wanyu/IteraTeR_v2 huggingface dataset:
Original: Resting on the graph-based representation of multi-agent architectures, this work presents a novel general regularized distributed solution for state estimation in networked systems.
Revised: This work presents a novel general regularized distributed solution for state estimation in networked systems.
Edit intent: clarity
Original: Resting on the graph-based representation of multi-agent architectures, this work presents a novel general regularized distributed solution for state estimation in networked systems.
Revised: Resting on the graph-based representation of multi-agent architectures, this work presents a novel general regularized distributed solution for the state estimation problem in networked systems.
Edit intent: clarity
Original:  Adopting a multivariate least-squares approach, the designed solution exploits the set of the available inter-agent relative measurements and resorts on the introduction of some regularization parameters, whose selection is shown to affect the estimation procedure convergence performance.
Revised:  Adopting a multivariate least-squares approach, the designed solution exploits the set of the available inter-sensor relative measurements and resorts on the introduction of some regularization parameters, whose selection is shown to affect the estimation procedure convergence performance.
Edit intent: clarity
Original:  Adopting a multivariate least-squares approach, the designed solution exploits the set of the available inter-agent relative measurements and resorts on the introduction of some regularization parameters, whose selection is shown to affect the estimation procedure convergence performance.
Revised:  Adopting a multivariate least-squares approach, the designed solution exploits the set of the available inter-agent relative measurements and leverages a general regularization framework, whose parameter selection is shown to affect the estimation procedure convergence performance.
Edit intent: clarity
Original:  Adopting a multivariate least-squares approach, the designed solution exploits the set of the available inter-agent relative measurements and resorts on the introduction of some regularization parameters, whose selection is shown to affect the estimation procedure convergence performance.
Revised:  Adopting a multivariate least-squares approach, the designed solution exploits the set of the available inter-agent relative measurements and resorts on the introduction of some regularization parameters, whose selection is shown to control the estimation procedure convergence performance.
Edit intent: clarity
Original:  As confirmed by the numerical results, this new general framework allows both the extension of the regularization approach investigated in literature and the convergence rate optimization of the distributed estimation in correspondence to any (undirected) graph modeling the given multi-agent system .
Revised:  As confirmed by the numerical results, this new estimation scheme allows (i) the extension of the regularization approach investigated in literature and the convergence rate optimization of the distributed estimation in correspondence to any (undirected) graph modeling the given multi-agent system .
Edit intent: clarity
Original:  As confirmed by the numerical results, this new general framework allows both the extension of the regularization approach investigated in literature and the convergence rate optimization of the distributed estimation in correspondence to any (undirected) graph modeling the given multi-agent system .
Revised:  As confirmed by the numerical results, this new general framework allows both the extension of other approaches investigated in the literature and (ii) the convergence optimization in correspondence to any (undirected) graph modeling the given multi-agent system .
Edit intent: clarity
Original:  As confirmed by the numerical results, this new general framework allows both the extension of the regularization approach investigated in literature and the convergence rate optimization of the distributed estimation in correspondence to any (undirected) graph modeling the given multi-agent system .
Revised:  As confirmed by the numerical results, this new general framework allows both the extension of the regularization approach investigated in literature and the convergence rate optimization of the distributed estimation in correspondence to any (undirected) graph modeling the given sensor network .
Edit intent: clarity
Original:  We show that those IFE methods can only achieve suboptimal convergence rates (i.e., O(h^{1/2 if the tangential derivative of the exact solution and the jump of the coefficient are not zero on the interface.
Revised:  We show that those IFE methods without penalties are not guaranteed to converge optimally if the tangential derivative of the exact solution and the jump of the coefficient are not zero on the interface.
Edit intent: clarity
Original:  Furthermore,  we derive the optimal approximation capabilities of both the Crouzeix-Raviart and the rotated-Q_1 IFE spaces for interface problems with variable coefficients via a unified approach different from multipoint Taylor expansions .
Revised:  Furthermore, different from multipoint Taylor expansions, we derive the optimal approximation capabilities of both the Crouzeix-Raviart and the rotated-Q_1 IFE spaces for interface problems with variable coefficients via a unified approach different from multipoint Taylor expansions .
Edit intent: coherence
Original:  Furthermore,  we derive the optimal approximation capabilities of both the Crouzeix-Raviart and the rotated-Q_1 IFE spaces for interface problems with variable coefficients via a unified approach different from multipoint Taylor expansions .
Revised:  Furthermore, we derive the optimal approximation capabilities of both the Crouzeix-Raviart and the rotated-Q_1 IFE spaces via a unified approach different from multipoint Taylor expansions .
Edit intent: clarity
Original:  In this work, we present the first end-to-end learning approach for directly predicting dense panoptic segmentation maps in the BEV, given a single monocular image in the frontal view (FV).
