wanyu/IteraTeR_v2 huggingface dataset:
Original: As the computational power of toady's devices increases , real-time physically-based rendering becomes possible, and is rapidly gaining attention across a variety of domains.
Revised: As the computational power of today's workstations , real-time physically-based rendering becomes possible, and is rapidly gaining attention across a variety of domains.
Edit intent: clarity
Original: As the computational power of toady's devices increases , real-time physically-based rendering becomes possible, and is rapidly gaining attention across a variety of domains.
Revised: As the computational power of toady's devices increases , real-time physically-based rendering is within reach, rapidly gaining attention across a variety of domains.
Edit intent: clarity
Original:  These include gaming, where physically-based rendering enhances immersion and overall entertainment experience, all the way to medicine, where it constitutes a powerful tool for intuitive volumetric data visualization.
Revised:  These have expeditiously applied to medicine, where it constitutes a powerful tool for intuitive volumetric data visualization.
Edit intent: clarity
Original:  These include gaming, where physically-based rendering enhances immersion and overall entertainment experience, all the way to medicine, where it constitutes a powerful tool for intuitive volumetric data visualization.
Revised:  These include gaming, where physically-based rendering enhances immersion and overall entertainment experience, all the way to medicine, where it is a powerful tool for intuitive volumetric data visualization.
Edit intent: clarity
Original:   However, leveraging the obvious benefits of physically-based rendering (also referred to as photo-realistic rendering) remains challenging on embedded devices such as optical see-through head-mounted displays because of their limited computational power, and restricted memory usage and power consumption.
Revised:  However, leveraging the obvious benefits of physically-based rendering remains challenging on embedded devices such as optical see-through head-mounted displays because of their limited computational power, and restricted memory usage and power consumption.
Edit intent: coherence
Original:   However, leveraging the obvious benefits of physically-based rendering (also referred to as photo-realistic rendering) remains challenging on embedded devices such as optical see-through head-mounted displays because of their limited computational power, and restricted memory usage and power consumption.
Revised:  However, leveraging the obvious benefits of physically-based rendering (also referred to as photo-realistic rendering) remains challenging on these devices because of limited computational power, and restricted memory usage and power consumption.
Edit intent: clarity
Original:   However, leveraging the obvious benefits of physically-based rendering (also referred to as photo-realistic rendering) remains challenging on embedded devices such as optical see-through head-mounted displays because of their limited computational power, and restricted memory usage and power consumption.
Revised:  However, leveraging the obvious benefits of physically-based rendering (also referred to as photo-realistic rendering) remains challenging on embedded devices such as optical see-through head-mounted displays because of their limited computational power, memory usage, and power consumption.
Edit intent: clarity
Original:  We navigate the compromise between memory requirement, computational power, and image quality to achieve reasonable rendering results by introducing a flexible representation of plenoptic functions and adapting a fast approximation algorithm for image generation from our plenoptic functions.
Revised:  We navigate the compromise between device limitations and image quality to achieve reasonable rendering results by introducing a flexible representation of plenoptic functions and adapting a fast approximation algorithm for image generation from our plenoptic functions.
Edit intent: clarity
Original:  In this paper we present a real-time decision support system (DSS) for geosteering that aims to approximate the uncertainty  with an ensemble of geo-model realizations.
Revised:  In this paper we present a real-time decision support system (DSS) for geosteering that aims to approximate the uncertainty with an ensemble of geomodel realizations.
Edit intent: fluency
Original:  As the drilling operation progresses, the ensemble Kalman filter is used to sequentially update the realizations using the data from real-time logging while drilling.
Revised:  As the drilling operation progresses, the ensemble Kalman filter is used to sequentially update the realizations using the measurements from real-time logging while drilling.
Edit intent: clarity
Original:  At every decision point a discretized dynamic programming algorithm computes all potential well trajectories until the end of the operation and the corresponding value of the well for each realization.
Revised:  At every decision point a discrete dynamic programming algorithm computes all potential well trajectories until the end of the operation and the corresponding value of the well for each realization.
Edit intent: fluency
Original:  At every decision point a discretized dynamic programming algorithm computes all potential well trajectories until the end of the operation and the corresponding value of the well for each realization.
Revised:  At every decision point a discretized dynamic programming algorithm computes all potential well trajectories for the entire drilling operation and the corresponding value of the well for each realization.
Edit intent: clarity
Original:  This approach works for a variety of objectives and constraints and suggests reproducible decision under uncertainty.
Revised:  This approach works for a variety of objectives and constraints and suggests reproducible decisions under uncertainty.
