wanyu/IteraTeR_v2 huggingface dataset:
Original:  In this paper, we propose an automated solution to identify  videos that are likely to be targeted by coordinated harassers  . First, we characterize and model YouTube videos along several axes (metadata, audio transcripts, thumbnails) based on a ground truth dataset of raid victims .
Revised:  In this paper, we propose an automated solution to identify videos that are likely to be targeted by coordinated harassers . First, we characterize and model YouTube videos along several axes (metadata, audio transcripts, thumbnails) based on a ground truth dataset of videos that were targeted by raids .
Edit intent: clarity
Original:  Then, we use an ensemble of classifiers to determine the likelihood that a video will be raided with high accuracy (AUC up to 94\%).
Revised:  Then, we use an ensemble of classifiers to determine the likelihood that a video will be raided with very good results (AUC up to 94\%).
Edit intent: clarity
Original:  Overall, our work paves the way for providing video platforms like YouTube with proactive systems to detect and mitigate coordinated hate attacks  .
Revised:  Overall, our work provides an important first step towards deploying proactive systems to detect and mitigate coordinated hate attacks .
Edit intent: clarity
Original:  Overall, our work paves the way for providing video platforms like YouTube with proactive systems to detect and mitigate coordinated hate attacks  .
Revised:  Overall, our work paves the way for providing video platforms like YouTube with proactive systems to detect and mitigate coordinated hate attacks on platforms like YouTube .
Edit intent: clarity
Original:  It follows from their result that a multilinear polynomial over the finite field of order 2 (a multilinear boolean polynomial) can be factored in time cubic in the size of the polynomial given as a string.
Revised:  It follows from their result that a multilinear polynomial over the finite field of order 2 can be factored in time cubic in the size of the polynomial given as a string.
Edit intent: clarity
Original:  We have later rediscovered this result and provided a simple factorization algorithm based on the computation of derivatives of multilinear boolean polynomials.
Revised:  Later, we have rediscovered this result and provided a simple factorization algorithm based on the computation of derivatives of multilinear boolean polynomials.
Edit intent: coherence
Original:  We have later rediscovered this result and provided a simple factorization algorithm based on the computation of derivatives of multilinear boolean polynomials.
Revised:  We have later rediscovered this result and provided a simple factorization algorithm based on computations over derivatives of multilinear boolean polynomials.
Edit intent: clarity
Original:  We have later rediscovered this result and provided a simple factorization algorithm based on the computation of derivatives of multilinear boolean polynomials.
Revised:  We have later rediscovered this result and provided a simple factorization algorithm based on the computation of derivatives of multilinear polynomials.
Edit intent: clarity
Original:  The algorithm has been applied to solve problems of compact representation of various combinatorial structures, including boolean functions and relational data tables.
Revised:  The algorithm has been applied to solve problems of compact representation of various combinatorial structures, including Boolean functions and relational data tables.
Edit intent: fluency
Original:  In this paper, we improve the known cubic upper complexity bound of this factorization algorithm and report on a preliminary experimental analysis.
Revised:  In this paper, we describe an improvement of this factorization algorithm and report on a preliminary experimental analysis.
Edit intent: clarity
Original:  In this paper, we improve the known cubic upper complexity bound of this factorization algorithm and report on a preliminary experimental analysis.
Revised:  In this paper, we improve the known cubic upper complexity bound of this factorization algorithm and report on preliminary experimental analysis.
Edit intent: fluency
Original:  For an example application, suppose one must remove %DIFDELCMD < \eps %%%  n edges from a bounded degree graph G to make it planar.
Revised:  As an application, suppose one must remove %DIFDELCMD < \eps %%% n edges from a bounded degree graph G to make it planar.
Edit intent: clarity
Original:  This result implies an algorithm, with the same running time, that produces a K_{3,3} or K_5 minor in G. No  sublinear time bound was known for this problem , prior to this result .
Revised:  This result implies an algorithm, with the same running time, that produces a K_{3,3} or K_5 minor in G. No prior sublinear time bound was known for this problem , prior to this result .
