wanyu/IteraTeR_v2 huggingface dataset:
Original:  Commonly these uncertainties are accounted for using random fields and processes  which require knowledge about the appearing probability distributions functions which is not readily available.
Revised:  Commonly these uncertainties are accounted for using random fields and processes which require knowledge about the appearing probability distributions functions that is not readily available.
Edit intent: fluency
Original:  In contrast to finite element approaches, no correlation length specification of the input fields as well as no averaging via Monte-Carlo simulations are necessary.
Revised:  In contrast to finite element approaches, no correlation length specification of the input fields as well as no Monte-Carlo simulations are necessary.
Edit intent: clarity
Original: We present a numerical implementation in Python of the recently developed unconditionally convergent representation of general Heun functions as integral series.
Revised: We present a numerical implementation of the recently developed unconditionally convergent representation of general Heun functions as integral series.
Edit intent: clarity
Original:  We produce two codes  available for download, one  especially aimed at reproducing the output of Mathematica's HeunG function , the other for general-purpose computations .
Revised:  We produce two codes available for download, one of which is especially aimed at reproducing the output of Mathematica's HeunG function , the other for general-purpose computations .
Edit intent: clarity
Original:  We produce two codes  available for download, one  especially aimed at reproducing the output of Mathematica's HeunG function , the other for general-purpose computations .
Revised:  We produce two codes available for download, one especially aimed at reproducing the output of Mathematica's HeunG function .
Edit intent: coherence
Original:  Moreover, PVTv2 achieves much better performance than recent works, including Swin Transformer , under ImageNet-1K pre-training .
Revised:  Moreover, PVTv2 achieves better performance than recent works, including Swin Transformer , under ImageNet-1K pre-training .
Edit intent: clarity
Original:  Moreover, PVTv2 achieves much better performance than recent works, including Swin Transformer , under ImageNet-1K pre-training .
Revised:  Moreover, PVTv2 achieves much better performance than recent works, including Swin Transformer .
Edit intent: clarity
Original: Transformer in computer vision has recently shown encouraging progress .
Revised: Transformer recently has shown encouraging progresses in computer vision .
Edit intent: clarity
Original:  With these simple modifications, our PVTv2 significantly improves PVTv1 on  classification, detection, and segmentation.
Revised:  With these modifications, our PVTv2 significantly improves PVTv1 on classification, detection, and segmentation.
Edit intent: clarity
Original:  Moreover, PVTv2 achieves better performance than recent works , including Swin Transformer.
Revised:  Moreover, PVTv2 achieves better performance than recent works such as Swin Transformer.
Edit intent: fluency
Original:  We hope this work will make state-of-the-art vision Transformer research more accessible . Code is available at URL .
Revised:  We hope this work will facilitate state-of-the-art vision Transformer research more accessible . Code is available at URL .
Edit intent: clarity
Original:  We hope this work will make state-of-the-art vision Transformer research more accessible . Code is available at URL .
Revised:  We hope this work will make state-of-the-art Transformer researches in computer vision . Code is available at URL .
Edit intent: clarity
Original: We consider online convex optimization (OCO) over a heterogeneous network with communication delay, where multiple local devices (workers ) together with a central coordinator (master ) execute a sequence of decisions to minimize the accumulation of time-varying global costs.
Revised: We consider online convex optimization (OCO) over a heterogeneous network with communication delay, where multiple workers together with a central coordinator (master ) execute a sequence of decisions to minimize the accumulation of time-varying global costs.
Edit intent: clarity
Original: We consider online convex optimization (OCO) over a heterogeneous network with communication delay, where multiple local devices (workers ) together with a central coordinator (master ) execute a sequence of decisions to minimize the accumulation of time-varying global costs.
Revised: We consider online convex optimization (OCO) over a heterogeneous network with communication delay, where multiple local devices (workers ) together with a master execute a sequence of decisions to minimize the accumulation of time-varying global costs.
Edit intent: clarity
Original:  (iii) somewhat surprisingly, GM-Th-QAOA outperforms its non-thresholded counterparts in terms of approximation ratios achieved.
