wanyu/IteraTeR_v2 huggingface dataset:
Original:  In VR, like in the real world, users integrate the multimodal sensory information they receive  to create a unified perception of the virtual world.
Revised:  In VR, users integrate multimodal sensory information they receive to create a unified perception of the virtual world.
Edit intent: coherence
Original:  In VR, like in the real world, users integrate the multimodal sensory information they receive  to create a unified perception of the virtual world.
Revised:  In VR, like in the real world, users integrate the multimodal sensory information they receive , to create a unified perception of the virtual world.
Edit intent: fluency
Original:  In this state-of-the-art report, we survey the body of work addressing multimodality in virtual reality, its role and benefits in the final user experience.
Revised:  In this state-of-the-art report, we survey the body of work addressing multimodality in VR, and its role and benefits in the final user experience.
Edit intent: fluency
Original: Developing the collision-free flocking behavior for a dynamic squad of fixed-wing UAVs is still a challenge due to kinematic complexity and environmental uncertainty.
Revised: Developing the flocking behavior for a dynamic squad of fixed-wing UAVs is still a challenge due to kinematic complexity and environmental uncertainty.
Edit intent: clarity
Original:  As a result, the variable-length system state can be encoded into a fixed-length embedding vector, which makes the learned DRL policies independent with the number or the order of followers.
Revised:  As a result, the variable-length system state can be encoded into a fixed-length embedding vector, which makes the learned DRL policy independent with the number or the order of followers.
Edit intent: fluency
Original:  As a result, the variable-length system state can be encoded into a fixed-length embedding vector, which makes the learned DRL policies independent with the number or the order of followers.
Revised:  As a result, the variable-length system state can be encoded into a fixed-length embedding vector, which makes the learned DRL policies independent with the number and the order of followers.
Edit intent: fluency
Original:  Finally, numerical simulation results demonstrate the effectiveness of the proposed method, and the learned policies can be directly transferred to semiphysical simulation without any parameter finetuning.
Revised:  Finally, numerical simulation results demonstrate the effectiveness of the proposed method, and the learned policies can be directly transferred to semi-physical simulation without any parameter finetuning.
Edit intent: fluency
Original:  Our main technical contributions are the following: We first prove an invariance principle for positive spectrahedrons via the well-known Lindeberg method.
Revised:  Our main technical contributions are the following: We first prove an invariance principle for positive spectrahedra via the well-known Lindeberg method.
Edit intent: fluency
Original:  Second, we prove various geometric properties of positive spectrahedrons such as their noise sensitivity , Gaussian surface area and a Littlewood-Offord theorem for positive spectrahedrons . Using these results, we give applications for constructing PRGs for positive spectrahedrons , learning theory, discrepancy sets for positive spectrahedrons (over the Boolean cube) and PRGs for intersections of structured polynomial threshold functions.
Revised:  Second, we prove an upper bound on noise sensitivity and a Littlewood-Offord theorem for positive spectrahedrons . Using these results, we give applications for constructing PRGs for positive spectrahedrons , learning theory, discrepancy sets for positive spectrahedrons (over the Boolean cube) and PRGs for intersections of structured polynomial threshold functions.
Edit intent: clarity
Original:  Second, we prove various geometric properties of positive spectrahedrons such as their noise sensitivity , Gaussian surface area and a Littlewood-Offord theorem for positive spectrahedrons . Using these results, we give applications for constructing PRGs for positive spectrahedrons , learning theory, discrepancy sets for positive spectrahedrons (over the Boolean cube) and PRGs for intersections of structured polynomial threshold functions.
Revised:  Second, we prove various geometric properties of positive spectrahedrons such as their noise sensitivity , Gaussian surface area and a Littlewood-Offord theorem for positive spectrahedra . Using these results, we give applications for constructing PRGs for positive spectrahedrons , learning theory, discrepancy sets for positive spectrahedrons (over the Boolean cube) and PRGs for intersections of structured polynomial threshold functions.
