wanyu/IteraTeR_v2 huggingface dataset:
Original:  As a result, we get extractors for small-space  sources over n bits with entropy requirement k\geq n^{1/2+\delta}  , whereas the previous best result (Chattopadhyay et al., STOC 2020) required k\geq n^{2/3+\delta} .
Revised:  As a result, we get extractors for small-space sources over n bits that require entropy k\geq n^{1/2+\delta} , whereas the previous best result (Chattopadhyay et al., STOC 2020) required k\geq n^{2/3+\delta} .
Edit intent: clarity
Original:  The previous best result (Chattopadhyay et al., STOC2020)required K\geq N^{1/2+o(1)}\cdot2 small-space sources: Using a known reduction to adversarial sources, we immediately obtain improved low-error extractors for space s sources over n bits that require entropy k\geq n^{1/2+\delta}\cdot s^{1/2-\delta}, whereas the previous best result (Chattopadhyay et al., STOC 2020) required k\geq n^{2/3+\delta}\cdot s^{1/3-\delta} .
Revised:  The previous best result (Chattopadhyay et al., STOC2020)required K\geq N^{1/2+o(1)}\cdot2 small-space sources in the negligible error regime. For space s sources over n bits that require entropy k\geq n^{1/2+\delta}\cdot s^{1/2-\delta}, whereas the previous best result (Chattopadhyay et al., STOC 2020) required k\geq n^{2/3+\delta}\cdot s^{1/3-\delta} .
Edit intent: clarity
Original:  The previous best result (Chattopadhyay et al., STOC2020)required K\geq N^{1/2+o(1)}\cdot2 small-space sources: Using a known reduction to adversarial sources, we immediately obtain improved low-error extractors for space s sources over n bits that require entropy k\geq n^{1/2+\delta}\cdot s^{1/2-\delta}, whereas the previous best result (Chattopadhyay et al., STOC 2020) required k\geq n^{2/3+\delta}\cdot s^{1/3-\delta} .
Revised:  The previous best result (Chattopadhyay et al., STOC2020)required K\geq N^{1/2+o(1)}\cdot2 small-space sources: Using a known reduction to adversarial sources, we immediately obtain improved low-error extractors for space s sources over n bits , our extractors require entropy k\geq n^{1/2+\delta}\cdot s^{1/2-\delta}, whereas the previous best result (Chattopadhyay et al., STOC 2020) required k\geq n^{2/3+\delta}\cdot s^{1/3-\delta} .
Edit intent: clarity
Original:  The previous best result (Chattopadhyay et al., STOC2020)required K\geq N^{1/2+o(1)}\cdot2 small-space sources: Using a known reduction to adversarial sources, we immediately obtain improved low-error extractors for space s sources over n bits that require entropy k\geq n^{1/2+\delta}\cdot s^{1/2-\delta}, whereas the previous best result (Chattopadhyay et al., STOC 2020) required k\geq n^{2/3+\delta}\cdot s^{1/3-\delta} .
Revised:  The previous best result (Chattopadhyay et al., STOC2020)required K\geq N^{1/2+o(1)}\cdot2 small-space sources: Using a known reduction to adversarial sources, we immediately obtain improved low-error extractors for space s sources over n bits that require entropy k\geq n^{1/2+\delta}\cdot s^{1/2-\delta}, whereas the previous best result required k\geq n^{2/3+\delta}\cdot s^{1/3-\delta} .
Edit intent: fluency
Original:  Our extractors require just k\geq s\cdot\log^Cn entropy for some constant C , which is an exponential improvement over the previous best result, which required k\geq s^{1.1}%DIFDELCMD < \cdot2%%% ^{\log^{0.51 .
Revised:  Our extractors require just k\geq s\cdot\log^Cn entropy for some constant C , which is }%DIFDELCMD < \cdot2%%% ^{\log^{0.51 .
Edit intent: clarity
Original:  We study the dialect bias in the summaries of such datasets generated by common summarization algorithms and observe that, for datasets that have sentences from more than one dialect, most summarization algorithms return summaries that under-represent the minority dialect .
Revised:  We study the dialect bias in the summaries of such datasets generated by common summarization approaches, i.e., they often return summaries that under-represent the minority dialect .
Edit intent: clarity
Original:  Crucially, our approach does not need the sentences in the dataset to have dialect labels, ensuring that the diversification process is independent of dialect classification and language identification models.
