wanyu/IteraTeR_v2 huggingface dataset:
Original:  We present several numerical examples to show the efficiency and accuracy of the proposed method.
Revised:  We present several numerical examples to show the performance of the proposed method.
Edit intent: clarity
Original: Transfer learning from synthetic to real data has been proved an effective way of mitigating data annotation constraints in various computer vision tasks  .
Revised: Knowledge transfer from synthetic to real data has been proved an effective way of mitigating data annotation constraints in various computer vision tasks .
Edit intent: clarity
Original: Transfer learning from synthetic to real data has been proved an effective way of mitigating data annotation constraints in various computer vision tasks  .
Revised: Transfer learning from synthetic to real data has been widely studied to mitigate data annotation constraints in various computer vision tasks .
Edit intent: clarity
Original:  However, the developments focused on 2D images but lag far behind for 3D point clouds  due to the lack of large-scale high-quality synthetic point cloud data and effective transfer methods.
Revised:  However, the study focused on 2D images but lag far behind for 3D point clouds due to the lack of large-scale high-quality synthetic point cloud data and effective transfer methods.
Edit intent: clarity
Original:  However, the developments focused on 2D images but lag far behind for 3D point clouds  due to the lack of large-scale high-quality synthetic point cloud data and effective transfer methods.
Revised:  However, the developments focused on 2D images but lag far behind for 3D point clouds due to the lack of large-scale synthetic datasets and effective transfer methods.
Edit intent: clarity
Original:  We address this issue by collecting SynLiDAR, a synthetic LiDAR point cloud dataset that contains large-scale point-wise annotated point cloud with accurate geometric shapes and comprehensive semantic classes , and designing PCT-Net, a point cloud translation network that aims to narrow down the gap with real-world point cloud data.
Revised:  We address this issue by collecting SynLiDAR, a large-scale synthetic LiDAR dataset that contains large-scale point-wise annotated point cloud with accurate geometric shapes and comprehensive semantic classes , and designing PCT-Net, a point cloud translation network that aims to narrow down the gap with real-world point cloud data.
Edit intent: fluency
Original:  We address this issue by collecting SynLiDAR, a synthetic LiDAR point cloud dataset that contains large-scale point-wise annotated point cloud with accurate geometric shapes and comprehensive semantic classes , and designing PCT-Net, a point cloud translation network that aims to narrow down the gap with real-world point cloud data.
Revised:  We address this issue by collecting SynLiDAR, a synthetic LiDAR point cloud dataset that contains point-wise annotated point cloud with accurate geometric shapes and comprehensive semantic classes , and designing PCT-Net, a point cloud translation network that aims to narrow down the gap with real-world point cloud data.
Edit intent: clarity
Original:  We address this issue by collecting SynLiDAR, a synthetic LiDAR point cloud dataset that contains large-scale point-wise annotated point cloud with accurate geometric shapes and comprehensive semantic classes , and designing PCT-Net, a point cloud translation network that aims to narrow down the gap with real-world point cloud data.
Revised:  We address this issue by collecting SynLiDAR, a synthetic LiDAR point cloud dataset that contains large-scale point-wise annotated point clouds with accurate geometric shapes and comprehensive semantic classes , and designing PCT-Net, a point cloud translation network that aims to narrow down the gap with real-world point cloud data.
Edit intent: fluency
Original:  On top of that, PCT-Net disentangles synthetic-to-real gaps into an appearance component and a sparsity component and translates SynLiDAR by aligning the two components with real-world data separately .
Revised:  On top of that, PCT-Net disentangles synthetic-to-real gap into an appearance component and a sparsity component and translates SynLiDAR by aligning the two components with real-world data separately .
Edit intent: fluency
Original: We introduce giotto-ph, a high-performance, open-source software package for the computation of Vietoris--Rips barcodes. giotto-ph is based on Morozov and Nigmetov's lockfree (multicore) implementation of Ulrich Bauer's Ripser package.