Edit intent: fluency
Original:  The system is tested on synthetic cases in  layer-cake geological environment where the target layer should be selected dynamically based on the prior (pre-drill) model and electromagnetic observations .
Revised:  The system is tested on synthetic cases in a layer-cake geological environment where the target layer should be selected dynamically based on the prior (pre-drill) model and electromagnetic observations .
Edit intent: fluency
Original:  The system is tested on synthetic cases in  layer-cake geological environment where the target layer should be selected dynamically based on the prior (pre-drill) model and electromagnetic observations .
Revised:  The system is tested on synthetic cases in layer-cake geological environment where the target layer should be selected dynamically based on the prior (pre-drill) model and the electromagnetic observations received while drilling .
Edit intent: clarity
Original:  The numerical closed-loop simulation experiments demonstrate the ability of the DSS to perform successful geosteering and landing of a well for different configurations of targets.
Revised:  The numerical closed-loop simulation experiments demonstrate the ability of the DSS to perform successful geosteering and landing of a well for different geological configurations of drilling targets.
Edit intent: clarity
Original:  Furthermore, the DSS allows to adjust and re-weight the objectives, making the DSS useful before fully-automated geosteering becomes reality.
Revised:  Furthermore, the DSS allows to adjust and reweight the objectives, making the DSS useful before fully-automated geosteering becomes reality.
Edit intent: fluency
Original:  Furthermore, the DSS allows to adjust and re-weight the objectives, making the DSS useful before fully-automated geosteering becomes reality.
Revised:  Furthermore, the DSS allows to adjust and re-weight the objectives, making the DSS useful before fully automated geosteering becomes reality.
Edit intent: fluency
Original:  A consequence of the identical individual conjecture is that the existence of the personal space and the behavior differentiation under high population density condition receive a possible theoretical explanation .
Revised:  A consequence of the identical individual conjecture is that the existence of the personal space and the behavior differentiation under high population density condition .
Edit intent: clarity
Original: Mesh denoising is a critical technology in geometry processing , which aims to recover high-fidelity 3D mesh models of objects from  noise-corrupted versions.
Revised: Mesh denoising is a critical technology in geometry processing that aims to recover high-fidelity 3D mesh models of objects from noise-corrupted versions.
Edit intent: coherence
Original: Mesh denoising is a critical technology in geometry processing , which aims to recover high-fidelity 3D mesh models of objects from  noise-corrupted versions.
Revised: Mesh denoising is a critical technology in geometry processing , which aims to recover high-fidelity 3D mesh models of objects from their noise-corrupted versions.
Edit intent: clarity
Original:  Building on the literature in convex optimization, our approach is based on estimators that minimize the error over structured families of convex sets that are specified as linear images of concisely described sets -- such as the simplex or the free spectrahedron -- in a higher-dimensional space that is not much larger than the ambient space.
Revised:  Building on the literature in convex optimization, our approach is based on estimators that minimize the error over structured families of convex sets that are specified as linear images of concisely described sets -- such as the simplex or the spectraplex -- in a higher-dimensional space that is not much larger than the ambient space.
Edit intent: clarity
Original: Despite a rise in the use of "learning by doing" pedagogical methods in praxis, little is known as to why these methods may improve learning outcomes.
Revised: Despite a rise in the use of "learning by doing" pedagogical methods in praxis, little is known as to how these methods improve learning outcomes.
Edit intent: clarity
Original:  6  letters).
Revised:  6 or more letters).
Edit intent: clarity
Original: We consider a  model of two-stage optimal decision making involving pure information learning beforehand and dynamic consumption afterwards: in stage-1 from initial time to a chosen stopping time, the individual investor has access to full market information and simply updates the underlying stock and mean-reverting drift processes by paying some information costs;
Revised: We consider a basic model of two-stage optimal decision making involving pure information learning beforehand and dynamic consumption afterwards: in stage-1 from initial time to a chosen stopping time, the individual investor has access to full market information and simply updates the underlying stock and mean-reverting drift processes by paying some information costs;
Edit intent: clarity
Original: We consider a  model of two-stage optimal decision making involving pure information learning beforehand and dynamic consumption afterwards: in stage-1 from initial time to a chosen stopping time, the individual investor has access to full market information and simply updates the underlying stock and mean-reverting drift processes by paying some information costs;
Revised: We consider a model of two-stage optimal decision making involving pure information learning beforehand and dynamic consumption afterwards: in stage-1 from initial time to a chosen stopping time, the individual investor has access to full market information and simply updates the underlying stock and mean-reverting drift processes by paying information costs;
Edit intent: clarity
Original:  Mathematically speaking, we formulate a composite optimal starting and control problem, in which the exterior problem is to determine the best time to initiate the investment-consumption decisions and the interior problem becomes a finite time horizon stochastic control problem with partial information.