Revised:  Crucially, this approach does not need the sentences in the dataset to have dialect labels, ensuring that the diversification process is independent of dialect classification and language identification models.
Edit intent: fluency
Original:  Crucially, our approach does not need the sentences in the dataset to have dialect labels, ensuring that the diversification process is independent of dialect classification and language identification models.
Revised:  Crucially, our approach does not need the posts being summarized to have dialect labels, ensuring that the diversification process is independent of dialect classification and language identification models.
Edit intent: clarity
Original:  Crucially, our approach does not need the sentences in the dataset to have dialect labels, ensuring that the diversification process is independent of dialect classification and language identification models.
Revised:  Crucially, our approach does not need the sentences in the dataset to have dialect labels, ensuring that the diversification process is independent of dialect classification / identification models.
Edit intent: clarity
Original:  We show the efficacy of our approach on Twitter datasets containing posts written in dialects used by different social groups defined by race , region or gender;
Revised:  We show the efficacy of our approach on Twitter datasets containing posts written in dialects used by different social groups defined by race or gender;
Edit intent: clarity
Original:  in all cases, our approach leads to improved dialect diversity compared to the standard summarization approaches.
Revised:  in all cases, our approach leads to improved dialect diversity compared to standard text summarization approaches.
Edit intent: fluency
Original: When using boundary integral equation methods, we represent solutions of a linear , partial differential equation as layer potentials.
Revised: When using boundary integral equation methods, we represent solutions of a linear partial differential equation as layer potentials.
Edit intent: fluency
Original:  To address this challenge, we establish new layer potential identities that can be used to modify the solution's representation . Similar to Gauss's law used to modify Laplace's double-layer potential, we provide new identities to modify Laplace's single-layer potential and Helmholtz layer potentials that avoid the close evaluation problem  .
Revised:  To address this challenge, we provide modified representations of the problem's solution . Similar to Gauss's law used to modify Laplace's double-layer potential, we provide new identities to modify Laplace's single-layer potential and Helmholtz layer potentials that avoid the close evaluation problem .
Edit intent: clarity
Original:  To address this challenge, we establish new layer potential identities that can be used to modify the solution's representation . Similar to Gauss's law used to modify Laplace's double-layer potential, we provide new identities to modify Laplace's single-layer potential and Helmholtz layer potentials that avoid the close evaluation problem  .
Revised:  To address this challenge, we establish new layer potential identities that can be used to modify the solution's representation . Similar to Gauss's law used to modify Laplace's double-layer potential, we use modified representations of Laplace's single-layer potential and Helmholtz layer potentials that avoid the close evaluation problem .
Edit intent: clarity
Original: COVID-19 -- a viral infectious disease -- has quickly emerged as a global pandemic infecting millions of people with a significant number of deaths across the globe.
Revised: COVID-19--a viral infectious disease--has quickly emerged as a global pandemic infecting millions of people with a significant number of deaths across the globe.
Edit intent: fluency
Original: Objectives: To predict mechanical ventilation requirement and mortality using computational modeling of chest radiographs ( CXR ) for coronavirus disease 2019 (COVID-19) patients.
Revised: We predict mechanical ventilation requirement and mortality using computational modeling of chest radiographs ( CXR ) for coronavirus disease 2019 (COVID-19) patients.
Edit intent: coherence
Original: Objectives: To predict mechanical ventilation requirement and mortality using computational modeling of chest radiographs ( CXR ) for coronavirus disease 2019 (COVID-19) patients.
Revised: Objectives: To predict mechanical ventilation requirement and mortality using computational modeling of chest radiographs ( CXRs ) for coronavirus disease 2019 (COVID-19) patients.
Edit intent: fluency
Original:  Machine learning classifiers to predict mechanical ventilation requirement and mortality were trained and evaluated on 353 baseline CXRstaken from COVID-19 positive patients .
Revised:  Machine learning classifiers to predict mechanical ventilation requirement and mortality were trained and evaluated using patient CXRs .
Edit intent: clarity
Original:  A novel radiomic embedding framework is also explored for outcome prediction.
Revised:  A novel radiomic embedding framework was also explored for outcome prediction.
Edit intent: fluency
Original:  Results: Classification models for mechanical ventilation requirement (test N=154) and mortality (test N=190) had AUCs of up to 0.904 and 0.936 , respectively.
Revised:  Results: Classification models for mechanical ventilation requirement and 0.936 , respectively.
Edit intent: clarity
Original:  Results: Classification models for mechanical ventilation requirement (test N=154) and mortality (test N=190) had AUCs of up to 0.904 and 0.936 , respectively.
