wanyu/IteraTeR_v2 huggingface dataset:
Original:  Over large-scale networks, the difficulty of addressing such inverse questions (or problems ) is compounded by the fact that usually only a limited portion of nodes can be probed, giving rise to a second important question: Despite the presence of several unobserved nodes, are partial and local observations still sufficient to discover the graph linking the probed nodes?
Revised:  Over large-scale networks, the difficulty of addressing such inverse questions (or problems ) is compounded by the fact that usually only a limited portion of nodes can be probed, giving rise to a second important question: Despite the presence of unobserved nodes, are partial and local observations still sufficient to discover the graph linking the probed nodes?
Edit intent: clarity
Original:  Over large-scale networks, the difficulty of addressing such inverse questions (or problems ) is compounded by the fact that usually only a limited portion of nodes can be probed, giving rise to a second important question: Despite the presence of several unobserved nodes, are partial and local observations still sufficient to discover the graph linking the probed nodes?
Revised:  Over large-scale networks, the difficulty of addressing such inverse questions (or problems ) is compounded by the fact that usually only a limited portion of nodes can be probed, giving rise to a second important question: Despite the presence of several unobserved nodes, can partial observations still be sufficient to discover the graph linking the probed nodes?
Edit intent: clarity
Original:  The article surveys recent advances on this inverse learning problem and related questions . Examples of applications are provided to illustrate how the interplay between graph learning and distributed optimization arises in practice, e.g., in cognitive engineered systems such as distributed detection, or in other real-world problems such as the mechanism of opinion formation over social networks and the mechanism of coordination in biological networks.
Revised:  The article surveys recent advances on this challenging learning problem and related questions . Examples of applications are provided to illustrate how the interplay between graph learning and distributed optimization arises in practice, e.g., in cognitive engineered systems such as distributed detection, or in other real-world problems such as the mechanism of opinion formation over social networks and the mechanism of coordination in biological networks.
Edit intent: clarity
Original:  To achieve the hierarchical decomposition, an algorithm to verify the KE graph is given by the solution space expression of Vertex-Cover , and the relation between multi-level KE graphs and maximal matching is illustrated and proved.
Revised:  To achieve the hierarchical decomposition, an algorithm to verify the KE graph is given by the solution space expression of vertex-cover , and the relation between multi-level KE graphs and maximal matching is illustrated and proved.
Edit intent: fluency
Original:  To achieve the hierarchical decomposition, an algorithm to verify the KE graph is given by the solution space expression of Vertex-Cover , and the relation between multi-level KE graphs and maximal matching is illustrated and proved.
Revised:  To achieve the hierarchical decomposition, an algorithm to verify the KE graph is given by the solution space expression of Vertex-Cover , and the relation between multi-layer KE graphs and maximal matching is illustrated and proved.
Edit intent: fluency
Original:  Furthermore, a framework to calculate the KE-layer number and approximate the minimal vertex-cover is proposed , with different strategies of switching nodes and counting energy.
Revised:  Furthermore, a framework to calculate the KE-layer number and approximate the minimal vertex-cover is provided , with different strategies of switching nodes and counting energy.
Edit intent: clarity
Original:  The phase transition phenomenon between different KE-layers are studied with the transition points located, the vertex cover numbers got by this strategy have comparable advantage against several other methods , and its efficiency outperforms the existing ones just before the transition point.
Revised:  The phase transition phenomenon between different KE-layers are studied with the transition points located, and searching of vertex-cover got by this strategy have comparable advantage against several other methods , and its efficiency outperforms the existing ones just before the transition point.
Edit intent: clarity
Original:  The phase transition phenomenon between different KE-layers are studied with the transition points located, the vertex cover numbers got by this strategy have comparable advantage against several other methods , and its efficiency outperforms the existing ones just before the transition point.
Revised:  The phase transition phenomenon between different KE-layers are studied with the transition points located, the vertex cover numbers got by this strategy presents comparable advantage against several other methods , and its efficiency outperforms the existing ones just before the transition point.
