wanyu/IteraTeR_v2 huggingface dataset:
Original:  We introduce the notion of "read-awareness" to log-structured merge trees, which allows hot objects to be pinned to faster storage , achieving better tiering and hot-cold separation of objects . Compared to the standard use of RocksDB on flash in datacenters today, PrismDB's average throughput on heterogeneous storage is 2.3 \times faster and its  tail latency is more than an order of magnitude better, using hardware than is half the cost .
Revised:  Compared to the standard use of RocksDB on flash in datacenters today, PrismDB's average throughput on heterogeneous storage is 2.3 \times faster and its tail latency is more than an order of magnitude better, using hardware than is half the cost .
Edit intent: coherence
Original:  We introduce the notion of "read-awareness" to log-structured merge trees, which allows hot objects to be pinned to faster storage , achieving better tiering and hot-cold separation of objects . Compared to the standard use of RocksDB on flash in datacenters today, PrismDB's average throughput on heterogeneous storage is 2.3 \times faster and its  tail latency is more than an order of magnitude better, using hardware than is half the cost .
Revised:  We introduce the notion of "read-awareness" to log-structured merge trees, which allows hot objects to be pinned to faster storage , achieving better tiering and hot-cold separation of objects . Compared to the standard use of RocksDB on flash in datacenters today, PrismDB's average throughput on heterogeneous storage is 2.3 \times faster and its read tail latency is more than an order of magnitude better, using hardware than is half the cost .
Edit intent: fluency
Original:  We introduce the notion of "read-awareness" to log-structured merge trees, which allows hot objects to be pinned to faster storage , achieving better tiering and hot-cold separation of objects . Compared to the standard use of RocksDB on flash in datacenters today, PrismDB's average throughput on heterogeneous storage is 2.3 \times faster and its  tail latency is more than an order of magnitude better, using hardware than is half the cost .
Revised:  We introduce the notion of "read-awareness" to log-structured merge trees, which allows hot objects to be pinned to faster storage , achieving better tiering and hot-cold separation of objects . Compared to the standard use of RocksDB on flash in datacenters today, PrismDB's average throughput on heterogeneous storage is 2.3 \times faster and its tail latency is 2\times better, using hardware than is half the cost .
Edit intent: clarity
Original:  We introduce the notion of "read-awareness" to log-structured merge trees, which allows hot objects to be pinned to faster storage , achieving better tiering and hot-cold separation of objects . Compared to the standard use of RocksDB on flash in datacenters today, PrismDB's average throughput on heterogeneous storage is 2.3 \times faster and its  tail latency is more than an order of magnitude better, using hardware than is half the cost .
Revised:  We introduce the notion of "read-awareness" to log-structured merge trees, which allows hot objects to be pinned to faster storage , achieving better tiering and hot-cold separation of objects . Compared to the standard use of RocksDB on flash in datacenters today, PrismDB's average throughput on heterogeneous storage is 2.3 \times faster and its tail latency is more than an order of magnitude better, using equivalently-priced hardware .
Edit intent: clarity
Original:  We evaluate our method using the face and the car latent space of StyleGAN, and demonstrate fine-grained disentangled edits along various attributes on both real photographs and StyleGAN generated images ) . For example, for faces, we vary camera pose, illumination variation, expression, facial hair, gender, and age .
Revised:  We evaluate our method using the face and the car latent space of StyleGAN, and demonstrate fine-grained disentangled edits along various attributes on both real photographs and StyleGAN generated images . For example, for faces, we vary camera pose, illumination variation, expression, facial hair, gender, and age .
Edit intent: fluency
Original: We propose Nephelai , a Compressive Sensing-based Cloud Radio Access Network (C-RAN), to reduce the uplink bit rate of the physical layer (PHY) between the gateways and the cloud server for multi-channel LPWANs. Recent research shows that single-channel LPWANs suffer from scalability issues.
Revised: We propose Nephalai , a Compressive Sensing-based Cloud Radio Access Network (C-RAN), to reduce the uplink bit rate of the physical layer (PHY) between the gateways and the cloud server for multi-channel LPWANs. Recent research shows that single-channel LPWANs suffer from scalability issues.
Edit intent: fluency
Original: 7\% PHY samples can be reduced by Nephelai when SF = 9 and SNR is high without degradation in the packet reception rate (PRR).
