wanyu/IteraTeR_v2 huggingface dataset:
Original:  The RL technique also has vulnerabilities itself .
Revised:  The RL algorithms also have vulnerabilities themselves .
Edit intent: clarity
Original:  We explain the major vulnerabilities of RL and present several attack models in which the attacks target the rewards, the measurements , and the actuators .
Revised:  We explain the major vulnerabilities of RL and present attack models where the attacker targets the information exchanged between the environment and the agent: the rewards, the measurements , and the actuators .
Edit intent: clarity
Original:  We explain the major vulnerabilities of RL and present several attack models in which the attacks target the rewards, the measurements , and the actuators .
Revised:  We explain the major vulnerabilities of RL and present several attack models in which the attacks target the rewards, the state observations , and the actuators .
Edit intent: clarity
Original:  We explain the major vulnerabilities of RL and present several attack models in which the attacks target the rewards, the measurements , and the actuators .
Revised:  We explain the major vulnerabilities of RL and present several attack models in which the attacks target the rewards, the measurements , and the action commands .
Edit intent: clarity
Original:  Finally , we discuss the future challenges of RL for cyber security and resiliency and emerging applications of RL-based CRMs.
Revised:  Finally , we discuss the future challenges of RL for cyber security and resilience and emerging applications of RL-based CRMs.
Edit intent: fluency
Original:  In this problem, our goal is to find a threshold decision tree that partitions data into k clusters and minimizes the k-medians or k-means objective.
Revised:  In this problem, our goal is to find a threshold decision tree that partitions data into k clusters and minimizes the k-medians or k-means objective.
Edit intent: fluency
Original:  The proposed ADMM sequence estimation (ADMMSE) FTN signaling detector demonstrates an excellent trade-off between performance and computational effort enabling , for the first time in the FTN signaling literature, successful detection and SE gains for QAM modulation orders as high as 64K (65,536).
Revised:  The proposed ADMM sequence estimation (ADMMSE) FTN signaling detector demonstrates an excellent trade-off between performance and computational effort enabling successful detection and SE gains for QAM modulation orders as high as 64K (65,536).
Edit intent: clarity
Original: Modern wireless cellular networks use massive multiple-input multiple-output (MIMO) technology.
Revised: Modern wireless cellular networks use massive multiple-input multiple-output technology.
Edit intent: clarity
Original:  There is an important class of linear Precoding called Regularized Zero-Forcing (RZF) . In this work, we propose a special kind of regularization matrix with different regularizations for different UE (Adaptive RZF) , using singular values of multi-antenna users.
Revised:  There is an important class of linear Precoding called Regularized Zero-Forcing . In this work, we propose a special kind of regularization matrix with different regularizations for different UE (Adaptive RZF) , using singular values of multi-antenna users.
Edit intent: clarity
Original:  There is an important class of linear Precoding called Regularized Zero-Forcing (RZF) . In this work, we propose a special kind of regularization matrix with different regularizations for different UE (Adaptive RZF) , using singular values of multi-antenna users.
Revised:  There is an important class of linear Precoding called Regularized Zero-Forcing (RZF) . In this work, we propose a special kind of regularization matrix with different regularizations for different UE , using singular values of multi-antenna users.
Edit intent: coherence
Original:  Moreover, by extending the Hong-Ou-Mandel effect to more than two states, we theoretically establish an experimental configuration able to generate entangled photon states with orbital angular momentum and conditions that provide conflict-free selections at every turn.
Revised:  Moreover, by extending the Hong-Ou-Mandel effect to more than two states, we theoretically establish an experimental configuration able to generate multi-photon states with orbital angular momentum and conditions that provide conflict-free selections at every turn.
Edit intent: clarity
Original:  This is thanks to the entanglement property that achieves no-conflict selections, even in the exploring phase to find the best arms.
Revised:  This is thanks to the quantum interference effect that achieves no-conflict selections, even in the exploring phase to find the best arms.
Edit intent: clarity
Original:  Specifically, a two-phase algorithm, is proposed, including two key phases: 1) user association phase and2) task offloading phase  .
