wanyu/IteraTeR_full_sent huggingface dataset:
Original:  In this paper, we propose a self-adaptive fuzzy reinforcement learning-based performance (stress) testing framework (SaFReL) that enables the tester agent to learn the optimal policy for generating stress test cases leading to performance breaking point without access to performance model of the system under test. SaFReL learns the optimal policy  through an initial learning  , then reuses it during a transfer learning phase, while keeping the learning running in the long-term .
Revised:  In this paper, we propose a self-adaptive fuzzy reinforcement learning-based performance testing framework. SaFReL learns the optimal policy through an initial learning , then reuses it during a transfer learning phase, while keeping the learning running in the long-term .
Edit intent: coherence
Original: We develop a framework that creates a new polygonal mesh representation of the 3D domain of a layer-by-layer 3D printing job on which we identify single, continuous tool paths covering each connected piece of the domain in every layer.
Revised: We develop a framework that creates a new polygonal mesh representation of the sparse infill domain of a layer-by-layer 3D printing job on which we identify single, continuous tool paths covering each connected piece of the domain in every layer.
Edit intent: meaning-changed
Original: We develop a framework that creates a new polygonal mesh representation of the 3D domain of a layer-by-layer 3D printing job on which we identify single, continuous tool paths covering each connected piece of the domain in every layer.
Revised: We develop a framework that creates a new polygonal mesh representation of the 3D domain of a layer-by-layer 3D printing job . We guarantee the existence of a single, continuous tool paths covering each connected piece of the domain in every layer.
Edit intent: clarity
Original: We develop a framework that creates a new polygonal mesh representation of the 3D domain of a layer-by-layer 3D printing job on which we identify single, continuous tool paths covering each connected piece of the domain in every layer.
Revised: We develop a framework that creates a new polygonal mesh representation of the 3D domain of a layer-by-layer 3D printing job on which we identify single, continuous tool path covering each connected piece of the domain in every layer.
Edit intent: fluency
Original:  The key construction at the heart of our framework is a novel Euler transformation that we introduced recently in a separate manuscript. Our Euler transformation converts a 2-dimensional cell complex K into a new 2-complex K^ such that every vertex in the 1-skeleton G^ of K^ has degree 4.
Revised:  The key construction at the heart of our framework is an Euler transformation which converts a 2-dimensional cell complex K into a new 2-complex K^ such that every vertex in the 1-skeleton G^ of K^ has degree 4.
Edit intent: clarity
Original:  Our algorithm produces a tool path that avoids material collisions and crossovers, and can be printed in a continuous fashion irrespective of complex geometry or topology of the domain (e.g., holes)  .
Revised:  Our algorithm produces a tool path that avoids material collisions and crossovers, and can be printed in a continuous fashion irrespective of complex geometry or topology of the domain (e.g., holes) . We implement our test our framework on several 3D objects. Apart from standard geometric shapes, we demonstrate the framework on the Stanford bunny .
Edit intent: meaning-changed
Original:  The Shapley value [ 1 ] is known to be the unique method that satisfies certain desirable properties , and this motivates its use. Unfortunately, despite this uniqueness result, there are a multiplicity of Shapley values used in explaining a model's prediction.
Revised:  The Shapley value [ 1 ] is known to be the unique method that satisfies certain good properties ( a multiplicity of Shapley values used in explaining a model's prediction.
Edit intent: clarity
Original:  Unfortunately, despite this uniqueness result, there are a multiplicity of Shapley values used in explaining a model's prediction. This is because there are many ways to apply the Shapley value that differ in how they reference the model, the training data, and the explanation context.
Revised:  Unfortunately, despite this uniqueness result, there are a multiplicity of ways in which the Shapley value that differ in how they reference the model, the training data, and the explanation context.
Edit intent: clarity
Original:  In this paper, we study an approach that applies the Shapley value to conditional expectations (CES) of sets of features (cf. 2%DIFDELCMD < ]%%% ) that subsumes several prior approaches within a common framework.