Revised:  (iii) somewhat surprisingly, GM-Th-QAOA outperforms non-thresholded counterparts in terms of approximation ratios achieved.
Edit intent: clarity
Original:  (iii) somewhat surprisingly, GM-Th-QAOA outperforms its non-thresholded counterparts in terms of approximation ratios achieved.
Revised:  (iii) somewhat surprisingly, GM-Th-QAOA outperforms its non-thresholded GM-QAOA in terms of approximation ratios achieved.
Edit intent: clarity
Original:  Experiments on large numbers of real pipelines crawled from GitHub suggest that Auto-Pipeline can successfully synthesize 60-70\% of these complex pipelines ( up to 10 steps ) in 10-20 seconds on average .
Revised:  Experiments on large numbers of real pipelines crawled from GitHub suggest that Auto-Pipeline can successfully synthesize 60-70\% of these complex pipelines with up to 10 steps ) in 10-20 seconds on average .
Edit intent: fluency
Original:  Experiments on large numbers of real pipelines crawled from GitHub suggest that Auto-Pipeline can successfully synthesize 60-70\% of these complex pipelines ( up to 10 steps ) in 10-20 seconds on average .
Revised:  Experiments on large numbers of real pipelines crawled from GitHub suggest that Auto-Pipeline can successfully synthesize 60-70\% of these complex pipelines ( up to 10 steps .
Edit intent: coherence
Original: Training large-scale deep neural networks (DNNs) currently requires a significant amount of energy, leading to serious environmental impacts.
Revised: Representing deep neural networks (DNNs) currently requires a significant amount of energy, leading to serious environmental impacts.
Edit intent: clarity
Original:  While it is common to train DNNs with forward and backward propagation in low-precision , training directly over low-precision weights, without keeping a copy of weights in high-precision , still remains to be an unsolved problem.
Revised:  While it is common to train DNNs with forward and backward propagation in low-precision typically keep a copy of weights in high-precision , still remains to be an unsolved problem.
Edit intent: clarity
Original:  This is due to complex interactions between learning algorithms and low-precision number systems  .
Revised:  This is due to complex interactions between the low-precision number systems .
Edit intent: clarity
Original:  To address this , we jointly design a low-precision training framework involving a logarithmic number system (LNS) and a multiplicative weight update training method, termed LNS-Madam.
Revised:  To address this issue, we develop a co-designed low-precision training framework involving a logarithmic number system (LNS) and a multiplicative weight update training method, termed LNS-Madam.
Edit intent: clarity
Original:  To address this , we jointly design a low-precision training framework involving a logarithmic number system (LNS) and a multiplicative weight update training method, termed LNS-Madam.
Revised:  To address this , we jointly design a low-precision training framework , termed LNS-Madam, in which we jointly design a logarithmic number system (LNS) and a multiplicative weight update training method, termed LNS-Madam.
Edit intent: clarity
Original:  By drawing the connection between LNS and multiplicative update, LNS-Madam ensures low quantization error during weight update , leading to a stable convergence even if the bitwidth is limited.
Revised:  By drawing the connection between LNS and multiplicative update, LNS-Madam results in low quantization error during weight update , leading to a stable convergence even if the bitwidth is limited.
Edit intent: clarity
Original:  By drawing the connection between LNS and multiplicative update, LNS-Madam ensures low quantization error during weight update , leading to a stable convergence even if the bitwidth is limited.
Revised:  By drawing the connection between LNS and multiplicative update, LNS-Madam ensures low quantization error during weight updates , leading to a stable convergence even if the bitwidth is limited.
Edit intent: fluency
Original:  By drawing the connection between LNS and multiplicative update, LNS-Madam ensures low quantization error during weight update , leading to a stable convergence even if the bitwidth is limited.
Revised:  By drawing the connection between LNS and multiplicative update, LNS-Madam ensures low quantization error during weight update , leading to a stable convergence even if the precision is limited.
