wanyu/IteraTeR_v2 huggingface dataset:
Original:  Notably, our novel criterion is not only competitive or better compared to state-of-the-art pruning criteria when successive retraining is performed, but clearly outperforms these previous criteria in the common application setting where the data of the task to be transferred to are very scarce and no retraining is possible .
Revised:  Notably, our novel criterion is not only competitive or better compared to state-of-the-art pruning criteria when successive retraining is performed, but clearly outperforms these previous criteria in the resource-constrained application scenario in which the data of the task to be transferred to are very scarce and no retraining is possible .
Edit intent: clarity
Original:  Notably, our novel criterion is not only competitive or better compared to state-of-the-art pruning criteria when successive retraining is performed, but clearly outperforms these previous criteria in the common application setting where the data of the task to be transferred to are very scarce and no retraining is possible .
Revised:  Notably, our novel criterion is not only competitive or better compared to state-of-the-art pruning criteria when successive retraining is performed, but clearly outperforms these previous criteria in the common application setting where the data of the task to be transferred to is very scarce and no retraining is possible .
Edit intent: fluency
Original:  Notably, our novel criterion is not only competitive or better compared to state-of-the-art pruning criteria when successive retraining is performed, but clearly outperforms these previous criteria in the common application setting where the data of the task to be transferred to are very scarce and no retraining is possible .
Revised:  Notably, our novel criterion is not only competitive or better compared to state-of-the-art pruning criteria when successive retraining is performed, but clearly outperforms these previous criteria in the common application setting where the data of the task to be transferred to are very scarce and one chooses to refrain from fine-tuning .
Edit intent: clarity
Original:  Our method can iteratively compress the model  while maintaining or even improving accuracy.
Revised:  Our method is able to compress the model while maintaining or even improving accuracy.
Edit intent: clarity
Original:  In this paper, we propose a novel criterion for CNN pruning inspired by neural network interpretability: The most relevant elements , i.e. weights or filters, are automatically found using their relevance scores obtained from concepts of explainable AI (XAI).
Revised:  In this paper, we propose a novel criterion for CNN pruning inspired by neural network interpretability: The most relevant units , i.e. weights or filters, are automatically found using their relevance scores obtained from concepts of explainable AI (XAI).
Edit intent: clarity
Original:  Recent work has shown that particular sets of PDs can differentiate between different shapes.
Revised:  Recent work has shown that well-chosen (finite) sets of PDs can differentiate between different shapes.
Edit intent: clarity
Original:  This trait is desirable because it provides a method of representing complex shapes using finite sets of descriptors.
Revised:  This trait is desirable because it provides a method of representing complex shapes using a finite set of descriptors.
Edit intent: fluency
Original:  The problem of choosing such a set of representative PDs and then using them to uniquely determine the shape is referred to as reconstruction.
Revised:  A related inverse problem is the following: given a set of representative PDs and then using them to uniquely determine the shape is referred to as reconstruction.
Edit intent: clarity
Original: Arlotto and Gurvich (2019) showed that the regret in the multisecretary problem is bounded  in the number of job openings, n , and the number of applicants, k , provided that the applicant valuations are drawn from a distribution with finite support.
Revised: \mbox{ Arlotto2019 regret in the multisecretary problem is bounded in the number of job openings, n , and the number of applicants, k , provided that the applicant valuations are drawn from a distribution with finite support.
Edit intent: clarity
Original: Arlotto and Gurvich (2019) showed that the regret in the multisecretary problem is bounded  in the number of job openings, n , and the number of applicants, k , provided that the applicant valuations are drawn from a distribution with finite support.
Revised: Arlotto and Gurvich (2019) showed that the regret in the multisecretary problem is bounded , both in the number of job openings, n , and the number of applicants, k , provided that the applicant valuations are drawn from a distribution with finite support.
Edit intent: clarity
Original: Arlotto and Gurvich (2019) showed that the regret in the multisecretary problem is bounded  in the number of job openings, n , and the number of applicants, k , provided that the applicant valuations are drawn from a distribution with finite support.