Revised:  Results: Classification models for mechanical ventilation requirement (test N=154) and mortality (test N=190) had AUCs of up to 0.904 and mortality prediction , respectively.
Edit intent: clarity
Original:  Our results also suggest that radiomic embedding improves DL models in medical image analysis, a technique that might be explored further in other pathologies.
Revised:  Our results also suggest instances where inclusion of radiomic features in DL improves model predictions, something that might be explored further in other pathologies.
Edit intent: clarity
Original:  Our results also suggest that radiomic embedding improves DL models in medical image analysis, a technique that might be explored further in other pathologies.
Revised:  Our results also suggest that radiomic embedding improves DL models in medical image analysis, a technique that might be explored in other pathologies.
Edit intent: clarity
Original:  The models proposed in this study and the prognostic information they provide , complementary to other clinical data, might be used to aid physician decision making and resource allocation during the COVID-19 pandemic.
Revised:  The models proposed in this study and the prognostic information they provide might aid physician decision making and resource allocation during the COVID-19 pandemic.
Edit intent: clarity
Original: Given a point set P\subset R^d,  kernel density estimation for Gaussian kernel is defined as \mathcal{G}_P(x) = 1{\left|P\right|}p\in Pe^{-\left\lVert x-p \right\rVert^2} for any x\inR^d.
Revised: Given a point set P\subset R^d, a kernel density estimation for Gaussian kernel is defined as \mathcal{G}_P(x) = 1{\left|P\right|}p\in Pe^{-\left\lVert x-p \right\rVert^2} for any x\inR^d.
Edit intent: fluency
Original:  This subset Q is called coreset .
Revised:  This subset Q is called coreset .
Edit intent: fluency
Original:  In this paper we study the intrinsic tradeoff between the space complexity of the sketch and its estimation error in the Random Oracle model.
Revised:  In this paper we study the intrinsic tradeoff between the space complexity of the sketch and its estimation error in the random oracle model.
Edit intent: fluency
Original:  We define a new measure of efficiency for cardinality estimators called the Fisher-Shannon ( \mathsf{Fish ) number H/I.
Revised:  We define a new measure of efficiency for cardinality estimators called the Fisher-Shannon ( Fish ) number H/I.
Edit intent: coherence
Original:  It captures the tension between the limiting Shannon entropy (H) of the sketch and its normalized Fisher information (I), which characterizes (asymptotically) the variance of a statistically efficient estimator.
Revised:  It captures the tension between the limiting Shannon entropy (H) of the sketch and its normalized Fisher information (I), which characterizes the variance of a statistically efficient estimator.
Edit intent: clarity
Original:  We prove that many variants of the \mathsf{PCSA Flajolet and Martin have Fish number H_0/I_0 , where H_0,I_0 are two precisely-defined constants, and that all base-q generalizations of (Hyper )\textsf{LogLog are strictly worse than H_0/I_0, but  tend to H_0/I_0 in the limit as q %DIFDELCMD < \to%%% \infty.
Revised:  We prove that all base-q variants of Flajolet and Martin have Fish number H_0/I_0 , where H_0,I_0 are two precisely-defined constants, and that all base-q generalizations of (Hyper )\textsf{LogLog are strictly worse than H_0/I_0, but tend to H_0/I_0 in the limit as q %DIFDELCMD < \to%%% \infty.
Edit intent: clarity
Original:  We prove that many variants of the \mathsf{PCSA Flajolet and Martin have Fish number H_0/I_0 , where H_0,I_0 are two precisely-defined constants, and that all base-q generalizations of (Hyper )\textsf{LogLog are strictly worse than H_0/I_0, but  tend to H_0/I_0 in the limit as q %DIFDELCMD < \to%%% \infty.
Revised:  We prove that many variants of the \mathsf{PCSA Flajolet and Martin have Fish number H_0/I_0 , where H_0,I_0 are two precisely-defined constants, and that all base-q Hyper )\textsf{LogLog are strictly worse than H_0/I_0, but tend to H_0/I_0 in the limit as q %DIFDELCMD < \to%%% \infty.
Edit intent: clarity
Original:  We prove that many variants of the \mathsf{PCSA Flajolet and Martin have Fish number H_0/I_0 , where H_0,I_0 are two precisely-defined constants, and that all base-q generalizations of (Hyper )\textsf{LogLog are strictly worse than H_0/I_0, but  tend to H_0/I_0 in the limit as q %DIFDELCMD < \to%%% \infty.