Revised:  Specifically, a two-phase algorithm, is proposed, including two key phases: and2) task offloading phase .
Edit intent: clarity
Original:  Specifically, a two-phase algorithm, is proposed, including two key phases: 1) user association phase and2) task offloading phase  .
Revised:  Specifically, a two-phase algorithm, is proposed, including two key phases: 1) user association phase 2) task offloading phase .
Edit intent: coherence
Original:  Specifically, a two-phase algorithm, is proposed, including two key phases: 1) user association phase and2) task offloading phase  .
Revised:  Specifically, a two-phase algorithm, is proposed, including two key phases: 1) user association phase anduser association phase .
Edit intent: clarity
Original: It is essential but challenging to predict future trajectories of various agents in complex scenes.
Revised: It is essential to predict future trajectories of various agents in complex scenes.
Edit intent: clarity
Original:  Whether it is internal personality factors of agents, interactive behavior of the neighborhood, or the influence of surroundings, it will have an impact on their future behavior styles .
Revised:  Whether it is internal personality factors of agents, interactive behavior of the neighborhood, or the influence of surroundings, it will have an impact on their future plannings .
Edit intent: clarity
Original:  In this paper, we propose the Multi-Style Network (MSN) to focus on this problem by divide agents' preference styles into several hidden behavior categories adaptively and train each category's prediction network separately, therefore giving agents all styles of predictions simultaneously.
Revised:  In this paper, we propose the Multi-Style Network (MSN) to focus on this problem by dividing agents' behaviors into several hidden behavior categories adaptively and train each category's prediction network separately, therefore giving agents all styles of predictions simultaneously.
Edit intent: clarity
Original:  In this paper, we propose the Multi-Style Network (MSN) to focus on this problem by divide agents' preference styles into several hidden behavior categories adaptively and train each category's prediction network separately, therefore giving agents all styles of predictions simultaneously.
Revised:  In this paper, we propose the Multi-Style Network (MSN) to focus on this problem by divide agents' preference styles into several hidden behavior categories adaptively , and then train each category's prediction network separately, therefore giving agents all styles of predictions simultaneously.
Edit intent: coherence
Original:  In this paper, we propose the Multi-Style Network (MSN) to focus on this problem by divide agents' preference styles into several hidden behavior categories adaptively and train each category's prediction network separately, therefore giving agents all styles of predictions simultaneously.
Revised:  In this paper, we propose the Multi-Style Network (MSN) to focus on this problem by divide agents' preference styles into several hidden behavior categories adaptively and train each category's prediction network jointly, thus giving agents multiple styles of predictions simultaneously.
Edit intent: clarity
Original:  Experiments demonstrate that our deterministic MSN-D and generative MSN-G outperform many recent state-of-the-art methods and show\\%DIF > - 20\\%  better multi-style characteristics in the visualized results .
Revised:  Experiments show that MSN outperforms current state-of-the-art methods and show\\%DIF > - 20\\% better multi-style characteristics in the visualized results .
Edit intent: clarity
Original:  Experiments demonstrate that our deterministic MSN-D and generative MSN-G outperform many recent state-of-the-art methods and show\\%DIF > - 20\\%  better multi-style characteristics in the visualized results .
Revised:  Experiments demonstrate that our deterministic MSN-D and generative MSN-G outperform many recent state-of-the-art methods and show\\%DIF > - 20\\% better multi-style characteristics in predictions .
Edit intent: clarity
Original: It is essential to predict future trajectories of various agents in complex scenes .
Revised: Trajectory prediction aims at forecasting agents' possible future locations considering their observations along with the video context. It is strongly required by a lot of autonomous platforms like tracking, detection, robot navigation, self-driving cars, and many other computer vision applications .
Edit intent: coherence
Original:  Whether it is  internal personality factors of agents, interactive behavior of the neighborhood, or the influence of surroundings, it will have an impact on their future plannings.
Revised:  Whether it is agents' internal personality factors of agents, interactive behavior of the neighborhood, or the influence of surroundings, it will have an impact on their future plannings.
