wanyu/IteraTeR_v2 huggingface dataset:
Original:  We proposed a quantum blackjack: we devised a quantum circuit reproducing classical blackjack and found the possibility of entanglement between strategies.
Revised:  We proposed a quantum blackjack: we devised a quantum circuit reproducing classical blackjack and found possible quantum entanglement between strategies.
Edit intent: clarity
Original:  This circuit can be realized in the near future where quantum computers are commonplace.
Revised:  This circuit can be realized in the near future when quantum computers are commonplace.
Edit intent: fluency
Original:  Furthermore, we showed  the player's expectation increases compared to the classical game , using quantum basic strategy, which is a quantum version of the popularly known basic strategy of blackjack.
Revised:  Furthermore, we showed that the player's expectation increases compared to the classical game , using quantum basic strategy, which is a quantum version of the popularly known basic strategy of blackjack.
Edit intent: fluency
Original:  Furthermore, we showed  the player's expectation increases compared to the classical game , using quantum basic strategy, which is a quantum version of the popularly known basic strategy of blackjack.
Revised:  Furthermore, we showed the player's expectation increases compared to the classical game using quantum basic strategy, which is a quantum version of the popularly known basic strategy of blackjack.
Edit intent: fluency
Original:  Furthermore, we showed  the player's expectation increases compared to the classical game , using quantum basic strategy, which is a quantum version of the popularly known basic strategy of blackjack.
Revised:  Furthermore, we showed the player's expectation increases compared to the classical game , using quantum basic strategy, which is a quantum version of the popular basic strategy of blackjack.
Edit intent: clarity
Original:  Numerical experiments on MNIST and CIFAR10 clearly demonstrate degeneracy breaking in deep non-linear networks and show that the align-then-memorize process occurs sequentially from the bottom layers of the network to the top.
Revised:  Numerical experiments on MNIST and CIFAR10 clearly demonstrate degeneracy breaking in deep non-linear networks and show that the align-then-memorise process occurs sequentially from the bottom layers of the network to the top.
Edit intent: clarity
Original:  We demonstrate the utility of these models in the domain of face modeling through inverse rendering and registrationtasks . Specifically, we show that our approach can be used to perform face recognition using only a single 3D scan (one scan total, not one per person), and further demonstrate how multiple scans can be incorporated to improve performance without requiring dense correspondence.
Revised:  As we demonstrate in the face domain, these models can be used to infer 3D reconstructions from 2D data (inverse graphics) or 3D data (registration) . Specifically, we show that our approach can be used to perform face recognition using only a single 3D scan (one scan total, not one per person), and further demonstrate how multiple scans can be incorporated to improve performance without requiring dense correspondence.
Edit intent: clarity
Original:  Here we design a state-of-the-art method using genetic algorithm that, with many degrees of freedom, leads to architectures whose functions are similar to biological retina, as well as effective alternatives that are different in structures and functions.
Revised:  Here we design a method using genetic algorithm that, with many degrees of freedom, leads to architectures whose functions are similar to biological retina, as well as effective alternatives that are different in structures and functions.
Edit intent: clarity
Original:  We compare this state-of-the-art model to natural evolution and discuss how our framework can come into goal-driven search and sustainable enhancement of neural network models in machine learning.
Revised:  We compare this model to natural evolution and discuss how our framework can come into goal-driven search and sustainable enhancement of neural network models in machine learning.
Edit intent: clarity
Original:  However, there has been little research on mobility disparity across income groups in US cities during the pandemic.
Revised:  However, there has been little research on the disparity of mobility adaptation across different income groups in US cities during the pandemic.
Edit intent: clarity
Original:  The authors tried to fill this gap by quantifying the impacts of the pandemic on human mobility by income group in Houston-The Woodlands-Sugar Land, Texasutilizing pseudonymized cell phone location data.
Revised:  The authors worked to fill this gap by quantifying the impacts of the pandemic on human mobility by income group in Houston-The Woodlands-Sugar Land, Texasutilizing pseudonymized cell phone location data.
Edit intent: fluency
Original:  The authors tried to fill this gap by quantifying the impacts of the pandemic on human mobility by income group in Houston-The Woodlands-Sugar Land, Texasutilizing pseudonymized cell phone location data.