Edit intent: fluency
Original:  This result implies an algorithm, with the same running time, that produces a K_{3,3} or K_5 minor in G. No  sublinear time bound was known for this problem , prior to this result .
Revised:  This result implies an algorithm, with the same running time, that produces a K_{3,3} or K_5 minor in G. No sublinear time bound was known for this problem .
Edit intent: clarity
Original: Over the last several years, the use of machine learning (ML) in neuroscience has been increasing exponentially .
Revised: Over the last several years, the use of machine learning (ML) in neuroscience has been rapidly increasing .
Edit intent: clarity
Original:  We qualitatively and quantitatively evaluate the proposed approach and verify that it extracts higher quality saliency maps compared to the existing approaches that are dependent on a fixed classifier.
Revised:  We qualitatively and quantitatively evaluate the proposed approach extracts higher quality saliency maps compared to the existing approaches that are dependent on a fixed classifier.
Edit intent: coherence
Original: Extracting saliency maps , which indicate parts of the image important to classification, requires many tricks to achieve satisfactory performancewhen using classifier-dependent methods.
Revised: Currently available methods for extracting saliency maps identify parts of the image important to classification, requires many tricks to achieve satisfactory performancewhen using classifier-dependent methods.
Edit intent: clarity
Original:  We observe that the proposed approach extracts higher quality saliency maps and outperforms existing weakly-supervised localization techniques, setting the new state of the art result  on the ImageNet dataset.
Revised:  We observe that the proposed approach extracts higher quality saliency maps and outperforms existing weakly-supervised localization techniques, setting the new state of the art result for localization task on the ImageNet dataset.
Edit intent: clarity
Original: Neural network optimization is often conceptualized as optimizing parameters, but it is ultimately a matter of optimizing a function defined by inputs and outputs.
Revised: To optimize a neural network one often thinks of optimizing its parameters, but it is ultimately a matter of optimizing a function defined by inputs and outputs.
Edit intent: clarity
Original:  In light of this we propose a learning rule, Hilbert-constrained gradient descent (HCGD), that regularizes the distance a network can travel through L^2-space in any one update.
Revised:  In light of this we propose a new learning rule that constrains the distance a network can travel through L^2-space in any one update.
Edit intent: clarity
Original:  In particular, the proposed framework produces one compressed model whose convolutional filters are sparse not only in the spatial domain but also in the Winograd domain.
Revised:  In particular, the proposed framework produces one compressed model whose convolutional filters can be made sparse either in the spatial domain but also in the Winograd domain.
Edit intent: clarity
Original:  In particular, the proposed framework produces one compressed model whose convolutional filters are sparse not only in the spatial domain but also in the Winograd domain.
Revised:  In particular, the proposed framework produces one compressed model whose convolutional filters are sparse not only in the spatial domain or in the Winograd domain.
Edit intent: clarity
Original:  From our experiments, we obtain 24.2\times, 47.7\times and 35.4\times compressed models for ResNet-18, AlexNet and CT-SRCNN, while their computational complexity is also reduced by 4.5\times, 5.1\times and 23.5\times, respectively.
Revised:  From our experiments, we obtain 24.2\times, 47.7\times and 35.4\times compressed models for ResNet-18, AlexNet and CT-SRCNN, while their computational cost is also reduced by 4.5\times, 5.1\times and 23.5\times, respectively.
Edit intent: clarity
Original: Previous experiments have explored the effect of gender and cognitive reflection on dishonesty .
Revised: Previous experiments have explored the effects of gender and cognitive reflection on dishonesty .
Edit intent: fluency
Original:  Exploring this interaction is important because previous work found that females tend to be both more intuitive than males .
Revised:  Exploring this interaction is important because previous work found that males tend to be both more intuitive than males .
Edit intent: fluency
Original:  In particular, algorithms to average a family of PDs have only been considered recently and are known to be computationally prohibitive.
