wanyu/IteraTeR_v2 huggingface dataset:
Original:  high success rates of the identified correlation attacks against existing fingerprinting schemes (e.g., the integrated correlation attack can distort 64.8 \% fingerprint bits by \\%DIF > fingerprint bits by just modifying 14.2 \% entries in a fingerprinted database), and (ii)
Revised:  high success rates of the identified correlation attacks against existing fingerprinting schemes (e.g., the integrated correlation attack can distort 64.8 \\%DIF > fingerprint bits by just modifying 14.2 \% entries in a fingerprinted database), and (ii)
Edit intent: fluency
Original:  high \\%DIF > entries in a fingerprinted database), and (ii) high robustness of the proposed mitigation techniques (e.g., after the proposed mitigation techniques, the integrated correlation attack can only distort 3 \% \\%DIF > fingerprint bits) .
Revised:  high \\%DIF > entries in a fingerprinted database), and (ii) high robustness of the proposed mitigation techniques (e.g., with the mitigation techniques, the integrated correlation attack can only distort 3 \% \\%DIF > fingerprint bits) .
Edit intent: clarity
Original:  high \\%DIF > entries in a fingerprinted database), and (ii) high robustness of the proposed mitigation techniques (e.g., after the proposed mitigation techniques, the integrated correlation attack can only distort 3 \% \\%DIF > fingerprint bits) .
Revised:  high \\%DIF > entries in a fingerprinted database), and (ii) high robustness of the proposed mitigation techniques (e.g., after the proposed mitigation techniques, the integrated correlation attack can only distort 3 \\%DIF > fingerprint bits) .
Edit intent: coherence
Original:  Our analysis explores the effects on polarization from different levels of tolerance to other views, responsiveness to other views, exposure to dissimilar actors, multiple ideological dimensions, economic self-interest, and external shocks.
Revised:  Our analysis explores the effects on polarization of different levels of tolerance to other views, responsiveness to other views, exposure to dissimilar actors, multiple ideological dimensions, economic self-interest, and external shocks.
Edit intent: fluency
Original: As data being produced by IoT applications continues to explode, there 's a growing need to bring computing power closer to the source of the data to meet the response-time, power-consumption and cost goals of performance-critical applications like Industrial Internet of Things (IIoT), Automated Driving, Medical Imaging or Surveillance among others.
Revised: As data being produced by IoT applications continues to explode, there is a growing need to bring computing power closer to the source of the data to meet the response-time, power-consumption and cost goals of performance-critical applications like Industrial Internet of Things (IIoT), Automated Driving, Medical Imaging or Surveillance among others.
Edit intent: fluency
Original: As data being produced by IoT applications continues to explode, there 's a growing need to bring computing power closer to the source of the data to meet the response-time, power-consumption and cost goals of performance-critical applications like Industrial Internet of Things (IIoT), Automated Driving, Medical Imaging or Surveillance among others.
Revised: As data being produced by IoT applications continues to explode, there 's a growing need to bring computing power closer to the source of the data to meet the response time, power dissipation and cost goals of performance-critical applications like Industrial Internet of Things (IIoT), Automated Driving, Medical Imaging or Surveillance among others.
Edit intent: clarity
Original: As data being produced by IoT applications continues to explode, there 's a growing need to bring computing power closer to the source of the data to meet the response-time, power-consumption and cost goals of performance-critical applications like Industrial Internet of Things (IIoT), Automated Driving, Medical Imaging or Surveillance among others.
Revised: As data being produced by IoT applications continues to explode, there 's a growing need to bring computing power closer to the source of the data to meet the response-time, power-consumption and cost goals of performance-critical applications in various domains like the Industrial Internet of Things (IIoT), Automated Driving, Medical Imaging or Surveillance among others.
Edit intent: clarity
Original:  This paper proposes a FPGA-based data collection and utilization framework that allows runtime platform and application data to be sent to an edge and cloud system via data collection agents running close to the platform.