Revised: We introduce giotto-ph, a high-performance, open-source software package for the computation of Vietoris-Rips barcodes. giotto-ph is based on Morozov and Nigmetov's lockfree (multicore) implementation of Ulrich Bauer's Ripser package.
Edit intent: fluency
Original:  It also contains a re-implementation of Boissonnat and Pritam's "Edge Collapser", implemented so far only in the GUDHI library .
Revised:  It also contains a re-working of the GUDHI library's implementation of Boissonnat and Pritam's "Edge Collapser", implemented so far only in the GUDHI library .
Edit intent: clarity
Original:  On the other hand, we increase parallelization opportunities and improve overall performance by adopting higher performance data structures.
Revised:  On the other hand, we increase parallelization opportunities and improve overall performance by adopting more efficient data structures.
Edit intent: clarity
Original:  The final implementation of our persistent homology backend establishes a new state of the art, surpassing even GPU-accelerated implementations such as Ripser++ when using as few as 5--10 CPU cores.
Revised:  Our persistent homology backend establishes a new state of the art, surpassing even GPU-accelerated implementations such as Ripser++ when using as few as 5--10 CPU cores.
Edit intent: clarity
Original:  The final implementation of our persistent homology backend establishes a new state of the art, surpassing even GPU-accelerated implementations such as Ripser++ when using as few as 5--10 CPU cores.
Revised:  The final implementation of our persistent homology backend establishes a new state of the art, surpassing even GPU-accelerated implementations such as Ripser++ when using as few as 5-10 CPU cores.
Edit intent: fluency
Original:  Furthermore, our implementation of the edge collapser algorithm has reduced dependencies and significantly improved run-times  .
Revised:  Furthermore, our implementation of Edge Collapser has fewer software dependencies and improved run-times .
Edit intent: clarity
Original:  We address these issues for a particularly pervasive type of domain shift called measurement shift , characterized by a change in measurement system (e. g. a change in sensor or lighting).
Revised:  We address these issues for a particularly pervasive type of domain shift called measurement shift -- characterized by a change in measurement system (e. g. a change in sensor or lighting).
Edit intent: fluency
Original:  We additionally propose Bottom-Up Feature Restoration (BUFR) , a bottom-up training scheme for FR which boosts performance by preserving learnt structure in the later layers of a network.
Revised:  We additionally propose Bottom-Up Feature Restoration (BUFR) -- a bottom-up training scheme for FR which boosts performance by preserving learnt structure in the later layers of a network.
Edit intent: fluency
Original:  Through experiments we demonstrate that BUFR often outperforms existing SFDA methods  in terms of accuracy, calibration, and data efficiency, while being less reliant on the performance of the source model in the target domain.
Revised:  We demonstrate that BUFR often outperforms existing SFDA methods in terms of accuracy, calibration, and data efficiency, while being less reliant on the performance of the source model in the target domain.
Edit intent: coherence
Original:  Through experiments we demonstrate that BUFR often outperforms existing SFDA methods  in terms of accuracy, calibration, and data efficiency, while being less reliant on the performance of the source model in the target domain.
Revised:  Through experiments we demonstrate that BUFR outperforms existing SFDA methods in terms of accuracy, calibration, and data efficiency, while being less reliant on the performance of the source model in the target domain.
Edit intent: clarity
Original: In the problem  Localization and trilateration with  minimum number of landmarks  , we faced 3-guard and classic Art Gallery Problem .
Revised: In the problem " Localization and trilateration with minimum number of landmarks , we faced 3-guard and classic Art Gallery Problem .
Edit intent: fluency
Original: In the problem  Localization and trilateration with  minimum number of landmarks  , we faced 3-guard and classic Art Gallery Problem .
Revised: In the problem Localization and trilateration with the minimum number of landmarks , we faced 3-guard and classic Art Gallery Problem .
Edit intent: fluency
Original: In the problem  Localization and trilateration with  minimum number of landmarks  , we faced 3-guard and classic Art Gallery Problem .
Revised: In the problem Localization and trilateration with minimum number of landmarks " , we faced 3-guard and classic Art Gallery Problem .