Edit intent: fluency
Original:  Whether it is  internal personality factors of agents, interactive behavior of the neighborhood, or the influence of surroundings, it will have an impact on their future plannings.
Revised:  Whether it is internal personality factors , interactive behaviors with the neighborhood, or the influence of surroundings, it will have an impact on their future plannings.
Edit intent: clarity
Original:  Whether it is  internal personality factors of agents, interactive behavior of the neighborhood, or the influence of surroundings, it will have an impact on their future plannings.
Revised:  Whether it is internal personality factors of agents, interactive behavior of the neighborhood, or the influence of surroundings, all of them might represent impacts on agents' future plannings.
Edit intent: clarity
Original:  We propose the Multi-Style Network (MSN) to focus on this problem by dividing agents ' behaviors into several hidden behavior categories adaptively, and then train each category's prediction networkjointly, thus giving agents multiple stylesof predictions simultaneously . Experiments show that  MSN outperforms current state-of-the-art methods with 10\\%DIF < -
Revised:  We propose the Multi-Style Network (MSN) to focus on this problem by dividing agents ' behaviors into several hidden behavior categories adaptively, and then train each category's prediction networkjointly, thus giving agents multiple stylesof predictions simultaneously . Experiments show that the proposed MSN outperforms current state-of-the-art methods with 10\\%DIF < -
Edit intent: fluency
Original:  We propose the Multi-Style Network (MSN) to focus on this problem by dividing agents ' behaviors into several hidden behavior categories adaptively, and then train each category's prediction networkjointly, thus giving agents multiple stylesof predictions simultaneously . Experiments show that  MSN outperforms current state-of-the-art methods with 10\\%DIF < -
Revised:  We propose the Multi-Style Network (MSN) to focus on this problem by dividing agents ' behaviors into several hidden behavior categories adaptively, and then train each category's prediction networkjointly, thus giving agents multiple stylesof predictions simultaneously . Experiments show that MSN outperforms current state-of-the-art methods up to 10\\%DIF < -
Edit intent: clarity
Original:  20\\% performance improvement on two widely used datasets, and %DIF > - 20\\% quantitatively on two widely used datasets, and presents better multi-style characteristics in predictions .
Revised:  20\\% %DIF > - 20\\% quantitatively on two widely used datasets, and presents better multi-style characteristics in predictions .
Edit intent: clarity
Original:  20\\% performance improvement on two widely used datasets, and %DIF > - 20\\% quantitatively on two widely used datasets, and presents better multi-style characteristics in predictions .
Revised:  20\\% performance improvement on two widely used datasets, and %DIF > - 20\\% quantitatively on two widely used datasets, and presents better multi-style characteristics qualitatively .
Edit intent: clarity
Original:  When a few pixel-level fine annotations are also affordable , it is natural to leverage both of the pixel-level (e.g., segmentation) and image level (e.g., classification) annotation to further improve the performance.
Revised:  When a few pixel-level fine annotations are also affordable . Naturally a question comes to us that whether the combination of pixel-level (e.g., segmentation) and image level (e.g., classification) annotation to further improve the performance.
Edit intent: coherence
Original:  In computational pathology , however, such weak or mixed supervision learning is still a challenging task , since the high resolution of whole slide images makes it unattainable to perform end-to-end training of classification models.
Revised:  In computational pathology , however, such weak or mixed supervision learning is still a challenging task , since the high resolution of whole slide images makes it difficult to do end-to-end training of classification models.
Edit intent: clarity
Original:  To handle those problems , we propose a mixed supervision learning framework for super high-resolution images to effectively utilize their various labels (e.g., sufficient image-level coarse annotations and a few pixel-level fine labels ).
Revised:  To handle this problem , we propose a mixed supervision learning framework for super high-resolution images to effectively utilize their various labels (e.g., sufficient image-level coarse annotations and a few pixel-level fine labels ).
Edit intent: coherence
Original:  To handle those problems , we propose a mixed supervision learning framework for super high-resolution images to effectively utilize their various labels (e.g., sufficient image-level coarse annotations and a few pixel-level fine labels ).
