wanyu/IteraTeR_v2 huggingface dataset:
Original: This paper attempts to compare and combine different approaches for de-tecting errors in Knowledge Graphs . Knowledge Graphs constitute a mainstreamapproach for the representation of relational information on big heterogeneous data, however, they may contain a big amount of imputed noise when constructed auto-matically .
Revised: Nowadays Knowledge Graphs constitute a mainstream approach for the representation of relational information on big heterogeneous data, however, they may contain a big amount of imputed noise when constructed auto-matically .
Edit intent: clarity
Original: This paper attempts to compare and combine different approaches for de-tecting errors in Knowledge Graphs . Knowledge Graphs constitute a mainstreamapproach for the representation of relational information on big heterogeneous data, however, they may contain a big amount of imputed noise when constructed auto-matically .
Revised: This paper attempts to compare and combine different approaches for de-tecting errors in Knowledge Graphs . Knowledge Graphs constitute a mainstreamapproach for the representation of relational information on big heterogeneous data, however, they may contain a big amount of imputed noise when constructed automatically .
Edit intent: fluency
Original:  To address this problem, different error detection methodologies have beenproposed , mainly focusing on path ranking and representation learning.
Revised:  To address this problem, different error detection methodologies have been proposed , mainly focusing on path ranking and representation learning.
Edit intent: fluency
Original:  This workpresents various mainstream approaches and proposes a novel hybrid and modularmethodology for the task.
Revised:  This work presents various mainstream approaches and proposes a novel hybrid and modularmethodology for the task.
Edit intent: fluency
Original:  This workpresents various mainstream approaches and proposes a novel hybrid and modularmethodology for the task.
Revised:  This workpresents various mainstream approaches and proposes a hybrid and modular methodology for the task.
Edit intent: clarity
Original:  We compare these methods on two benchmarks and one real-world biomedical publications dataset, showcasing the potential of our approach anddrawing insights regarding the state-of-art in error detection in Knowledge Graphs
Revised:  We compare different methods on two benchmarks and one real-world biomedical publications dataset, showcasing the potential of our approach anddrawing insights regarding the state-of-art in error detection in Knowledge Graphs
Edit intent: clarity
Original: This paper considers a status update communication system consisting of a source-destination link with timeliness requirements.
Revised: In this work, we investigate information freshness in a status update communication system consisting of a source-destination link with timeliness requirements.
Edit intent: clarity
Original:  Under the assumption of ergodicity, we obtain a general formula of the stationary distribution of the AoI  .
Revised:  We obtain a general formula of the stationary distribution of the AoI .
Edit intent: clarity
Original:  Under the assumption of ergodicity, we obtain a general formula of the stationary distribution of the AoI  .
Revised:  Under the assumption of ergodicity, we obtain a general formula of the stationary distribution of the AoI , under the assumption of ergodicity .
Edit intent: fluency
Original:  We relate this result to a discrete time queueing system and provide a general expression of the generating function of AoI in relation with the system time and the peak age of information (PAoI)  .
Revised:  We relate this result to a discrete time queueing system and provide a general expression of the generating function of AoI in relation with the system time and the peak age of information (PAoI) metric .
Edit intent: clarity
Original: Worldwide Severe acute respiratory syndrome coronavirus 2 ( SARS-Cov-2 ) infection is disrupting in the economy and anxiety of people.
Revised: Worldwide Severe acute respiratory syndrome coronavirus 2 ( SARS-CoV-2 ) infection is disrupting in the economy and anxiety of people.
Edit intent: clarity
Original:  By analysing 48 almost complete virus genome sequences, we found out that the viruses that invaded Taiwan, the United States, and Japan were introduced independently.
Revised:  By analyzing 48 almost complete virus genome sequences, we found out that the viruses that invaded Taiwan, the United States, and Japan were introduced independently.
Edit intent: fluency
Original:  As a result, content delivery has been quickly pushed to network edges . Compared with classical content delivery networks, edge caches with smaller size usually suffer from more bursty requests , which makes conventional caching algorithms perform poorly in edge networks.