Edit intent: clarity
Original: Biomedical researchers working on a specific disease need up-to-date and unified access to knowledge relevant to the disease of their interest.
Revised: In biomedical research, unified access to knowledge relevant to the disease of their interest.
Edit intent: clarity
Original:  In this study, we propose a pipeline to automatically retrieve and integrate relevant knowledge based on a semantic graphrepresentation , the iASiS Open Data Graph.
Revised:  In this study, we propose a framework to automatically retrieve and integrate relevant knowledge based on a semantic graphrepresentation , the iASiS Open Data Graph.
Edit intent: clarity
Original:  Results: The disease-specific semantic graph can provide easy access to resources relevant to specific concepts and individual aspects of these concepts , in the form of concept relations and attributes.
Revised:  This disease-specific semantic graph can provide easy access to resources relevant to specific concepts and individual aspects of these concepts , in the form of concept relations and attributes.
Edit intent: coherence
Original:  Results: The disease-specific semantic graph can provide easy access to resources relevant to specific concepts and individual aspects of these concepts , in the form of concept relations and attributes.
Revised:  Results: The disease-specific semantic graph provides access to knowledge relevant to specific concepts and individual aspects of these concepts , in the form of concept relations and attributes.
Edit intent: clarity
Original:  Results: The disease-specific semantic graph can provide easy access to resources relevant to specific concepts and individual aspects of these concepts , in the form of concept relations and attributes.
Revised:  Results: The disease-specific semantic graph can provide easy access to resources relevant to specific concepts and their individual aspects , in the form of concept relations and attributes.
Edit intent: clarity
Original:  Results from exemplary queries are presented, investigating the potential of this approach in integrating and accessing knowledge as an automatically generated semantic graph  .
Revised:  Results from exemplary queries are presented, investigating the potential of this automatically generated semantic graph .
Edit intent: clarity
Original:  We use the synchronisation confidence score as a proxy for audio-visual correlation and based on it we can detect adversarial attacks.
Revised:  We use the synchronisation confidence score as a proxy for audiovisual correlation and based on it we can detect adversarial attacks.
Edit intent: fluency
Original:  To the best of our knowledge, this is the first work on detection of adversarial attacks on audio-visual speech recognition models.
Revised:  To the best of our knowledge, this is the first work on detection of adversarial attacks on audiovisual speech recognition models.
Edit intent: fluency
Original:  We apply recent adversarial attacks on two audio-visual speech recognition models trained on the GRID and LRW datasets.
Revised:  We apply recent adversarial attacks on two audiovisual speech recognition models trained on the GRID and LRW datasets.
Edit intent: fluency
Original:  The experimental results demonstrated that the proposed approach is an effective way for detecting such attacks.
Revised:  The experimental results demonstrate that the proposed approach is an effective way for detecting such attacks.
Edit intent: fluency
Original: Articles in high-impact journals are by definition more highly cited on average .
Revised: Articles in high-impact journals are , on average, more frequently cited .
Edit intent: clarity
Original:  But are they cited more often because the articles are somehow  " better "?
Revised:  But are they cited more often because those articles are somehow " better "?
Edit intent: clarity
Original:  But are they cited more often because the articles are somehow  " better "?
Revised:  But are they cited more often because the articles are somehow more " better "?
Edit intent: clarity
Original:  Or are they cited more often simply because they appeared in a high-impact journal?
Revised:  Or are they cited more often simply because they are published in a high-impact journal?
Edit intent: clarity
Original:  Although some evidence suggests the latter  the causal relationship is not clear.
Revised:  Although some evidence suggests the latter , the causal relationship is not clear.
Edit intent: fluency
Original:  We here compare citations of published journal articles to citations of their preprint versions to uncover the causal mechanism.
Revised:  We here compare citations of preprints to citations of their preprint versions to uncover the causal mechanism.
