wanyu/IteraTeR_v2 huggingface dataset:
Original:  We achieve 84.3\% mIoU score on thecityscapes validation set and 54.3\% on the ADE20K valida-tion set.
Revised:  We achieve 84.3\% mIoU score on thecityscapes validation set and 54.3\% on the ADE20K validation set.
Edit intent: fluency
Original:  In addition, providing fine-grained access control for different types of data (e.g., text, image , etc.) may not be feasible for different data storage options.
Revised:  In addition, providing fine-grained access control for different types of data (e.g., text, images , etc.) may not be feasible for different data storage options.
Edit intent: fluency
Original:  To address these challenges, we provide a fine-grained access control framework tailored for distribute data analytics platforms, which is protected against evasion attacks with two distinct layers of defenses .
Revised:  To address these challenges, we provide a fine-grained access control framework tailored for distributed data analytics platforms, which is protected against evasion attacks with two distinct layers of defenses .
Edit intent: fluency
Original:  To address these challenges, we provide a fine-grained access control framework tailored for distribute data analytics platforms, which is protected against evasion attacks with two distinct layers of defenses .
Revised:  To address these challenges, we provide a fine-grained access control framework tailored for distribute data analytics platforms, which is protected against evasion attacks with two distinct layers of defense .
Edit intent: fluency
Original: Transient stability has been extensively studied in the framework of Lyapunov stability .
Revised: Power system transient stability has been extensively studied in the framework of Lyapunov stability .
Edit intent: clarity
Original:  Despite substantial results, conventional transient stability theories suffer from the stringent requirement of prior knowledge of the post-disturbance equilibrium .
Revised:  Despite substantial results, conventional theories suffer from the stringent requirement of prior knowledge of the post-disturbance equilibrium .
Edit intent: clarity
Original:  Despite substantial results, conventional transient stability theories suffer from the stringent requirement of prior knowledge of the post-disturbance equilibrium .
Revised:  Despite substantial results, conventional transient stability theories suffer from the stringent requirement of knowing the post-disturbance equilibrium .
Edit intent: clarity
Original:  This paper aims to bridge such a theory-practice gap by pursuing two objectives .
Revised:  This paper aims to bridge such a theory-practice gap .
Edit intent: clarity
Original:  First, we derive checkable conditions under which converging to augmented synchronization implies convergence of all states to the equilibrium set, and hence lay a theoretical foundation for the empirical wisdom.
Revised:  First, we derive conditions under which converging to augmented synchronization implies convergence of all states to the equilibrium set, and hence lay a theoretical foundation for the empirical wisdom.
Edit intent: clarity
Original:  First, we derive checkable conditions under which converging to augmented synchronization implies convergence of all states to the equilibrium set, and hence lay a theoretical foundation for the empirical wisdom.
Revised:  First, we derive checkable conditions under which the convergence to augmented synchronization implies convergence of all states to the equilibrium set, and hence lay a theoretical foundation for the empirical wisdom.
Edit intent: clarity
Original:  First, we derive checkable conditions under which converging to augmented synchronization implies convergence of all states to the equilibrium set, and hence lay a theoretical foundation for the empirical wisdom.
Revised:  First, we derive checkable conditions under which converging to augmented synchronization implies the convergence to the equilibrium set, and hence lay a theoretical foundation for the empirical wisdom.
Edit intent: clarity
Original:  First, we derive checkable conditions under which converging to augmented synchronization implies convergence of all states to the equilibrium set, and hence lay a theoretical foundation for the empirical wisdom.
Revised:  First, we derive checkable conditions under which converging to augmented synchronization implies convergence of all states to the equilibrium set, laying the first theoretical foundation for the empirical wisdom.
Edit intent: coherence
Original:  Second, we establish several theorems that answer under what conditions the power system can converge to augmented synchronization.
Revised:  Then, we reveal from what initial values the power system can converge to augmented synchronization.
Edit intent: clarity
Original:  Second, we establish several theorems that answer under what conditions the power system can converge to augmented synchronization.