Revised:  To handle those problems , we propose a hybrid supervision learning framework for super high-resolution images to effectively utilize their various labels (e.g., sufficient image-level coarse annotations and a few pixel-level fine labels ).
Edit intent: fluency
Original:  To handle those problems , we propose a mixed supervision learning framework for super high-resolution images to effectively utilize their various labels (e.g., sufficient image-level coarse annotations and a few pixel-level fine labels ).
Revised:  To handle those problems , we propose a mixed supervision learning framework for this kind of high resolution images with sufficient image-level coarse annotations and a few pixel-level fine labels ).
Edit intent: clarity
Original:  During the patch training stage, this framework can make use of coarse image-level labels to refine self-supervised learning and generate high-quality pixel-level pseudo labels.
Revised:  During the patch training stage, this framework can make use of coarse image-level labels to refine generated pixel-level pseudo labels.
Edit intent: clarity
Original:  A comprehensive strategy is proposed to suppress pixel-level false positives and false negatives.
Revised:  Complete strategy is proposed to suppress pixel-level false positives and false negatives.
Edit intent: clarity
Original:  In our work, we propose a solution for this problem - a publicly-available Android application for synchronized video recording on multiple smartphones with sub-millisecond accuracy.
Revised:  In our work, we propose a solution for this problem -- a publicly-available Android application for synchronized video recording on multiple smartphones with sub-millisecond accuracy.
Edit intent: fluency
Original:  Also, we estimate the time drift parameter for those smartphones, which is less than 1.2 millisecond per minute for most of the considered devices, that makes smartphones' camera system a worthy analog for professional multi-view systems.
Revised:  Also, we estimate the time drift parameter for those smartphones, which is less than 1.2 msec per minute for most of the considered devices, that makes smartphones' camera system a worthy analog for professional multi-view systems.
Edit intent: clarity
Original:  In contrast, WiCluster is both preciseand requires weaker label-information that can be easily collected  .
Revised:  In contrast, WiCluster is precise, requires weaker label-information that can be easily collected .
Edit intent: clarity
Original:  These losses only require simple to acquire priors: a sketch of the floorplan, approximate location of access-point locations and a few CSI packets that are labeled with the corresponding zone in the floorplan.
Revised:  These losses only require simple to acquire priors: a sketch of the floorplan, approximate access-point locations and a few CSI packets that are labeled with the corresponding zone in the floorplan.
Edit intent: fluency
Original:  These losses only require simple to acquire priors: a sketch of the floorplan, approximate location of access-point locations and a few CSI packets that are labeled with the corresponding zone in the floorplan.
Revised:  These losses only require simple to acquire priors: a sketch of the floorplan, approximate location of access-point locations and a few CSI packets that are labelled with the corresponding zone in the floorplan.
Edit intent: fluency
Original:  Thirdly, we report results and a robustness study for 2D positioning in a single-floor office building and 3D positioning in a two-floor hometo show the robustness of our method .
Revised:  Thirdly, we report results and a robustness study for 2D positioning in two single-floor office building and 3D positioning in a two-floor hometo show the robustness of our method .
Edit intent: fluency
Original:  Thirdly, we report results and a robustness study for 2D positioning in a single-floor office building and 3D positioning in a two-floor hometo show the robustness of our method .
Revised:  Thirdly, we report results and a robustness study for 2D positioning in a single-floor office buildings and 3D positioning in a two-floor hometo show the robustness of our method .
Edit intent: fluency
Original:  Thirdly, we report results and a robustness study for 2D positioning in a single-floor office building and 3D positioning in a two-floor hometo show the robustness of our method .
Revised:  Thirdly, we report results and a robustness study for 2D positioning in a single-floor office building and 3D positioning in a two-story home .
Edit intent: clarity
Original:  Our findings show that AdaptSky does not only exhibit a fast-adapting learning and outperform the state-of-the-art baseline approach in data rate and fairness, but also it generalizes very well 
Revised:  Our findings show that AdaptSky does not only exhibit a fast-adapting learning and outperform the state-of-the-art baseline approach in data rate and fairness, but also it generalizes very well .