Revised:  In this work, we present the first BEV panoptic segmentation approach for directly predicting dense panoptic segmentation maps in the BEV, given a single monocular image in the frontal view (FV).
Edit intent: clarity
Original:  When the circuit elements are limited to a subset of SU(4) --- or equivalently, when the Hamiltonian may be mapped onto free fermionic models --- several identities exist that combine and simplify the circuit.
Revised:  When the circuit elements are limited to a subset of SU(4) -- or equivalently, when the Hamiltonian may be mapped onto free fermionic models --- several identities exist that combine and simplify the circuit.
Edit intent: fluency
Original:  When the circuit elements are limited to a subset of SU(4) --- or equivalently, when the Hamiltonian may be mapped onto free fermionic models --- several identities exist that combine and simplify the circuit.
Revised:  When the circuit elements are limited to a subset of SU(4) --- or equivalently, when the Hamiltonian may be mapped onto free fermionic models -- several identities exist that combine and simplify the circuit.
Edit intent: fluency
Original:  Based on matrix analysis, we show that Hamiltonian simulation of certain spin models known as free fermions can be performed in a quantum circuit with a depth that is independent of simulation time and that grows linearly in the number of spins.
Revised:  Based on matrix analysis, we show that Hamiltonian simulation of certain spin Hamiltonians known as free fermions can be performed in a quantum circuit with a depth that is independent of simulation time and that grows linearly in the number of spins.
Edit intent: clarity
Original:  Based on matrix analysis, we show that Hamiltonian simulation of certain spin models known as free fermions can be performed in a quantum circuit with a depth that is independent of simulation time and that grows linearly in the number of spins.
Revised:  Based on matrix analysis, we show that Hamiltonian simulation of certain spin models known as free fermions . The depth of the compressed circuits is independent of simulation time and that grows linearly in the number of spins.
Edit intent: clarity
Original:  Based on matrix analysis, we show that Hamiltonian simulation of certain spin models known as free fermions can be performed in a quantum circuit with a depth that is independent of simulation time and that grows linearly in the number of spins.
Revised:  Based on matrix analysis, we show that Hamiltonian simulation of certain spin models known as free fermions can be performed in a quantum circuit with a depth that is independent of simulation time and grows linearly with the number of spins.
Edit intent: clarity
Original:  Our analysis shows how to efficiently and accurately compress these circuits with a numerical algorithm that scales cubically in the number of spins . Numerical experiments show that our circuit synthesis algorithm easily scales up to O (10^3) spins.
Revised:  Our analysis shows how to efficiently and accurately compress these circuits with a numerical algorithm that scales cubically in the number of spins enabling circuit synthesis beyond O (10^3) spins.
Edit intent: clarity
Original:  In particular, VITALITY promotes serendipitous discovery of relevant literature using transformer language models, allowing users to find semantically similar papers in a word embedding space given (1) a list of input paper(s) or (2) a working abstract.
Revised:  In particular, VitaLITy promotes serendipitous discovery of relevant literature using transformer language models, allowing users to find semantically similar papers in a word embedding space given (1) a list of input paper(s) or (2) a working abstract.
Edit intent: fluency
Original:  VITALITY visualizes this document-level embedding space in an interactive 2-D scatterplot using dimension reduction.
Revised:  VitaLITy visualizes this document-level embedding space in an interactive 2-D scatterplot using dimension reduction.
Edit intent: clarity
Original:  VITALITY also summarizes meta information about the document corpus or search query, including keywords and co-authors, and allows users to save and export papers for use in a literature review.
Revised:  VitaLITy also summarizes meta information about the document corpus or search query, including keywords and co-authors, and allows users to save and export papers for use in a literature review.
Edit intent: clarity
Original:  We present qualitative findings from an evaluation of VITALITY , suggesting it can be a promising complementary technique for conducting academic literature reviews.
Revised:  We present qualitative findings from an evaluation of VitaLITy , suggesting it can be a promising complementary technique for conducting academic literature reviews.
Edit intent: clarity
Original: In object re-identification (ReID), the development of deep learning techniques often involves model update and deployment.
Revised: In object re-identification (ReID), the development of deep learning techniques often involves model updates and deployment.
Edit intent: fluency
Original:  Therefore, backward-compatible representation is proposed to enable the "new" features compatible with "old" ' features , free from the re-extracting process.
Revised:  Therefore, backward-compatible representation is proposed to enable "new" features compatible with "old" ' features , free from the re-extracting process.
Edit intent: fluency
Original:  Therefore, backward-compatible representation is proposed to enable the "new" features compatible with "old" ' features , free from the re-extracting process.
Revised:  Therefore, backward-compatible representation is proposed to enable the "new" features to be compared with "old" ' features , free from the re-extracting process.