Revised:  Indeed, this was recently exemplified in a string of papers which show that the simple task of averaging a few PDs can be computationally prohibitive.
Edit intent: clarity
Original:  We propose in this article a tractable framework to carry out fundamental tasks on PDs , namely evaluating distances, computing barycenters and carrying out clustering.
Revised:  We propose in this article a tractable framework to carry out standard tasks on PDs , namely evaluating distances, computing barycenters and carrying out clustering.
Edit intent: clarity
Original:  We propose in this article a tractable framework to carry out fundamental tasks on PDs , namely evaluating distances, computing barycenters and carrying out clustering.
Revised:  We propose in this article a tractable framework to carry out fundamental tasks on PDs , namely evaluating distances, estimating barycenters and performing clustering.
Edit intent: clarity
Original:  Previous work showed that when there is a classifier that has very small error on all tasks, there is a collaborative algorithm that finds a single classifier for all tasks and it uses O(\ln^2 (k)) times the sample complexity to learn a single task.
Revised:  Previous work showed that when there is a classifier that has very small error on all tasks, there is a collaborative algorithm that finds a single classifier for all tasks and has O((\ln (k)) times the sample complexity to learn a single task.
Edit intent: clarity
Original:  In this work, we design new algorithms for both the realizable and the non-realizable settings using only O(\ln (k)) times the sample complexity to learn a single task.
Revised:  In this work, we design new algorithms for both the realizable and the non-realizable setting, having sample complexity only O(\ln (k)) times the sample complexity to learn a single task.
Edit intent: clarity
Original: Tendermint-core blockchains offer strong consistency (no forks) in an open system relying on two ingredients (i) a set of validators that generate blocks via a variant of Practical Byzantine Fault Tolerant (PBFT) consensus protocol and (ii) a rewarding mechanism that dynamically selects nodes to be validators for the next block via  proof-of-stake , a non-energy consuming alternative of proof-of-work.
Revised: Tendermint-core blockchains offer strong consistency (no forks) in an open system combining two ingredients (i) a set of validators that generate blocks via a variant of Practical Byzantine Fault Tolerant (PBFT) consensus protocol and (ii) a rewarding mechanism that dynamically selects nodes to be validators for the next block via proof-of-stake , a non-energy consuming alternative of proof-of-work.
Edit intent: clarity
Original: Tendermint-core blockchains offer strong consistency (no forks) in an open system relying on two ingredients (i) a set of validators that generate blocks via a variant of Practical Byzantine Fault Tolerant (PBFT) consensus protocol and (ii) a rewarding mechanism that dynamically selects nodes to be validators for the next block via  proof-of-stake , a non-energy consuming alternative of proof-of-work.
Revised: Tendermint-core blockchains offer strong consistency (no forks) in an open system relying on two ingredients (i) a set of validators that generate blocks via a variant of Practical Byzantine Fault Tolerant (PBFT) consensus protocol and (ii) a selection strategy that dynamically selects nodes to be validators for the next block via proof-of-stake , a non-energy consuming alternative of proof-of-work.
Edit intent: clarity
Original: Tendermint-core blockchains offer strong consistency (no forks) in an open system relying on two ingredients (i) a set of validators that generate blocks via a variant of Practical Byzantine Fault Tolerant (PBFT) consensus protocol and (ii) a rewarding mechanism that dynamically selects nodes to be validators for the next block via  proof-of-stake , a non-energy consuming alternative of proof-of-work.
Revised: Tendermint-core blockchains offer strong consistency (no forks) in an open system relying on two ingredients (i) a set of validators that generate blocks via a variant of Practical Byzantine Fault Tolerant (PBFT) consensus protocol and (ii) a rewarding mechanism that dynamically selects nodes to be validators for the next block via a proof-of-stake , a non-energy consuming alternative of proof-of-work.
Edit intent: fluency
Original:  The contribution of this paper is twofold .
Revised:  The contribution of this paper is two-fold .
Edit intent: fluency
Original:   Our second contribution relates to the fairness of Tendermint rewarding mechanism.