Edit intent: fluency
Original:  Second, we prove various geometric properties of positive spectrahedrons such as their noise sensitivity , Gaussian surface area and a Littlewood-Offord theorem for positive spectrahedrons . Using these results, we give applications for constructing PRGs for positive spectrahedrons , learning theory, discrepancy sets for positive spectrahedrons (over the Boolean cube) and PRGs for intersections of structured polynomial threshold functions.
Revised:  Second, we prove various geometric properties of positive spectrahedrons such as their noise sensitivity , Gaussian surface area and a Littlewood-Offord theorem for positive spectrahedrons . Using these results, we give applications for constructing PRGs for positive spectrahedra , learning theory, discrepancy sets for positive spectrahedrons (over the Boolean cube) and PRGs for intersections of structured polynomial threshold functions.
Edit intent: fluency
Original:  Second, we prove various geometric properties of positive spectrahedrons such as their noise sensitivity , Gaussian surface area and a Littlewood-Offord theorem for positive spectrahedrons . Using these results, we give applications for constructing PRGs for positive spectrahedrons , learning theory, discrepancy sets for positive spectrahedrons (over the Boolean cube) and PRGs for intersections of structured polynomial threshold functions.
Revised:  Second, we prove various geometric properties of positive spectrahedrons such as their noise sensitivity , Gaussian surface area and a Littlewood-Offord theorem for positive spectrahedrons . Using these results, we give applications for constructing PRGs for positive spectrahedrons , learning theory, discrepancy sets for positive spectrahedra (over the Boolean cube) and PRGs for intersections of structured polynomial threshold functions.
Edit intent: fluency
Original: This paper introduces a new  interior point method algorithm that solves semidefinite programming (SDP) with variable size n \times n and m constraints in the (current) matrix multiplication time m ^{\omega when m \geq }  \Omega(n^2) .
Revised: This paper introduces a new interior point method analysis for semidefinite programming (SDP) with variable size n \times n and m constraints in the (current) matrix multiplication time m ^{\omega when m \geq } \Omega(n^2) .
Edit intent: clarity
Original: This paper introduces a new  interior point method algorithm that solves semidefinite programming (SDP) with variable size n \times n and m constraints in the (current) matrix multiplication time m ^{\omega when m \geq }  \Omega(n^2) .
Revised: This paper introduces a new interior point method algorithm that solves semidefinite programming (SDP) with variable size n \times n and m constraints when m \geq } \Omega(n^2) .
Edit intent: coherence
Original:  Our algorithm is based on two novel techniques: \bullet Maintaining the inverse of a Kronecker product using lazy updates . \bullet A general amortization scheme for positive semidefinite matrices.
Revised:  Our algorithm is based on two novel techniques: \bullet Maintaining the inverse of a Kronecker product using lazy updates , a general amortization scheme for positive semidefinite matrices.
Edit intent: fluency
Original:  Under these circumstances, it is critical to understand  discussions surrounding these claims on Twitter, a major platform where the claims disseminate .
Revised:  Under these circumstances, it is critical to understand the discussions surrounding these claims on Twitter, a major platform where the claims disseminate .
Edit intent: fluency
Original:  Under these circumstances, it is critical to understand  discussions surrounding these claims on Twitter, a major platform where the claims disseminate .
Revised:  Under these circumstances, it is critical to understand discussions surrounding these claims on Twitter, a major platform where the claims were disseminated .
Edit intent: clarity
Original:  To this end, we collected and release the VoterFraud2020 dataset, a multi-modal dataset with 7.6M tweets and 25.
Revised:  To this end, we collected and released the VoterFraud2020 dataset, a multi-modal dataset with 7.6M tweets and 25.
Edit intent: fluency
Original:  We also include in the dataset aggregated information for all external links and YouTube videos that appear in the tweets.
Revised:  The dataset also includes aggregate data for all external links and YouTube videos that appear in the tweets.
Edit intent: clarity
Original:  To prove this, we work directly at the level of Benjamini-Schramm limits, and exploit the entropic characterization of the Liouville property on stationary random graphs to show that non-negative curvature and spectral expansion are incompatible "at infinity".