Revised:  This paper proposes a data collection and utilization framework that allows runtime platform and application data to be sent to an edge and cloud system via data collection agents running close to the platform.
Edit intent: clarity
Original:  Agents are connected to a cloud system able to train AI models to improve overall energy efficiency of an AI application executed on a FPGA-based edge platform.
Revised:  Agents are connected to a cloud system able to train AI models to improve overall energy efficiency of an AI application executed on an edge platform.
Edit intent: clarity
Original:  As future work  we foresee the possibility to train, deploy and continuously improve a base model able to efficiently adapt the execution of edge applications.
Revised:  As future work , we foresee the possibility to train, deploy and continuously improve a base model able to efficiently adapt the execution of edge applications.
Edit intent: fluency
Original:  The upper bound and lower bound of the error estimator are proved, in which proof, a key ingredient is a novel stabilizer employed in the discrete scheme.
Revised:  The upper bound and lower bound of the error estimator are proved, in which proof, the key ingredient is a novel stabilizer employed in the discrete scheme.
Edit intent: fluency
Original:  Therefore , we propose a HIN-based Interest Compositions model with graph neural network for Recommendation ( short for HicRec).
Revised:  Therefore , we propose a HIN-based Interest Composition model for Recommendation ( short for HicRec).
Edit intent: coherence
Original:  Therefore , we propose a HIN-based Interest Compositions model with graph neural network for Recommendation ( short for HicRec).
Revised:  Therefore , we propose a HIN-based Interest Compositions model with graph neural network for Recommendation ( HicRec).
Edit intent: coherence
Original:  Above all, our model learns users and items representations from various graphs corresponding to the meta-paths with the help of the graph convolution network (GCN).
Revised:  Specially, the representations of users and items representations from various graphs corresponding to the meta-paths with the help of the graph convolution network (GCN).
Edit intent: clarity
Original:  Lastly, the interests intra- and inter-meta-paths are composed and applied to recommendation.
Revised:  Lastly, the interests intra- and inter-meta-paths for recommendation.
Edit intent: clarity
Original:  Extensive experiments are conducted on three real-world datasets and the results show that the HicRec outperforms various baselines.
Revised:  Extensive experiments are conducted on three real-world datasets and the results demonstrate the outperformance of our proposed HicRec against the baselines.
Edit intent: clarity
Original:  Specifically, with the weak correlation assumption over image-text pairs, we propose a two-tower pre-training model  within the cross-modal contrastive learning (CMCL) framework.
Revised:  Specifically, with the weak correlation assumption over image-text pairs, we propose a two-tower pre-training model within the cross-modal contrastive learning framework.
Edit intent: clarity
Original:  The presented method will be integrated into the publicly available open source VVC encoder VVenC v0.3.
Revised:  The presented method was integrated into the publicly available open source VVC encoder VVenC v0.3.
Edit intent: clarity
Original:  Here, to better understand such divide, we characterize and compare the pandemic narrativesof the Democratic and Republican politicians on social media using novel computational methods including computational framinganalysis and semantic role analysis.
Revised:  As shown in this case, as well as in most major social issues, strongly polarized narrative frameworks facilitate such narratives. To understand polarization and other social chasms, it is critical to dissect these diverging narratives. Here, taking the Democratic and Republican politicians on social media using novel computational methods including computational framinganalysis and semantic role analysis.
Edit intent: clarity
Original:  By using contrasting framing and semantic roles, the Democrats emphasize the government's role in responding to the pandemic, and the Republicans emphasize the roles of individuals and support for small businesses.
Revised:  We then perform an automatic framing analysis to characterize the ways in which they frame their narratives, where we found that the Democrats emphasize the government's role in responding to the pandemic, and the Republicans emphasize the roles of individuals and support for small businesses.
Edit intent: clarity
Original:  Through statistical analysis we reveal two robust empirical discoveries, namely that (1) people increasingly deviate from the shortest path as the distance between origin and destination increases, and (2) individual choices exhibit direction-dependent asymmetries when origin and destination are swapped.