Revised:  We prove that many variants of the \mathsf{PCSA Flajolet and Martin have Fish number H_0/I_0 , where H_0,I_0 are two precisely-defined constants, and that all base-q generalizations of ( )\textsf{LogLog are strictly worse than H_0/I_0, but tend to H_0/I_0 in the limit as q %DIFDELCMD < \to%%% \infty.
Edit intent: clarity
Original:  We prove that many variants of the \mathsf{PCSA Flajolet and Martin have Fish number H_0/I_0 , where H_0,I_0 are two precisely-defined constants, and that all base-q generalizations of (Hyper )\textsf{LogLog are strictly worse than H_0/I_0, but  tend to H_0/I_0 in the limit as q %DIFDELCMD < \to%%% \infty.
Revised:  We prove that many variants of the \mathsf{PCSA Flajolet and Martin have Fish number H_0/I_0 , where H_0,I_0 are two precisely-defined constants, and that all base-q generalizations of (Hyper \textsf{LogLog are strictly worse than H_0/I_0, but tend to H_0/I_0 in the limit as q %DIFDELCMD < \to%%% \infty.
Edit intent: fluency
Original:  We prove that many variants of the \mathsf{PCSA Flajolet and Martin have Fish number H_0/I_0 , where H_0,I_0 are two precisely-defined constants, and that all base-q generalizations of (Hyper )\textsf{LogLog are strictly worse than H_0/I_0, but  tend to H_0/I_0 in the limit as q %DIFDELCMD < \to%%% \infty.
Revised:  We prove that many variants of the \mathsf{PCSA Flajolet and Martin have Fish number H_0/I_0 , where H_0,I_0 are two precisely-defined constants, and that all base-q generalizations of (Hyper )\textsf{LogLog are strictly worse than H_0/I_0, but that they tend to H_0/I_0 in the limit as q %DIFDELCMD < \to%%% \infty.
Edit intent: clarity
Original:  The difficulty in proving the consistency is that a standard method of realizability a la Kleene does not work for the consistency, though it validates CT, as it does not model MLTT;
Revised:  The difficulty in proving the consistency is that a standard method of realizability \`{a la Kleene does not work for the consistency, though it validates CT, as it does not model MLTT;
Edit intent: fluency
Original:  We overcome this point and prove the consistency by novel realizability a la game semantics, which is based on the author's previous work.
Revised:  We overcome this point and prove the consistency by novel realizability \`{a la game semantics, which is based on the author's previous work.
Edit intent: fluency
Original:  Our work is aimed at producing a \emph{(\alpha,\Delta)-kernel of D_P(\kappa)}, namely a set %DIFDELCMD < \calS %%%  such that (after a shift) it holds that (1-\alpha)D_P(\kappa)\subset %DIFDELCMD < \CH%%% (%DIFDELCMD < \calS%%%  ) \subset (1+\alpha)D_P(\kappa-\Delta).
Revised:  Our work is aimed at producing a \emph{(\alpha,\Delta)-kernel of D_P(\kappa)}, namely a set %DIFDELCMD < \calS %%% such that (after a shift) it holds that (1-\alpha)D_P(\kappa)\subset %DIFDELCMD < \CH%%% %DIFDELCMD < \calS%%% ) \subset (1+\alpha)D_P(\kappa-\Delta).
Edit intent: fluency
Original:  We introduce a Soft Shadow Network to generate convincing soft shadows for 2D object cutouts automatically . SSN takes an object cutout mask as input and thus is agnostic to image types such as painting and vector art.
Revised:  We introduce a Soft Shadow Network (SSN) to generates controllable soft shadows for 2D object cutouts automatically . SSN takes an object cutout mask as input and thus is agnostic to image types such as painting and vector art.
Edit intent: clarity
Original:  We introduce a Soft Shadow Network to generate convincing soft shadows for 2D object cutouts automatically . SSN takes an object cutout mask as input and thus is agnostic to image types such as painting and vector art.
Revised:  We introduce a Soft Shadow Network to generate convincing soft shadows for image compositing . SSN takes an object cutout mask as input and thus is agnostic to image types such as painting and vector art.
Edit intent: clarity
Original:  We introduce a Soft Shadow Network to generate convincing soft shadows for 2D object cutouts automatically . SSN takes an object cutout mask as input and thus is agnostic to image types such as painting and vector art.