Revised: Arlotto and Gurvich (2019) showed that the regret in the multisecretary problem is bounded in the number of job openings, n , and the number of applicants, k , provided that the applicant valuations have finite support.
Edit intent: clarity
Original:  While the authors in Ref \mbox{ C-I-D-G-2011 networks are sparse, there  exist some real-world networks , for instance, social networks\mbox{ Leskovec-2007 , urban networks \mbox{ Schlapfer-2014 , information networks \mbox{ Lambiotte-2016 , which are by observation dense.
Revised:  While the authors in Ref \mbox{ C-I-D-G-2011 networks are sparse, there still exist some real-world networks , for instance, social networks\mbox{ Leskovec-2007 , urban networks \mbox{ Schlapfer-2014 , information networks \mbox{ Lambiotte-2016 , which are by observation dense.
Edit intent: coherence
Original:  While the authors in Ref \mbox{ C-I-D-G-2011 networks are sparse, there  exist some real-world networks , for instance, social networks\mbox{ Leskovec-2007 , urban networks \mbox{ Schlapfer-2014 , information networks \mbox{ Lambiotte-2016 , which are by observation dense.
Revised:  While the authors in Ref \mbox{ C-I-D-G-2011 networks are sparse, there exist some real-world networks including social networks , urban networks \mbox{ Schlapfer-2014 , information networks \mbox{ Lambiotte-2016 , which are by observation dense.
Edit intent: clarity
Original:  From theoretical point of view, our method can be used not only to produce desired scale-free graphs with  power-law exponent  1<\gamma\leq2  but also to establish  unexpected networked models which disprove some widely known statements, such as "Scale-free networks are ultrasmall" due to Cohen,et al , in \mbox{ \cite{R-C-2003}\hspace{0pt} .
Revised:  From theoretical point of view, our method can be used not only to produce desired scale-free graphs with power-law exponent 1<\gamma\leq2 , but also to establish unexpected networked models which disprove some widely known statements, such as "Scale-free networks are ultrasmall" due to Cohen,et al , in \mbox{ \cite{R-C-2003}\hspace{0pt} .
Edit intent: fluency
Original:  From theoretical point of view, our method can be used not only to produce desired scale-free graphs with  power-law exponent  1<\gamma\leq2  but also to establish  unexpected networked models which disprove some widely known statements, such as "Scale-free networks are ultrasmall" due to Cohen,et al , in \mbox{ \cite{R-C-2003}\hspace{0pt} .
Revised:  From theoretical point of view, our method can be used not only to produce desired scale-free graphs with power-law exponent 1<\gamma\leq2 but also to establish unexpected networked models which disprove some widely known statements, such as "Scale-free networks are ultrasmall" due to Cohen, , in \mbox{ \cite{R-C-2003}\hspace{0pt} .
Edit intent: clarity
Original: Cancer diagnosis, prognosis  and therapeutic response predictions are based on morphological information from histology slides and molecular profiles from genomic data.
Revised: Cancer diagnosis, prognosis , and therapeutic response predictions are based on morphological information from histology slides and molecular profiles from genomic data.
Edit intent: fluency
Original:  However, most deep learning-based objective outcome prediction and grading paradigms are based on histology or genomics alone and do not make use of the complimentary information in an intuitive manner.
Revised:  However, most deep learning-based objective outcome prediction and grading paradigms are based on histology or genomics alone and do not make use of the complementary information in an intuitive manner.
Edit intent: fluency
Original:  In this work, we propose Pathomic Fusion, a strategy for end-to-end multimodal fusion of histology image and genomic (mutations, CNV, mRNAseq) features for survival outcome prediction and patient stratification, where histologic features are also learned via graph convolutional networks (GCNs) .
Revised:  In this work, we propose Pathomic Fusion, a strategy for end-to-end multimodal fusion of histology image and genomic (mutations, CNV, mRNAseq) features for survival outcome prediction .
Edit intent: coherence
Original:  Our approach models pairwise feature interactions across modalities by taking the Kronecker product of gated feature representations , and controls the expressiveness of each representation via a gating-based attention mechanism.