Revised:  Second, we establish several theorems that answer under what conditions the power system can achieve augmented synchronization.
Edit intent: clarity
Original:  These two results enable a new equilibrium-independent analytic for transient stability , which essentially re-defines the nominal motion of power systems as augmented synchronization rather than certain equilibrium.
Revised:  Our results open the possibility of an equilibrium-independent analytic for transient stability , which essentially re-defines the nominal motion of power systems as augmented synchronization rather than certain equilibrium.
Edit intent: clarity
Original:  These two results enable a new equilibrium-independent analytic for transient stability , which essentially re-defines the nominal motion of power systems as augmented synchronization rather than certain equilibrium.
Revised:  These two results enable a new equilibrium-independent power system stability analytic that re-defines the nominal motion of power systems as augmented synchronization rather than certain equilibrium.
Edit intent: clarity
Original:  These two results enable a new equilibrium-independent analytic for transient stability , which essentially re-defines the nominal motion of power systems as augmented synchronization rather than certain equilibrium.
Revised:  These two results enable a new equilibrium-independent analytic for transient stability , which essentially re-defines the nominal motion as augmented synchronization rather than certain equilibrium.
Edit intent: clarity
Original:  Rudimentary single-machine examples and the IEEE 9-bus benchmark system well verify our results and illustrate interesting implications.
Revised:  Rudimentary single-machine examples and the IEEE 9-bus system well verify our results and illustrate interesting implications.
Edit intent: clarity
Original:  Rudimentary single-machine examples and the IEEE 9-bus benchmark system well verify our results and illustrate interesting implications.
Revised:  Rudimentary single-machine examples and the IEEE 9-bus benchmark system well verify our results and illustrate promising implications.
Edit intent: clarity
Original: Given the increase in the use of personal data for training Deep Neural Networks (DNNs) in tasks such as medical imaging and diagnosis, differentially private training of DNNs is surging in importance and there is a huge body of work focusing on providing better privacy-utility trade-off.
Revised: Given the increase in the use of personal data for training Deep Neural Networks (DNNs) in tasks such as medical imaging and diagnosis, differentially private training of DNNs is surging in importance and there is a large body of work focusing on providing better privacy-utility trade-off.
Edit intent: clarity
Original:  We show that our method, which we dub HyperNeRF, outperforms existing methods on both tasks by significant margins . Compared to Nerfies, HyperNeRF reduces average error rates by 8.6 \% for interpolation and 8.8 \% for novel-view synthesis, as measured by LPIPS. 
Revised:  We show that our method, which we dub HyperNeRF, outperforms existing methods on both tasks . Compared to Nerfies, HyperNeRF reduces average error rates by 8.6 \% for interpolation and 8.8 \% for novel-view synthesis, as measured by LPIPS. 
Edit intent: clarity
Original:  The PSUTS fall into two kinds, machine PSUTS and human PSUTS.
Revised:  The PSUTS fall into two kinds, Post-Selection Using Validation Sets (PSUVS) and Post-Selection Using Test Sets (PSUTS). Each kind has two types of post-selectors, machines and humans.
Edit intent: clarity
Original:  The connectionist school received criticisms for its " scruffiness " due to a huge number of network parameters and now the worse machine PSUTS ;
Revised:  The connectionist school received criticisms for its " scruffiness " and now the worse machine PSUTS ;
Edit intent: clarity
Original:  The connectionist school received criticisms for its " scruffiness " due to a huge number of network parameters and now the worse machine PSUTS ;
Revised:  The connectionist school received criticisms for its " scruffiness " due to a huge number of network parameters and now the Post-Selection ;
Edit intent: clarity
Original:  but the seemingly "clean" symbolic school seems more brittle because of a weaker generalization power using human PSUTS.
Revised:  but the seemingly "clean" symbolic school seems more brittle because of its human PSUTS.
Edit intent: clarity
Original:  This paper formally defines what PSUTS is, analyzes why error-backprop methods with random initial weights suffer from severe local minima, why  PSUTS violates well-established research ethics, and how every paper that used PSUTS should have at least transparently reported PSUTS.