Revised:  Mathematically speaking, we formulate a composite optimal starting and control problem, in which the exterior problem is to determine the best time to initiate the investment-consumption decisions and the interior problem becomes a finite time stochastic control problem with partial information.
Edit intent: clarity
Original: We consider a basic model of two-stage optimal decision making involving pure information learning beforehand and dynamic consumption afterwards: in stage-1 from  initial time to a chosen stopping time, the individual investor has access to full market information and simply updates the underlying stock and mean-reverting drift processes by paying information costs;
Revised: We consider a two-stage optimal decision making involving pure information learning beforehand and dynamic consumption afterwards: in stage-1 from initial time to a chosen stopping time, the individual investor has access to full market information and simply updates the underlying stock and mean-reverting drift processes by paying information costs;
Edit intent: clarity
Original: We consider a basic model of two-stage optimal decision making involving pure information learning beforehand and dynamic consumption afterwards: in stage-1 from  initial time to a chosen stopping time, the individual investor has access to full market information and simply updates the underlying stock and mean-reverting drift processes by paying information costs;
Revised: We consider a basic model of two-stage optimal decision making involving full market information acquisition beforehand and dynamic consumption afterwards: in stage-1 from initial time to a chosen stopping time, the individual investor has access to full market information and simply updates the underlying stock and mean-reverting drift processes by paying information costs;
Edit intent: clarity
Original: We consider a basic model of two-stage optimal decision making involving pure information learning beforehand and dynamic consumption afterwards: in stage-1 from  initial time to a chosen stopping time, the individual investor has access to full market information and simply updates the underlying stock and mean-reverting drift processes by paying information costs;
Revised: We consider a basic model of two-stage optimal decision making involving pure information learning beforehand and dynamic consumption afterwards: in stage-1 from the initial time to a chosen stopping time, the individual investor has access to full market information and simply updates the underlying stock and mean-reverting drift processes by paying information costs;
Edit intent: fluency
Original: We consider a basic model of two-stage optimal decision making involving pure information learning beforehand and dynamic consumption afterwards: in stage-1 from  initial time to a chosen stopping time, the individual investor has access to full market information and simply updates the underlying stock and mean-reverting drift processes by paying information costs;
Revised: We consider a basic model of two-stage optimal decision making involving pure information learning beforehand and dynamic consumption afterwards: in stage-1 from initial time to a chosen stopping time, the investor has access to full market information and simply updates the underlying stock and mean-reverting drift processes by paying information costs;
Edit intent: clarity
Original: We consider a basic model of two-stage optimal decision making involving pure information learning beforehand and dynamic consumption afterwards: in stage-1 from  initial time to a chosen stopping time, the individual investor has access to full market information and simply updates the underlying stock and mean-reverting drift processes by paying information costs;
Revised: We consider a basic model of two-stage optimal decision making involving pure information learning beforehand and dynamic consumption afterwards: in stage-1 from initial time to a chosen stopping time, the individual investor has access to full market information to update all underlying processes subjecting to information costs;
Edit intent: clarity
Original:  in stage-2 starting from the chosen stopping time, the investor terminates the costly information acquisition while the public stock prices are still available and free .
Revised:  in stage-2 starting from the chosen stopping time, the investor terminates the costly full information learning but the public stock prices are still available and free .
Edit intent: clarity
Original:  in stage-2 starting from the chosen stopping time, the investor terminates the costly information acquisition while the public stock prices are still available and free .
Revised:  in stage-2 starting from the chosen stopping time, the investor terminates the costly information acquisition while the public stock prices are still available .
Edit intent: clarity
Original:  Therefore, during stage-2, the investor  starts the investment and consumption based on previous full information and the dynamic partial observationsafter the stopping time .
Revised:  Therefore, during stage-2, the investor starts the investment and consumption based on partial observations .
Edit intent: clarity
Original:  Moreover, the investor adopts the habit formation preference  , in which the past consumption affects his current decisions.
Revised:  Moreover, the habit formation preference , in which the past consumption affects his current decisions.
Edit intent: clarity
Original:  Moreover, the investor adopts the habit formation preference  , in which the past consumption affects his current decisions.
Revised:  Moreover, the investor adopts the habit formation preference is employed , in which the past consumption affects his current decisions.