Revised:  Our approach models pairwise feature interactions across modalities by taking the Kronecker product of gated feature representations and controls the expressiveness of each representation via a gating-based attention mechanism.
Edit intent: fluency
Original:  Based on a rigorous 15-fold cross validation , our results demonstrate that the proposed multimodal fusion paradigm improves prognostic determinations from grading and molecular subtyping as well as unimodal deep networks trained on histology and genomic data alone.
Revised:  Based on a rigorous 15-fold cross-validation , our results demonstrate that the proposed multimodal fusion paradigm improves prognostic determinations from grading and molecular subtyping as well as unimodal deep networks trained on histology and genomic data alone.
Edit intent: fluency
Original:  In this work, we propose Pathomic Fusion, a strategy for end-to-end multimodal fusion of histology image and genomic (mutations, CNV, mRNAseq ) features for survival outcome prediction.
Revised:  In this work, we propose Pathomic Fusion, a strategy for end-to-end multimodal fusion of histology image and genomic (mutations, CNV, RNA-Seq ) features for survival outcome prediction.
Edit intent: clarity
Original:  The proposed framework is able to model pairwise interactions across features in different modalities and control their relative importance .
Revised:  Following supervised learning, we are able to interpret and saliently localize features across each modality, and understand how feature importance shifts when conditioning on multimodal input .
Edit intent: clarity
Original:  Based on a rigorous 15-fold cross-validation, our results demonstrate that the proposed multimodal fusion paradigm improves prognostic determinations from  grading and molecular subtyping  as well as unimodal deep networks trained on histology and genomic data alone.
Revised:  In a 15-fold cross-validation, our results demonstrate that the proposed multimodal fusion paradigm improves prognostic determinations from grading and molecular subtyping as well as unimodal deep networks trained on histology and genomic data alone.
Edit intent: clarity
Original:  Based on a rigorous 15-fold cross-validation, our results demonstrate that the proposed multimodal fusion paradigm improves prognostic determinations from  grading and molecular subtyping  as well as unimodal deep networks trained on histology and genomic data alone.
Revised:  Based on a rigorous 15-fold cross-validation, our results demonstrate that the proposed multimodal fusion paradigm improves prognostic determinations from grading and molecular subtyping , as well as unimodal deep networks trained on histology and genomic data alone.
Edit intent: fluency
Original: Living systems transmit heritable information in molecules that form replicating stores (e.g. genome sequence) and in the arrangements of molecules that form cycling stores (e.g. regulators assembled around a gene sequence) .
Revised: Living systems transmit heritable information using the replicating gene sequences and the cycling regulators assembled around a gene sequence) .
Edit intent: clarity
Original: Living systems transmit heritable information in molecules that form replicating stores (e.g. genome sequence) and in the arrangements of molecules that form cycling stores (e.g. regulators assembled around a gene sequence) .
Revised: Living systems transmit heritable information in molecules that form replicating stores (e.g. genome sequence) and in the arrangements of molecules that form cycling stores (e.g. regulators assembled around gene sequences .
Edit intent: fluency
Original:  Here I develop a framework for heredity and development that includes the analysis of cycling stores in terms of what an organism can sense about itself and its environment by defining entities, their sensors, and the sensed properties.
Revised:  Here I develop a framework for heredity and development that includes the cycling regulators parsed in terms of what an organism can sense about itself and its environment by defining entities, their sensors, and the sensed properties.
Edit intent: clarity
Original:  Each configuration of these entities and sensors is thus a potentially vast store of information that drives complex development in each generation.
Revised:  Each configuration of these entities and sensors is thus a potentially vast amount of information driving complex development in each generation.
Edit intent: clarity
Original:  and (3) regulation of sensors can prevent detection of some perturbations , which is one way to increase robustness of development and of cell types .
Revised:  and (3) regulation of sensors prevents detection of some perturbations , which is one way to increase robustness of development and of cell types .
Edit intent: clarity
Original:  and (3) regulation of sensors can prevent detection of some perturbations , which is one way to increase robustness of development and of cell types .