Revised: 7\% PHY samples can be reduced by Nephalai when SF = 9 and SNR is high without degradation in the packet reception rate (PRR).
Edit intent: fluency
Original: In this work, we develop and study a discontinuous Galerkin (DG) method to approximate the solution of 1D nonlinear wave equations.
Revised: We develop and study a discontinuous Galerkin (DG) method to approximate the solution of 1D nonlinear wave equations.
Edit intent: clarity
Original: In this work, we develop and study a discontinuous Galerkin (DG) method to approximate the solution of 1D nonlinear wave equations.
Revised: In this work, we develop and study a discontinuous Galerkin (DG) method to approximate the solution of one-dimensional nonlinear wave equations.
Edit intent: fluency
Original:  We show that the numerical scheme is consistent, stable and convergent if a nonuniform time mesh is considered.
Revised:  We show that the numerical scheme is stable if a nonuniform time mesh is considered.
Edit intent: clarity
Original:  We also investigate the blow-up phenomena and we prove that  the numerical blow-up time converges toward the theoretical one.
Revised:  We also investigate the blow-up phenomena and we prove that the numerical blow-up time tends toward the theoretical one.
Edit intent: clarity
Original:  We propose a generalized graph approach to emotion recognition that can take any time-varying (dynamic ) data modality as input.
Revised:  We propose a generalized approach to emotion recognition that can take any time-varying (dynamic ) data modality as input.
Edit intent: clarity
Original:  To this end, we present the \emph{Learnable Graph Inception Network (L-GrIN) that jointly learns to recognize emotion and to identify the underlying graph structure in  data.
Revised:  To this end, we present the \emph{Learnable Graph Inception Network (L-GrIN) that jointly learns to recognize emotion and to identify the underlying graph structure in data.
Edit intent: fluency
Original:  We evaluate the proposed architecture on four benchmark emotion recognition databases spanning three different modalities (video, audio, mocap ), where each database captures one of the following emotional cues: facial expressions, speech and body gestures.
Revised:  We evaluate the proposed architecture on four benchmark emotion recognition databases spanning three different modalities (video, audio, motion capture ), where each database captures one of the following emotional cues: facial expressions, speech and body gestures.
Edit intent: clarity
Original: Two agents' decision-making problems can be modeled as the gamewith two players , and a Nash equilibrium is the basic solution conception representing good play in games . Counterfactual regret minimization (CFR) is a popular method to solve Nash equilibrium strategy in  two-player zero-sum games with imperfect information.
Revised: In general, two-agent decision-making problems can be modeled as the gamewith two players , and a Nash equilibrium is the basic solution conception representing good play in games . Counterfactual regret minimization (CFR) is a popular method to solve Nash equilibrium strategy in two-player zero-sum games with imperfect information.
Edit intent: coherence
Original: Two agents' decision-making problems can be modeled as the gamewith two players , and a Nash equilibrium is the basic solution conception representing good play in games . Counterfactual regret minimization (CFR) is a popular method to solve Nash equilibrium strategy in  two-player zero-sum games with imperfect information.
Revised: Two agents' decision-making problems can be modeled as a two-player game , and a Nash equilibrium is the basic solution conception representing good play in games . Counterfactual regret minimization (CFR) is a popular method to solve Nash equilibrium strategy in two-player zero-sum games with imperfect information.
Edit intent: clarity
Original: Two agents' decision-making problems can be modeled as the gamewith two players , and a Nash equilibrium is the basic solution conception representing good play in games . Counterfactual regret minimization (CFR) is a popular method to solve Nash equilibrium strategy in  two-player zero-sum games with imperfect information.
Revised: Two agents' decision-making problems can be modeled as the gamewith two players , and a typical solution is to find a Nash equilibrium in such game . Counterfactual regret minimization (CFR) is a popular method to solve Nash equilibrium strategy in two-player zero-sum games with imperfect information.
Edit intent: clarity
Original: Two agents' decision-making problems can be modeled as the gamewith two players , and a Nash equilibrium is the basic solution conception representing good play in games . Counterfactual regret minimization (CFR) is a popular method to solve Nash equilibrium strategy in  two-player zero-sum games with imperfect information.
Revised: Two agents' decision-making problems can be modeled as the gamewith two players , and a Nash equilibrium is the basic solution conception representing good play in games . Counterfactual regret minimization (CFR) is a well-known method to find a Nash equilibrium strategy in two-player zero-sum games with imperfect information.