Revised:  Through statistical analysis we reveal two robust empirical discoveries, namely that (1) people increasingly deviate from the shortest path when the distance between origin and destination increases, and (2) individual choices exhibit direction-dependent asymmetries when origin and destination are swapped.
Edit intent: clarity
Original:  Through statistical analysis we reveal two robust empirical discoveries, namely that (1) people increasingly deviate from the shortest path as the distance between origin and destination increases, and (2) individual choices exhibit direction-dependent asymmetries when origin and destination are swapped.
Revised:  Through statistical analysis we reveal two robust empirical discoveries, namely that (1) people increasingly deviate from the shortest path as the distance between origin and destination increases, and (2) chosen paths are statistically different when origin and destination are swapped.
Edit intent: clarity
Original:  Modelling pedestrian path preferences by vector-based navigation increases the model 's predictive power by 35\%, compared to a model  based on minimizing distance with stochastic effects.
Revised:  Modelling pedestrian path preferences by vector-based navigation model based on minimizing distance with stochastic effects.
Edit intent: clarity
Original:  We show that these empirical findings and modelling results generalise across two major US cities with drastically different street networks, suggesting that vector-based navigation is a universal property of human path planning , independent of specific city environments.
Revised:  Our findings generalize across two major US cities with drastically different street networks, suggesting that vector-based navigation is a universal property of human path planning , independent of specific city environments.
Edit intent: clarity
Original:  We show that these empirical findings and modelling results generalise across two major US cities with drastically different street networks, suggesting that vector-based navigation is a universal property of human path planning , independent of specific city environments.
Revised:  We show that these empirical findings and modelling results generalise across two major US cities with different street networks, suggesting that vector-based navigation is a universal property of human path planning , independent of specific city environments.
Edit intent: clarity
Original:  We show that these empirical findings and modelling results generalise across two major US cities with drastically different street networks, suggesting that vector-based navigation is a universal property of human path planning , independent of specific city environments.
Revised:  We show that these empirical findings and modelling results generalise across two major US cities with drastically different street networks, hinting to the fact that vector-based navigation is a universal property of human path planning , independent of specific city environments.
Edit intent: clarity
Original:  We show that these empirical findings and modelling results generalise across two major US cities with drastically different street networks, suggesting that vector-based navigation is a universal property of human path planning , independent of specific city environments.
Revised:  We show that these empirical findings and modelling results generalise across two major US cities with drastically different street networks, suggesting that vector-based navigation might be a universal property of human path planning , independent of specific city environments.
Edit intent: clarity
Original:  It is true already for the case, when m = 2. But  an FPTAS still can exist for some other particular cases of the problem.
Revised:  It is true already for the case, when m = 2. But , an FPTAS still can exist for some other particular cases of the problem.
Edit intent: fluency
Original:  In this note  we show that the m-dimensional knapsack problem with a \Delta-modular constraints matrix admits an FPTAS with the arithmetical complexity O(T_{LP} \cdot (1/\varepsilon)^{m+3} \cdot (2m)^{2m + 6} \cdot \Delta), where T_{LP} is the linear programming complexity bound.
Revised:  In this note , we show that the m-dimensional knapsack problem with a \Delta-modular constraints matrix admits an FPTAS with the arithmetical complexity O(T_{LP} \cdot (1/\varepsilon)^{m+3} \cdot (2m)^{2m + 6} \cdot \Delta), where T_{LP} is the linear programming complexity bound.
Edit intent: fluency
Original:  Furthermore, we survey the modeling for HPF and various computational models , including brain-inspired SLAM, spatial concept formation, and deep generative models.
Revised:  Furthermore, we survey the modeling for HPF and various computational ones , including brain-inspired SLAM, spatial concept formation, and deep generative models.
