wanyu/IteraTeR_v2 huggingface dataset:
Original:  The results show that the generated generators were able to achieve a good performance on most of the fitness functions over these three problems but on Zelda and Sokoban  they tend to depend on the initial state than modifying the map.
Revised:  The results show that the generated generators were able to achieve a good performance on most of the fitness functions over these three problems . However, on Zelda and Sokoban they tend to depend on the initial state than modifying the map.
Edit intent: coherence
Original:  The results show that the generated generators were able to achieve a good performance on most of the fitness functions over these three problems but on Zelda and Sokoban  they tend to depend on the initial state than modifying the map.
Revised:  The results show that the generated generators were able to achieve a good performance on most of the fitness functions over these three problems but on Zelda and Sokoban , they tend to depend on the initial state than modifying the map.
Edit intent: fluency
Original: In this paper, we deal with the study of the impact of worldwide nation measures for COVID-19 anti-pandemic.
Revised: In this paper, we deal with the study of the impact of nationwide measures COVID-19 anti-pandemic.
Edit intent: clarity
Original:  We show a comparison between deterministic and two machine learning technics for forecasting .
Revised:  We show a comparison between deterministic and two machine learning tools .
Edit intent: clarity
Original:  While the visual information from overhead images with powerful models and efficient algorithms yields good performance on scene recognition, additional information is always a bonus, for example, the corresponding audio information.
Revised:  While the visual information from overhead images with powerful models and efficient algorithms yields considerable performance on scene recognition, additional information is always a bonus, for example, the corresponding audio information.
Edit intent: clarity
Original:  The source code is publicly available for reproducibility URL
Revised:  The source code is publicly available for reproducibility purposes.
Edit intent: clarity
Original: Implicit feedback, such as user clicks, is a major source of supervision for learning to rank (LTR) model estimation in modern retrieval systems.
Revised: Recent advances in unbiased learning to rank (LTR) model estimation in modern retrieval systems.
Edit intent: clarity
Original:  Though effective, it only corrects the bias introduced by treating clicked documents as relevant, but cannot handle the bias caused by treating unclicked ones as irrelevant.
Revised:  Though effective, it only corrects the bias introduced by treating clicked documents as relevant, IPS ignores the bias caused by treating unclicked ones as irrelevant.
Edit intent: clarity
Original:  We then derive a new weighting scheme  called Propensity Ratio Scoring (PRS) that takes a holistic treatment on both clicks and non-clicks.
Revised:  We then derive a new weighting scheme , called Propensity Ratio Scoring (PRS) that takes a holistic treatment on both clicks and non-clicks.
Edit intent: fluency
Original:  We then derive a new weighting scheme  called Propensity Ratio Scoring (PRS) that takes a holistic treatment on both clicks and non-clicks.
Revised:  We then derive a new weighting scheme called Propensity Ratio Scoring (PRS) , which provides treatments on both clicks and non-clicks.
Edit intent: clarity
Original:  Besides correcting the bias in clicked documents , PRS avoids relevant-relevant  comparisons in LTR training in expectation and enjoys a lower variability.
Revised:  Besides correcting the bias in clicks , PRS avoids relevant-relevant comparisons in LTR training in expectation and enjoys a lower variability.
Edit intent: clarity
Original:  Besides correcting the bias in clicked documents , PRS avoids relevant-relevant  comparisons in LTR training in expectation and enjoys a lower variability.
Revised:  Besides correcting the bias in clicked documents , PRS avoids relevant-relevant document comparisons in LTR training in expectation and enjoys a lower variability.
Edit intent: coherence
Original:  Besides correcting the bias in clicked documents , PRS avoids relevant-relevant  comparisons in LTR training in expectation and enjoys a lower variability.
Revised:  Besides correcting the bias in clicked documents , PRS avoids relevant-relevant comparisons in LTR training and enjoys a lower variability.
Edit intent: clarity
Original:  Our empirical study confirms that PRS ensures a more effective use of click data in various situations, which leads to its superior performance in an extensive set of LTR benchmarks  .
Revised:  Our extensive empirical evaluations confirm that PRS ensures a more effective use of click data in various situations, which leads to its superior performance in an extensive set of LTR benchmarks .