Edit intent: clarity
Original:  We here compare citations of published journal articles to citations of their preprint versions to uncover the causal mechanism.
Revised:  We here compare citations of published journal articles to citations of the published version to uncover the causal mechanism.
Edit intent: clarity
Original:  We show that high-impact journals seem to select articles that tend to attract more citations.
Revised:  We show that high-impact journals select articles that tend to attract more citations.
Edit intent: clarity
Original:  The use of journal metrics in research evaluation has been increasingly criticised in recent years and article-level citations are sometimes suggested as an alternative.
Revised:  The use of journal metrics in research evaluation has been increasingly criticized in recent years and article-level citations are sometimes suggested as an alternative.
Edit intent: fluency
Original:  In this paper, we introduce a new Pull model and study the AoI optimization problem under replication schemes .
Revised:  In this paper, we study the AoI optimization problem under replication schemes .
Edit intent: clarity
Original:  Furthermore, we consider a more realistic scenario where the user has no  knowledge of the system.
Revised:  Furthermore, we consider a more realistic scenario where the user has no prior knowledge of the system.
Edit intent: clarity
Original: The Age-of-Information (AoI) has recently been proposed as an important metric for investigating the timeliness performance in information-update systems.
Revised: The Age-of-Information is an important metric for investigating the timeliness performance in information-update systems.
Edit intent: clarity
Original:  waiting wisely can significantly reduce the AoI and improve the AoI-based utility in most scenarios.
Revised:  waiting for more than one response can often significantly reduce the AoI and improve the AoI-based utility in most scenarios.
Edit intent: clarity
Original:  A more accurate reference genome enables increased accuracy in read mappings, which provides more accurate variant information and thus health data on the donor .
Revised:  A more sensitive downstream analysis is critical for a better understanding of the genome donor (e.g., health characteristics) .
Edit intent: clarity
Original:  Therefore, read data sets from sequenced samples should ideally be mapped to the latest available reference genome  .
Revised:  Therefore, read sets from sequenced samples should ideally be mapped to the latest available reference genome .
Edit intent: clarity
Original:  Unfortunately, the increasingly large amounts of available genomic data makes it prohibitively expensive to fully map each read data set to its respective reference genome every time the reference is updated.
Revised:  Unfortunately, the increasingly large amount of available genomic data makes it prohibitively expensive to fully map each read data set to its respective reference genome every time the reference is updated.
Edit intent: fluency
Original:  Unfortunately, the increasingly large amounts of available genomic data makes it prohibitively expensive to fully map each read data set to its respective reference genome every time the reference is updated.
Revised:  Unfortunately, the increasingly large amounts of available genomic data makes it prohibitively expensive to fully re-map each read set to its respective reference genome every time the reference is updated.
Edit intent: clarity
Original:  Several tools that attempt to reduce the procedure of updating a read data set from one reference to another (i.e., remapping) have been published.
Revised:  There are several tools that attempt to reduce the procedure of updating a read data set from one reference to another (i.e., remapping) have been published.
Edit intent: clarity
Original:  Several tools that attempt to reduce the procedure of updating a read data set from one reference to another (i.e., remapping) have been published.
Revised:  Several tools that attempt to accelerate the process of updating a read data set from one reference to another (i.e., remapping) have been published.
Edit intent: clarity
Original:  The main drawback of existing approaches is that if a read maps to a region in the old reference without similar regions in the new reference, it cannot be remapped.
Revised:  The main drawback of existing approaches is that if a read maps to a region in the old reference that does not appear with a reasonable degree of similarity in the new reference, it cannot be remapped.
Edit intent: clarity
Original:  The main drawback of existing approaches is that if a read maps to a region in the old reference without similar regions in the new reference, it cannot be remapped.
Revised:  The main drawback of existing approaches is that if a read maps to a region in the old reference without similar regions in the new reference, the read cannot be remapped.