Revised:  and (3) regulation of sensors can prevent detection of some perturbations .
Edit intent: clarity
Original: There are fundamental topological problems , such as unknot recognition and 3-sphere recognition, for which the existence of a polynomial time algorithm remains unknown.
Revised: For many fundamental problems in computational topology , such as unknot recognition and 3-sphere recognition, for which the existence of a polynomial time algorithm remains unknown.
Edit intent: clarity
Original: There are fundamental topological problems , such as unknot recognition and 3-sphere recognition, for which the existence of a polynomial time algorithm remains unknown.
Revised: There are fundamental topological problems , such as unknot recognition and 3-sphere recognition, the existence of a polynomial time algorithm remains unknown.
Edit intent: coherence
Original: There are fundamental topological problems , such as unknot recognition and 3-sphere recognition, for which the existence of a polynomial time algorithm remains unknown.
Revised: There are fundamental topological problems , such as unknot recognition and 3-sphere recognition, for which the existence of a polynomial-time solution remains unknown.
Edit intent: clarity
Original:  One of the key operations in normal surface theory is finding a non-trivial normal disc or sphere in a 3-dimensional triangulation.
Revised:  One of the key operations in normal surface theory is finding a non-trivial normal sphere or disc in a 3-dimensional triangulation.
Edit intent: fluency
Original:  Our first result shows that an algebraic abstraction of this problem is NP-hard , which (assuming P\neqNP ) suggests that any polynomial time solution will need to exploit some geometric or topological intuition.
Revised:  Our first result shows that an algebraic abstraction of this problem is NP-hard . Assuming P\neqNP ) suggests that any polynomial time solution will need to exploit some geometric or topological intuition.
Edit intent: coherence
Original:  Our first result shows that an algebraic abstraction of this problem is NP-hard , which (assuming P\neqNP ) suggests that any polynomial time solution will need to exploit some geometric or topological intuition.
Revised:  Our first result shows that an algebraic abstraction of this problem is NP-hard , which (assuming P\neqNP ) suggests that any polynomial-time procedure for finding a non-trivial normal sphere or disc will need to exploit some geometric or topological intuition.
Edit intent: clarity
Original:  While the idea of extending multigrid methods to saddle point systems is not new and can be found, e.g., in the context of Stokes and Oseen equations in literature, the main contributions of this work are (i)
Revised:  While the idea of extending multigrid methods to saddle point systems can already be found, e.g., in the context of Stokes and Oseen equations in literature, the main contributions of this work are (i)
Edit intent: clarity
Original:  the development  of an interface aggregation strategy specifically suited for generating Lagrange multiplier aggregates that are required for coupling structural equilibrium equations with contact constraints and (ii) an analysis of saddle point smoothers in the context of constrained interface problems.
Revised:  the development of an interface aggregation strategy specifically suited for generating Lagrange multiplier aggregates that are required for coupling structural equilibrium equations with contact constraints and (ii) a review of saddle point smoothers in the context of constrained interface problems.
Edit intent: clarity
Original:  The proposed method is simpler to implement, computationally less expensive than the ideas from 1%DIFDELCMD < ]%%% , and -- in the authors' opinion -- the presented approach is more intuitive for contact problems.
Revised:  The 1%DIFDELCMD < ]%%% , and -- in the authors' opinion -- the presented approach is more intuitive for contact problems.
Edit intent: clarity
Original:  The proposed method is simpler to implement, computationally less expensive than the ideas from 1%DIFDELCMD < ]%%% , and -- in the authors' opinion -- the presented approach is more intuitive for contact problems.
Revised:  The proposed method is simpler to implement, computationally less expensive than the ideas from %DIFDELCMD < ]%%% , and -- in the authors' opinion -- the presented approach is more intuitive for contact problems.
Edit intent: clarity
Original:  Initially, we experimentally show with global optimality guarantees that for the single OD pair with two routes network, CPURR does not provide a significantly better solution compared to the UE in terms of expected total monetary cost whenever the OD demand is stochastic.