Edit intent: clarity
Original: Aligning biological sequences belongs to the most important problems in computational sequence analysis;
Revised: Sequences of nucleotides (for DNA and RNA) or amino acids (for proteins) are central objects in biology. Among the most important problems in computational sequence analysis;
Edit intent: clarity
Original:  it allows for detecting evolutionary relationships between sequences and for predicting biomolecular structure and function.
Revised:  it allows for detecting evolutionary relationships between sequences , and to predict biomolecular structure and function.
Edit intent: fluency
Original:  Typically this is addressed through profile models, which capture position-specificities like conservation in sequences, but assume an independent evolution of different positions.
Revised:  This is typically addressed through profile models, which capture position-specificities like conservation in sequences, but assume an independent evolution of different positions.
Edit intent: clarity
Original:  RNA sequences are an exception where the coevolution of paired bases in the secondary structure is taken into account.
Edit intent: coherence
Original:  Our results highlight the utility of Wikipediafor studying reactions to the pandemic across the globe, and illustrate how the disease is rippling through society.
Revised:  Our results highlight the utility of Wikipedia for studying reactions to the pandemic across the globe, and illustrate how the disease is rippling through society.
Edit intent: fluency
Original: We study how the coronavirus disease 2019 ( COVID-19 ) pandemic, alongside the severe mobility restrictions that ensued, has impacted information access on Wikipedia, the world's largest online encyclopedia.
Revised: We study how the COVID-19 ) pandemic, alongside the severe mobility restrictions that ensued, has impacted information access on Wikipedia, the world's largest online encyclopedia.
Edit intent: clarity
Original: We study how the coronavirus disease 2019 ( COVID-19 ) pandemic, alongside the severe mobility restrictions that ensued, has impacted information access on Wikipedia, the world's largest online encyclopedia.
Revised: We study how the coronavirus disease 2019 ( COVID-19 pandemic, alongside the severe mobility restrictions that ensued, has impacted information access on Wikipedia, the world's largest online encyclopedia.
Edit intent: fluency
Original:  Health- and entertainment- related topics are found to have gained, and sports- and transportation- related topics, to have lost attention   .
Revised:  Health- and entertainment- related topics are found to have gained, and sports- and transportation- related topics, to have lost attentionvolume .
Edit intent: coherence
Original:  Health- and entertainment- related topics are found to have gained, and sports- and transportation- related topics, to have lost attention   .
Revised:  Health- and entertainment- related topics are found to have gained, and sports- and transportation- related topics, to have lost attention nature .
Edit intent: fluency
Original:  Our results highlight the utility of Wikipedia for studying reactions to the pandemic across the globe, and illustrate how the disease is rippling through society \WP  .
Revised:  Our results highlight the utility of \WP .
Edit intent: clarity
Original:  These changes are most pronounced for language editions associated with countries in which the most severe mobility restrictions were implemented.
Revised:  These changes are most pronounced for language editions associated with countries where the most severe mobility restrictions were implemented.
Edit intent: clarity
Original:  %DIFDELCMD < \eg%%%  , attention towards entertainment%DIFDELCMD < \hyp %DIFDELCMD < %%% related topics is lingering and even increasing, while the interest in health%DIFDELCMD < \hyp %%% and biology%DIFDELCMD < \hyp %%% related topics was either small or transient.
Revised:  %DIFDELCMD < \eg%%% , attention towards %DIFDELCMD < \hyp %DIFDELCMD < %%% related topics is lingering and even increasing, while the interest in health%DIFDELCMD < \hyp %%% and biology%DIFDELCMD < \hyp %%% related topics was either small or transient.
Edit intent: clarity
Original:  %DIFDELCMD < \eg%%%  , attention towards entertainment%DIFDELCMD < \hyp %DIFDELCMD < %%% related topics is lingering and even increasing, while the interest in health%DIFDELCMD < \hyp %%% and biology%DIFDELCMD < \hyp %%% related topics was either small or transient.
Revised:  %DIFDELCMD < \eg%%% , attention towards entertainment%DIFDELCMD < \hyp %DIFDELCMD < %%% entertainment-related topics is lingering and even increasing, while the interest in health%DIFDELCMD < \hyp %%% and biology%DIFDELCMD < \hyp %%% related topics was either small or transient.
