models, is freely available on Github.
Edit intent: fluency
Original:  We also hope that researchers and software developers will be inspired to improve and expand this system moving forward to better meet the needs of public safety and human rights .
Revised:  We also hope that researchers and software developers will be inspired to improve and expand this system moving forward to better meet the needs of human rights and public safety .
Edit intent: fluency
Original:  We provide evidence that the stress intensity factor is a natural bifurcation parameter, and that the resulting bifurcation diagram is a periodic ``snaking curve'' . We then prove qualitative properties of the equilibria and convergence rates of finite-cell approximations to the ``exact'' bifurcation diagram.
Revised:  We provide evidence that the stress intensity factor is a natural bifurcation parameter, and that the resulting bifurcation diagram is a periodic "snaking curve" . We then prove qualitative properties of the equilibria and convergence rates of finite-cell approximations to the ``exact'' bifurcation diagram.
Edit intent: fluency
Original:  We provide evidence that the stress intensity factor is a natural bifurcation parameter, and that the resulting bifurcation diagram is a periodic ``snaking curve'' . We then prove qualitative properties of the equilibria and convergence rates of finite-cell approximations to the ``exact'' bifurcation diagram.
Revised:  We provide evidence that the stress intensity factor is a natural bifurcation parameter, and that the resulting bifurcation diagram is a periodic ``snaking curve'' . We then prove qualitative properties of the equilibria and convergence rates of finite-cell approximations to the "exact" bifurcation diagram.
Edit intent: fluency
Original:  One way to achieve a "sweet spot" of low false positive rates, while maintaining high enough recall to be usable, is to focus on repairing classes of simple bugs, such as bugs with single statement fixes, or that match a small set of bug templates (Long and Rinard, 2016;
Revised:  One way to achieve acceptable performance is to focus on repairing classes of simple bugs, such as bugs with single statement fixes, or that match a small set of bug templates (Long and Rinard, 2016;
Edit intent: clarity
Original:  One way to achieve a "sweet spot" of low false positive rates, while maintaining high enough recall to be usable, is to focus on repairing classes of simple bugs, such as bugs with single statement fixes, or that match a small set of bug templates (Long and Rinard, 2016;
Revised:  One way to achieve a "sweet spot" of low false positive rates, while maintaining high enough recall to be usable, is to focus on classes of simple bugs, such as bugs with single statement fixes, or that match a small set of bug templates (Long and Rinard, 2016;
Edit intent: clarity
Original:  However, it is very difficult to estimate the recall of repair techniques based on templates or based on repairing simple bugs, as there are no datasets about how often the associated bugs occur in code.
Revised:  However, it is very difficult to estimate the recall of repair techniques for simple bugs, as there are no datasets about how often the associated bugs occur in code.
Edit intent: coherence
Original:  To fill this gap, we provide two versions of the dataset containing 24412 and 153751 single statement bug-fix changes mined from 100 popular open-source Java Maven projectsand from 1000 popular open-source Java projects respectively , annotated by whether they match any of a set of 16 bug templates, inspired by state-of-the-art program repair techniques.
Revised:  To fill this gap, we provide two versions of the dataset containing 24412 and 153751 single statement bug-fix changes mined from 100 popular open-source Java projects , annotated by whether they match any of a set of 16 bug templates, inspired by state-of-the-art program repair techniques.
Edit intent: coherence
Original:  In an initial analysis, we find that for both datasets about 33\% of the simple bug fixes match the templates, indicating that a remarkable number of single-statement bugs can be repaired with a relatively small set of templates.
Revised:  In an initial analysis, we find that about 33\% of the simple bug fixes match the templates, indicating that a remarkable number of single-statement bugs can be repaired with a relatively small set of templates.
Edit intent: clarity
Original:  Further, we find that SStuBs appear with a frequency of about one bug per 1600-2500 lines of code (as measured by the size of the project's latest version) , allowing researchers to make an informed case about the potential impact of improved program repair methods .
Revised:  Further, we find that SStuBs appear with a frequency of about one bug per 1600-2500 lines of code (as measured by the size of the project's latest version) . We hope that the dataset will prove a resource for both future work in program repair and studies in empirical software engineering .
Edit intent: clarity
Original: Captioning has attracted much attention in image and video understanding while little work examines audio captioning.
Revised: Captioning has attracted much attention in image and video understanding while a small amount of work examines audio captioning.
Edit intent: clarity
Original:  We test the model on the current car dataset, previous Hospital Dataset and the Joint Dataset , indicating its generalization capability across different scenes.
Revised:  We test the model on the current car dataset, previous Hospital Dataset and the Joint dataset , indicating its generalization capability across different scenes.
Edit intent: fluency
Original:  However, though detailed audio captions can now be automatically generated, human annotations still outperform model captions in many aspects.
Revised:  However, though detailed audio captions can now be automatically generated, human annotations still outperform model captions on many aspects.