Edit intent: clarity
Original:  The HPF-PGM is a computational model that is highly consistent with the anatomical structure and functions of the HPF , in contrast to typical conventional SLAM models . By referencing the brain, we suggest the importance of the integration of egocentric/allocentric information from the entorhinal cortex to the hippocampus and the use of discrete-event queues.
Revised:  The HPF-PGM as a computational model that is highly consistent with the anatomical structure and functions of the HPF , in contrast to typical conventional SLAM models . By referencing the brain, we suggest the importance of the integration of egocentric/allocentric information from the entorhinal cortex to the hippocampus and the use of discrete-event queues.
Edit intent: fluency
Original:  The HPF-PGM is a computational model that is highly consistent with the anatomical structure and functions of the HPF , in contrast to typical conventional SLAM models . By referencing the brain, we suggest the importance of the integration of egocentric/allocentric information from the entorhinal cortex to the hippocampus and the use of discrete-event queues.
Revised:  The HPF-PGM is a computational model that is highly consistent with the anatomical structure and functions of the HPF . By referencing the brain, we suggest the importance of the integration of egocentric/allocentric information from the entorhinal cortex to the hippocampus and the use of discrete-event queues.
Edit intent: coherence
Original:  The model, called kS2L-F, assumes  requests in each stage arrive sequentially regardless of the same booking time and the decision (accept or reject) must be made immediately.
Revised:  The model, called kS2L-F, assumes that requests in each stage arrive sequentially regardless of the same booking time and the decision (accept or reject) must be made immediately.
Edit intent: fluency
Original:  The model is surprisingly not easy even for only two locations .
Revised:  In spite of only two locations .
Edit intent: coherence
Original:  In this paper, we remove all the holes of unknown CR  ;
Revised:  In this paper, we remove all the holes of unknown CR 's ;
Edit intent: fluency
Original:  We implemented it in the Andromeda ~ 2 proof assistant, which supports user-definable type theories.
Revised:  We implemented it in the Andromeda 2 proof assistant, which supports user-definable type theories.
Edit intent: fluency
Original: Deep neural networks unlocked a vast range of new applications by solving tasks of which many were previouslydeemed as reserved to higher human intelligence.
Revised: Deep neural networks unlocked a vast range of new applications by solving tasks of which many were previously deemed as reserved to higher human intelligence.
Edit intent: fluency
Original:  One of the developments enabling this success was a boost incomputing power provided by special purpose hardware , such as graphic or tensor processing units.
Revised:  One of the developments enabling this success was a boost in computing power provided by special purpose hardware , such as graphic or tensor processing units.
Edit intent: fluency
Original:  Fully parallel and analogue hardwarepromises to overcomethese challenges, yet the impact of analogue neuron noise and its propagation, i.e. accumulation, threatensrendering such approaches inept.
Revised:  Fully parallel and analogue hardwarepromises to overcomethese challenges, yet the impact of analogue neuron noise and its propagation, i.e. accumulation, threatens rendering such approaches inept.
Edit intent: fluency
Original:  We find that noise accumulation is generally bound, and adding additional network layers does not worsenthe signal to noise ratio beyond this limit.
Revised:  We find that noise accumulation is generally bound, and adding additional network layers does not worsen the signal to noise ratio beyond this limit.
Edit intent: fluency
Original:  Most importantly, noise accumulation can be suppressed entirelywhen neuron activation functions have a slope smaller than unity.
Revised:  Most importantly, noise accumulation can be suppressed entirely when neuron activation functions have a slope smaller than unity.
Edit intent: fluency
Original:  We therefore developed the frameworkfor noise of deep neural networks implemented in analog systems, and identify criteria allowing engineers todesign noise-resilient novel neural network hardware.
Revised:  We therefore developed the framework for noise of deep neural networks implemented in analog systems, and identify criteria allowing engineers todesign noise-resilient novel neural network hardware.
Edit intent: fluency
Original:  We therefore developed the frameworkfor noise of deep neural networks implemented in analog systems, and identify criteria allowing engineers todesign noise-resilient novel neural network hardware.