Revised:  To establish this, we work directly at the level of Benjamini-Schramm limits, and exploit the entropic characterization of the Liouville property on stationary random graphs to show that non-negative curvature and spectral expansion are incompatible "at infinity".
Edit intent: clarity
Original:  However, DL suffers from a universal phenomenon: instability, despite universal approximating properties that often guarantee the existence of stable neural networks (NNs).
Revised:  However, current DL methods typically suffer from instability, even when universal approximation properties guarantee the existence of stable neural networks (NNs).
Edit intent: clarity
Original:  These results provide basic foundations for Smale's 18th problem and imply a potentially vast, and crucial, classification theory describing conditions under which (stable) NNs with a given accuracy can be computed by an algorithm.
Revised:  These results imply a classification theory describing conditions under which (stable) NNs with a given accuracy can be computed by an algorithm.
Edit intent: clarity
Original:  We begin this theory by initiating a unified theory for compressed sensing and DL, leading to sufficient conditions for the existence of algorithms that compute stable NNs in inverse problems.
Revised:  We begin this theory by establishing sufficient conditions for the existence of algorithms that compute stable NNs in inverse problems.
Edit intent: coherence
Original:  We introduce Fast Iterative REstarted NETworks (FIRENETs), which we  prove and numerically verify are stable.
Revised:  We introduce Fast Iterative REstarted NETworks (FIRENETs), which we both prove and numerically verify are stable.
Edit intent: clarity
Original:  As a corollary of our results, we also obtain a slight improvement on the weakest assumption on a measurement matrix with i.i.d. rows sufficient for uniform recovery in standard compressed sensing, improving on results by Mendelson and Lecu\'e  and Dirksen, Lecu\'e and Rauhut.
Revised:  As a corollary of our results, we also obtain a slight improvement on the weakest assumption on a measurement matrix with i.i.d. rows sufficient for uniform recovery in standard compressed sensing, improving on results by Lecu\'e and Dirksen, Lecu\'e and Rauhut.
Edit intent: clarity
Original: In this paper , we derive a posteriori error estimates for mixed-dimensional elliptic equations exhibiting a hierarchical structure.
Revised: This paper focuses on deriving a posteriori error estimates for mixed-dimensional elliptic equations exhibiting a hierarchical structure.
Edit intent: clarity
Original:  Exploiting the exterior calculus perspective of such equations, we introduce mixed-dimensional variables and operators, which, together with careful construction of the functional spaces, allow us to recast the set of partial differential equations as a regular linear elliptic problem structure-wise.
Revised:  After careful construction of the functional spaces, allow us to recast the set of partial differential equations as a regular linear elliptic problem structure-wise.
Edit intent: coherence
Original:  Our estimators are tested using three different families of locally-mass conservative methods on synthetic problems and verification benchmarks of flow in fractured porous media.
Revised:  Our estimators are tested with four numerical methods on matching and nonmatching grids for both synthetic and benchmarks of flow in fractured porous media.
Edit intent: clarity
Original:  The numerical results support our theoretical findings while showcasing satisfactory effectivity indices .
Revised:  The numerical results support our theoretical findings with satisfactory results .
Edit intent: clarity
Original:  For each of the reviewed approaches, the "Issues to consider" section draws attention to important points that should be considered in future LEO SatNets location management.
Revised:  The "Issues to consider" section draws attention to important points that should be considered in future LEO SatNets location management.
Edit intent: clarity
Original:  For each of the reviewed approaches, the "Issues to consider" section draws attention to important points that should be considered in future LEO SatNets location management.
Revised:  For each of the reviewed approaches, the "Issues to consider" section draws attention to critical points related to each of the reviewed approaches that should be considered in future LEO SatNets location management.
Edit intent: clarity
Original:  We demonstrate that Gaius achieves the same level of accuracy but is up to one order-of magnitude faster.
Revised:  We demonstrate that Gaius achieves the same level of accuracy but is up to one order of magnitude faster.
Edit intent: fluency
Original:  We also show that Gaius can scale training to datasets an order of magnitude beyond a single machine's GPU and CPU memory capacity, enabling training of configurations with more than a billion edges and 550GB of total parameters on a single AWS P3.2xLarge instance .