Edit intent: clarity
Original:  The existing backward-compatible methods  simply conduct constraints in the embedding space or discriminative space and ignore the intra-class variance of the old embeddings, resulting in a risk of damaging the discriminability of new embeddings .
Revised:  The existing backward-compatible methods simply conduct constraints in the embedding space or discriminative space and ignore the intra-class variance of the old embeddings, resulting in a risk of damaging the discriminative capability of new features .
Edit intent: clarity
Original:  Besides, we also propose a scheme to filter the old embeddings with low credibility, which can further improve the compatibility robustness.
Revised:  Besides, we also propose a scheme to filter the old embeddings with low credibility, further improving the compatibility robustness.
Edit intent: coherence
Original:  The various phenomena found by topic X-ray may provide a new paradigm for explaining and understanding the evolution of human science and technology.
Revised:  The various phenomena found by scientific x-ray may provide a new paradigm for explaining and understanding the evolution of human science and technology.
Edit intent: clarity
Original:  The various phenomena found by topic X-ray may provide a new paradigm for explaining and understanding the evolution of human science and technology.
Revised:  The various phenomena found by topic X-ray may provide a new paradigm for explaining and understanding the evolution of science and technology.
Edit intent: clarity
Original:  This paper proposes a hardware-based disaggregated memory device , Clio, that  manages disaggregated memory at the device side with novel software-hardware co-designs . Clio includes a  hardware-based virtual memory system, a customized network stack , and a framework for computation offloading.
Revised:  This paper proposes a hardware-based disaggregated memory system , Clio, that manages disaggregated memory at the device side with novel software-hardware co-designs . Clio includes a hardware-based virtual memory system, a customized network stack , and a framework for computation offloading.
Edit intent: clarity
Original:  This paper proposes a hardware-based disaggregated memory device , Clio, that  manages disaggregated memory at the device side with novel software-hardware co-designs . Clio includes a  hardware-based virtual memory system, a customized network stack , and a framework for computation offloading.
Revised:  This paper proposes a hardware-based disaggregated memory device , Clio, that manages disaggregated memory at the memory node . Clio includes a hardware-based virtual memory system, a customized network stack , and a framework for computation offloading.
Edit intent: clarity
Original:  This paper proposes a hardware-based disaggregated memory device , Clio, that  manages disaggregated memory at the device side with novel software-hardware co-designs . Clio includes a  hardware-based virtual memory system, a customized network stack , and a framework for computation offloading.
Revised:  This paper proposes a hardware-based disaggregated memory device , Clio, that manages disaggregated memory at the device side with novel software-hardware co-designs . Clio includes a hardware-based virtual memory system, a customized network system , and a framework for computation offloading.
Edit intent: clarity
Original:  Therefore, advanced service robots require superior tactile intelligence to guarantee naturalness and safety when making physical contact with human subjects .
Revised:  Therefore, advanced service robots require superior tactile intelligence to guarantee naturalness and safety when making physical contact with a human .
Edit intent: clarity
Original:  Tactile intelligence is the capability to percept and recognize tactile informationfrom touch behaviors, in which understanding the physical meaning of touching actions is crucial.
Revised:  Tactile intelligence is an essential capability of perception and recognition from tactile information, based on the learning from a large amount of tactile data and the understanding of the physical meaning of touching actions is crucial.
Edit intent: clarity
Original:  The dataset contains 12 types of 24,000 touch actions from 50 subjects.
Revised:  The dataset consists of information from 50 subjects who performed a total of 24,000 touch actions from 50 subjects.
Edit intent: clarity
Original:  The dataset details are described, the data are preliminarily analyzed, and the validity of the dataset is tested through a convolutional neural network LeNet-5 which classifying different types of touch actions.
Revised:  The dataset details are described, the data are preliminarily analyzed, and the validity of the collected information is tested through a convolutional neural network LeNet-5 which classifying different types of touch actions.
Edit intent: clarity
Original:  The dataset details are described, the data are preliminarily analyzed, and the validity of the dataset is tested through a convolutional neural network LeNet-5 which classifying different types of touch actions.
Revised:  The dataset details are described, the data are preliminarily analyzed, and the validity of the dataset is tested through a convolutional neural network LeNet-5 classifying different types of touch actions.
Edit intent: coherence
Original:  We believe that the TacAct dataset would be  beneficial for the community  to understand the touch intention under various circumstances and to develop learning-based intelligent algorithms for different applications .
Revised:  We believe that the TacAct dataset would be beneficial for the community to understand the tactile profile under various circumstances and to develop learning-based intelligent algorithms for different applications .
Edit intent: clarity
Original:  We believe that the TacAct dataset would be  beneficial for the community  to understand the touch intention under various circumstances and to develop learning-based intelligent algorithms for different applications .
Revised:  We believe that the TacAct dataset would be beneficial for the community to understand the touch intention under various circumstances .