Revised:  We therefore developed the frameworkfor noise of deep neural networks implemented in analog systems, and identify criteria allowing engineers to design noise-resilient novel neural network hardware.
Edit intent: fluency
Original:  In this paper, we present a new catalog mental model called 5W1H+R .
Revised:  In this paper, we present 5W1H+R .
Edit intent: clarity
Original:  We conclude mental models are important to make data catalogs more useful and to boost metadata management efforts that are crucial for data science tasks .
Revised:  We conclude mental models are important to make data catalogs more useful and to boost metadata management efforts .
Edit intent: clarity
Original:  Our dataset harmonizes eight disparate AND datasets into a uniform format, with a single rich feature set drawn from the Semantic Scholar  S2  database.
Revised:  Our dataset harmonizes eight disparate AND datasets into a uniform format, with a single rich feature set drawn from the Semantic Scholar ( S2 database.
Edit intent: fluency
Original:  Our dataset harmonizes eight disparate AND datasets into a uniform format, with a single rich feature set drawn from the Semantic Scholar  S2  database.
Revised:  Our dataset harmonizes eight disparate AND datasets into a uniform format, with a single rich feature set drawn from the Semantic Scholar S2 ) database.
Edit intent: fluency
Original:  On this basis, this paper integrates user behavior data under different social networks, and proposes a user topic preference model MSNT (Multiple Social Networks Topic model) for multiple social networks.
Revised:  On this basis, this paper integrates user behavior data under different social networks, and proposes a user preference discovery model on multiple social networks.
Edit intent: clarity
Original: One of the advantages of using natural language processing (NLP) technology for music is to fully exploit the embedding based representation learning paradigm that can easily handle classical tasks such as semantic similarity .
Revised: In natural language processing (NLP) technology for music is to fully exploit the embedding based representation learning paradigm that can easily handle classical tasks such as semantic similarity .
Edit intent: clarity
Original:  Nevertheless ,  it is still unclear which is the best combination of calibration methods and by how much can we further improve the performance with such methods.
Revised:  Nevertheless , it is yet unknown which calibration method is the best combination of calibration methods and by how much can we further improve the performance with such methods.
Edit intent: clarity
Original: Learning-based blind image quality assessment (BIQA) methods have recently drawn much attention for their superior performance compared to traditional methods .
Revised: Learning-based blind image quality assessment (BIQA) .
Edit intent: clarity
Original:  However, most of them do not effectively leverage the relationship between distortion-related factors, showing limited feature representation capacity .
Revised:  However, most previous methods do not effectively leverage the relationship between distortion-related factors, showing limited feature representation capacity .
Edit intent: clarity
Original:  However, most of them do not effectively leverage the relationship between distortion-related factors, showing limited feature representation capacity .
Revised:  However, most of them do not effectively model the relationship between distortion-related factors, showing limited feature representation capacity .
Edit intent: clarity
Original:  In this paper, we show that human perceptual quality is highly correlated with distortion type and degree, and is biased by image content in most IQA systems.
Revised:  In this work, we start from the analysis of the relationship between perceptual image quality and is biased by image content in most IQA systems.
Edit intent: clarity
Original:  In GraphIQA, each distortion is represented as a graph i.e.\ieno DGR.
Revised:  In GraphIQA, each distortion is represented as a graph ,\ieno DGR.
Edit intent: coherence
Original:  In GraphIQA, each distortion is represented as a graph i.e.\ieno DGR.
Revised:  In GraphIQA, each distortion is represented as a graph i.e.\ieno, DGR.
Edit intent: fluency
Original:  Specifically, we develop two sub-networks to learn the DGRs: a) Type Discrimination Network (TDN) that embeds DGR into a compact code for better discriminating distortion types  ;
Revised:  Specifically, we develop two sub-networks to learn the DGRs: a) Type Discrimination Network (TDN) that aims to embed DGR into a compact code for better discriminating distortion types ;
Edit intent: clarity