Revised:  As a result, content caching is gradually extending to network edges . Compared with classical content delivery networks, edge caches with smaller size usually suffer from more bursty requests , which makes conventional caching algorithms perform poorly in edge networks.
Edit intent: clarity
Original:  As a result, content delivery has been quickly pushed to network edges . Compared with classical content delivery networks, edge caches with smaller size usually suffer from more bursty requests , which makes conventional caching algorithms perform poorly in edge networks.
Revised:  As a result, content delivery has been quickly pushed to network edges . Compared with classical content delivery networks, caches in edge networks with smaller sizes usually have to accommodate more bursty requests , which makes conventional caching algorithms perform poorly in edge networks.
Edit intent: clarity
Original:  This paperaims to propose an effective caching decision policycalled PA-Cache that uses evolving deep learning to adaptively learn time-varying content popularity to decide which content to evict when the cache is full.
Revised:  This paperaims to propose an effective caching decision policycalled PA-Cache that uses evolving deep learning to adaptively learn time-varying content popularity and determines which contents should be replaced when the cache is full.
Edit intent: clarity
Original:  Unlike prior learning-based approaches that either use a small set of features for decision making or require the entire training dataset to be available for learning a fine-tuned but might outdated prediction model , PA-Cache weights a large set of critical features to train the neural network in an evolving manner so as to meet the edge requests with fluctuations and bursts.
Revised:  Unlike prior learning-based approaches that either use a small set of features for decision making or require the entire training dataset to be available for learning a fine-tuned but might outdated prediction model , PA-Cache weighs a large set of critical features to train the neural network in an evolving manner so as to meet the edge requests with fluctuations and bursts.
Edit intent: fluency
Original:  We demonstrate the effectiveness of PA-Cache through extensive experiments with real-world data traces from a large commercial video-on-demand service provider.
Revised:  We demonstrate the effectiveness of PA-Cache on real-world data traces from a large commercial video-on-demand service provider.
Edit intent: clarity
Original:  We demonstrate the effectiveness of PA-Cache through extensive experiments with real-world data traces from a large commercial video-on-demand service provider.
Revised:  We demonstrate the effectiveness of PA-Cache through extensive experiments with real-world traces from a large commercial video-on-demand service provider.
Edit intent: clarity
Original:  We demonstrate the effectiveness of PA-Cache through extensive experiments with real-world data traces from a large commercial video-on-demand service provider.
Revised:  We demonstrate the effectiveness of PA-Cache through extensive experiments with real-world data traces from a large online video-on-demand service provider.
Edit intent: clarity
Original:  The evaluation shows that \rb{The results show that PA-Cache outperforms existing popular caching algorithms and approximates the optimal algorithm with only a 3.8\\% performance gap when the cache percentage is 1.0\\%} PA-Cache improves the hit rate in comparison with state-of-the-art methods at a lower computational cost .
Revised:  \rb{The results show that PA-Cache outperforms existing popular caching algorithms and approximates the optimal algorithm with only a 3.8\\% performance gap when the cache percentage is 1.0\\%} PA-Cache improves the hit rate in comparison with state-of-the-art methods at a lower computational cost .
Edit intent: clarity
Original:  The evaluation shows that \rb{The results show that PA-Cache outperforms existing popular caching algorithms and approximates the optimal algorithm with only a 3.8\\% performance gap when the cache percentage is 1.0\\%} PA-Cache improves the hit rate in comparison with state-of-the-art methods at a lower computational cost .
Revised:  The evaluation shows that \rb{The results show that PA-Cache outperforms existing popular caching algorithms and approximates the optimal algorithm with only a 3.8\\% performance gap when the cache percentage is 1.0\\%}. PA-Cache improves the hit rate in comparison with state-of-the-art methods at a lower computational cost .