Revised:  The authors tried to fill this gap by quantifying the impacts of the pandemic on human mobility by income in Greater Houston, Texas. In this study, we determined human mobility using pseudonymized, spatially disaggregated cell phone location data.
Edit intent: clarity
Original:  A longitudinal study was performed on mobility as measured by the total travel distance, the radius of gyration, and the number of visited locations  in April 2020 compared to the data in January and February 2020.
Revised:  A longitudinal study was performed on mobility as measured by the total travel distance, radius of gyration, and the number of visited locations in April 2020 compared to the data in January and February 2020.
Edit intent: fluency
Original:  A longitudinal study was performed on mobility as measured by the total travel distance, the radius of gyration, and the number of visited locations  in April 2020 compared to the data in January and February 2020.
Revised:  A longitudinal study was performed on mobility as measured by the total travel distance, the radius of gyration, number of visited locations in April 2020 compared to the data in January and February 2020.
Edit intent: fluency
Original:  A longitudinal study was performed on mobility as measured by the total travel distance, the radius of gyration, and the number of visited locations  in April 2020 compared to the data in January and February 2020.
Revised:  A longitudinal study was performed on mobility as measured by the total travel distance, the radius of gyration, and the number of visited locations in April 2020 compared to the data in a baseline.
Edit intent: clarity
Original:  An apparent disparity in mobility has been found across income groups.
Revised:  An apparent disparity in mobility was found across estimated income groups.
Edit intent: clarity
Original:  In particular, there was a strong negative correlation ( \r{ho = -0.90) between the estimated income bracket of a travelerand the travel distance in April.
Revised:  In particular, there was a strong negative correlation ( \rho = -0.90) between the estimated income bracket of a travelerand the travel distance in April.
Edit intent: fluency
Original:  In particular, there was a strong negative correlation ( \r{ho = -0.90) between the estimated income bracket of a travelerand the travel distance in April.
Revised:  In particular, there was a strong negative correlation ( \r{ho = -0.90) between a traveler's estimated income and travel distance in April.
Edit intent: clarity
Original:  Furthermore, larger percentage drops among higher-income brackets in the radius of gyration and number of visited locations implied different adaptability in mobility .
Revised:  Disparities in mobility adaptability were further shown since those in higher income brackets experienced larger percentage drops among higher-income brackets in the radius of gyration and number of visited locations implied different adaptability in mobility .
Edit intent: clarity
Original:  Furthermore, larger percentage drops among higher-income brackets in the radius of gyration and number of visited locations implied different adaptability in mobility .
Revised:  Furthermore, larger percentage drops in the radius of gyration and number of visited locations implied different adaptability in mobility .
Edit intent: clarity
Original:  Furthermore, larger percentage drops among higher-income brackets in the radius of gyration and number of visited locations implied different adaptability in mobility .
Revised:  Furthermore, larger percentage drops among higher-income brackets in the radius of gyration and the number of distinct visited locations than did those in lower income brackets .
Edit intent: clarity
Original:  In this study , we determined human mobility using pseudonymized, spatially disaggregated cell phone location data.
Revised:  In this paper , we determined human mobility using pseudonymized, spatially disaggregated cell phone location data.
Edit intent: clarity
Original:  In this paper we present a universal framework for obtaining safe and complete algorithms which unify the previous results, while also allowing for easy generalizations to assembly problems including many practical aspects.
Revised:  In this paper we present a universal framework for obtaining safe and complete algorithms which unify the previous results, while also allowing for easy generalisations to assembly problems including many practical aspects.
Edit intent: fluency
Original:  The hydrostructure allows for simple characterizations of the existing safe walks, and of their new practical versions.
Revised:  The hydrostructure allows for simple characterisations of the existing safe walks, and of their new practical versions.
Edit intent: fluency
Original:  Almost all of our characterizations are directly adaptable to optimal verification algorithms, and simple enumeration algorithms.
Revised:  Almost all of our characterisations are directly adaptable to optimal verification algorithms, and simple enumeration algorithms.