Edit intent: clarity
Original:  To address this major limitation in existing tools, we propose AirLift, a fast and comprehensive technique for moving alignments from one genome to another.
Revised:  To address this major limitation in existing tools, we propose AirLift, a fast and comprehensive technique for remapping alignments from one genome to another.
Edit intent: clarity
Original:  AirLift can reduce 1) the number of reads that need to be mapped from the entire read set by up to 99.9\% and 2)\\%DIF > and 2) the overall execution time to remap the reads between the two most recent reference versions by 6.94x, 44.0 x, and 16.4 x for large (human), medium (C. elegans), and small (yeast) references, respectively .
Revised:  AirLift can reduce 1) the number of reads that need to be mapped from the entire read set by up to 99.99\\%DIF > and 2) the overall execution time to remap the reads between the two most recent reference versions by 6.94x, 44.0 x, and 16.4 x for large (human), medium (C. elegans), and small (yeast) references, respectively .
Edit intent: coherence
Original:  The proposed OeSNN-UAD approach was experimentally compared to the state-of-the-art unsupervised methods and algorithms for anomaly detection in stream data .
Revised:  The proposed OeSNN-UAD detector was experimentally compared to the state-of-the-art unsupervised methods and algorithms for anomaly detection in stream data .
Edit intent: clarity
Original:  The proposed OeSNN-UAD approach was experimentally compared to the state-of-the-art unsupervised methods and algorithms for anomaly detection in stream data .
Revised:  The proposed OeSNN-UAD approach was experimentally compared with state-of-the-art unsupervised methods and algorithms for anomaly detection in stream data .
Edit intent: fluency
Original:  The proposed OeSNN-UAD approach was experimentally compared to the state-of-the-art unsupervised methods and algorithms for anomaly detection in stream data .
Revised:  The proposed OeSNN-UAD approach was experimentally compared to the state-of-the-art unsupervised and semi-supervised detectors of anomalies in stream data .
Edit intent: clarity
Original:  According to the results of these experiments, our approach significantly outperforms other solutions provided in the literature in the case of  Numenta Anomaly Benchmark . Also in the case of real data files category of Yahoo Anomaly Benchmark  , OeSNN-UAD outperforms other selected algorithms, whereas in the case of Yahoo Anomaly Benchmark synthetic data files, it provides competitive results to the results recently reported in the literature.
Revised:  According to the results of these experiments, our approach significantly outperforms other solutions provided in the literature in the case of data streams from the Numenta Anomaly Benchmark . Also in the case of real data files category of Yahoo Anomaly Benchmark , OeSNN-UAD outperforms other selected algorithms, whereas in the case of Yahoo Anomaly Benchmark synthetic data files, it provides competitive results to the results recently reported in the literature.
Edit intent: clarity
Original:  According to the results of these experiments, our approach significantly outperforms other solutions provided in the literature in the case of  Numenta Anomaly Benchmark . Also in the case of real data files category of Yahoo Anomaly Benchmark  , OeSNN-UAD outperforms other selected algorithms, whereas in the case of Yahoo Anomaly Benchmark synthetic data files, it provides competitive results to the results recently reported in the literature.
Revised:  According to the results of these experiments, our approach significantly outperforms other solutions provided in the literature in the case of Numenta Anomaly Benchmark repository. Also, in the case of real data files category of Yahoo Anomaly Benchmark , OeSNN-UAD outperforms other selected algorithms, whereas in the case of Yahoo Anomaly Benchmark synthetic data files, it provides competitive results to the results recently reported in the literature.
Edit intent: clarity
Original:  According to the results of these experiments, our approach significantly outperforms other solutions provided in the literature in the case of  Numenta Anomaly Benchmark . Also in the case of real data files category of Yahoo Anomaly Benchmark  , OeSNN-UAD outperforms other selected algorithms, whereas in the case of Yahoo Anomaly Benchmark synthetic data files, it provides competitive results to the results recently reported in the literature.