Revised:  This paper formally defines what PSUTS is, analyzes why error-backprop from randomly initialized weights suffers from severe local minima, why PSUTS violates well-established research ethics, and how every paper that used PSUTS should have at least transparently reported PSUTS.
Edit intent: clarity
Original:  For improved transparency in future publications , this paper proposes a new standard for performance evaluation of AI , called developmental errors for all networks trained, along with Three Learning Conditions: (1) an incremental learning architecture  , (2) a training experience and (3) a limited amount of computational resources.
Revised:  For improved transparency in future publications , this paper proposes a new AI metrics , called developmental errors for all networks trained, along with Three Learning Conditions: (1) an incremental learning architecture , (2) a training experience and (3) a limited amount of computational resources.
Edit intent: clarity
Original:  For improved transparency in future publications , this paper proposes a new standard for performance evaluation of AI , called developmental errors for all networks trained, along with Three Learning Conditions: (1) an incremental learning architecture  , (2) a training experience and (3) a limited amount of computational resources.
Revised:  For improved transparency in future publications , this paper proposes a new standard for performance evaluation of AI , called developmental errors for all networks trained, under Three Learning Conditions: (1) an incremental learning architecture , (2) a training experience and (3) a limited amount of computational resources.
Edit intent: coherence
Original:  In this paper, we propose a hardware-algorithm co-design of efficient and adaptive lossy compressor for scientific data on FPGAs (called CEAZ) to accelerate parallel I/O.
Revised:  In this paper, we propose a hardware-algorithm co-design for an efficient and adaptive lossy compressor for scientific data on FPGAs (called CEAZ) to accelerate parallel I/O.
Edit intent: fluency
Original:  Our contribution is fourfold: (1) We propose an efficient Huffman coding approach that can adaptively update Huffman codewords online based on codewords generated offline ( from a variety of representative scientific datasets ). (2) We derive a theoretical analysis to support a precise control of compression ratio under an error-bounded compression mode, enabling accurate offline Huffman codewords generation.
Revised:  Our contribution is fourfold: (1) We propose an efficient Huffman coding approach that can adaptively update Huffman codewords online based on codewords generated offline , from a variety of representative scientific datasets ). (2) We derive a theoretical analysis to support a precise control of compression ratio under an error-bounded compression mode, enabling accurate offline Huffman codewords generation.
Edit intent: fluency
Original:  Our contribution is fourfold: (1) We propose an efficient Huffman coding approach that can adaptively update Huffman codewords online based on codewords generated offline ( from a variety of representative scientific datasets ). (2) We derive a theoretical analysis to support a precise control of compression ratio under an error-bounded compression mode, enabling accurate offline Huffman codewords generation.
Revised:  Our contribution is fourfold: (1) We propose an efficient Huffman coding approach that can adaptively update Huffman codewords online based on codewords generated offline ( from a variety of representative scientific datasets . Moreover, we derive a theoretical analysis to support a precise control of compression ratio under an error-bounded compression mode, enabling accurate offline Huffman codewords generation.
Edit intent: coherence
Original:  (3) We develop an efficient compression pipeline by adopting cuSZ's dual-quantization algorithm to our hardware use case.
Revised:  In addition, we develop an efficient compression pipeline by adopting cuSZ's dual-quantization algorithm to our hardware use case.
Edit intent: coherence
Original:  (4) We evaluate CEAZ on five real-world datasets with both a single FPGA board and 128 nodes from Bridges-2 supercomputer . Experiments show that CEAZ outperforms the second-best FPGA-based lossy compressor by 2X of throughput and 9.6X of compression ratio.
Revised:  (4) We evaluate CEAZ on five real-world datasets with both a single FPGA board and 128 nodes from Bridges-2 supercomputer . Experiments show that CEAZ outperforms the second-best FPGA-based lossy compressor by 2X of throughput and 9.6X of ratio.