Revised:  In this paper, we study an approach that applies the Shapley value to conditional expectations (CES) of sets of features (cf. %DIFDELCMD < ]%%% ) that subsumes several prior approaches within a common framework.
Edit intent: coherence
Original:  In this paper, we study an approach that applies the Shapley value to conditional expectations (CES) of sets of features (cf. 2%DIFDELCMD < ]%%% ) that subsumes several prior approaches within a common framework. We provide the first algorithm for the general version of CES. We show that CES can result in counterintuitive attributions in theory and in practice (we study a diabetes prediction task);
Revised:  In this paper, we study an approach that applies the Shapley value to conditional expectations (CES) of sets of features (cf. 2%DIFDELCMD < ]%%% These give very different results, rendering the uniqueness result meaningless. Furthermore, we find that previously proposed approaches can produce counterintuitive attributions in theory and in practice (we study a diabetes prediction task);
Edit intent: meaning-changed
Original:  We show that CES can result in counterintuitive attributions in theory and in practice (we study a diabetes prediction task); for instance, CES can assign non-zero attributions to features that are not  referenced by the model.
Revised:  We show that CES can result in counterintuitive attributions in theory and in practice---for instance, they can assign non-zero attributions to features that are not referenced by the model.
Edit intent: clarity
Original:  For example, a pollination interaction may be particularly likely if the proportions of a bee's tongue match flower shapein a beneficial way. Empirical evidence for trait matching , however, varies significantly in strength among different types of ecological networks.
Revised:  For example, a pollination interaction may be particularly likely if the proportions of a bee's tongue fit a plant's flower shape. Empirical estimates of the importance of trait-matching for determining species interactions , however, varies significantly in strength among different types of ecological networks.
Edit intent: clarity
Original:  Using simulated and real data, we contrast conventional regression models with Machine Learning (ML) models (Random Forest, Boosted Regression Trees, Deep Neural Networks, Convolutional Neural Networks, Support Vector Machines, naive Bayes, and k-Nearest-Neighbor), testing their ability to predict species interactions based on traits, and infer trait combinations causally responsible for species interactions.
Revised:  Using simulated and real data, we contrast conventional generalized linear models (GLM) with more flexible Machine Learning (ML) models (Random Forest, Boosted Regression Trees, Deep Neural Networks, Convolutional Neural Networks, Support Vector Machines, naive Bayes, and k-Nearest-Neighbor), testing their ability to predict species interactions based on traits, and infer trait combinations causally responsible for species interactions.
Edit intent: meaning-changed
Original:  In two case studies, the best ML models could successfully predict species interactions in a global plant-pollinator database and infer ecologically plausible trait matching rules for a plant-hummingbird network from Costa Rica , without any prior assumptions about the system .
Revised:  In two case studies, the best ML models successfully predicted species interactions in a global plant-pollinator database and infer ecologically plausible trait matching rules for a plant-hummingbird network from Costa Rica , without any prior assumptions about the system .
Edit intent: clarity
Original:  In two case studies, the best ML models could successfully predict species interactions in a global plant-pollinator database and infer ecologically plausible trait matching rules for a plant-hummingbird network from Costa Rica , without any prior assumptions about the system .
Revised:  In two case studies, the best ML models could successfully predict species interactions in a global plant-pollinator database and inferred ecologically plausible trait-matching rules for a plant-hummingbird network from Costa Rica , without any prior assumptions about the system .
Edit intent: fluency
Original:  In two case studies, the best ML models could successfully predict species interactions in a global plant-pollinator database and infer ecologically plausible trait matching rules for a plant-hummingbird network from Costa Rica , without any prior assumptions about the system .
Revised:  In two case studies, the best ML models could successfully predict species interactions in a global plant-pollinator database and infer ecologically plausible trait matching rules for a plant-hummingbird network , without any prior assumptions about the system .