Edit intent: fluency
Original: In the problem  Localization and trilateration with  minimum number of landmarks  , we faced 3-guard and classic Art Gallery Problem .
Revised: In the problem Localization and trilateration with minimum number of landmarks , we faced the 3-Guard and classic Art Gallery Problem .
Edit intent: fluency
Original: In the problem  Localization and trilateration with  minimum number of landmarks  , we faced 3-guard and classic Art Gallery Problem .
Revised: In the problem Localization and trilateration with minimum number of landmarks , we faced 3-guard and classic Art Gallery Problems .
Edit intent: fluency
Original:  The goal of the art gallery problem is to find the minimum number of guards within a simple polygon to observe and protect the entire of it .
Revised:  The goal of the art gallery problem is to find the minimum number of guards within a simple polygon to observe and protect its entirety .
Edit intent: clarity
Original:  It has many applications in Robotics, Telecommunication and so on and there are some approaches to handle the art gallery problem which is theoretically NP-hard.
Revised:  It has many applications in robotics, telecommunications, etc. There are some approaches to handle the art gallery problem which is theoretically NP-hard.
Edit intent: coherence
Original:  It has many applications in Robotics, Telecommunication and so on and there are some approaches to handle the art gallery problem which is theoretically NP-hard.
Revised:  It has many applications in Robotics, Telecommunication and so on and there are some approaches to handle the art gallery problem that is theoretically NP-hard.
Edit intent: fluency
Original:  This paper offers an efficient method based on the Particle Filter algorithm which solves the most fundamental state of the problem near optimal .
Revised:  This paper offers an efficient method based on the Particle Filter algorithm which solves the most fundamental state of the problem in a nearly optimal manner .
Edit intent: clarity
Original:  The experimental results on the randomly polygons generated by Bottino shows }\hspace{0pt} show } that the new method is more accurate with less or equal guards.
Revised:  The experimental results on the random polygons generated by Bottino shows }\hspace{0pt} show } that the new method is more accurate with less or equal guards.
Edit intent: fluency
Original:  The experimental results on the randomly polygons generated by Bottino shows }\hspace{0pt} show } that the new method is more accurate with less or equal guards.
Revised:  The experimental results on the randomly polygons generated by Bottino shows }\hspace{0pt} show } that the new method is more accurate with fewer or equal guards.
Edit intent: fluency
Original:  Furthermore, we discuss the resampling and particle numbers to minimize the running time.
Revised:  Furthermore, we discuss resampling and particle numbers to minimize the running time.
Edit intent: fluency
Original:  Furthermore, we discuss the resampling and particle numbers to minimize the running time.
Revised:  Furthermore, we discuss the resampling and particle numbers to minimize the run time.
Edit intent: fluency
Original:  These models aim to learn binding mechanics through drug-target interaction datasets and use the learned knowledge while predicting the affinity of any protein-compound pair.
Revised:  These models aim to learn binding mechanics through drug-target interaction datasets and use the learned knowledge for predicting the affinity of any protein-compound pair.
Edit intent: clarity
Original:  These models aim to learn binding mechanics through drug-target interaction datasets and use the learned knowledge while predicting the affinity of any protein-compound pair.
Revised:  These models aim to learn binding mechanics through drug-target interaction datasets and use the learned knowledge while predicting the affinity of an input protein-compound pair.
Edit intent: clarity
Original:  Insufficiently focused on the binding mechanics, the resulting models struggle while predicting the drug-target affinities (DTA), especially between de novo biomolecules.
Revised:  This results in models that struggle while predicting the drug-target affinities (DTA), especially between de novo biomolecules.
Edit intent: clarity
Original:  Insufficiently focused on the binding mechanics, the resulting models struggle while predicting the drug-target affinities (DTA), especially between de novo biomolecules.
Revised:  Insufficiently focused on the binding mechanics, the resulting models struggle while predicting drug-target affinities (DTA), especially between de novo biomolecules.
Edit intent: fluency
Original:  Here we present DebiasedDTA, the first  model debiasing approach that avoids dataset biases in order to boost the affinity prediction on novel biomolecules.