Edit intent: clarity
Original: To mitigate the inspector's workload and improve the quality of the product, computer vision-based anomaly detection (AD) techniques are gradually deployed in real-world industrial scenarios.
Revised: Anomaly detection plays a pivotal role in numerous real-world industrial scenarios.
Edit intent: clarity
Original:  Nevertheless, there are two disturbing factors that need researchers and deployers to prioritize: (i) the simplistic prior latent distribution inducing limited expressive capability;
Revised:  Nevertheless, there are two disturbing factors that need us to prioritize: (i) the simplistic prior latent distribution inducing limited expressive capability;
Edit intent: clarity
Original:  In particular, a patch-wise variational inference model coupled with solving the jigsaw puzzle is designed, which is a simple yet effective way to increase the expressiveness and complexity of the latent manifold.
Revised:  In particular, a patch-wise variational inference model coupled with solving the jigsaw puzzle is designed, which is a simple yet effective way to increase the expressiveness of the latent manifold.
Edit intent: clarity
Original:  This alleviates the blurry reconstruction problem .
Revised:  This makes using the model on high-dimensional practical data possible .
Edit intent: clarity
Original:  In addition, the Hilbert-Schmidt Independence Criterion (HSIC) bottleneck is introduced to constrain the over-regularization representation . Comprehensive experiments, conducted on the MVTec AD dataset, demonstrate the superior performance of our propo
Revised:  In addition, the Hilbert-Schmidt Independence Criterion (HSIC) bottleneck is introduced to constrain the over-regularization representation . Comprehensive experiments, conducted on the MVTec AD dataset, demonstrate the superior performance of our proposed method.
Edit intent: clarity
Original: In this paper, a CNN-based structure for time-frequency localization of audio signal information in the ASR acoustic model is proposed for Persian speech recognition.
Revised: In this paper, a CNN-based structure for time-frequency localization of information in the ASR acoustic model is proposed for Persian speech recognition.
Edit intent: clarity
Original:  Research has shown that the receptive fields' time-frequency flexibility in some mammals' auditory neurons system improves recognition performance.
Revised:  Research has shown that the receptive fields' spectrotemporal plasticity of some neurons in mammals' primary auditory cortex and midbrain makes localization facilities that improve recognition performance.
Edit intent: clarity
Original:  Biosystems have inspired many artificial systems because of their high efficiency and performance, so time-frequency localization has been used extensively to improve system performance.
Revised:  As biosystems have inspired many artificial systems because of their high efficiency and performance, so time-frequency localization has been used extensively to improve system performance.
Edit intent: coherence
Original:  Biosystems have inspired many artificial systems because of their high efficiency and performance, so time-frequency localization has been used extensively to improve system performance.
Revised:  Biosystems have inspired many man-maid systems because of their high efficiency and performance, so time-frequency localization has been used extensively to improve system performance.
Edit intent: clarity
Original:  In the last few years, much work has been done to localize time-frequency information in ASR systems, which has used the spatial  immutability properties of methods such as TDNN, CNN  and LSTM-RNN. However, most of these models have large parameter volumes and are challenging to train.
Revised:  In the last few years, much work has been done to localize time-frequency information in ASR systems, which has used the spatial or temporal immutability properties of methods such as TDNN, CNN and LSTM-RNN. However, most of these models have large parameter volumes and are challenging to train.
Edit intent: clarity
Original:  In the last few years, much work has been done to localize time-frequency information in ASR systems, which has used the spatial  immutability properties of methods such as TDNN, CNN  and LSTM-RNN. However, most of these models have large parameter volumes and are challenging to train.
Revised:  In the last few years, much work has been done to localize time-frequency information in ASR systems, which has used the spatial immutability properties of methods such as TDNN, CNN , and LSTM-RNN. However, most of these models have large parameter volumes and are challenging to train.
Edit intent: fluency
Original:  In the structure we have designed, called Time-Frequency Convolutional Maxout Neural Network (TFCMNN) , two parallel blocks consisting of 1D-CMNN each have weight sharing in one dimension, are applied simultaneously but independently to the feature vectors.
Revised:  We have presented a structure called Time-Frequency Convolutional Maxout Neural Network (TFCMNN) , two parallel blocks consisting of 1D-CMNN each have weight sharing in one dimension, are applied simultaneously but independently to the feature vectors.
Edit intent: clarity
Original:  In the structure we have designed, called Time-Frequency Convolutional Maxout Neural Network (TFCMNN) , two parallel blocks consisting of 1D-CMNN each have weight sharing in one dimension, are applied simultaneously but independently to the feature vectors.
Revised:  In the structure we have designed, called Time-Frequency Convolutional Maxout Neural Network (TFCMNN) in which two parallel time-domain and frequency-domain 1D-CMNN each have weight sharing in one dimension, are applied simultaneously but independently to the feature vectors.
Edit intent: clarity