Edit intent: clarity
Original:  In two case studies, the best ML models could successfully predict species interactions in a global plant-pollinator database and infer ecologically plausible trait matching rules for a plant-hummingbird network from Costa Rica , without any prior assumptions about the system .
Revised:  In two case studies, the best ML models could successfully predict species interactions in a global plant-pollinator database and infer ecologically plausible trait matching rules for a plant-hummingbird network from Costa Rica , without any prior assumptions .
Edit intent: clarity
Original: In a recent article, Zemblys et al. 1 reported on a new method for the classification of eye-movements using deep neural networks. I will refer to this paper as the "gazeNet paper "  . I have found 2 errors and two problems with that paper that are explained herein.
Revised: In a recent article, Zemblys et al. 1 reported on a new method for the classification of eye-movements ( "gazeNet paper " . I have found 2 errors and two problems with that paper that are explained herein.
Edit intent: coherence
Original:  Error 1: The gazeNet machine-learning based \textit{\textbf{  classification method was built assuming that a hand-scored dataset from Lund University was all collected at 500 Hz, but in fact, six of the 34 recording files were actually collected at 200 Hz . Of the six datasets that were used as the training set for the gazeNet algorithm, 2 were actually collected at 200 Hz.
Revised:  \textit{\textbf{ classification method was built assuming that a hand-scored dataset from Lund University was all collected at 500 Hz, but in fact, six of the 34 recording files were actually collected at 200 Hz . Of the six datasets that were used as the training set for the gazeNet algorithm, 2 were actually collected at 200 Hz.
Edit intent: clarity
Original:  Error 1: The gazeNet machine-learning based \textit{\textbf{  classification method was built assuming that a hand-scored dataset from Lund University was all collected at 500 Hz, but in fact, six of the 34 recording files were actually collected at 200 Hz . Of the six datasets that were used as the training set for the gazeNet algorithm, 2 were actually collected at 200 Hz.
Revised:  Error 1: The gazeNet machine-learning based \textit{\textbf{Error 1: classification method was built assuming that a hand-scored dataset from Lund University was all collected at 500 Hz, but in fact, six of the 34 recording files were actually collected at 200 Hz . Of the six datasets that were used as the training set for the gazeNet algorithm, 2 were actually collected at 200 Hz.
Edit intent: meaning-changed
Original:  Error 1: The gazeNet machine-learning based \textit{\textbf{  classification method was built assuming that a hand-scored dataset from Lund University was all collected at 500 Hz, but in fact, six of the 34 recording files were actually collected at 200 Hz . Of the six datasets that were used as the training set for the gazeNet algorithm, 2 were actually collected at 200 Hz.
Revised:  Error 1: The gazeNet machine-learning based \textit{\textbf{ The gazeNet classification method was built assuming that a hand-scored dataset from Lund University was all collected at 500 Hz, but in fact, six of the 34 recording files were actually collected at 200 Hz . Of the six datasets that were used as the training set for the gazeNet algorithm, 2 were actually collected at 200 Hz.
Edit intent: fluency
Original:  Error 1: The gazeNet machine-learning based \textit{\textbf{  classification method was built assuming that a hand-scored dataset from Lund University was all collected at 500 Hz, but in fact, six of the 34 recording files were actually collected at 200 Hz . Of the six datasets that were used as the training set for the gazeNet algorithm, 2 were actually collected at 200 Hz.
Revised:  Error 1: The gazeNet machine-learning based \textit{\textbf{ classification method was built assuming that a hand-scored dataset from Lund University was all collected at 500 Hz, but in fact, six of the 34 recording files were actually collected at 200Hz . Of the six datasets that were used as the training set for the gazeNet algorithm, 2 were actually collected at 200 Hz.