Revised:  Here we present DebiasedDTA, the first model debiasing approach that avoids dataset biases in order to boost affinity prediction for novel biomolecules.
Edit intent: coherence
Original:  DebiasedDTA uses ensemble learning and weight sample adaptation for bias identification and avoidance and is applicable to almost all existing DTA prediction models.
Revised:  DebiasedDTA uses ensemble learning and sample weight adaptation for bias identification and avoidance and is applicable to almost all existing DTA prediction models.
Edit intent: fluency
Original:  Known biomolecules also benefit from the performance boost, though the boost is amplified as the test biomolecules become more dissimilar to the training set.
Revised:  Known biomolecules also benefit from the performance improvement, especially when the test biomolecules are dissimilar to the training set.
Edit intent: clarity
Original:  The experiments also show that DebiasedDTA can augment the DTA prediction models of different input and model structures and can avoid biases of different sources.
Revised:  The experiments also show that DebiasedDTA can augment DTA prediction models of different input and model structures and can avoid biases of different sources.
Edit intent: fluency
Original:  The experiments also show that DebiasedDTA can augment the DTA prediction models of different input and model structures and can avoid biases of different sources.
Revised:  The experiments also show that DebiasedDTA can augment the DTA prediction models of different input and model structures and is able to avoid biases of different sources.
Edit intent: clarity
Original: The number of sub-populations of tumour cells constituting a tumour and the immunogenicity of tumour cells are two major components of intra-tumour heterogeneity (ITH) , and play a key role in the immune response against solid tumours.
Revised: Intra-tumour heterogeneity (ITH) , and play a key role in the immune response against solid tumours.
Edit intent: clarity
Original: The number of sub-populations of tumour cells constituting a tumour and the immunogenicity of tumour cells are two major components of intra-tumour heterogeneity (ITH) , and play a key role in the immune response against solid tumours.
Revised: The number of sub-populations of tumour cells constituting a tumour and the immunogenicity of tumour cells are two major components of intra-tumour heterogeneity (ITH) has a strong impact on the efficacy of the immune response against solid tumours.
Edit intent: coherence
Original:  First, the number of sub-populations of tumour cells negatively correlates with the ability of the CD8+ T cells to produce an efficient anti-tumoural response.
Revised:  First, the number of sub-populations of tumour cells negatively correlates with the ability of the CD8+ T cells to mount an effective anti-tumour immune response.
Edit intent: clarity
Original:  Second, the fraction of non-immunogenic cells within a tumour can significantly reduce the effectiveness of the immune response.
Revised:  Second, the presence of a larger percentage of tumour cells that are not effectively targeted by CD8+ T cells may reduce the effectiveness of the immune response.
Edit intent: clarity
Original:  Ultimately, our model may provide a framework to help biologists and clinicians to better understand the prognostic outcomes of immunotherapy.
Revised:  Ultimately, our model may provide a framework to help biologists and clinicians to better understand the mechanisms that are responsible for the emergence of different outcomes of immunotherapy.
Edit intent: clarity
Original:  In this work, we discuss mesh deformation techniques for structured, quadrilateral meshes.
Revised:  In this work, we address mesh deformation techniques for structured, quadrilateral meshes.
Edit intent: clarity
Original: We consider the problem of coarse-graining in  finite-volume fluid models.
Revised: We consider the problem of coarse-graining in the context of finite-volume fluid models.
Edit intent: clarity
Original:  Projecting a variable on a fine grid onto a coarser grid will in general cause some information about the solution to be lost.
Revised:  Projecting a variable on a fine grid onto a coarser grid will in general cause some information about the variable to be lost.
Edit intent: clarity
Original:  In particular, horizontal divergences and gradients will not be the same when calculated on the coarse grid from a projected solution as when they are calculated on the fine grid.
Revised:  In particular, horizontal divergences , gradients or other operators calculated on the coarse grid from a projected solution as when they are calculated on the fine grid.
Edit intent: clarity
Original:  In particular, horizontal divergences and gradients will not be the same when calculated on the coarse grid from a projected solution as when they are calculated on the fine grid.