Edit intent: fluency
Original:  %DIFDELCMD < \eg%%%  , attention towards entertainment%DIFDELCMD < \hyp %DIFDELCMD < %%% related topics is lingering and even increasing, while the interest in health%DIFDELCMD < \hyp %%% and biology%DIFDELCMD < \hyp %%% related topics was either small or transient.
Revised:  %DIFDELCMD < \eg%%% , attention towards entertainment%DIFDELCMD < \hyp %DIFDELCMD < %%% related topics is lingering and even increasing, while the interest in %DIFDELCMD < \hyp %%% and biology%DIFDELCMD < \hyp %%% related topics was either small or transient.
Edit intent: fluency
Original:  %DIFDELCMD < \eg%%%  , attention towards entertainment%DIFDELCMD < \hyp %DIFDELCMD < %%% related topics is lingering and even increasing, while the interest in health%DIFDELCMD < \hyp %%% and biology%DIFDELCMD < \hyp %%% related topics was either small or transient.
Revised:  %DIFDELCMD < \eg%%% , attention towards entertainment%DIFDELCMD < \hyp %DIFDELCMD < %%% related topics is lingering and even increasing, while the interest in health%DIFDELCMD < \hyp %%% %DIFDELCMD < \hyp %%% related topics was either small or transient.
Edit intent: coherence
Original:  Our results highlight the utility of %DIFDELCMD < \WP %%%  for studying how the pandemic affected people's needs, interests, and concerns.
Revised:  Our results highlight the utility of %DIFDELCMD < \WP %%% for studying how the pandemic is affecting people's needs, interests, and concerns.
Edit intent: clarity
Original:  We consider selfish clients, where each selfish client has private side information and a private value of each data chunk it wants.
Revised:  We consider selfish clients, where each selfish client has private side information and a private valuation of each data chunk it wants.
Edit intent: fluency
Original:  In this context, our objectives are following: 1) to motivate each selfish client to reveal the correct side information and true value of each data chunk it wants;
Revised:  In this context, our objectives are following: 1) to motivate each selfish client to reveal the correct side information and true valuation of each data chunk it wants;
Edit intent: clarity
Original:  2) to maximize the social welfare, i.e., the total value of the data chunks recovered by the clients minus the total cost incurred by the transmissions from the server.
Revised:  2) to maximize the social welfare, i.e., the total valuation of the data chunks recovered by the clients minus the total cost incurred by the transmissions from the server.
Edit intent: clarity
Original:  Our main contribution is to develop computationally efficient coding schemes and incentive schemes for achieving the first objective perfectly and achieving the second objective optimally or approximately ( with guaranteed approximation ratios  ).
Revised:  Our main contribution is to jointly develop coding schemes and incentive schemes for achieving the first objective perfectly and achieving the second objective optimally or approximately ( with guaranteed approximation ratios ).
Edit intent: clarity
Original:  Our main contribution is to develop computationally efficient coding schemes and incentive schemes for achieving the first objective perfectly and achieving the second objective optimally or approximately ( with guaranteed approximation ratios  ).
Revised:  Our main contribution is to develop computationally efficient coding schemes and incentive schemes for achieving the first objective perfectly and achieving the second objective optimally or approximately with guaranteed approximation ratios ).
Edit intent: fluency
Original: In this paper, we propose a parallel WaveGAN (PWG)-like neural vocoder with a quasi-periodic (QP) architecture to improve the pitch controllability of PWG. PWG is a compact non-autoregressive (non-AR) speech generation model, whose generation speed is much faster than real-time.
Revised: In this paper, we propose a parallel WaveGAN (PWG)-like neural vocoder with a quasi-periodic (QP) architecture to improve the pitch controllability of PWG. PWG is a compact non-autoregressive (non-AR) speech generation model, whose generative speed is much faster than real-time.
Edit intent: clarity
Original:  While PWG is taken as a vocoder to generate speech on the basis of acoustic features such as spectral and prosodic features, PWG-generated speechcontains a high fidelity .
Revised:  While PWG is taken as a vocoder to generate speech on the basis of acoustic features such as spectral and prosodic features, PWG generates high-fidelity speech .
Edit intent: clarity
Original:  However, because of the fixed and generic network structure , the pitch accuracy of PWG-generated speech degrades when the PWG vocoder conditioned on the acoustic features including unseen pitch features such as scaled pitches .