Edit intent: fluency
Original:  Error 1: The gazeNet machine-learning based \textit{\textbf{  classification method was built assuming that a hand-scored dataset from Lund University was all collected at 500 Hz, but in fact, six of the 34 recording files were actually collected at 200 Hz . Of the six datasets that were used as the training set for the gazeNet algorithm, 2 were actually collected at 200 Hz. Problem 1\underline{\textit{\textbf{ has to do with the fact that even among the 500 Hz data, the inter-timestamp intervals varied widely.
Revised:  Error 1: The gazeNet machine-learning based \textit{\textbf{ classification method was built assuming that a hand-scored dataset from Lund University was all collected at 500 Hz, but in fact, six of the 34 recording files were actually collected at 200 Hz . Of the six datasets that were used as the training set for the gazeNet algorithm, 2 were actually collected at 200Hz.\underline{\textit{\textbf{ has to do with the fact that even among the 500 Hz data, the inter-timestamp intervals varied widely.
Edit intent: coherence
Original:  Problem 2 \underline{\textit{\textbf{ is that there are many unusual discontinuities in the saccade trajectories from the Lund University dataset that make it a very poor choice for the construction of an automatic classification method.
Revised:  \underline{\textit{\textbf{ is that there are many unusual discontinuities in the saccade trajectories from the Lund University dataset that make it a very poor choice for the construction of an automatic classification method.
Edit intent: coherence
Original:  Problem 2 \underline{\textit{\textbf{ is that there are many unusual discontinuities in the saccade trajectories from the Lund University dataset that make it a very poor choice for the construction of an automatic classification method.
Revised:  Problem 2 \underline{\textit{\textbf{Problem 2 is that there are many unusual discontinuities in the saccade trajectories from the Lund University dataset that make it a very poor choice for the construction of an automatic classification method.
Edit intent: coherence
Original:  True negatives are not errors, and any unmatched event misclassified as a true negative is actually driving the kappa statistic higher, whereas unmatched events should be driving the kappa statistic lower.
Revised:  True negatives are not errors, and any unmatched event misclassified as a true negative is actually driving kappa higher, whereas unmatched events should be driving the kappa statistic lower.
Edit intent: fluency
Original:  True negatives are not errors, and any unmatched event misclassified as a true negative is actually driving the kappa statistic higher, whereas unmatched events should be driving the kappa statistic lower.
Revised:  True negatives are not errors, and any unmatched event misclassified as a true negative is actually driving the kappa statistic higher, whereas unmatched events should be driving kappa lower.
Edit intent: fluency
Original: We reveal the different interpretations of the future in their judgments of future economic conditions by applying weakly supervised learning and text mining. In the Economy Watcher Survey, which is a market survey published by the Japanese government, there are assessments of current and future economic conditions by people from various fields.
Revised: The Economy Watcher Survey, which is a market survey published by the Japanese government, there are assessments of current and future economic conditions by people from various fields.
Edit intent: coherence
Original:  In our research, we separate the assessments of future economic conditions into  near and distant future economic conditions using learning from positive and unlabeled data (PU learning) , which is weakly supervised learning.
Revised:  In our research, we separate the assessments of future economic conditions into economic conditions of the near and distant future economic conditions using learning from positive and unlabeled data (PU learning) , which is weakly supervised learning.
Edit intent: meaning-changed
Original:  In our research, we separate the assessments of future economic conditions into  near and distant future economic conditions using learning from positive and unlabeled data (PU learning) , which is weakly supervised learning. The dataset is composed of several periods, and we develop a PU learning algorithm for efficient training, using the dataset with the time series.
Revised:  In our research, we separate the assessments of future economic conditions into near and distant future economic conditions using learning from positive and unlabeled data (PU learning) . Because the dataset includes data from several periods, and we develop a PU learning algorithm for efficient training, using the dataset with the time series.
Edit intent: coherence
Original:  This paper deals with the following separability problem in 3D space: Given a rigid polyhedron P with n vertices , does a semi-rigid polyhedron G exist, such that both polyhedra can be transformed into an inseparable assembled state, where the fixture snaps on to P, by applying a linear force and exploiting the mild flexibility of G? If such a flexible snapping polyhedron exists, devise an efficient and robust algorithm that constructs it.