Edit intent: clarity
Original: In recent years, as blockchain adoption has been expanding across a wide range of domains, e.g., supply chain finance, digital asset, etc., the confidentiality of smart contracts is now a fundamental demand for practical applications.
Revised: In recent years, as blockchain adoption has been expanding across a wide range of domains, e.g., supply chain finance, digital asset, etc., the confidentiality of smart contracts has now become a fundamental demand for practical applications.
Edit intent: coherence
Original:  However, while new privacy protection techniques keep coming out , how existing ones can best fit development settings is little studied . State-of-the-art solutions suffer from limited architectural support in terms of programming interfaces , thus can hardly reach general developers.
Revised:  However, while new privacy protection techniques are emerging , how existing ones can best fit development settings is little studied . State-of-the-art solutions suffer from limited architectural support in terms of programming interfaces , thus can hardly reach general developers.
Edit intent: clarity
Original:  However, while new privacy protection techniques keep coming out , how existing ones can best fit development settings is little studied . State-of-the-art solutions suffer from limited architectural support in terms of programming interfaces , thus can hardly reach general developers.
Revised:  However, while new privacy protection techniques keep coming out , how existing ones can best fit development settings are understudied . State-of-the-art solutions suffer from limited architectural support in terms of programming interfaces , thus can hardly reach general developers.
Edit intent: clarity
Original:  However, while new privacy protection techniques keep coming out , how existing ones can best fit development settings is little studied . State-of-the-art solutions suffer from limited architectural support in terms of programming interfaces , thus can hardly reach general developers.
Revised:  However, while new privacy protection techniques keep coming out , how existing ones can best fit development settings is little studied . State-of-the-art solutions lack architectural support - in terms of programming interfaces , thus can hardly reach general developers.
Edit intent: clarity
Original:  However, while new privacy protection techniques keep coming out , how existing ones can best fit development settings is little studied . State-of-the-art solutions suffer from limited architectural support in terms of programming interfaces , thus can hardly reach general developers.
Revised:  However, while new privacy protection techniques keep coming out , how existing ones can best fit development settings is little studied . State-of-the-art solutions suffer from limited architectural support in terms of programming interfaces - thus are hardly able to reach general developers.
Edit intent: clarity
Original:  The key capability of Cloakis allowing developers to implement and deploy practical solutions to multi-party transaction (MPT) problems, i.e.,  transact with secret inputs and states owned by different parties, by simply specifying it.
Revised:  The key capability of Cloak is to allow developers to implement and deploy practical solutions to multi-party transaction (MPT) problems, i.e., transact with secret inputs and states owned by different parties, by simply specifying it.
Edit intent: fluency
Original:  The key capability of Cloakis allowing developers to implement and deploy practical solutions to multi-party transaction (MPT) problems, i.e.,  transact with secret inputs and states owned by different parties, by simply specifying it.
Revised:  The key capability of Cloakis allowing developers to implement and deploy practical solutions to multi-party transaction (MPT) problems, i.e., transact with secret inputs and states owned by different parties, by simply specifying it.
Edit intent: fluency
Original:  The key capability of Cloakis allowing developers to implement and deploy practical solutions to multi-party transaction (MPT) problems, i.e.,  transact with secret inputs and states owned by different parties, by simply specifying it.
Revised:  The key capability of Cloakis allowing developers to implement and deploy practical solutions to multi-party transaction (MPT) problems, i.e., to transact with secret inputs and states owned by different parties, by simply specifying it.
Edit intent: fluency
Original:  To this end, Cloak allows users to specify privacy invariants in a declarative way, automatically generate runtime with verifiably enforced privacy and deploy it to the existing platforms with TEE-Blockchain architecture to enable the MPT.
Revised:  To this end, Cloak allows users to specify privacy invariants in a declarative way, automatically generate runtime with verifiably enforced privacy and deploy it to the existing platforms with TEE-Blockchain architecture , enabling the MPT.