Revised:  We introduce a Soft Shadow Network to generate convincing soft shadows for 2D object cutouts automatically . SSN takes a 2D object mask as input and thus is agnostic to image types such as painting and vector art.
Edit intent: fluency
Original:  A user study shows that SSN generated shadows are often indistinguishable from shadows calculated by  physics-based rendering.
Revised:  A user study shows that the generated shadows are often indistinguishable from shadows calculated by physics-based rendering.
Edit intent: clarity
Original:  A user study shows that SSN generated shadows are often indistinguishable from shadows calculated by  physics-based rendering.
Revised:  A user study shows that SSN generated shadows are often indistinguishable from shadows calculated by a physics-based rendering.
Edit intent: fluency
Original:  Our user study shows that the generated shadows are often indistinguishable from shadows calculated by a physics-based renderer  .
Revised:  Our user studies show that the generated shadows are often indistinguishable from shadows calculated by a physics-based renderer .
Edit intent: fluency
Original: Several papers have proposed deep-learning-based models to predict the mean opinion score (MOS) of synthesized speech, showing the possibility of replacing human raters.
Revised: Several studies have proposed deep-learning-based models to predict the mean opinion score (MOS) of synthesized speech, showing the possibility of replacing human raters.
Edit intent: clarity
Original:  However, inter- and intra-rater variability in MOSs makes it hard to ensure the generalization ability of the models.
Revised:  However, inter- and intra-rater variability in MOSs makes it hard to ensure the high performance of the models.
Edit intent: clarity
Original:  In this paper, we propose a method using multi-task learning (MTL) with spoofing detection (SD) and spoofing type classification (STC) to improve the generalization ability of a MOS prediction model . Besides, we use the focal loss to maximize the synergy between SD and STC for MOS prediction.
Revised:  In this paper, we propose a multi-task learning (MTL) with spoofing detection (SD) and spoofing type classification (STC) to improve the generalization ability of a MOS prediction model . Besides, we use the focal loss to maximize the synergy between SD and STC for MOS prediction.
Edit intent: clarity
Original:  In this paper, we propose a method using multi-task learning (MTL) with spoofing detection (SD) and spoofing type classification (STC) to improve the generalization ability of a MOS prediction model . Besides, we use the focal loss to maximize the synergy between SD and STC for MOS prediction.
Revised:  In this paper, we propose a method using multi-task learning (MTL) with spoofing detection (SD) and spoofing type classification (STC) . Besides, we use the focal loss to maximize the synergy between SD and STC for MOS prediction.
Edit intent: clarity
Original:  We follow the latter path and establish a new condition -- the clique dynamics condition -- which is less restrictive than the ones in the literature.
Revised:  We follow the latter path and establish a new condition---the clique dynamics condition---, which is less restrictive than the ones in the literature.
Edit intent: fluency
Original:  The clique dynamics condition implies rapid mixing of a Markov chain that utilizes cliques of incompatible polymers that naturally arise from the translation of algorithmic problems into polymer models.
Revised:  The clique dynamics condition implies rapid mixing by utilizing cliques of incompatible polymers that naturally arise from the translation of algorithmic problems into polymer models.
Edit intent: clarity
Original: Traditional adaptive steganography is a technique used for covert communication with high security, but the scheme is invalid in the case of stego image is damaged by lossychannels , such as JPEG compression of channels.
Revised: Traditional adaptive steganography is a technique used for covert communication with high security, but it is invalid in the case of stego image is damaged by lossychannels , such as JPEG compression of channels.
Edit intent: clarity
Original:  To deal with such problem, robust adaptive steganography is proposed to enable the receiver to extract the secret message from the damaged stego image . Previous works utilise reverse engineering and compression-resistant domain constructing to implement robust adaptive steganography.
Revised:  To deal with such problem, robust adaptive steganography is proposed to enable the receiver to extract secret messages from the damaged stego image . Previous works utilise reverse engineering and compression-resistant domain constructing to implement robust adaptive steganography.
Edit intent: fluency
Original:  To deal with such problem, robust adaptive steganography is proposed to enable the receiver to extract the secret message from the damaged stego image . Previous works utilise reverse engineering and compression-resistant domain constructing to implement robust adaptive steganography.
Revised:  To deal with such problem, robust adaptive steganography is proposed to enable the receiver to extract the secret message from the damaged stego images . Previous works utilise reverse engineering and compression-resistant domain constructing to implement robust adaptive steganography.
Edit intent: fluency