wanyu/IteraTeR_v2 huggingface dataset:
Original:  The preliminary results show that an effective compute precision of 6-bits is achievable owing to the inherent compensation effect . A 4-bit 200x200 VMM utilizing the proposed approach exhibits a significantly high energy efficiency of ~1.5 POps/J and a throughput of 2.5 TOps/s while considering the contribution due to the input/output (I/O) circuitry.
Revised:  The preliminary results show that an effective compute precision of 6-bits is achievable owing to an inherent compensation effect . A 4-bit 200x200 VMM utilizing the proposed approach exhibits a significantly high energy efficiency of ~1.5 POps/J and a throughput of 2.5 TOps/s while considering the contribution due to the input/output (I/O) circuitry.
Edit intent: fluency
Original:  The preliminary results show that an effective compute precision of 6-bits is achievable owing to the inherent compensation effect . A 4-bit 200x200 VMM utilizing the proposed approach exhibits a significantly high energy efficiency of ~1.5 POps/J and a throughput of 2.5 TOps/s while considering the contribution due to the input/output (I/O) circuitry.
Revised:  The preliminary results show that an effective compute precision of 6-bits is achievable owing to the inherent compensation effect . A 4-bit 200x200 VMM utilizing the proposed approach exhibits a significantly high energy efficiency of ~1.5 POps/J and a throughput of 2.5 TOps/s including the contribution from the input/output (I/O) circuitry.
Edit intent: clarity
Original:  We analyze about two hundred naturally occurring networks with distinct dynamical origins, and }  find that a large number of these follow the finite size scaling hypothesis without any self-tuning.
Revised:  We analyze about two hundred naturally occurring networks with distinct dynamical origins, and } find that a large number of the networks studied follow a finite size scaling hypothesis without any self-tuning.
Edit intent: clarity
Original:  Notably this is the case of biological protein interaction networks, technological computer and hyperlink networks and informational citation and lexical networks . Marked deviations appear in other examples , especially infrastructure and transportation networks, but also social , affiliation and annotation networks.
Revised:  This is the case of biological protein interaction networks, technological computer and hyperlink networks and informational citation and lexical networks . Marked deviations appear in other examples , especially infrastructure and transportation networks, but also social , affiliation and annotation networks.
Edit intent: coherence
Original:  Notably this is the case of biological protein interaction networks, technological computer and hyperlink networks and informational citation and lexical networks . Marked deviations appear in other examples , especially infrastructure and transportation networks, but also social , affiliation and annotation networks.
Revised:  Notably this is the case of biological protein interaction networks, technological computer and hyperlink networks , and informational networks in general . Marked deviations appear in other examples , especially infrastructure and transportation networks, but also social , affiliation and annotation networks.
Edit intent: clarity
Original:  Notably this is the case of biological protein interaction networks, technological computer and hyperlink networks and informational citation and lexical networks . Marked deviations appear in other examples , especially infrastructure and transportation networks, but also social , affiliation and annotation networks.
Revised:  Notably this is the case of biological protein interaction networks, technological computer and hyperlink networks and informational citation and lexical networks . Marked deviations appear in other cases , especially infrastructure and transportation networks, but also social , affiliation and annotation networks.
Edit intent: clarity
Original:  Notably this is the case of biological protein interaction networks, technological computer and hyperlink networks and informational citation and lexical networks . Marked deviations appear in other examples , especially infrastructure and transportation networks, but also social , affiliation and annotation networks.
Revised:  Notably this is the case of biological protein interaction networks, technological computer and hyperlink networks and informational citation and lexical networks . Marked deviations appear in other examples , especially infrastructure and transportation but also social , affiliation and annotation networks.
Edit intent: fluency
Original:  We show that the 2D product logic Diff x Diff is non-finitely axiomatisable, but can be axiomatised by infinitely many Sahlqvist axioms.
Revised:  We show that the two-dimensional product logic Diff x Diff is non-finitely axiomatisable, but can be axiomatised by infinitely many Sahlqvist axioms.
Edit intent: fluency
Original: We present COBS, a compact bit-sliced signature index, which is a cross-over between an inverted index and Bloom filters.