Revised:  Our second contribution relates to the fairness of the rewarding mechanism.
Edit intent: fluency
Original:  Additionally, we provethat there exists an (eventual) fair rewarding mechanism in repeated consensus-based blockchains if and only if the system is ( eventually) synchronous .
Revised:  Additionally, we provethat there exists an (eventual) fair rewarding mechanism if and only if the system is ( eventually) synchronous .
Edit intent: clarity
Original:  We present an adaptive LSTM that advances the state of the art for the Penn Treebank and Wikitext-2 word-modeling tasks while using fewer parameters and converging in  half as many iterations.
Revised:  We present an adaptive LSTM that advances the state of the art for the Penn Treebank and WikiText-2 word-modeling tasks while using fewer parameters and converging in half as many iterations.
Edit intent: fluency
Original:  Work was done upon the potential of brain wave activity patterns to be detected as electrical signals, classified and translated into commands following BCI constructing paradigm.
Revised:  Work was done upon the potential of brain wave activity patterns to be detected as electrical signals, classified and translated into commands following Brain Computer Interfaces (BCI) constructing paradigm.
Edit intent: clarity
Original:  However, The interface constructed was for the first time a device which can reconstruct this command physically.
Revised:  However, the interface constructed was for the first time a device which can reconstruct this command physically.
Edit intent: fluency
Original:  Objectives of the project is to address the challenges of the inaccurate performance and cost of user-training which are yet the main issues preventing BCI from being upgraded into more immersive and effective technology.
Revised:  Objectives of the project is to address the challenges of the inaccurate performance in user-training which are yet the main issues preventing BCI from being upgraded into more immersive and effective technology.
Edit intent: clarity
Original:  The design requirements addressed were the communication speed of the droplet movement and the accuracy of hitting fixed targets.
Revised:  The design requirements addressed were the communication speed of the droplet and accuracy of hitting fixed targets.
Edit intent: clarity
Original:  The tests achieved an average speed of 0.469 cm/s and average accuracy of 81.6\% for the best volume from many were tried .
Revised:  The tests achieved an average speed of 0.469 cm/s and average accuracy of 81.6\% were obtained from the best volume from many were tried .
Edit intent: clarity
Original:  The tests achieved an average speed of 0.469 cm/s and average accuracy of 81.6\% for the best volume from many were tried .
Revised:  The tests achieved an average speed of 0.469 cm/s and average accuracy of 81.6\% for the best volume for the droplet .
Edit intent: clarity
Original:  A conclusion to be drawn was that the promise of this other point of view on BCI systems to be more Brain-Real World Systems .
Revised:  A conclusion to be drawn was that the promise of this other point of view on BCI systems to be more Brain-Real World Systems 
Edit intent: fluency
Original:  This raises the question of whether there might be simple ways to improve the test performance of an already trained model without having to re-train or even fine-tune it with new data.
Revised:  This raises the question of whether there might be simple ways to improve the test performance of an already trained model without having to re-train or fine-tune it with new data.
Edit intent: clarity
Original:  Based on a detailed data analysis, this paper introduces a novel automatic fake news credibility inference model, namely FakeDetector . Based on a set of explicit and latent features extracted from the textual information, FakeDetector builds a deep diffusive network model to learn the representations of news articles, creators and subjects simultaneously.
Revised:  This paper introduces a novel automatic fake news credibility inference model, namely FakeDetector . Based on a set of explicit and latent features extracted from the textual information, FakeDetector builds a deep diffusive network model to learn the representations of news articles, creators and subjects simultaneously.
Edit intent: clarity
Original:  Based on a detailed data analysis, this paper introduces a novel automatic fake news credibility inference model, namely FakeDetector . Based on a set of explicit and latent features extracted from the textual information, FakeDetector builds a deep diffusive network model to learn the representations of news articles, creators and subjects simultaneously.