Edit intent: clarity
Original:  Moreover, the investor adopts the habit formation preference  , in which the past consumption affects his current decisions.
Revised:  Moreover, the investor adopts the habit formation preference , in which the past consumption affects the investor's current decisions.
Edit intent: clarity
Original:  Mathematically speaking, we formulate a composite optimal starting and control problem, in which the exterior problem is to determine the best time to initiate the investment-consumption decisions and the interior problem becomes a finite time stochastic control problem with partial information.
Revised:  Mathematically speaking, we formulate a composite problem, in which the exterior problem is to determine the best time to initiate the investment-consumption decisions and the interior problem becomes a finite time stochastic control problem with partial information.
Edit intent: clarity
Original:  Mathematically speaking, we formulate a composite optimal starting and control problem, in which the exterior problem is to determine the best time to initiate the investment-consumption decisions and the interior problem becomes a finite time stochastic control problem with partial information.
Revised:  Mathematically speaking, we formulate a composite optimal starting and control problem, in which the exterior problem is to determine the best time to initiate investment-consumption decisions and the interior problem becomes a finite time stochastic control problem with partial information.
Edit intent: fluency
Original: We consider a two-stage optimal decision making involving full market information acquisition beforehand and dynamic consumption afterwards: in stage-1 from the initial time to a chosen stopping time , the investor has access to full market information to update all underlying processes subjecting to information costs ;
Revised: We consider a two-stage optimal decision making involving full market information acquisition beforehand and dynamic consumption afterwards: in stage-1 , the investor has access to full market information to update all underlying processes subjecting to information costs ;
Edit intent: clarity
Original:  Mathematically speaking, we formulate a composite problem, in which the exterior problem is to determine the best time to initiate investment-consumption decisions and the interior problem becomes a control problem with partial information.
Edit intent: coherence
Original:  The value function of the composite problem is characterized as the unique viscosity solution of some variational inequalities.
Revised:  The value function of the composite problem is proved to be the unique viscosity solution of some variational inequalities.
Edit intent: clarity
Original: We formulate a composite problem involving the decision making of the optimal entry time and dynamic consumption afterwards : in stage-1, the investor has access to full market information subjecting to some information costs and needs to choose an optimal stopping time to initiate stage-2;
Revised: This paper studies a composite problem involving the decision making of the optimal entry time and dynamic consumption afterwards : in stage-1, the investor has access to full market information subjecting to some information costs and needs to choose an optimal stopping time to initiate stage-2;
Edit intent: clarity
Original: We formulate a composite problem involving the decision making of the optimal entry time and dynamic consumption afterwards : in stage-1, the investor has access to full market information subjecting to some information costs and needs to choose an optimal stopping time to initiate stage-2;
Revised: We formulate a composite problem involving the decision making of the optimal entry time and dynamic consumption afterwards . In stage-1, the investor has access to full market information subjecting to some information costs and needs to choose an optimal stopping time to initiate stage-2;
Edit intent: fluency
Original:  in stage-2 starting from the chosen stopping time , the investor terminates the costly full information acquisition and starts dynamic investment and consumption under partial observations of free public stock prices.
Revised:  in stage-2 , the investor terminates the costly full information acquisition and starts dynamic investment and consumption under partial observations of free public stock prices.
Edit intent: clarity
Original:  For this, recurrent layers had been added to the Deep Q-Network in order to allow it to handle past dependencies.
Revised:  For this, recurrent layers have been added to the Deep Q-Network in order to allow it to handle past dependencies.
Edit intent: fluency
Original: Many of the computing systems developed using machine learning are opaque: it is difficult to explain why they do what they do , or how they work.
Revised: Many of the computing systems programmed using Machine Learning are opaque: it is difficult to explain why they do what they do , or how they work.
Edit intent: clarity
Original: Many of the computing systems developed using machine learning are opaque: it is difficult to explain why they do what they do , or how they work.
Revised: Many of the computing systems developed using machine learning are opaque: it is difficult to know why they do what they do , or how they work.
Edit intent: clarity
Original: Many of the computing systems developed using machine learning are opaque: it is difficult to explain why they do what they do , or how they work.
Revised: Many of the computing systems developed using machine learning are opaque: it is difficult to explain why they do what they do or how they work.
Edit intent: fluency
Original:  The Explainable AI research program aims to develop analytic techniques for rendering such systems transparent, but lacks a general understanding of what it actually takes to do so .
Revised:  The Explainable Artificial Intelligence research program aims to develop analytic techniques for rendering such systems transparent, but lacks a general understanding of what it actually takes to do so .
Edit intent: fluency