Revised: We present COBS, a COmpact Bit-sliced Signature index, which is a cross-over between an inverted index and Bloom filters.
Edit intent: fluency
Original:  Query results may contain a number of false positives which decreases exponentially with the query length and the false positive rate of the index determined at construction time .
Revised:  Query results may contain a number of false positives which decreases exponentially with the query length .
Edit intent: clarity
Original:  We compare COBS to seven other index software packages on 100 000 microbial DNA samples.
Revised:  We compare COBS to seven other index software packages on 100000 microbial DNA samples.
Edit intent: fluency
Original:  COBS' compact but simple data structure outperforms the other indexes in construction time and query performance with Mantis by Pandey et al. on second place.
Revised:  COBS' compact but simple data structure outperforms the other indexes in construction time and query performance with Mantis by Pandey et al. in second place.
Edit intent: coherence
Original:  However, different from Mantis and other previous work, COBS does not need the complete index in RAM and is thus designed to scale to larger document sets.
Revised:  However, unlike Mantis and other previous work, COBS does not need the complete index in RAM and is thus designed to scale to larger document sets.
Edit intent: coherence
Original: This work proposes an improved reversible data hiding scheme in encrypted images using parametric binary tree labeling(IPBTL-RDHEI), which takes advantage of the spatial correlation in the entire original image  not in small image blocks to reserve room for embedding databefore image encryption, then the original image is encrypted with a secret key and parametric binary tree labeling is used to label image pixels in two different categories.
Revised: This work proposes an improved reversible data hiding scheme in encrypted images using parametric binary tree labeling(IPBTL-RDHEI), which takes advantage of the spatial correlation in the entire original image but not in small image blocks to reserve room for embedding databefore image encryption, then the original image is encrypted with a secret key and parametric binary tree labeling is used to label image pixels in two different categories.
Edit intent: fluency
Original: This work proposes an improved reversible data hiding scheme in encrypted images using parametric binary tree labeling(IPBTL-RDHEI), which takes advantage of the spatial correlation in the entire original image  not in small image blocks to reserve room for embedding databefore image encryption, then the original image is encrypted with a secret key and parametric binary tree labeling is used to label image pixels in two different categories.
Revised: This work proposes an improved reversible data hiding scheme in encrypted images using parametric binary tree labeling(IPBTL-RDHEI), which takes advantage of the spatial correlation in the entire original image not in small image blocks to reserve room for hiding data. Then the original image is encrypted with a secret key and parametric binary tree labeling is used to label image pixels in two different categories.
Edit intent: clarity
Original: This work proposes an improved reversible data hiding scheme in encrypted images using parametric binary tree labeling(IPBTL-RDHEI), which takes advantage of the spatial correlation in the entire original image  not in small image blocks to reserve room for embedding databefore image encryption, then the original image is encrypted with a secret key and parametric binary tree labeling is used to label image pixels in two different categories.
Revised: This work proposes an improved reversible data hiding scheme in encrypted images using parametric binary tree labeling(IPBTL-RDHEI), which takes advantage of the spatial correlation in the entire original image not in small image blocks to reserve room for embedding databefore image encryption, then the original image is encrypted with an encryption key and the parametric binary tree labeling is used to label image pixels in two different categories.
Edit intent: clarity
Original: This work proposes an improved reversible data hiding scheme in encrypted images using parametric binary tree labeling(IPBTL-RDHEI), which takes advantage of the spatial correlation in the entire original image  not in small image blocks to reserve room for embedding databefore image encryption, then the original image is encrypted with a secret key and parametric binary tree labeling is used to label image pixels in two different categories.
Revised: This work proposes an improved reversible data hiding scheme in encrypted images using parametric binary tree labeling(IPBTL-RDHEI), which takes advantage of the spatial correlation in the entire original image not in small image blocks to reserve room for embedding databefore image encryption, then the original image is encrypted with a secret key and parametric binary tree is used to label image pixels in two different categories.