Edit intent: fluency
Original:  Finally, we report on two case-studies where we have adopted the RMQFMU, and provide guidelines meant to aid practitioners in the useof the tool .
Revised:  Finally, we report on two case-studies where we have adopted the RMQFMU, and provide guidelines meant to aid practitioners in its use .
Edit intent: clarity
Original:  Crowdsourcing has become one of the standard tools for cheap and time-efficient data collection for simple problems such as image classification : thanks in large part to advances in research on aggregation methods.
Revised:  In simple problems such as image classification, crowdsourcing has become one of the standard tools for cheap and time-efficient data collection for simple problems such as image classification : thanks in large part to advances in research on aggregation methods.
Edit intent: coherence
Original:  Crowdsourcing has become one of the standard tools for cheap and time-efficient data collection for simple problems such as image classification : thanks in large part to advances in research on aggregation methods.
Revised:  Crowdsourcing has become one of the standard tools for cheap and time-efficient data collection : thanks in large part to advances in research on aggregation methods.
Edit intent: coherence
Original:  At a higher level, we also contribute to the more general challenge of collecting high-quality datasets using crowdsourcing: we develop a principled pipeline for constructing datasets of crowdsourced audio transcriptions in any novel domain.
Revised:  At a higher level, we also contribute to the more general challenge of developing the methodology for reliable data collection via crowdsourcing. In that, we design a principled pipeline for constructing datasets of crowdsourced audio transcriptions in any novel domain.
Edit intent: clarity
Original:  On the development set , the achieved CCC is  0.469  for valence and  0.649  for arousal, which significantly outperforms the baseline method with the corresponding CCC of  0.210 and 0.230  for valence and arousal, respectively.
Revised:  On the development set , the achieved CCC is 0.469 ) for valence and 0.649 for arousal, which significantly outperforms the baseline method with the corresponding CCC of 0.210 and 0.230 for valence and arousal, respectively.
Edit intent: fluency
Original:  On the development set , the achieved CCC is  0.469  for valence and  0.649  for arousal, which significantly outperforms the baseline method with the corresponding CCC of  0.210 and 0.230  for valence and arousal, respectively.
Revised:  On the development set , the achieved CCC is 0.469 for valence and 0.649 ) for arousal, which significantly outperforms the baseline method with the corresponding CCC of 0.210 and 0.230 for valence and arousal, respectively.
Edit intent: fluency
Original:  On the development set , the achieved CCC is  0.469  for valence and  0.649  for arousal, which significantly outperforms the baseline method with the corresponding CCC of  0.210 and 0.230  for valence and arousal, respectively.
Revised:  On the development set , the achieved CCC is 0.469 for valence and 0.649 for arousal, which significantly outperforms the baseline method with the corresponding CCC of 0.210 and 0.230 ) for valence and arousal, respectively.
Edit intent: fluency
Original:  Existing methods addressing it directly regress hand meshes via 2D convolutional neural networks, which leads to artifacts due to perspective distortions in the images.
Revised:  Existing methods addressing it directly regress hand meshes via 2D convolutional neural networks, which leads to artefacts due to perspective distortions in the images.
Edit intent: fluency
Original:  In extensive evaluations on three public benchmarks, i.e., SynHand5M, depth-based HANDS19 challenge and HO-3D, the proposed HandVoxNet++ achieves the state-of-the-art performance.
Revised:  In extensive evaluations on three public benchmarks, i.e., SynHand5M, depth-based HANDS19 challenge and HO-3D, the proposed HandVoxNet++ achieves state-of-the-art performance.
Edit intent: clarity
Original:  In this paper, we consider temporal property graphs (TPGs) and propose temporal regular path queries ( TRPQ ) that incorporate time into TPGs navigation.
Revised:  In this paper, we consider temporal property graphs (TPGs) and propose temporal regular path queries ( TRPQs ) that incorporate time into TPGs navigation.
Edit intent: fluency