Revised:  We also show that Gaius can scale training to datasets an order of magnitude beyond a single machine's GPU and CPU memory capacity, enabling training of configurations with more than a billion edges and 550 GB of total parameters on a single AWS P3.2xLarge instance .
Edit intent: fluency
Original:  With sufficiently high functional capacity (or expressive power), we show that it is especially good for solving forward and inverse physics problems involving partial differential equations (PDEs).
Revised:  With sufficiently high functional capacity (or expressive power), we show that it is especially powerful for solving forward and inverse physics problems involving partial differential equations (PDEs).
Edit intent: clarity
Original:  These provide some of the first natural problems in these classes.
Revised:  This provides the first natural problems in these classes.
Edit intent: clarity
Original: This paper proposes an online end-to-end diarization that can handle overlapping speech and flexible numbers of speakers.
Revised: We propose a streaming diarization method based on an end-to-end diarization that can handle overlapping speech and flexible numbers of speakers.
Edit intent: clarity
Original:  This papersolves both problems by applying a modified extension of the speaker-tracing buffer method that deals with variable numbers of speakers . Experiments on CALLHOME and DIHARD II datasets show that the proposed online method achieves comparable performance to the offline EEND method . Compared with the state-of-the-art online method based on a fully supervised approach (UIS-RNN), the proposed method shows better performance on the DIHARD II dataset .
Revised:  This papersolves both problems by applying a modified extension of the speaker-tracing buffer method that deals with variable numbers of speakers . Experiments on CALLHOME and DIHARD II datasets show that the proposed method achieves comparable performance to the offline EEND method . Compared with the state-of-the-art online method based on a fully supervised approach (UIS-RNN), the proposed method shows better performance on the DIHARD II dataset .
Edit intent: fluency
Original: Sepsis is the leading cause of mortality in the the ICU, responsible for 6\% of all hospitalizations and 35\% of all in-hospital deaths in USA.
Revised: Sepsis is the leading cause of mortality in the ICU, responsible for 6\% of all hospitalizations and 35\% of all in-hospital deaths in USA.
Edit intent: fluency
Original:  This framework can be tweaked easily, to reflect a clinician's own confidence of of the framework, and can be easily modified to factor in human expert opinion, whenever it's accessible.
Revised:  This framework can be tweaked easily, to reflect a clinician's own confidence of the framework, and can be easily modified to factor in human expert opinion, whenever it's accessible.
Edit intent: fluency
Original:  We first infer patient-specific, dynamic cardiovascular states using a novel physiology-driven recurrent neural network trained in an unsupervised manner.
Revised:  Our method handles partial observability by leveraging known cardiovascular physiology, introducing a novel physiology-driven recurrent neural network trained in an unsupervised manner.
Edit intent: clarity
Original: This paper discusses the value-at-risk (VaR) concept and assesses the financial adequacy of the price probability determined by frequency of trades at price p.
Revised: This paper discusses the value-at-risk (VaR) based on the price probability determined by frequency of trades at price p.
Edit intent: clarity
Original: This paper discusses the value-at-risk (VaR) concept and assesses the financial adequacy of the price probability determined by frequency of trades at price p.
Revised: This paper discusses the value-at-risk (VaR) concept and assesses the financial adequacy of the price probability determined by frequencies of trades at price p.
Edit intent: fluency
Original:  This extension is deemed to be beneficial in scenarios like research evaluation, science history modelling , and information retrieval.
Revised:  This extension is deemed to be beneficial in scenarios like research evaluation, science history modeling , and information retrieval.
Edit intent: fluency
Original:  We adopt a series of metrics for measuring the unfolding of backward citations of a focus paper, tracing back to its knowledge ancestors generation by generation.
Revised:  We adopt a series of metrics for measuring the unfolding of backward citations of a focal paper, tracing back to its knowledge ancestors generation by generation.
Edit intent: fluency
Original:  Citations more than one generation away are found to be still relevant to the focus paper, from either a forward or backward perspective .