Revised: Fixtures for constraining the movement of parts have been extensively investigated in robotics, since they are essential for using robots in automated manufacturing. This paper deals with the following separability problem in 3D space: Given a rigid polyhedron P with n vertices , does a semi-rigid polyhedron G exist, such that both polyhedra can be transformed into an inseparable assembled state, where the fixture snaps on to P, by applying a linear force and exploiting the mild flexibility of G? If such a flexible snapping polyhedron exists, devise an efficient and robust algorithm that constructs it.
Edit intent: meaning-changed
Original:  This paper deals with the following separability problem in 3D space: Given a rigid polyhedron P with n vertices , does a semi-rigid polyhedron G exist, such that both polyhedra can be transformed into an inseparable assembled state, where the fixture snaps on to P, by applying a linear force and exploiting the mild flexibility of G? If such a flexible snapping polyhedron exists, devise an efficient and robust algorithm that constructs it.
Revised:  This paper deals with the design and optimized synthesis of a special type of fixtures, which we call P with n vertices , does a semi-rigid polyhedron G exist, such that both polyhedra can be transformed into an inseparable assembled state, where the fixture snaps on to P, by applying a linear force and exploiting the mild flexibility of G? If such a flexible snapping polyhedron exists, devise an efficient and robust algorithm that constructs it.
Edit intent: meaning-changed
Original:  This paper deals with the following separability problem in 3D space: Given a rigid polyhedron P with n vertices , does a semi-rigid polyhedron G exist, such that both polyhedra can be transformed into an inseparable assembled state, where the fixture snaps on to P, by applying a linear force and exploiting the mild flexibility of G? If such a flexible snapping polyhedron exists, devise an efficient and robust algorithm that constructs it.
Revised:  This paper deals with the following separability problem in 3D space: Given a rigid polyhedronsnapping fixtures P with n vertices , does a semi-rigid polyhedron G exist, such that both polyhedra can be transformed into an inseparable assembled state, where the fixture snaps on to P, by applying a linear force and exploiting the mild flexibility of G? If such a flexible snapping polyhedron exists, devise an efficient and robust algorithm that constructs it.
Edit intent: meaning-changed
Original:  This paper deals with the following separability problem in 3D space: Given a rigid polyhedron P with n vertices , does a semi-rigid polyhedron G exist, such that both polyhedra can be transformed into an inseparable assembled state, where the fixture snaps on to P, by applying a linear force and exploiting the mild flexibility of G? If such a flexible snapping polyhedron exists, devise an efficient and robust algorithm that constructs it.
Revised:  This paper deals with the following separability problem in 3D space: Given a rigid polyhedron. Given a polyhedral workpiece P with n vertices , does a semi-rigid polyhedron G exist, such that both polyhedra can be transformed into an inseparable assembled state, where the fixture snaps on to P, by applying a linear force and exploiting the mild flexibility of G? If such a flexible snapping polyhedron exists, devise an efficient and robust algorithm that constructs it.
Edit intent: meaning-changed
Original:  This paper deals with the following separability problem in 3D space: Given a rigid polyhedron P with n vertices , does a semi-rigid polyhedron G exist, such that both polyhedra can be transformed into an inseparable assembled state, where the fixture snaps on to P, by applying a linear force and exploiting the mild flexibility of G? If such a flexible snapping polyhedron exists, devise an efficient and robust algorithm that constructs it.
Revised:  This paper deals with the following separability problem in 3D space: Given a rigid polyhedron P with n vertices and of constant genus, which we need to hold, a snapping fixture is a semi-rigid polyhedron G exist, such that both polyhedra can be transformed into an inseparable assembled state, where the fixture snaps on to P, by applying a linear force and exploiting the mild flexibility of G? If such a flexible snapping polyhedron exists, devise an efficient and robust algorithm that constructs it.
Edit intent: meaning-changed