Edit intent: clarity
Original: Two agents' decision-making problems can be modeled as the gamewith two players , and a Nash equilibrium is the basic solution conception representing good play in games . Counterfactual regret minimization (CFR) is a popular method to solve Nash equilibrium strategy in  two-player zero-sum games with imperfect information.
Revised: Two agents' decision-making problems can be modeled as the gamewith two players , and a Nash equilibrium is the basic solution conception representing good play in games . Counterfactual regret minimization (CFR) is a popular method to solve Nash equilibrium strategy in a two-player zero-sum games with imperfect information.
Edit intent: fluency
Original: Two agents' decision-making problems can be modeled as the gamewith two players , and a Nash equilibrium is the basic solution conception representing good play in games . Counterfactual regret minimization (CFR) is a popular method to solve Nash equilibrium strategy in  two-player zero-sum games with imperfect information.
Revised: Two agents' decision-making problems can be modeled as the gamewith two players , and a Nash equilibrium is the basic solution conception representing good play in games . Counterfactual regret minimization (CFR) is a popular method to solve Nash equilibrium strategy in two-player zero-sum game with imperfect information.
Edit intent: fluency
Original:  In this paper , we propose a novel CFR based method , exponential counterfactual regret minimization , which also can be called as ECFR.
Revised:  In this paper , we propose a novel CFR-based method named exponential counterfactual regret minimization , which also can be called as ECFR.
Edit intent: fluency
Original:  Finally, we show that , ECFR can converge faster compared with the prior state-of-the-art CFR based methodsin the experiment .
Revised:  Finally, we show that , ECFR can converge faster compared with the prior state-of-the-art CFR-based methods .
Edit intent: clarity
Original:  the stationary probability of a node is computed as a ratio of the cash distributed by this a node to the total cash distributed by all nodes together.
Revised:  the stationary probability of a node is computed as a ratio of the cash distributed by this node to the total cash distributed by all nodes together.
Edit intent: fluency
Original: In this paper, we describe  VISIONE, a video search system that allows users to search for videos using textual keywords, occurrence of objects and their spatial relationships, occurrence of colors and their spatial relationships, and image similarity.
Revised: In this paper, we describe in details VISIONE, a video search system that allows users to search for videos using textual keywords, occurrence of objects and their spatial relationships, occurrence of colors and their spatial relationships, and image similarity.
Edit intent: clarity
Original:  We report an extensive analysis of the system retrieval performance, using the query logs generated during the Video Browser Showdown (VBS) 2019 competition.
Revised:  In addition, we report an extensive analysis of the system retrieval performance, using the query logs generated during the Video Browser Showdown (VBS) 2019 competition.
Edit intent: coherence
Original: This paper introduces RL Brush , a level-editing tool for tile-based games designed for mixed-initiative co-creation.
Revised: This paper introduces RL Brush , a level-editing tool for tile-based games designed for mixed-initiative co-creation.
Edit intent: fluency
Original:  Here, we apply RL Brush \textit{ to designing levels for the classic puzzle game Sokoban .
Revised:  Here, we apply RL Brush \textit{ to designing levels for the classic puzzle game Sokoban .
Edit intent: fluency
Original:  We put the tool online and tested it with 39 different sessions.
Revised:  We put the tool online and tested it in 39 different sessions.
Edit intent: fluency
Original:  Here, we apply \textit{RL Brush to designing levels for the classic puzzle game Sokoban .
Revised:  Here, we apply \textit{RL Brush to designing levels for the classic puzzle game Sokoban .
Edit intent: fluency
Original: This paper derives predictive reduced-order models for rocket engine combustion dynamics via  a scientific machine learning approach , based on Operator Inference, that blends data-driven learning with physics-based modeling.
Revised: This paper derives predictive reduced-order models for rocket engine combustion dynamics via Operator Inference, a scientific machine learning approach , based on Operator Inference, that blends data-driven learning with physics-based modeling.
Edit intent: fluency
Original: This paper derives predictive reduced-order models for rocket engine combustion dynamics via  a scientific machine learning approach , based on Operator Inference, that blends data-driven learning with physics-based modeling.