Edit intent: clarity
Original:  Our findings show that a rather large part of statistically similar network structures is persistent and general: they form in different securities' and persist in time for mature and IPO companies.
Revised:  Our findings show that a rather large part of statistically similar network structures form in different securities' and persist in time for mature and IPO companies.
Edit intent: clarity
Original:  We also find evidence of institutional herding that hints at the existence of an investor information network .
Revised:  We also find evidence of institutional herding .
Edit intent: clarity
Original:  Our findings show that a rather large part of statistically similar network structures form in different securities ' and persist in time for mature and IPO companies.
Revised:  Our findings show that a rather large part of statistically similar network structures form in different securities and persist in time for mature and IPO companies.
Edit intent: fluency
Original: In this paper, we present a new dataset for Form Understanding in Noisy Scanned Documents (FUNSD) . Form Understanding (FoUn) aims at extracting and structuring the textual content of forms.
Revised: We present a new dataset for Form Understanding in Noisy Scanned Documents (FUNSD) . Form Understanding (FoUn) aims at extracting and structuring the textual content of forms.
Edit intent: coherence
Original: In this paper, we present a new dataset for Form Understanding in Noisy Scanned Documents (FUNSD) . Form Understanding (FoUn) aims at extracting and structuring the textual content of forms.
Revised: In this paper, we present a new dataset for form understanding in noisy scanned documents (FUNSD) . Form Understanding (FoUn) aims at extracting and structuring the textual content of forms.
Edit intent: fluency
Original: In this paper, we present a new dataset for Form Understanding in Noisy Scanned Documents (FUNSD) . Form Understanding (FoUn) aims at extracting and structuring the textual content of forms.
Revised: In this paper, we present a new dataset for Form Understanding in Noisy Scanned Documents (FUNSD) that aims at extracting and structuring the textual content of forms.
Edit intent: clarity
Original:  The documents are noisy and exhibit large variabilities in their representation making FoUn a challenging task.
Revised:  The documents are noisy and vary widely in appearance, making form understanding (FoUn) a challenging task.
Edit intent: clarity
Original:  The proposed dataset can be used for various tasks  including text detection, optical character recognition (OCR) , spatial layout analysis  and entity labeling/linking.
Revised:  The proposed dataset can be used for various tasks , including text detection, optical character recognition (OCR) , spatial layout analysis and entity labeling/linking.
Edit intent: fluency
Original:  The proposed dataset can be used for various tasks  including text detection, optical character recognition (OCR) , spatial layout analysis  and entity labeling/linking.
Revised:  The proposed dataset can be used for various tasks including text detection, optical character recognition , spatial layout analysis and entity labeling/linking.
Edit intent: clarity
Original:  The proposed dataset can be used for various tasks  including text detection, optical character recognition (OCR) , spatial layout analysis  and entity labeling/linking.
Revised:  The proposed dataset can be used for various tasks including text detection, optical character recognition (OCR) , spatial layout analysis , and entity labeling/linking.
Edit intent: fluency
Original:  To the best of our knowledge  this is the first publicly available dataset with comprehensive annotations addressing the FoUn task.
Revised:  To the best of our knowledge , this is the first publicly available dataset with comprehensive annotations addressing the FoUn task.
Edit intent: fluency
Original:  To the best of our knowledge  this is the first publicly available dataset with comprehensive annotations addressing the FoUn task.
Revised:  To the best of our knowledge this is the first publicly available dataset with comprehensive annotations to address FoUn task.
Edit intent: fluency
Original:  We introduce two new preconditioners to tackle this problem respectively for Dirichlet or Neumann boundary data, that take the form of square roots of local operators .
Revised:  We introduce two new preconditioners , in the form of square roots of local operators .
Edit intent: coherence
Original:  We introduce two new preconditioners to tackle this problem respectively for Dirichlet or Neumann boundary data, that take the form of square roots of local operators .
Revised:  We introduce two new preconditioners to tackle this problem respectively for Dirichlet or Neumann boundary data, that take the form of square-roots of local operators .
Edit intent: fluency
Original:  We apply this method to densest subgraph and k-means .
Revised:  We apply this method to densest subgraph problem .
Edit intent: clarity
Original:  In a previous paper, Chierichetti et al.~ NIPS 2017%DIFDELCMD < ] %%% showed that problems such as k-means can be approximated up to a constant factor while ensuring that none of two protected class (e.g., gender, ethnicity) is disparately impacted.
Revised:  In a previous paper, Chierichetti et al.~ %DIFDELCMD < ] %%% showed that problems such as k-means can be approximated up to a constant factor while ensuring that none of two protected class (e.g., gender, ethnicity) is disparately impacted.
Edit intent: clarity
Original:  We complement several recent papers in this line of research by introducing a general method to reduce bias in the data through random projections in a ``fair'' subspace.
Revised:  We complement several recent papers in this line of research by introducing a general method to reduce bias in the data through random projections in a "fair" subspace.
Edit intent: fluency