Edit intent: fluency
Original: Fontenele and collaborators \mbox{ fontenele reported extensive analyses of power-law scalings of neuronal avalanches from experimental recordings and from numerical simulations of a model.
Revised: Fontenele and collaborators reported extensive analyses of power-law scalings of neuronal avalanches from experimental recordings and from numerical simulations of a model.
Edit intent: fluency
Original: Fontenele and collaborators \mbox{ fontenele reported extensive analyses of power-law scalings of neuronal avalanches from experimental recordings and from numerical simulations of a model.
Revised: Fontenele and collaborators \mbox{ fontenele reported extensive analyses of power-law scalings of neuronal avalanches in experimental recordings and from numerical simulations of a model.
Edit intent: clarity
Original: Fontenele and collaborators \mbox{ fontenele reported extensive analyses of power-law scalings of neuronal avalanches from experimental recordings and from numerical simulations of a model.
Revised: Fontenele and collaborators \mbox{ fontenele reported extensive analyses of power-law scalings of neuronal avalanches from experimental recordings and in a critical theoretical model.
Edit intent: clarity
Original:  One of their main conclusions is that the brain may operate at criticality in specific regimes.
Revised:  One of their main conclusions is that the brain operates at criticality in specific regimes.
Edit intent: clarity
Original: We introduce Wavesplit, an end-to-end speech separation system.
Revised: We introduce Wavesplit, an end-to-end source separation system.
Edit intent: clarity
Original:  From a single recording of mixed speech , the model infers and clusters representations of each speaker and then estimates each source signal conditioned on the inferred representations.
Revised:  From a single mixture , the model infers and clusters representations of each speaker and then estimates each source signal conditioned on the inferred representations.
Edit intent: clarity
Original:  From a single recording of mixed speech , the model infers and clusters representations of each speaker and then estimates each source signal conditioned on the inferred representations.
Revised:  From a single recording of mixed speech , the model infers a representation for each source and then estimates each source signal conditioned on the inferred representations.
Edit intent: clarity
Original:  From a single recording of mixed speech , the model infers and clusters representations of each speaker and then estimates each source signal conditioned on the inferred representations.
Revised:  From a single recording of mixed speech , the model infers and clusters representations of each speaker and then estimates each source signal given the inferred representations.
Edit intent: clarity
Original:  The model is trained on the raw waveform to jointly perform the two tasks .
Revised:  The model is trained to jointly perform the two tasks .
Edit intent: clarity
Original:  Our model infers a set of speaker representations through clustering, which addresses the fundamental permutation problem of speech separation.
Revised:  Our model infers a set of source representations via clustering, which addresses the fundamental permutation problem of speech separation.
Edit intent: clarity
Original: Reduction to the satisfiablility problem for constrained Horn clauses (CHCs) is a widely studied approach to automated program verification.
Revised: Reduction to the satisfiability problem for constrained Horn clauses (CHCs) is a widely studied approach to automated program verification.
Edit intent: fluency
Original:  This paper proposes a novel translation of pointer-manipulating Rust programs into CHCs, which clears away pointers and heaps by leveraging ownership.
Revised:  This paper proposes a novel translation of pointer-manipulating Rust programs into CHCs, which clears away pointers and memories by leveraging ownership.
Edit intent: clarity
Original:  At the cost of slightly changing the output graph class these bikernels can be turned into into kernels.
Revised:  At the cost of slightly changing the output graph class our bikernels can be turned into into kernels.
Edit intent: clarity
Original:  Finally, we demonstrate how these constructions can be combined to create 'multikernels', meaning graphs who represent kernels for multiple problems at once.
Revised:  Finally, we demonstrate how these constructions can be combined to create 'multikernels', meaning graphs that represent kernels for multiple problems at once.
Edit intent: fluency
Original:  Concretely, we show that r-DOMINATING SET, TOTAL r-DOMINATION, and r-ROMAN DOMINATION admit a multikernel;
Revised:  Concretely, we show that r-Dominating Set, Total r-Domination, and r-Roman Domination admit a multikernel;
Edit intent: fluency
Original:  as well as r-DOMINATING SET and 2r-INDEPENDENT SET for multiple values of r at once.