Revised: This paper derives predictive reduced-order models for rocket engine combustion dynamics via a scientific machine learning approach that blends data-driven learning with physics-based modeling.
Edit intent: coherence
Original:  However, in most applications, the success of MOT is severely hindered by a lack of sub-exponential time algorithms.
Revised:  However, in most applications, the success of MOT is severely limited by a lack of sub-exponential time algorithms.
Edit intent: clarity
Original:  We identify two such properties: decomposability of the cost into either (i) local interactions and simple global interactions;
Revised:  We identify two such properties: decomposability of the cost into either (i) local and simple global interactions;
Edit intent: fluency
Original: Multimarginal Optimal Transport (MOT) has recently attracted significant interest due to applications in machine learning, statistics, and the sciences.
Revised: Multimarginal Optimal Transport (MOT) has attracted significant interest due to applications in machine learning, statistics, and the sciences.
Edit intent: clarity
Original:  Indeed, in general, MOT requires exponential time in the number of marginals k and their support sizes n.
Revised:  Indeed, MOT in general requires exponential time in the number of marginals k and their support sizes n.
Edit intent: fluency
Original:  This paper develops a general theory about  " structural properties " that make MOT solvable in poly(n,k) time.
Revised:  This paper develops a general theory about what " structural properties " that make MOT solvable in poly(n,k) time.
Edit intent: coherence
Original:  This paper develops a general theory about  " structural properties " that make MOT solvable in poly(n,k) time.
Revised:  This paper develops a general theory about " structure " that make MOT solvable in poly(n,k) time.
Edit intent: clarity
Original:  This paper develops a general theory about  " structural properties " that make MOT solvable in poly(n,k) time.
Revised:  This paper develops a general theory about " structural properties " makes MOT solvable in poly(n,k) time.
Edit intent: coherence
Original:  Simulations on fine lattices suffer from critical slowdown, the rapid growth of autocorrelations in the Markov chain with decreasing lattice spacing .
Revised:  Simulations on fine lattices suffer from critical slowdown, the rapid growth of autocorrelations in the Markov chain .
Edit intent: clarity
Original:  This paper discusses hierarchical sampling methods to tame this growth in autocorrelations.
Revised:  This paper discusses hierarchical sampling methods to tame the growth in autocorrelations.
Edit intent: fluency
Original:  For an observable with lattice errors of order \alpha and an integrated autocorrelation time that grows like \mathrm{int}\propto a^{-z}, multilevel Monte Carlo (MLMC) can reduce the cost from O(\text{stat}^{-2}\text{disc}^{-(1+z)/\alpha}) to O(\text{stat}^{-2}\vert\log \text{disc} \vert^2+\text{disc}^{-1/\alpha}) .
Revised:  For observables with lattice errors of order \alpha and an integrated autocorrelation time that grows like \mathrm{int}\propto a^{-z}, multilevel Monte Carlo (MLMC) can reduce the cost from O(\text{stat}^{-2}\text{disc}^{-(1+z)/\alpha}) to O(\text{stat}^{-2}\vert\log \text{disc} \vert^2+\text{disc}^{-1/\alpha}) .
Edit intent: fluency
Original:  For an observable with lattice errors of order \alpha and an integrated autocorrelation time that grows like \mathrm{int}\propto a^{-z}, multilevel Monte Carlo (MLMC) can reduce the cost from O(\text{stat}^{-2}\text{disc}^{-(1+z)/\alpha}) to O(\text{stat}^{-2}\vert\log \text{disc} \vert^2+\text{disc}^{-1/\alpha}) .
Revised:  For an observable with lattice errors of order \alpha and integrated autocorrelation times that grow like \mathrm{int}\propto a^{-z}, multilevel Monte Carlo (MLMC) can reduce the cost from O(\text{stat}^{-2}\text{disc}^{-(1+z)/\alpha}) to O(\text{stat}^{-2}\vert\log \text{disc} \vert^2+\text{disc}^{-1/\alpha}) .
Edit intent: fluency
Original:  For an observable with lattice errors of order \alpha and an integrated autocorrelation time that grows like \mathrm{int}\propto a^{-z}, multilevel Monte Carlo (MLMC) can reduce the cost from O(\text{stat}^{-2}\text{disc}^{-(1+z)/\alpha}) to O(\text{stat}^{-2}\vert\log \text{disc} \vert^2+\text{disc}^{-1/\alpha}) .