Revised:  However, when the input acoustic features include unseen pitches , the pitch accuracy of PWG-generated speech degrades when the PWG vocoder conditioned on the acoustic features including unseen pitch features such as scaled pitches .
Edit intent: clarity
Original:  The proposed QPPWG adopts a pitch-dependent dilated convolution network (PDCNN) module, which introduces the pitch information into PWG via the dynamically changed network architecture, to improve the pitch controllability and speech modeling capability of vanilla PWG. Both objective and subjective evaluation results confirm the higher pitch accuracy and comparable speech quality of QPPWG-generated speech , while the QPPWG model size is only 70 \% of that of vanilla PWG.
Revised:  The proposed QPPWG adopts a pitch-dependent dilated convolution network (PDCNN) module, which introduces the pitch information into PWG via the dynamically changed network architecture, to improve the pitch controllability and speech modeling capability of vanilla PWG. Both objective and subjective evaluation results show the higher pitch accuracy and comparable speech quality of QPPWG-generated speech , while the QPPWG model size is only 70 \% of that of vanilla PWG.
Edit intent: clarity
Original:  The proposed QPPWG adopts a pitch-dependent dilated convolution network (PDCNN) module, which introduces the pitch information into PWG via the dynamically changed network architecture, to improve the pitch controllability and speech modeling capability of vanilla PWG. Both objective and subjective evaluation results confirm the higher pitch accuracy and comparable speech quality of QPPWG-generated speech , while the QPPWG model size is only 70 \% of that of vanilla PWG.
Revised:  The proposed QPPWG adopts a pitch-dependent dilated convolution network (PDCNN) module, which introduces the pitch information into PWG via the dynamically changed network architecture, to improve the pitch controllability and speech modeling capability of vanilla PWG. Both objective and subjective evaluation results confirm the higher pitch accuracy and comparable speech quality of QPPWG-generated speech when the QPPWG model size is only 70 \% of that of vanilla PWG.
Edit intent: coherence
Original:  However, collecting the required training data and building these advanced systems from scratch is time and resource consuming.
Revised:  However, collecting the required training data and building these advanced systems from scratch are time and resource consuming.
Edit intent: fluency
Original:  A more economical approach is to develop a neural vocoder to enhance the speech generated by existing  TTS systems.
Revised:  An economical approach is to develop a neural vocoder to enhance the speech generated by existing TTS systems.
Edit intent: clarity
Original: We study an optimal movement strategy of agents during an ongoing epidemic  among the (D) states  of a country having various levels of infection spreading.
Revised: We study an optimal movement strategy of agents during an ongoing epidemic , among the (D) states of a country having various levels of infection spreading.
Edit intent: fluency
Original:  Due to the random (but fixed in time) choices of the agents, the system essentially forms a set of D/2 coupled Minority Games, played simultaneously.
Edit intent: coherence
Original: In this paper, we present a model to predict the spread of the Covid-19 epidemic andapply it to the specific case of Italy.
Revised: In this paper, we present a model to predict the spread of the Covid-19 epidemic and apply it to the specific case of Italy.
Edit intent: fluency
Original:  Using this model, we were able to reproduce the real behavior of theepidemic within a confidence interval of 5 \%.
Revised:  Using this model, we were able to reproduce the real behavior of the epidemic with an average error of 5 \%.
Edit intent: clarity
Original:  Using this model, we were able to reproduce the real behavior of theepidemic within a confidence interval of 5 \%.
Revised:  Using this model, we were able to reproduce the real behavior of theepidemic within a confidence interval of 5 
Edit intent: fluency
Original:  \\%DIF > . Moreover, we illustrate possible futurescenarios , associated to different intervals ofR0 . This model has been used since thebeginning of March 2020, predicting the Italian peak of the epidemic in April 2020with about 100.000 detected active cases.
Revised:  \\%DIF > . Moreover, we illustrate possible future scenarios , associated to different intervals ofR0 . This model has been used since thebeginning of March 2020, predicting the Italian peak of the epidemic in April 2020with about 100.000 detected active cases.
Edit intent: fluency
Original:  \\%DIF > . Moreover, we illustrate possible futurescenarios , associated to different intervals ofR0 . This model has been used since thebeginning of March 2020, predicting the Italian peak of the epidemic in April 2020with about 100.000 detected active cases.