Revised:  Initially, we experimentally show for the single OD pair with two routes network, CPURR does not provide a significantly better solution compared to the UE in terms of expected total monetary cost whenever the OD demand is stochastic.
Edit intent: clarity
Original:  Finally, the simulation results in the Sioux Falls network demonstrate that both OPS and AOPS consistently outperform CPURR both in expected total travel time and in expected total monetary cost.
Revised:  Finally, the simulation results using the Sioux Falls network demonstrate that both OPS and AOPS consistently outperform CPURR both in expected total travel time and in expected total monetary cost.
Edit intent: clarity
Original: We design a coordination mechanism for truck drivers that uses pricing schemes to alleviate traffic congestion in a general transportation network.
Revised: We design a coordination mechanism for truck drivers that uses pricing-and-routing schemes that can help alleviate traffic congestion in a general transportation network.
Edit intent: clarity
Original:  A basic characteristic of the mechanism is that the coordinator asks the truck drivers to declare their desired OD pair , as well as their individual VOT from a set of N available options, and guarantees that the resulting pricing scheme is Pareto-improving, i.e. every truck driver will be better-off compared to the User Equilibrium (UE)
Revised:  The main characteristic of the mechanism is that the coordinator asks the truck drivers to declare their desired OD pair , as well as their individual VOT from a set of N available options, and guarantees that the resulting pricing scheme is Pareto-improving, i.e. every truck driver will be better-off compared to the User Equilibrium (UE)
Edit intent: clarity
Original:  A basic characteristic of the mechanism is that the coordinator asks the truck drivers to declare their desired OD pair , as well as their individual VOT from a set of N available options, and guarantees that the resulting pricing scheme is Pareto-improving, i.e. every truck driver will be better-off compared to the User Equilibrium (UE)
Revised:  A basic characteristic of the mechanism is that the coordinator asks the truck drivers to declare their desired OD pair and pick their individual VOT from a set of N available options, and guarantees that the resulting pricing scheme is Pareto-improving, i.e. every truck driver will be better-off compared to the User Equilibrium (UE)
Edit intent: clarity
Original:  A basic characteristic of the mechanism is that the coordinator asks the truck drivers to declare their desired OD pair , as well as their individual VOT from a set of N available options, and guarantees that the resulting pricing scheme is Pareto-improving, i.e. every truck driver will be better-off compared to the User Equilibrium (UE)
Revised:  A basic characteristic of the mechanism is that the coordinator asks the truck drivers to declare their desired OD pair , as well as their individual VOT from a set of N available options, and guarantees that the resulting pricing-and-routing scheme is Pareto-improving, i.e. every truck driver will be better-off compared to the User Equilibrium (UE)
Edit intent: clarity
Original:  To achieve computational efficiency, we additionally propose an Approximately Optimum Pricing Scheme (AOPS) and we prove that it satisfies the aforementioned characteristics.
Revised:  To achieve computational efficiency, we propose an Approximately Optimum Pricing Scheme (AOPS) and we prove that it satisfies the aforementioned characteristics.
Edit intent: coherence
Original:  To achieve computational efficiency, we additionally propose an Approximately Optimum Pricing Scheme (AOPS) and we prove that it satisfies the aforementioned characteristics.
Revised:  To achieve computational efficiency, we additionally propose an Approximately Optimum Pricing Scheme (AOPS) and prove that it satisfies the aforementioned characteristics.
Edit intent: fluency
Original:  Finally, the simulation results using the Sioux Falls network demonstrate that both OPS and AOPS consistently outperform CPURR both in expected total travel time and in expected total monetary cost  .
Revised:  Finally, the simulation results using the Sioux Falls network demonstrate that both OPS and AOPS consistently outperform CPURR both in expected total travel time and expected total monetary cost .
Edit intent: fluency
Original:  To achieve computational efficiency, we propose an Approximately Optimum Pricing Scheme (AOPS) and prove that it satisfies the aforementioned properties.
Revised:  To improve computational efficiency, we propose an Approximately Optimum Pricing Scheme (AOPS) and prove that it satisfies the aforementioned properties.
Edit intent: clarity