Revised:  Citations more than one generation away are still relevant to the focus paper, from either a forward or backward perspective .
Edit intent: clarity
Original:  Citations more than one generation away are found to be still relevant to the focus paper, from either a forward or backward perspective .
Revised:  Citations more than one generation away are found to be still relevant to the focal paper, from either a forward or backward perspective .
Edit intent: fluency
Original:  Yet , backward citation generations are generally smaller in the size of networks but higher in topic relevance to the paper of interest.
Revised:  Yet , backward citation generations are higher in topic relevance to the paper of interest.
Edit intent: coherence
Original:  This is implicational for recommending citations in tasks of searching related literature but further research is needed regarding this question .
Revised:  Furthermore, the backward citation generations shed lights for literature recommendation, science evaluation, and sociology of science studies .
Edit intent: coherence
Original:  In this study, we introduce a class of network models that have a tiny memory footprint in terms of their computational graphs.
Revised:  In this study, we introduce a class of network models that have a small memory footprint in terms of their computational graphs.
Edit intent: fluency
Original:  Furthermore, the trade-off between accuracy and latency of these so-called iterative neural networks is improved by adding multiple intermediate outputs both during training and inference.
Revised:  Furthermore, the trade-off between accuracy and latency of these so-called iterative neural networks is improved by adding multiple intermediate outputs during both training and inference.
Edit intent: fluency
Original: Running neural network (NN ) on microcontroller unites (MCU ) is becoming increasingly important, but is very difficult due to the tiny SRAM size of MCU. Prior work proposes many algorithm-level techniques to reduce NN memory footprints, but all at the cost of sacrificing accuracy and generality, which disqualifies MCUs for many important use cases.
Revised: Running neural networks (NNs ) on microcontroller unites (MCU ) is becoming increasingly important, but is very difficult due to the tiny SRAM size of MCU. Prior work proposes many algorithm-level techniques to reduce NN memory footprints, but all at the cost of sacrificing accuracy and generality, which disqualifies MCUs for many important use cases.
Edit intent: clarity
Original: Running neural network (NN ) on microcontroller unites (MCU ) is becoming increasingly important, but is very difficult due to the tiny SRAM size of MCU. Prior work proposes many algorithm-level techniques to reduce NN memory footprints, but all at the cost of sacrificing accuracy and generality, which disqualifies MCUs for many important use cases.
Revised: Running neural network (NN ) on microcontroller units (MCUs ) is becoming increasingly important, but is very difficult due to the tiny SRAM size of MCU. Prior work proposes many algorithm-level techniques to reduce NN memory footprints, but all at the cost of sacrificing accuracy and generality, which disqualifies MCUs for many important use cases.
Edit intent: fluency
Original: The QAnon conspiracy theory claims that a cabal of (literally) bloodthirsty politicians and media personalities are engaged in a war to destroy society.
Revised: The QAnon conspiracy theory claims that a cabal of (literally) blood-thirsty politicians and media personalities are engaged in a war to destroy society.
Edit intent: fluency
Original:  By interpreting cryptic "drops" of information from an anonymous insider calling themselves Q, adherents of the conspiracy theory believe that they are being led by Donald Trump in an active fight against this cabal.
Revised:  By interpreting cryptic "drops" of information from an anonymous insider calling themself Q, adherents of the conspiracy theory believe that they are being led by Donald Trump in an active fight against this cabal.
Edit intent: fluency
Original:  By interpreting cryptic "drops" of information from an anonymous insider calling themselves Q, adherents of the conspiracy theory believe that they are being led by Donald Trump in an active fight against this cabal.
Revised:  By interpreting cryptic "drops" of information from an anonymous insider calling themselves Q, adherents of the conspiracy theory believe that Donald Trump is leading them in an active fight against this cabal.
Edit intent: clarity
Original:  Nevertheless, we still have relatively little understanding of how the theory evolved and was spread on the Web, and the role played in that by multiple platforms.
Revised:  Nevertheless, we still have relatively little understanding of how the theory evolved and spread on the Web, and the role played in that by multiple platforms.
Edit intent: clarity