Revised:  as well as r-Dominating Set and 2r-Independent Set for multiple values of r at once.
Edit intent: fluency
Original: Nearly all Internet services rely on the Domain Name System (DNS) to resolve human-readable names to IP addresses.
Revised: Recent concerns over the privacy implications of the Domain Name System (DNS) to resolve human-readable names to IP addresses.
Edit intent: clarity
Original: Recent concerns over the privacy implications of the Domain Name System (DNS) have led to encrypting DNS queries and responses through protocols like DNS-over-HTTPS (DoH) and DNS-over-TLS (DoT) .
Revised: Emerging protocols such as DNS-over-HTTPS (DoH) and DNS-over-TLS (DoT) .
Edit intent: clarity
Original:  While the trend towards encryption is a positivedevelopment, the resulting centralization of the DNS has fomented tussles involving ISPs, browser and device vendors, content delivery networks, and users.
Revised:  While the trend towards encryption is positive, deployment of these protocols has in some cases resulted in further centralization of the DNS has fomented tussles involving ISPs, browser and device vendors, content delivery networks, and users.
Edit intent: clarity
Original:  We then explore how a refactored client DNS mechanism can open up new possibilities for de-centralized name resolution, preserving the benefits of encrypted DNS while satisfying other architectural desiderata , including performance , resilience, and privacy.
Revised:  We then explore how a refactored client DNS mechanism can open up new possibilities for de-centralized name resolution, preserving the benefits of encrypted DNS while satisfying other desirable properties , including performance , resilience, and privacy.
Edit intent: clarity
Original:  We then explore how a refactored client DNS mechanism can open up new possibilities for de-centralized name resolution, preserving the benefits of encrypted DNS while satisfying other architectural desiderata , including performance , resilience, and privacy.
Revised:  We then explore how a refactored client DNS mechanism can open up new possibilities for de-centralized name resolution, preserving the benefits of encrypted DNS while satisfying other architectural desiderata , including performance and privacy.
Edit intent: clarity
Original: The inference of chemical reaction networks is an important task in understanding the chemical processes in life sciences and environment .
Revised: The inference of chemical reaction networks is essential to understand and design the chemical processes in life sciences and environment .
Edit intent: clarity
Original: The inference of chemical reaction networks is an important task in understanding the chemical processes in life sciences and environment .
Revised: The inference of chemical reaction networks is an important task in understanding the chemical processes in engineering and life sciences .
Edit intent: clarity
Original:  This work presents a neural network approach for discovering unknown reaction pathways from concentration time series data.
Revised:  This work presents a neural network approach that autonomously discovers reaction pathways from concentration time series data.
Edit intent: clarity
Original:  This work presents a neural network approach for discovering unknown reaction pathways from concentration time series data.
Revised:  This work presents a neural network approach for discovering unknown reaction pathways from the time-resolved species concentration data.
Edit intent: clarity
Original:  The neural network denoted as Chemical Reaction Neural Network (CRNN), is designed to be equivalent to chemical reaction networks by following the fundamental physics laws of the Law of Mass Action and  Arrhenius Law.
Revised:  The proposed Chemical Reaction Neural Network (CRNN), is designed to be equivalent to chemical reaction networks by following the fundamental physics laws of the Law of Mass Action and Arrhenius Law.
Edit intent: clarity
Original:  The neural network denoted as Chemical Reaction Neural Network (CRNN), is designed to be equivalent to chemical reaction networks by following the fundamental physics laws of the Law of Mass Action and  Arrhenius Law.
Revised:  The neural network denoted as Chemical Reaction Neural Network (CRNN), by design, satisfies the fundamental physics laws of the Law of Mass Action and Arrhenius Law.
Edit intent: clarity
Original:  The CRNN is physically interpretable , and its weights correspond to the reaction pathways and rate constants of the chemical reaction network.