Edit intent: fluency
Original:  The long-standing open problem of finding all the safe parts of the solutions was recently solved by a major theoretical result [RECOMB '16 ]  . This safe and complete genome assembly algorithm was followed by other works improving the time bounds, as well as extending the results for different notions of assembly solution.
Revised:  The long-standing open problem of finding all the safe parts of the solutions was recently solved [RECOMB '16 ] . This safe and complete genome assembly algorithm was followed by other works improving the time bounds, as well as extending the results for different notions of assembly solution.
Edit intent: clarity
Original:  The long-standing open problem of finding all the safe parts of the solutions was recently solved by a major theoretical result [RECOMB '16 ]  . This safe and complete genome assembly algorithm was followed by other works improving the time bounds, as well as extending the results for different notions of assembly solution.
Revised:  The long-standing open problem of finding all the safe parts of the solutions was recently solved by a major theoretical result [RECOMB 2016 ] . This safe and complete genome assembly algorithm was followed by other works improving the time bounds, as well as extending the results for different notions of assembly solution.
Edit intent: clarity
Original:  Moreover, it defines two second-order AI virtues, prudence and fortitude, that bolster achieving the basic virtues by helping with overcoming bounded ethicality or the many hidden psychological forces that impair ethical decision making and that are hitherto completely disregarded in AI ethics.
Revised:  Moreover, it defines two second-order AI virtues, prudence and fortitude, that bolster achieving the basic virtues by helping with overcoming bounded ethicality or the many hidden psychological forces that impair ethical decision making and that are hitherto disregarded in AI ethics.
Edit intent: clarity
Original:  The key challenge for developing better 3D attribute control methods is the lack of paired training data in which one attribute is changed while other attributes are held fixed---e .g., a pair of 3D faces where one is male and the other is female but all other attributes, such as race and expression, are the same.
Revised:  The key challenge for developing better 3D attribute control methods is the lack of paired training data in which one attribute is changed while other attributes are held fixed -- e .g., a pair of 3D faces where one is male and the other is female but all other attributes, such as race and expression, are the same.
Edit intent: fluency
Original:  Second, unlike previous approaches which integrate the computationally heavy patch searching and replacement operation in the inpainting model, CR lossencourages a vanilla CNN to simulate this behavior during training, thus no extra computations are required during inference.
Revised:  Second, unlike previous approaches which integrate the computationally heavy patch searching and replacement operation in the inpainting model, CR lossencourages a vanilla CNN to simulate this behavior during training, and only the inpainting generator is required during the inference.
Edit intent: clarity
Original:  Experimental results demonstrate that the proposed inpainting model with the CR loss compares favourably against the state-of-the-arts in terms of quantitative and visual performance.
Revised:  Experimental results demonstrate that the proposed inpainting model compares favourably against the state-of-the-arts in terms of quantitative and visual performance.
Edit intent: clarity
Original:  Experimental results demonstrate that the proposed inpainting model with the CR loss compares favourably against the state-of-the-arts in terms of quantitative and visual performance.
Revised:  Experimental results demonstrate that the proposed inpainting model with the CR loss compares favourably against the state-of-the-art in terms of quantitative and visual performance.
Edit intent: fluency
Original:  The second is to present alternative proofs unifying several results about the possibility of relabelling deterministic automata with different  conditions.
Revised:  The second is to present characterisations on the possibility of relabelling deterministic automata with different conditions.
Edit intent: clarity
Original:  The second is to present alternative proofs unifying several results about the possibility of relabelling deterministic automata with different  conditions.
Revised:  The second is to present alternative proofs unifying several results about the possibility of relabelling automata with different conditions.
Edit intent: clarity
Original: Inferring programs which generate 2D and 3D shapes is important for reverse engineering, enabling shape editing, and more.
Revised: Inferring programs which generate 2D and 3D shapes is important for reverse engineering, editing, and more.
Edit intent: clarity
Original:  LEST circumvents this problem by leveraging the fact that predicted latent programs are executable : for a given shape \mathbf{x^* \in S^* }  and its predicted program z \in P, we execute z to obtain a shape x \in S and train on (z \in P, \mathbf{x\in S}  ) pairs, rather than (z \in P , \mathbf{x}^* \in S^* ) pairs.