Edit intent: fluency
Original:   In our evaluation on both examples and real-world applications, developers manage to deploy business services on blockchain in a concise manner by only developing Cloak smart contracts  whose size is less than 30\% of the deployed ones  and the gas cost of deployed MPTs reduces 19\%  .
Revised:  In our evaluation on both examples and real-world applications, developers manage to deploy business services on blockchain in a concise manner by only developing Cloak smart contracts , whose size is less than 30\% of the deployed ones and the gas cost of deployed MPTs reduces 19\% .
Edit intent: fluency
Original:   In our evaluation on both examples and real-world applications, developers manage to deploy business services on blockchain in a concise manner by only developing Cloak smart contracts  whose size is less than 30\% of the deployed ones  and the gas cost of deployed MPTs reduces 19\%  .
Revised:  In our evaluation on both examples and real-world applications, developers manage to deploy business services on blockchain in a concise manner by only developing Cloak smart contracts whose size is less than 30\% of the deployed ones , and the gas cost of deployed MPTs reduces 19\% .
Edit intent: fluency
Original:   In our evaluation on both examples and real-world applications, developers manage to deploy business services on blockchain in a concise manner by only developing Cloak smart contracts  whose size is less than 30\% of the deployed ones  and the gas cost of deployed MPTs reduces 19\%  .
Revised:  In our evaluation on both examples and real-world applications, developers manage to deploy business services on blockchain in a concise manner by only developing Cloak smart contracts whose size is less than 30\% of the deployed ones and the gas cost of deployed MPTs reduced by 19\% .
Edit intent: fluency
Original: In linear control theory, a structured system is a system whose entries of its system matrices are either fixed zero or indeterminate .
Revised: In linear control theory, a structured system whose entries of its system matrices are either fixed zero or indeterminate .
Edit intent: clarity
Original: In linear control theory, a structured system is a system whose entries of its system matrices are either fixed zero or indeterminate .
Revised: In linear control theory, a structured system is a system whose entries of system matrices are either fixed zero or indeterminate .
Edit intent: clarity
Original:  This paper introduces a new controllability notion, termed partial strong structural controllability ( PSSC), which naturally extends SSC and bridges the gap between structural controllability and SSC. Dividing the indeterminate entries into two categories, generic entries and unspecified entries, a system is PSSC, if for almost all values of the generic entries in the parameter space except for a set of measure zero, and any nonzero (complex)
Revised:  This paper introduces a new controllability notion, termed partial strong structural controllability ( SSC) and bridges the gap between structural controllability and SSC. Dividing the indeterminate entries into two categories, generic entries and unspecified entries, a system is PSSC, if for almost all values of the generic entries in the parameter space except for a set of measure zero, and any nonzero (complex)
Edit intent: coherence
Original:  Finally, we show the established results can induce a new graph-theoretic criterion for SSC in maximum matchings over the system bipartite graph representations.
Revised:  Finally, we show the established results can induce a new maximum matching based criterion for SSC in maximum matchings over the system bipartite graph representations.
Edit intent: clarity
Original:  Finally, we show the established results can induce a new graph-theoretic criterion for SSC in maximum matchings over the system bipartite graph representations.
Revised:  Finally, we show the established results can induce a new graph-theoretic criterion for SSC over the system bipartite graph representations.
Edit intent: clarity
Original:  Third, we investigate recent advancements in artificial intelligence (AI)/machine learning (ML) methods in current VHetNets and discuss the core challenges of integrating AI/ML in VHetNets .
Revised:  Third, we investigate recent advancements in artificial intelligence (AI)/machine learning (ML) solutions are discussed. Accordingly, the core challenges of integrating AI/ML in VHetNets .
Edit intent: clarity
Original:  Finally, we discuss potential future research directions for advancing the autonomous and evolving capabilities of VHetNets .
Revised:  Finally, the potential future research directions for advancing the autonomous and evolving capabilities of VHetNets .
Edit intent: coherence
Original:  In this paper, we propose a model, SSI , to improve sequential recommendation consistency with Self-Supervised Imitation.
Revised:  In this paper, we propose a model, SSI , to improve sequential recommendation consistency with Self-Supervised Imitation.