Revised:  Based on a detailed data analysis, this paper introduces a novel automatic fake news credibility inference model, namely FAKEDETECTOR . Based on a set of explicit and latent features extracted from the textual information, FakeDetector builds a deep diffusive network model to learn the representations of news articles, creators and subjects simultaneously.
Edit intent: fluency
Original:  Based on a detailed data analysis, this paper introduces a novel automatic fake news credibility inference model, namely FakeDetector . Based on a set of explicit and latent features extracted from the textual information, FakeDetector builds a deep diffusive network model to learn the representations of news articles, creators and subjects simultaneously.
Revised:  Based on a detailed data analysis, this paper introduces a novel automatic fake news credibility inference model, namely FakeDetector . Based on a set of explicit and latent features extracted from the textual information, FAKEDETECTOR builds a deep diffusive network model to learn the representations of news articles, creators and subjects simultaneously.
Edit intent: clarity
Original:  Extensive experiments have been done on a real-world fake news dataset to compare FakeDetector with several state-of-the-art models, and the experimental results have demonstrated the effectiveness of the proposed model.
Revised:  Extensive experiments have been done on a real-world fake news dataset to compare FAKEDETECTOR with several state-of-the-art models, and the experimental results have demonstrated the effectiveness of the proposed model.
Edit intent: fluency
Original: We study the fundamental problem of distributed energy-aware network formation with mobile agents of limited computational power that have the capability to wirelessly transmit and receive energy in a peer-to-peer manner.
Revised: We study the fundamental problem of distributed network formation among mobile agents of limited computational power that have the capability to wirelessly transmit and receive energy in a peer-to-peer manner.
Edit intent: clarity
Original:  Further, we theoretically and experimentally evaluate a plethora of energy redistribution protocols that exploit different levels of knowledge in order to achieve desired energy distributions which require, for instance, that every agent has  twice the energy of the agents of higher depth ( according to the tree network) .
Revised:  Further, we theoretically and experimentally evaluate a plethora of energy redistribution protocols that exploit different levels of knowledge in order to achieve desired energy distributions among the agents which require that every agent has twice the energy of the agents of higher depth ( according to the tree network) .
Edit intent: clarity
Original:  Further, we theoretically and experimentally evaluate a plethora of energy redistribution protocols that exploit different levels of knowledge in order to achieve desired energy distributions which require, for instance, that every agent has  twice the energy of the agents of higher depth ( according to the tree network) .
Revised:  Further, we theoretically and experimentally evaluate a plethora of energy redistribution protocols that exploit different levels of knowledge in order to achieve desired energy distributions which require, for instance, that every agent has twice the energy of the agents of higher depth , according to the tree network) .
Edit intent: fluency
Original:  Our study shows that without using any knowledge about the network structure, such energy distributions cannot be achieved in a timely manner, which means that there might be high energy loss during the redistribution process.
Revised:  Our study shows that without using any knowledge about the network structure, such energy distributions cannot be achieved in a timely manner, meaning that there might be high energy loss during the redistribution process.
Edit intent: coherence
Original:  We consider the computational complexity of finding and verifying various solution concepts in trading networks---multi-sided matching markets with bilateral contracts---under the assumption of full substitutability of agents' preferences.
Revised:  We consider the computational complexity of finding and verifying various solution concepts in trading networks-multi-sided matching markets with bilateral contracts---under the assumption of full substitutability of agents' preferences.
Edit intent: fluency
Original:  We consider the computational complexity of finding and verifying various solution concepts in trading networks---multi-sided matching markets with bilateral contracts---under the assumption of full substitutability of agents' preferences.
Revised:  We consider the computational complexity of finding and verifying various solution concepts in trading networks---multi-sided matching markets with bilateral contracts-under the assumption of full substitutability of agents' preferences.
Edit intent: fluency
Original:  First, we show that outcomes that satisfy an economically intuitive solution concept---trail stability---always exist and can be found in linear time.
Revised:  It is known that outcomes that satisfy an economically intuitive solution concept---trail stability---always exist and can be found in linear time.
Edit intent: coherence