Revised:  \\%DIF > . Moreover, we illustrate possible futurescenarios , associated to different intervals ofR0 . This model has been used since the beginning of March 2020, predicting the Italian peak of the epidemic in April 2020with about 100.000 detected active cases.
Edit intent: fluency
Original:  \\%DIF > . Moreover, we illustrate possible futurescenarios , associated to different intervals ofR0 . This model has been used since thebeginning of March 2020, predicting the Italian peak of the epidemic in April 2020with about 100.000 detected active cases.
Revised:  \\%DIF > . Moreover, we illustrate possible futurescenarios , associated to different intervals ofR0 . This model has been used since thebeginning of March 2020, predicting the Italian peak of the epidemic in April 2020 with about 100.000 detected active cases.
Edit intent: fluency
Original:  The real peak of the epidemic happened onthe 20th of April 2020, with 108.000 active cases.
Revised:  The real peak of the epidemic happened on the 20th of April 2020, with 108.000 active cases.
Edit intent: fluency
Original: In this paper, we consider the sparse phase retrival problem, recovering an s-sparse signal x^{\natural}\inR^n from m phaseless samples y_i=|\langlex^{\natural},a_i\rangle| for i=1,\ldots,m.
Revised: In this paper, we consider the sparse phase retrieval problem, recovering an s-sparse signal x^{\natural}\inR^n from m phaseless samples y_i=|\langlex^{\natural},a_i\rangle| for i=1,\ldots,m.
Edit intent: fluency
Original:  Our proposed algorithm is theoretically guaranteed to give an exact sparse signal recovery in finite (in particular, at most O(\log m + \log(\|x^{\natural}\|_2/|x_{\min}^{\natural}|))) steps, when \{a_i\}_{i=1}^{m} are i.i.d. standard Gaussian random vector with m\sim O(s\log(n/s)) and the initialization is in a neighbourhood of the underlying sparse signal.
Revised:  Our proposed algorithm is theoretically guaranteed to give an exact sparse signal recovery in finite (in particular, at most O(\log m + \log(\|x^{\natural}\|_2/|x_{\min}^{\natural}|))) steps, when \{a_i\}_{i=1}^{m} are i.i.d. standard Gaussian random vector with m\sim O(s\log(n/s)) and the initialization is in a neighborhood of the underlying sparse signal.
Edit intent: fluency
Original:  This is why we report in this paper the first known attempt to try to perform adversarial attack on voice conversion.
Revised:  This is why we report in this paper the first known attempt to perform adversarial attack on voice conversion.
Edit intent: coherence
Original:  We also run sentiment analysis and the results show that trust for the authorities remained a prevalent emotion, but mixed feelings of trust for authorities, fear for the outbreak, and anticipation for the potential preventive measures will be taken are identified .
Revised:  Sentiment analysis shows that fear for the unknown nature of the coronavirus is dominant in all topics .
Edit intent: coherence
Original:  VP is defined as a changing of brain signals when perceiving visual information and VI is defined as a changing of brain signals when  memorizing visual information  .
Revised:  VP and VI are defined as a changing of brain signals when memorizing visual information .
Edit intent: clarity
Original:  VP is defined as a changing of brain signals when perceiving visual information and VI is defined as a changing of brain signals when  memorizing visual information  .
Revised:  VP is defined as a changing of brain signals when perceiving visual information and VI is defined as a changing of brain signals when perceiving and memorizing visual information .
Edit intent: clarity
Original:  VP is defined as a changing of brain signals when perceiving visual information and VI is defined as a changing of brain signals when  memorizing visual information  .
Revised:  VP is defined as a changing of brain signals when perceiving visual information and VI is defined as a changing of brain signals when memorizing visual information , respectively .
Edit intent: coherence
Original:  As a result, we obtained a high performance of 43.00\% (chance level is 16.67\%) in the 6-class classification (VP) of subject 1.
Revised:  As a result, the 6-class classification (VP) of subject 1.
Edit intent: coherence
Original:  The average performance was 32.56\% . Also, the binary classification performance which classifies two paradigms was 90.16\% .
Revised:  The average performance was 32.56\% and the binary classification performance which classifies two paradigms was 90.16\% .
Edit intent: coherence
Original: Deep learning (DL) can be employed as a numerical method to approximate functions.
Revised: Deep learning (DL) is a numerical method to approximate functions.
Edit intent: clarity