Revised:  For an observable with lattice errors of order \alpha and an integrated autocorrelation time that grows like \mathrm{int}\propto a^{-z}, multilevel Monte Carlo (MLMC) reduces the cost from O(\text{stat}^{-2}\text{disc}^{-(1+z)/\alpha}) to O(\text{stat}^{-2}\vert\log \text{disc} \vert^2+\text{disc}^{-1/\alpha}) .
Edit intent: clarity
Original:  The efficiency of the approach is demonstrated on two model systems, including a topological oscillator that is badly affected by critical slowdown due to freezing of the topological charge .
Revised:  The efficiency of the approach is demonstrated on two model systems, including a topological oscillator that is badly affected by critical slowdown from topological charge freezing .
Edit intent: clarity
Original:  On fine lattices, the new methods are orders of magnitude faster than standard sampling based on Hybrid Monte Carlo  .
Revised:  On fine lattices, the new methods are orders of magnitude faster than standard Hybrid Monte Carlo .
Edit intent: clarity
Original:  On fine lattices, the new methods are orders of magnitude faster than standard sampling based on Hybrid Monte Carlo  .
Revised:  On fine lattices, the new methods are orders of magnitude faster than standard sampling based on Hybrid Monte Carlo sampling .
Edit intent: clarity
Original:  Our results indicate that while Russia has been a donor country in the late 1990s and early 2000s, it has experienced a relatively symmetric circulation of researchers in more recent years.
Revised:  Our results indicate that while Russia has been a donor country in the late 1990s and early 2000s, it has experienced a relatively balanced circulation of researchers in more recent years.
Edit intent: clarity
Original:   Using subject categories of publications, we quantify the impact of migration on each field of scholarship.
Revised:  Using subject categories of publications, we quantify the impact of migration on each discipline of scholarship.
Edit intent: clarity
Original:  Our analysis shows that Russia has suffered a net loss in almost all disciplines and more so in neuroscience, decision sciences, dentistry , biochemistry, and mathematics.
Revised:  Our analysis shows that Russia has suffered a net loss in most disciplines and more so in neuroscience, decision sciences, dentistry , biochemistry, and mathematics.
Edit intent: clarity
Original:  Our analysis shows that Russia has suffered a net loss in almost all disciplines and more so in neuroscience, decision sciences, dentistry , biochemistry, and mathematics.
Revised:  Our analysis shows that Russia has suffered a net loss in almost all disciplines and more so in neuroscience, decision sciences, mathematics , biochemistry, and mathematics.
Edit intent: clarity
Original:  Methodologically, our new approach of handling big data can be adopted as a framework of analysis for studying scholarly migration in other countries.
Revised:  Methodologically, our novel approach of handling big data can be adopted as a framework of analysis for studying scholarly migration in other countries.
Edit intent: clarity
Original: We study international mobility in academia  with a focus on migration of researchers to and from Russia.
Revised: We study international mobility in academia , with a focus on migration of researchers to and from Russia.
Edit intent: fluency
Original:  Migration of researchers is observed through the changes in their affiliation addresses which alter the mode country of affiliation over different years.
Revised:  Migration of researchers is observed through the changes in their affiliation addresses , which altered their mode countries of affiliation across different years.
Edit intent: fluency
Original:  Only 5.2\\%DIF < of these researchers are internationally mobile, but they account %DIF > of these researchers were internationally mobile,  for a substantial proportion of citations.
Revised:  While only 5.2\\%DIF < of these researchers are internationally mobile, but they account %DIF > of these researchers were internationally mobile, for a substantial proportion of citations.
Edit intent: clarity
Original:  Only 5.2\\%DIF < of these researchers are internationally mobile, but they account %DIF > of these researchers were internationally mobile,  for a substantial proportion of citations.
Revised:  Only 5.2\\%DIF < of these researchers are %DIF > of these researchers were internationally mobile, for a substantial proportion of citations.
Edit intent: coherence
Original:  Only 5.2\\%DIF < of these researchers are internationally mobile, but they account %DIF > of these researchers were internationally mobile,  for a substantial proportion of citations.
Revised:  Only 5.2\\%DIF < of these researchers are internationally mobile, but they account %DIF > of these researchers were internationally mobile, they accounted for a substantial proportion of citations.
Edit intent: coherence