Edit intent: fluency
Original: This work proposes an improved reversible data hiding scheme in encrypted images using parametric binary tree labeling(IPBTL-RDHEI), which takes advantage of the spatial correlation in the entire original image  not in small image blocks to reserve room for embedding databefore image encryption, then the original image is encrypted with a secret key and parametric binary tree labeling is used to label image pixels in two different categories.
Revised: This work proposes an improved reversible data hiding scheme in encrypted images using parametric binary tree labeling(IPBTL-RDHEI), which takes advantage of the spatial correlation in the entire original image not in small image blocks to reserve room for embedding databefore image encryption, then the original image is encrypted with a secret key and parametric binary tree labeling is used to label encrypted pixels into two different categories.
Edit intent: fluency
Original:  Due to the reversibility of IPBTL-RDHEI, the original content of the image and the secret information can be restored and extracted losslessly and separately.
Revised:  Due to the reversibility of IPBTL-RDHEI, the original plaintext image and the secret information can be restored and extracted losslessly and separately.
Edit intent: clarity
Original:  \kappa + 2{3m\kappa}} {3m\kappa}} ) where the value of \alpha is depending on the type of constraints, e.g., \alpha=1 for matroid constraint, \kappa is the degree of independence, e.g., \kappa=1 for independent items, and m is the number of items +\kappa{18m^2}}-\kappa+2{3m\kappa}) is a valid upper bound on the adaptivity gap, i.e., the ratio of the values of best adaptive policy and best non-adaptive policy is bounded by \alpha(1-e^{-\kappa{2}+\kappa{18m^2}}-\kappa+2{3m\kappa}) } .
Revised:  \kappa + 2{3m\kappa}} {3m\kappa}} ) where the value of \alpha is depending on the type of constraints, e.g., \alpha=1 for matroid constraint, \kappa is the degree of independence, e.g., \kappa=1 for independent items, and m is the number of items . Since our policy is non-adaptive, \alpha(1-e^{-\kappa{2+\kappa{18m^2}}-\kappa+2{3m\kappa}) is a valid upper bound on the adaptivity gap, i.e., the ratio of the values of best adaptive policy and best non-adaptive policy is bounded by \alpha(1-e^{-\kappa{2}+\kappa{18m^2}}-\kappa+2{3m\kappa}) } .
Edit intent: coherence
Original: In this paper, we study the stochastic submodular maximization problem with dependent items subject to a variety of packing constraints such as matroid and knapsack constraints.
Revised: In this paper, we study the stochastic submodular maximization problem with dependent items subject to packing constraints such as matroid and knapsack constraints.
Edit intent: clarity
Original:  Since our policy is non-adaptive, \alpha(1-e^{-\kappa{2+\kappa{18m^2}}-\kappa+2{3m\kappa}) is a valid upper bound on }  the adaptivity gap, i.e., the ratio of the values of best adaptive policy and best non-adaptive policy is bounded by \alpha(1-e^{-\kappa{2+\kappa{18m^2}}-\kappa+2{3m\kappa}) }  .
Revised:  +\kappa{18m^2}}-\kappa+2{3m\kappa}) is a valid upper bound on } the adaptivity gap, i.e., the ratio of the values of best adaptive policy and best non-adaptive policy is bounded by \alpha(1-e^{-\kappa{2+\kappa{18m^2}}-\kappa+2{3m\kappa}) } .
Edit intent: coherence
Original:  Since our policy is non-adaptive, \alpha(1-e^{-\kappa{2+\kappa{18m^2}}-\kappa+2{3m\kappa}) is a valid upper bound on }  the adaptivity gap, i.e., the ratio of the values of best adaptive policy and best non-adaptive policy is bounded by \alpha(1-e^{-\kappa{2+\kappa{18m^2}}-\kappa+2{3m\kappa}) }  .
Revised:  Since our policy is non-adaptive, \alpha(1-e^{-\kappa{2+\kappa{18m^2}}-\kappa+2{3m\kappa}) is a valid upper bound on } the adaptivity gap, i.e., the ratio of the values of best adaptive policy and best non-adaptive policy +\kappa{18m^2}}-\kappa+2{3m\kappa}) } .
Edit intent: clarity
Original: We introduce an embedded--hybridized discontinuous Galerkin ( EDG--HDG ) method for the coupled Stokes--Darcy system.