Revised:  LEST circumvents this problem by leveraging the fact that predicted latent programs are executable . For a given shape \mathbf{x^* \in S^* } and its predicted program z \in P, we execute z to obtain a shape x \in S and train on (z \in P, \mathbf{x\in S} ) pairs, rather than (z \in P , \mathbf{x}^* \in S^* ) pairs.
Edit intent: fluency
Original:  LEST circumvents this problem by leveraging the fact that predicted latent programs are executable : for a given shape \mathbf{x^* \in S^* }  and its predicted program z \in P, we execute z to obtain a shape x \in S and train on (z \in P, \mathbf{x\in S}  ) pairs, rather than (z \in P , \mathbf{x}^* \in S^* ) pairs.
Revised:  LEST circumvents this problem by leveraging the fact that predicted latent programs are executable : for a given shape ^* \in S^* } and its predicted program z \in P, we execute z to obtain a shape x \in S and train on (z \in P, \mathbf{x\in S} ) pairs, rather than (z \in P , \mathbf{x}^* \in S^* ) pairs.
Edit intent: fluency
Original:  LEST circumvents this problem by leveraging the fact that predicted latent programs are executable : for a given shape \mathbf{x^* \in S^* }  and its predicted program z \in P, we execute z to obtain a shape x \in S and train on (z \in P, \mathbf{x\in S}  ) pairs, rather than (z \in P , \mathbf{x}^* \in S^* ) pairs.
Revised:  LEST circumvents this problem by leveraging the fact that predicted latent programs are executable : for a given shape \mathbf{x^* \in S^* } and its predicted program z , one can execute z to obtain a shape x \in S and train on (z \in P, \mathbf{x\in S} ) pairs, rather than (z \in P , \mathbf{x}^* \in S^* ) pairs.
Edit intent: clarity
Original:  LEST circumvents this problem by leveraging the fact that predicted latent programs are executable : for a given shape \mathbf{x^* \in S^* }  and its predicted program z \in P, we execute z to obtain a shape x \in S and train on (z \in P, \mathbf{x\in S}  ) pairs, rather than (z \in P , \mathbf{x}^* \in S^* ) pairs.
Revised:  LEST circumvents this problem by leveraging the fact that predicted latent programs are executable : for a given shape \mathbf{x^* \in S^* } and its predicted program z \in P, we execute z to obtain a shape x and train on (z \in P, \mathbf{x\in S} ) pairs, rather than (z \in P , \mathbf{x}^* \in S^* ) pairs.
Edit intent: fluency
Original:  LEST circumvents this problem by leveraging the fact that predicted latent programs are executable : for a given shape \mathbf{x^* \in S^* }  and its predicted program z \in P, we execute z to obtain a shape x \in S and train on (z \in P, \mathbf{x\in S}  ) pairs, rather than (z \in P , \mathbf{x}^* \in S^* ) pairs.
Revised:  LEST circumvents this problem by leveraging the fact that predicted latent programs are executable : for a given shape \mathbf{x^* \in S^* } and its predicted program z \in P, we execute z to obtain a shape x \in S and train on (z \in S} ) pairs, rather than (z \in P , \mathbf{x}^* \in S^* ) pairs.
Edit intent: fluency
Original:  LEST circumvents this problem by leveraging the fact that predicted latent programs are executable : for a given shape \mathbf{x^* \in S^* }  and its predicted program z \in P, we execute z to obtain a shape x \in S and train on (z \in P, \mathbf{x\in S}  ) pairs, rather than (z \in P , \mathbf{x}^* \in S^* ) pairs.
Revised:  LEST circumvents this problem by leveraging the fact that predicted latent programs are executable : for a given shape \mathbf{x^* \in S^* } and its predicted program z \in P, we execute z to obtain a shape x \in S and train on (z \in P, \mathbf{x\in S} ) pairs, rather than (z , \mathbf{x}^* \in S^* ) pairs.
Edit intent: fluency
Original:  LEST circumvents this problem by leveraging the fact that predicted latent programs are executable : for a given shape \mathbf{x^* \in S^* }  and its predicted program z \in P, we execute z to obtain a shape x \in S and train on (z \in P, \mathbf{x\in S}  ) pairs, rather than (z \in P , \mathbf{x}^* \in S^* ) pairs.