Edit intent: clarity
Original:  In this study, we demonstrate the use of agronomic knowledge of crop growth drivers in a Long Short-Term Memory-based, Domain-guided neural network (DgNN) for in-season crop progress estimation.
Revised:  In this study, we demonstrate the use of agronomic knowledge of crop growth drivers in a Long Short-Term Memory-based, domain-guided neural network (DgNN) for in-season crop progress estimation.
Edit intent: fluency
Original:  The DgNN had a 3.5 \% higher Nash-Sutfliffe efficiency over all growth stages and 33 \% more weeks with highest cosine similarity than the other NNs during test years.
Revised:  The DgNN had a 3.5 \% higher Nash-Sutfliffe efficiency over all growth stages and 33 \% more weeks with highest cosine similarity than the next best NN during test years.
Edit intent: clarity
Original: The method-of-moments implementation of the electric-field integral equation yields many code-verification challenges due to the different sources of numerical error and their possible interactions.
Revised: The method-of-moments implementation of the electric-field integral equation yields many code-verification challenges due to the various sources of numerical error and their possible interactions.
Edit intent: fluency
Original:  We present a compact and two exponential size integer programs (IPs) for k-BMF and show that the compact IP has a weak LP relaxation, while the exponential size LPs have a stronger equivalent LP relaxation.
Revised:  We present a compact and two exponential size integer programs (IPs) for k-BMF and show that the compact IP has a weak LP relaxation, while the exponential size IPs have a stronger equivalent LP relaxation.
Edit intent: fluency
Original: We develop a learning-based algorithm for the control of robotic systems governed by unknown, nonlinear dynamics to satisfy  tasks expressed as signal temporal logic specifications.
Revised: We develop a learning-based algorithm for the control of autonomous systems governed by unknown, nonlinear dynamics to satisfy tasks expressed as signal temporal logic specifications.
Edit intent: clarity
Original:  Most existing algorithms either assume certain parametric forms for the  dynamic terms or resort to unnecessarily large control inputs (e.g., using reciprocal functions) in order to provide theoretical guarantees.
Revised:  Most existing algorithms either assume certain parametric forms for the unknown dynamic terms or resort to unnecessarily large control inputs (e.g., using reciprocal functions) in order to provide theoretical guarantees.
Edit intent: clarity
Original:  Most existing algorithms either assume certain parametric forms for the  dynamic terms or resort to unnecessarily large control inputs (e.g., using reciprocal functions) in order to provide theoretical guarantees.
Revised:  Most existing algorithms either assume certain parametric forms for the dynamic terms or resort to unnecessarily large control inputs in order to provide theoretical guarantees.
Edit intent: coherence
Original:  The proposed algorithm avoids the aforementioned drawbacks by innovatively integrating neural network-based learning with adaptive control.
Revised:  The proposed algorithm addresses these drawbacks by integrating neural-network-based learning with adaptive control.
Edit intent: clarity
Original:  It then incorporates this neural network into an online closed-loop adaptive control mechanism in such a way that the resulting behavior satisfies a user-defined task.
Revised:  It then incorporates this neural network into an online closed-form adaptive control policy in such a way that the resulting behavior satisfies a user-defined task.
Edit intent: clarity
Original:  It then incorporates this neural network into an online closed-loop adaptive control mechanism in such a way that the resulting behavior satisfies a user-defined task.
Revised:  It then incorporates this neural network into an online closed-loop adaptive control mechanism in such a way that the resulting behavior satisfies the user-defined task.
Edit intent: fluency
Original:  An analysis of the thematic content reveals the most severe heat wave events within the recent decades (1995 , 2003 , 2010 ), the cities and countries/regions affected ( Australia, United States, and Europe ), and the ecological and medical impacts (drought, urban heat islands, excess hospital admissions, and mortality).
Revised:  An analysis of the thematic content reveals the most severe heat wave events within the recent decades (1995 , 2003 ), the cities and countries/regions affected ( Australia, United States, and Europe ), and the ecological and medical impacts (drought, urban heat islands, excess hospital admissions, and mortality).