Revised: We introduce an embedded-hybridized discontinuous Galerkin ( EDG--HDG ) method for the coupled Stokes--Darcy system.
Edit intent: fluency
Original: We introduce an embedded--hybridized discontinuous Galerkin ( EDG--HDG ) method for the coupled Stokes--Darcy system.
Revised: We introduce an embedded--hybridized discontinuous Galerkin ( EDG-HDG ) method for the coupled Stokes--Darcy system.
Edit intent: fluency
Original: We introduce an embedded--hybridized discontinuous Galerkin ( EDG--HDG ) method for the coupled Stokes--Darcy system.
Revised: We introduce an embedded--hybridized discontinuous Galerkin ( EDG--HDG ) method for the coupled Stokes-Darcy system.
Edit intent: fluency
Original:  This EDG--HDG method is a pointwise mass-conserving discretization resulting in a divergence-conforming velocity field on the whole domain.
Revised:  This EDG-HDG method is a pointwise mass-conserving discretization resulting in a divergence-conforming velocity field on the whole domain.
Edit intent: fluency
Original:  In the proposed scheme, coupling between the Stokes and Darcy domains is achieved naturally through the EDG--HDG facet variables.
Revised:  In the proposed scheme, coupling between the Stokes and Darcy domains is achieved naturally through the EDG-HDG facet variables.
Edit intent: fluency
Original: To address the lack of comparative evaluation of Human-in-the-Loop Topic Modeling (HLTM) systems, we implement and evaluate three contrasting HLTM  approaches using simulation experiments.
Revised: To address the lack of comparative evaluation of Human-in-the-Loop Topic Modeling (HLTM) systems, we implement and evaluate three contrasting HLTM modeling approaches using simulation experiments.
Edit intent: clarity
Original:  These approaches are based on previously proposed frameworks, including constraints and informed prior-based methods.
Revised:  These approaches extend previously proposed frameworks, including constraints and informed prior-based methods.
Edit intent: clarity
Original:  User control is desired , so we propose a control metric to measure whether refinement operations are applied as usersexpect .
Revised:  Users should have a sense of control in HLTM systems , so we propose a control metric to measure whether refinement operations are applied as usersexpect .
Edit intent: clarity
Original:  User control is desired , so we propose a control metric to measure whether refinement operations are applied as usersexpect .
Revised:  User control is desired , so we propose a control metric to measure whether refinement operations ' results match users' expectations .
Edit intent: clarity
Original: Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive cancers with an extremely poor prognosis.
Revised: Pancreatic Ductal Adenocarcinoma (PDAC) is one of the most aggressive cancers with an extremely poor prognosis.
Edit intent: fluency
Original:  Deep learning architectures, such as convolutional neural networks (CNNs) , have been shown to outperform traditional techniques in computer vision tasks , such as object detection .
Revised:  Deep learning architectures, such as convolutional neural networks (CNNs) have been shown to outperform traditional techniques in computer vision tasks , such as object detection .
Edit intent: fluency
Original:  Deep learning architectures, such as convolutional neural networks (CNNs) , have been shown to outperform traditional techniques in computer vision tasks , such as object detection .
Revised:  Deep learning architectures, such as convolutional neural networks (CNNs) , have been shown to outperform these feature-based models in computer vision tasks , such as object detection .
Edit intent: clarity
Original:  Deep learning architectures, such as convolutional neural networks (CNNs) , have been shown to outperform traditional techniques in computer vision tasks , such as object detection .
Revised:  Deep learning architectures, such as convolutional neural networks (CNNs) , have been shown to outperform traditional techniques in computer vision tasks .
Edit intent: clarity
Original:  However, they require large sample sizes for training which limits their development .
Revised:  However, training a CNN from scratch needs a large sample size which is not feasible in most medical imaging studies .
Edit intent: coherence
Original:  As an alternative solution, CNN-based transfer learning has shown the potential for achieving reasonable performance using datasets with small sample sizes .
Revised:  As an alternative solution, CNN-based transfer learning has shown potential for achieving reasonable performance using datasets with small sample sizes .