Revised:  Consequently, the CRNN is physically interpretable , and its weights correspond to the reaction pathways and rate constants of the chemical reaction network.
Edit intent: coherence
Original:  The CRNN is physically interpretable , and its weights correspond to the reaction pathways and rate constants of the chemical reaction network.
Revised:  The CRNN is physically interpretable such that the reaction pathways and rate constants of the chemical reaction network.
Edit intent: clarity
Original:  The physical interpretability also makes the CRNN not only capable of fitting the data for a given system but also developing knowledge of unknown pathways that could be generalized to similar chemical systems .
Revised:  The physical interpretability also makes the CRNN capable of not only fitting the data for a given system but also developing knowledge of unknown pathways that could be generalized to similar chemical systems .
Edit intent: fluency
Original:  We theoretically show that clearing price converges to the true value when a common prior probability distribution of information of each player is uniformly biased distribution .
Revised:  We theoretically show that clearing price converges to the true value when a common prior probability distribution of information of each player satisfies some conditions .
Edit intent: clarity
Original:  On the other hand, asynchronous (async) parallel computing has exhibited much better speed-up over its synchronous (sync) counterpart.
Revised:  On the other hand, asynchronous (async) parallel computing has exhibited significantly higher speed-up over its synchronous (sync) counterpart.
Edit intent: clarity
Original:  However, async-parallel implementation has only been demonstrated to the non-adaptive SGMs . The difficulty for adaptive SGMs originates from the second moment term that makes the convergence analysis challenging with async updates .
Revised:  However, async-parallel implementation has only been demonstrated to the non-adaptive SGMs . The difficulty for analyzing adaptive SGMs with async updates originates from the second moment term that makes the convergence analysis challenging with async updates .
Edit intent: clarity
Original:  However, async-parallel implementation has only been demonstrated to the non-adaptive SGMs . The difficulty for adaptive SGMs originates from the second moment term that makes the convergence analysis challenging with async updates .
Revised:  However, async-parallel implementation has only been demonstrated to the non-adaptive SGMs . The difficulty for adaptive SGMs originates from the second moment term .
Edit intent: coherence
Original: The evaluation of a link prediction algorithm requires to estimate the possibility of the existence of all unobserved links in a network .
Revised: Link prediction has aroused extensive attention since it can both discover hidden connections and predict future links in the networks. Many unsupervised link prediction algorithms have been proposed to find these links in a network .
Edit intent: coherence
Original: The evaluation of a link prediction algorithm requires to estimate the possibility of the existence of all unobserved links in a network .
Revised: The evaluation of a link prediction algorithm requires to estimate the possibility of the existence of all unobserved links in a variety of networks .
Edit intent: clarity
Original:  However, the number of unobserved links grows exponentially with the increase of the number of nodes, which limits link prediction in large networks  .
Revised:  However, there is an evaluation conundrum in unsupervised link prediction. Unobserved links heavily outnumber observed links in large networks .
Edit intent: clarity
Original:  We use this method to evaluate the performance of twelve link predictors on ten real-world networks of different contexts and scales .
Revised:  We use this method to evaluate the performance of twelve link predictors on ten real-world networks of different contexts and sizes .
Edit intent: clarity
Original:  Our findings show that the proposed scheme is a fast and effective evaluation method .
Revised:  Our findings have broad implications for link prediction .
Edit intent: clarity
Original:  The computational load for processing such queries, however, lies entirely with the server hosting the SPARQL endpoint, which can easily become overloaded and in the worst case not only become slow in responding but even crash so that the data becomes temporarily unavailable .
Revised:  The computational load for processing such queries, however, lies entirely with the server hosting the endpoint .
Edit intent: coherence
Original:  Recently proposed interfaces, such as Triple Pattern Fragments, have therefore shifted  the query processing load from the server to the client .
Revised:  Recently proposed interfaces, such as Triple Pattern Fragments, have therefore shifted some of the query processing load from the server to the client .
Edit intent: clarity