Edit intent: fluency
Original: Solving partially-observable Markov decision processes (POMDPs) is critical when applying deep reinforcement learning (DRL) to real-world robotics problems, where agents have an incomplete view of the world.
Revised: Solving partially-observable Markov decision processes (POMDPs) is critical when applying reinforcement learning to real-world robotics problems, where agents have an incomplete view of the world.
Edit intent: clarity
Original: Solving partially-observable Markov decision processes (POMDPs) is critical when applying deep reinforcement learning (DRL) to real-world robotics problems, where agents have an incomplete view of the world.
Revised: Solving partially-observable Markov decision processes (POMDPs) is critical when applying deep reinforcement learning (DRL) to real-world problems, where agents have an incomplete view of the world.
Edit intent: clarity
Original:  We present graph convolutional memory (GCM)  for solving POMDPs using deep reinforcement learning.
Revised:  We present graph convolutional memory (GCM) for solving POMDPs using reinforcement learning.
Edit intent: clarity
Original:  We show GCM outperforms long short-term memory (LSTM), gated transformers for reinforcement learning (GTrXL), and differentiable neural computers (DNCs) on control, long-term non-sequential recall, and 3D navigation tasks while using significantly fewer parameters.
Revised:  We show GCM outperforms long short-term memory (LSTM), gated transformers for reinforcement learning (GTrXL), and differentiable neural computers (DNCs) on control, memorization, and navigation tasks while using significantly fewer parameters.
Edit intent: clarity
Original:  Those HVAC systems in modern smart buildings rely on real-time sensor readings, which in practice often suffer from various faults and could also be vulnerable to malicious attacks.
Revised:  These HVAC systems in modern smart buildings rely on real-time sensor readings, which in practice often suffer from various faults and could also be vulnerable to malicious attacks.
Edit intent: fluency
Original:  Those HVAC systems in modern smart buildings rely on real-time sensor readings, which in practice often suffer from various faults and could also be vulnerable to malicious attacks.
Revised:  Those HVAC systems in smart buildings rely on real-time sensor readings, which in practice often suffer from various faults and could also be vulnerable to malicious attacks.
Edit intent: clarity
Original:  Through extensive numerical experiments, we demonstrate that the proposed fault-tolerant HVAC control framework can significantly reduce building temperature violations under a variety of sensor fault patterns while maintaining energy efficiency.
Revised:  Through extensive experiments, we demonstrate that the proposed fault-tolerant HVAC control framework can significantly reduce building temperature violations under a variety of sensor fault patterns while maintaining energy efficiency.
Edit intent: clarity
Original: After a grasp has been planned, if the object orientation changes, the initial grasp may but not always have to be modified to accommodate the orientation change.
Revised: After a grasp has been planned, if the object orientation changes, the initial grasp may not have to be modified to accommodate the orientation change.
Edit intent: clarity
Original:  Prior studies have primarily focused on processing text for classification and small-scale databases .
Revised:  Prior studies have only focused on processing text for classification and small-scale databases .
Edit intent: clarity
Original:  This paper describes a novel multimodal deep learning architecture, called TechDoc, for technical document classification, which utilizes both natural language and descriptive images to train hierarchical classifiers .
Revised:  This paper presents a novel multimodal deep learning architecture, called TechDoc, for technical document classification, which utilizes both natural language and descriptive images to train hierarchical classifiers .
Edit intent: clarity
Original:  This paper describes a novel multimodal deep learning architecture, called TechDoc, for technical document classification, which utilizes both natural language and descriptive images to train hierarchical classifiers .
Revised:  This paper describes a novel multimodal deep learning architecture, TechDoc, for technical document classification, which utilizes both natural language and descriptive images to train hierarchical classifiers .
Edit intent: clarity
Original: Implicitly filtered Large Eddy Simulation (LES) is by nature numerically under-resolved.
Revised: Implicitly filtered large-eddy simulation (LES) is by nature numerically under-resolved.
Edit intent: fluency