Revised:  In particular, horizontal divergences and gradients will not be the same when calculated on the coarse grid after projecting may differ from those calculated on the fine grid.
Edit intent: clarity
Original:  Therefore, it is necessary to choose the method of coarse-graining carefully via a weighted average so that these properties will be conserved in the resulting field.
Revised:  In some cases we are able to choose averaging weights for coarse-graining carefully via a weighted average so that these properties will be conserved in the resulting field.
Edit intent: clarity
Original:  We then take the particular case of a regular triangular mesh  in which the fine-grid resolution is some integer multiple N of the coarse-grid resolution.
Revised:  These conditions are applied to a regular triangular mesh in which the fine-grid resolution is some integer multiple N of the coarse-grid resolution.
Edit intent: clarity
Original:  For this case we  particular values for the averaging weights  preserve the divergence for general N, and different weights that preserve the gradient for the case N = 2.
Revised:  For this case we find particular values for the averaging weights preserve the divergence for general N, and different weights that preserve the gradient for the case N = 2.
Edit intent: fluency
Original:  For this case we  particular values for the averaging weights  preserve the divergence for general N, and different weights that preserve the gradient for the case N = 2.
Revised:  For this case we particular values for the averaging weights that preserve the divergence for general N, and different weights that preserve the gradient for the case N = 2.
Edit intent: fluency
Original:  For this case we  particular values for the averaging weights  preserve the divergence for general N, and different weights that preserve the gradient for the case N = 2.
Revised:  For this case we particular values for the averaging weights preserve the divergence , and a set of different averaging weights that preserve the gradient for the case N = 2.
Edit intent: clarity
Original: We present a general approach for controlling robotic systems that make and break contact with their environments : linear contact-implicit model-predictive control ( LCI-MPC) .
Revised: We present a general approach for controlling robotic systems that make and break contact with their environments . Contact-implicit model-predictive control ( LCI-MPC) .
Edit intent: clarity
Original:  To enable real-time performance , we devise a custom structure-exploiting linear solver for the contact dynamics .
Revised:  To enable real-time performance , we devise a structure-exploiting linear solver for the contact dynamics .
Edit intent: clarity
Original:  We demonstrate that the policy can respond to disturbances by discovering and exploiting new contact modes and is robust to model mismatch and unmodeled environments for a collection of simulated robotic systems, including : pushbot, hopper, quadruped, and biped.
Revised:  We demonstrate that the policy can respond to disturbances by discovering and exploiting new contact modes across a variety of robotic systems, including : pushbot, hopper, quadruped, and biped.
Edit intent: clarity
Original:  We demonstrate that the policy can respond to disturbances by discovering and exploiting new contact modes and is robust to model mismatch and unmodeled environments for a collection of simulated robotic systems, including : pushbot, hopper, quadruped, and biped.
Revised:  We demonstrate that the policy can respond to disturbances by discovering and exploiting new contact modes and is robust to model mismatch and unmodeled environments for a collection of simulated robotic systems, including a pushbot, hopper, quadruped, and biped.
Edit intent: fluency
Original:  We demonstrate that the policy can respond to disturbances by discovering and exploiting new contact modes and is robust to model mismatch and unmodeled environments for a collection of simulated robotic systems, including : pushbot, hopper, quadruped, and biped.
Revised:  We demonstrate that the policy can respond to disturbances by discovering and exploiting new contact modes and is robust to model mismatch and unmodeled environments for a collection of simulated robotic systems, including : pushbot, hopper, and planar quadruped and biped.
Edit intent: clarity
Original: We address the problem of text-guided video temporal grounding, which aims to identify the time interval of  certain event based on a natural language description.
Revised: We address the problem of text-guided video temporal grounding, which aims to identify the time interval of a certain event based on a natural language description.
Edit intent: fluency
Original:  While RGB images provide abundant visual cues of certain event , the performance may be affected by background clutters.
Revised:  While RGB images provide abundant visual cues of certain events , the performance may be affected by background clutters.
Edit intent: fluency