Edit intent: fluency
Original:  As an alternative solution, CNN-based transfer learning has shown the potential for achieving reasonable performance using datasets with small sample sizes .
Revised:  As an alternative solution, CNN-based transfer learning has shown the potential for achieving reasonable performance using small datasets .
Edit intent: clarity
Original:  In this work, we developed  a CNN-based transfer learning approach for prognostication in PDAC patients for overall survival .
Revised:  In this work, we developed a CNN-based transfer learning approach for prognostication of PDAC patients for overall survival .
Edit intent: fluency
Original:  A transfer learning approach may fill the gap between radiomics and deep learning analytics for cancer prognosis and improve performance beyond what CNNs can achieve using small datasets  .
Revised:  A transfer learning approach may fill the gap between radiomics and deep learning analytics for cancer prognosis and improve performance beyond what CNNs can achieve using small datasets in medical imaging .
Edit intent: clarity
Original:  We therefore draw inspiration from  meta-learning and functional programming to propose a class of Embedded Meta-Learning (EML) architectures that represent both data and tasks in a shared latent space . EML architectures are applicable to any type of machine learning task, including supervised learning and reinforcement learning.
Revised:  We therefore draw inspiration from meta-learning to propose a class of Embedded Meta-Learning (EML) architectures that represent both data and tasks in a shared latent space . EML architectures are applicable to any type of machine learning task, including supervised learning and reinforcement learning.
Edit intent: clarity
Original:  We demonstrate the flexibility of these architectures by showing that they can perform meta-mappings, i.e. that they can exhibit zero-shot remapping of behavior to adapt to new tasks.
Revised:  We demonstrate the utility of this perspective by exhibiting zero-shot remapping of behavior to adapt to new tasks.
Edit intent: clarity
Original:  We suggest that the key to achieving these challenges is representing the task being performed along with the computations used to perform it .
Revised:  The key to achieving these challenges is representing the task being performed along with the computations used to perform it .
Edit intent: clarity
Original:  We suggest that the key to achieving these challenges is representing the task being performed along with the computations used to perform it .
Revised:  We suggest that the key to achieving these challenges is representing the task being performed in such a way that this task representation is itself transformable .
Edit intent: clarity
Original:  HoMM approaches can be applied to any type of machine learning task , including supervised learning and reinforcement learning .
Revised:  HoMM approaches can be applied to any type of machine learning task .
Edit intent: clarity
Original: We propose and analyze a novel accelerated primal-dual coordinate descent framework for computing the optimal transport (OT) distance between two discrete probability distributions  .
Revised: We provide theoretical complexity analysis for new algorithms to compute the optimal transport (OT) distance between two discrete probability distributions .
Edit intent: clarity
Original:  First, we introduce the accelerated primal-dual randomized coordinate descent \emph{ (APDRCD) algorithm for computing OT.
Revised:  First, we introduce the \emph{ (APDRCD) algorithm for computing OT.
Edit intent: clarity
Original:  Then we provide a complexity upper bound %DIFDELCMD < \mathcal{O}%%% \bigOtil (n^{5/2}{\varepsilon}) for the APDRCD method for approximating OT distance, where n stands for the number of atoms of these probability measures and \varepsilon > 0 is the desired accuracy.
Revised:  Then we provide a complexity upper bound %DIFDELCMD < \mathcal{O}%%% \bigOtil (n^{5/2}{\varepsilon}) where n stands for the number of atoms of these probability measures and \varepsilon > 0 is the desired accuracy.
Edit intent: clarity
Original:  This upper bound matches the best known complexities of  adaptive primal-dual accelerated gradient descent (APDAGD)
Revised:  This complexity bound matches the best known complexities of adaptive primal-dual accelerated gradient descent (APDAGD)
Edit intent: clarity
Original:  and  adaptive primal-dual accelerate mirror descent (APDAMD)
Revised:  and the adaptive primal-dual accelerate mirror descent (APDAMD)
Edit intent: fluency
Original:  and  adaptive primal-dual accelerate mirror descent (APDAMD)
Revised:  and adaptive primal-dual accelerated mirror descent (APDAMD)
Edit intent: fluency