Revised:  LEST circumvents this problem by leveraging the fact that predicted latent programs are executable : for a given shape \mathbf{x^* \in S^* } and its predicted program z \in P, we execute z to obtain a shape x \in S and train on (z \in P, \mathbf{x\in S} ) pairs, rather than (z \in P , \mathbf{x}^* ) pairs.
Edit intent: fluency
Original: Many real-world applications involve analyzing time-dependent phenomena, which are intrinsically functional---consisting of curves varying over a continuum , which is timein this case .
Revised: Many real-world applications involve analyzing time-dependent phenomena, which are intrinsically functional, consisting of curves varying over a continuum , which is timein this case .
Edit intent: fluency
Original: Many real-world applications involve analyzing time-dependent phenomena, which are intrinsically functional---consisting of curves varying over a continuum , which is timein this case .
Revised: Many real-world applications involve analyzing time-dependent phenomena, which are intrinsically functional---consisting of curves varying over a continuum (e.g., time) .
Edit intent: clarity
Original:  This is even more critical when we have new incoming data and want to update the FDA results in real-time .
Revised:  The analysis problem becomes even more challenging when we must update the FDA results in real-time .
Edit intent: clarity
Original:  To perform such an analysis while addressing the computational problem, we introduce new incremental and progressive algorithms that promptly generate the magnitude-shape (MS) plot, which reveals both the functional magnitude and shape outlyingness of time-series data.
Revised:  To perform FDA while addressing the computational problem, we introduce new incremental and progressive algorithms that promptly generate the magnitude-shape (MS) plot, which reveals both the functional magnitude and shape outlyingness of time-series data.
Edit intent: clarity
Original:  To perform such an analysis while addressing the computational problem, we introduce new incremental and progressive algorithms that promptly generate the magnitude-shape (MS) plot, which reveals both the functional magnitude and shape outlyingness of time-series data.
Revised:  To perform such an analysis while addressing the computational problem, we introduce new incremental and progressive algorithms that promptly generate the magnitude-shape (MS) plot, which conveys both the functional magnitude and shape outlyingness of time-series data.
Edit intent: clarity
Original:  To perform such an analysis while addressing the computational problem, we introduce new incremental and progressive algorithms that promptly generate the magnitude-shape (MS) plot, which reveals both the functional magnitude and shape outlyingness of time-series data.
Revised:  To perform such an analysis while addressing the computational problem, we introduce new incremental and progressive algorithms that promptly generate the magnitude-shape (MS) plot, which reveals both the functional magnitude and shape outlyingness of time series data.
Edit intent: fluency
Original:  For representation of the photoacoustic data , we propose a modification of the Curvelet transform corresponding to the restriction to the range of the photoacoustic forward operator.
Revised:  Effective representation of the photoacoustic data , we propose a modification of the Curvelet transform corresponding to the restriction to the range of the photoacoustic forward operator.
Edit intent: fluency
Original:  For representation of the photoacoustic data , we propose a modification of the Curvelet transform corresponding to the restriction to the range of the photoacoustic forward operator.
Revised:  For representation of the photoacoustic data requires basis defined on the range of the photoacoustic forward operator.
Edit intent: clarity
Original:  The data reconstruction problem DR is a standard compressed sensing recovery problem, which we solve using an ADMM-type algorithm, SALSA.
Revised:  The data reconstruction problem DR is a standard compressed sensing recovery problem, which we solve using an ADMMtype algorithm, SALSA.
Edit intent: fluency
Original:  To this end, the resource optimization problem, i.e., resource block (RB ) and power allocation,  are studied for UAV-assisted 5G networks to meet the objective of jointly maximizing the average sum-rate and minimizing the transmit power of UAV while satisfying the URLLC requirements.
Revised:  To this end, the resource optimization problem, i.e., resource blocks (RBs ) and power allocation, are studied for UAV-assisted 5G networks to meet the objective of jointly maximizing the average sum-rate and minimizing the transmit power of UAV while satisfying the URLLC requirements.
Edit intent: clarity