Edit intent: coherence
Original:  An analysis of the thematic content reveals the most severe heat wave events within the recent decades (1995 , 2003 , 2010 ), the cities and countries/regions affected ( Australia, United States, and Europe ), and the ecological and medical impacts (drought, urban heat islands, excess hospital admissions, and mortality).
Revised:  An analysis of the thematic content reveals the most severe heat wave events within the recent decades (1995 , 2003 , 2010 ), the cities and countries/regions affected ( United States, and Europe ), and the ecological and medical impacts (drought, urban heat islands, excess hospital admissions, and mortality).
Edit intent: coherence
Original:  An analysis of the thematic content reveals the most severe heat wave events within the recent decades (1995 , 2003 , 2010 ), the cities and countries/regions affected ( Australia, United States, and Europe ), and the ecological and medical impacts (drought, urban heat islands, excess hospital admissions, and mortality).
Revised:  An analysis of the thematic content reveals the most severe heat wave events within the recent decades (1995 , 2003 , 2010 ), the cities and countries/regions affected ( Australia, United States, Europe, and Australia ), and the ecological and medical impacts (drought, urban heat islands, excess hospital admissions, and mortality).
Edit intent: coherence
Original:  our result extends a stability result of Skraba and Turner for the p-Wasserstein distance on barcodes in the 1-parameter case, and is also a close analogue of a universality property for the interleaving distance given by the second author.
Revised:  this extends a stability result of Skraba and Turner for the p-Wasserstein distance on barcodes in the 1-parameter case, and is also a close analogue of a universality property for the interleaving distance given by the second author.
Edit intent: fluency
Original:  our result extends a stability result of Skraba and Turner for the p-Wasserstein distance on barcodes in the 1-parameter case, and is also a close analogue of a universality property for the interleaving distance given by the second author.
Revised:  our result extends a stability theorem of Skraba and Turner for the p-Wasserstein distance on barcodes in the 1-parameter case, and is also a close analogue of a universality property for the interleaving distance given by the second author.
Edit intent: clarity
Original:  In experiments we show that the proposed approach achieves 1) implicit human geometry and appearance reconstruction with high-quality details, 2) photo-realistic rendering of the human from arbitrary views, and 3) animation of the human with arbitrary poses.
Revised:  In experiments we show that the proposed approach achieves 1) implicit human geometry and appearance reconstruction with high-quality details, 2) photo-realistic rendering of the human from novel views, and 3) animation of the human with arbitrary poses.
Edit intent: clarity
Original:  In experiments we show that the proposed approach achieves 1) implicit human geometry and appearance reconstruction with high-quality details, 2) photo-realistic rendering of the human from arbitrary views, and 3) animation of the human with arbitrary poses.
Revised:  In experiments we show that the proposed approach achieves 1) implicit human geometry and appearance reconstruction with high-quality details, 2) photo-realistic rendering of the human from arbitrary views, and 3) animation of the human with novel poses.
Edit intent: clarity
Original:  Neural networks can circumvent these limitations but are faced with high demands on the used datasets.
Revised:  Conventional neural networks can circumvent these limitations but are faced with high demands on the used datasets.
Edit intent: clarity
Original:  However, current architectures of vision transformers (ViTs) are simply inherited from natural language processing (NLP ) tasks and have not been sufficiently investigated and optimized .
Revised:  However, current architectures of vision transformers (ViTs) inherited the success of NLP but their structures have not been sufficiently investigated and optimized .
Edit intent: clarity
Original:  Moreover, to cater for the variance of distinct architectures, we introduceprivate class token and self-attention maps in the super-transformer.
Revised:  Moreover, to cater for the variance of distinct architectures, we introduce class token and self-attention maps in the super-transformer.
Edit intent: coherence
Original:  Commonly these uncertainties are accounted for using random fields and processes  which require knowledge about the appearing probability distributions functions which is not readily available.
Revised:  Commonly these uncertainties are accounted for using random fields and processes , which require knowledge about the appearing probability distributions functions which is not readily available.
Edit intent: fluency