Revised:  According to the results of these experiments, our approach significantly outperforms other solutions provided in the literature in the case of Numenta Anomaly Benchmark . Also in the case of real data files of the Yahoo Anomaly Benchmark , OeSNN-UAD outperforms other selected algorithms, whereas in the case of Yahoo Anomaly Benchmark synthetic data files, it provides competitive results to the results recently reported in the literature.
Edit intent: clarity
Original:  According to the results of these experiments, our approach significantly outperforms other solutions provided in the literature in the case of  Numenta Anomaly Benchmark . Also in the case of real data files category of Yahoo Anomaly Benchmark  , OeSNN-UAD outperforms other selected algorithms, whereas in the case of Yahoo Anomaly Benchmark synthetic data files, it provides competitive results to the results recently reported in the literature.
Revised:  According to the results of these experiments, our approach significantly outperforms other solutions provided in the literature in the case of Numenta Anomaly Benchmark . Also in the case of real data files category of Yahoo Anomaly Benchmark repository , OeSNN-UAD outperforms other selected algorithms, whereas in the case of Yahoo Anomaly Benchmark synthetic data files, it provides competitive results to the results recently reported in the literature.
Edit intent: clarity
Original: We exhibit a randomized algorithm which given a square n\times n complex matrix A with \|A\| < \le 1 and \delta>0, computes with high probability invertible V and diagonal D such that \|A-VDV^{-1}\|\le \delta and \|V\|\|V^{-1}\| \le O(n^{2.5}/\delta) in O(T_{MM}\>(n)\log^2(n/\delta)) arithmetic operations on a floating point machine with O(\log^4(n/\delta)\log n) bits of precision.
Revised: We exhibit a randomized algorithm which given a square n\times n complex matrix A with \|A\| \le 1 and \delta>0, computes with high probability invertible V and diagonal D such that \|A-VDV^{-1}\|\le \delta and \|V\|\|V^{-1}\| \le O(n^{2.5}/\delta) in O(T_{MM}\>(n)\log^2(n/\delta)) arithmetic operations on a floating point machine with O(\log^4(n/\delta)\log n) bits of precision.
Edit intent: clarity
Original:  The algorithm is a variant of the practical spectral bisection algorithm in numerical linear algebra (Beavers and Denman, 1974).
Revised:  The algorithm is a variant of the spectral bisection algorithm in numerical linear algebra (Beavers and Denman, 1974).
Edit intent: clarity
Original:  In this paper, we propose a novel criterion for CNN pruning inspired by neural network interpretability: The most relevant elements, i.e. weights or filters, are automatically found using their relevance score in the sense of explainable AI (XAI).
Revised:  In this paper, we propose a novel criterion for CNN pruning inspired by neural network interpretability: The most relevant elements, i.e. weights or filters, are automatically found using their relevance scores obtained from concepts of explainable AI (XAI).
Edit intent: clarity
Original:  By that we for the first time link the two disconnected lines of interpretability and model compression research.
Revised:  By exploring this idea, we connect the lines of interpretability and model compression research.
Edit intent: clarity
Original:  We show in particular that our proposed method can efficiently prune transfer-learned CNN models where networks pre-trained on large corpora are adapted to specialized tasks.
Revised:  We show that our proposed method can efficiently prune transfer-learned CNN models where networks pre-trained on large corpora are adapted to specialized tasks.
Edit intent: coherence
Original:  We show in particular that our proposed method can efficiently prune transfer-learned CNN models where networks pre-trained on large corpora are adapted to specialized tasks.
Revised:  We show in particular that our proposed method can efficiently prune CNN models in transfer-learning setups in which networks pre-trained on large corpora are adapted to specialized tasks.
Edit intent: clarity
Original:  To this end, the method is evaluated on a broad range of computer vision datasets.
Revised:  The method is evaluated on a broad range of computer vision datasets.
Edit intent: clarity