wanyu/IteraTeR_v2 huggingface dataset:
Original:  In addition, we show how presentation of simulated full-field complex visual stimuli, designed to approximate visual scenes, leads to reduced correlation of local excitatory responses and increased excitatory response selectivity (lifetime sparseness).
Revised:  In addition, we show how presentation of simulated full-field complex visual stimuli, designed to approximate visual scenes, leads to reduced correlation of nearby excitatory neurons, increased excitatory response selectivity (lifetime sparseness).
Edit intent: clarity
Original: Crowdsourcing is now invaluable in many domains for performing data collection and analysis by distributing tasks to workers, yet the true potential of crowdsourcing lies in workers not only performing tasks or answering questions but also in using their intuition and experience to contribute new tasks or questions for subsequent crowd analysis .
Revised: Crowdsourcing is now invaluable in many domains for performing data collection and analysis by distributing tasks to workers, yet the true potential of crowdsourcing lies in workers not only performing tasks or answering questions but also contribute new questions for subsequent crowd analysis .
Edit intent: clarity
Original:  The method handles non-network growing question sets equally well.
Edit intent: coherence
Original:  Experiments and simulations demonstrate that this algorithm can efficiently explore an unbounded set of questions while maintaining confidence in crowd answers.
Revised:  Experiments and simulations demonstrate that these algorithms can efficiently explore an unbounded set of questions while maintaining confidence in crowd answers.
Edit intent: clarity
Original:  Experiments and simulations demonstrate that this algorithm can efficiently explore an unbounded set of questions while maintaining confidence in crowd answers.
Revised:  Experiments and simulations demonstrate that this algorithm can efficiently explore an unbounded set of questions without losing confidence in crowd answers.
Edit intent: clarity
Original:  In this way, we quantify the Power of Integration of cities (their capacity to integrate diverse cultures), and characterize the relations between cultures when they act in the role of hosts and immigrants.
Revised:  In this way, we quantify the Power of Integration of cities (their capacity to integrate diverse cultures), and characterize the relations between different cultures when acting as hosts or immigrants.
Edit intent: clarity
Original: Sorting is at the core of many database operations, such as index creation, sort-merge joins  and user-requested output sorting.
Revised: Sorting is at the core of many database operations, such as index creation, sort-merge joins , and user-requested output sorting.
Edit intent: fluency
Original:  Being able to sort two gigabytes of eight byte records in as little as 50 milliseconds, our approach achieves a 2.32-fold improvement over the state-of-the-art GPU-based radix sort for uniform distributions, sustaining a minimum speed-up of no less than a factor of 1.66 for skewed distributions.
Revised:  Being able to sort two gigabytes of eight-byte records in as little as 50 milliseconds, our approach achieves a 2.32-fold improvement over the state-of-the-art GPU-based radix sort for uniform distributions, sustaining a minimum speed-up of no less than a factor of 1.66 for skewed distributions.
Edit intent: fluency
Original:  Closer inspection of the bands reveals unusual ciliary "tangles" analogous to topological defects that break-up and re-form as the animal adjusts its swimming stroke.
Revised:  Closer inspection of the bands reveals unusual ciliary "tangles" analogous to topological defects that break up and re-form as the animal adjusts its swimming stroke.
Edit intent: fluency
Original:  Quantitative experiments and modeling suggest that these vortices create a physical tradeoff between feeding and swimming  , which manifests as distinct flow patterns or " eigenstrokes " representing each behavior---potentially implicating neuronal control of cilia.
Revised:  Quantitative experiments and modeling demonstrate that these vortices create a physical tradeoff between feeding and swimming , which manifests as distinct flow patterns or " eigenstrokes " representing each behavior---potentially implicating neuronal control of cilia.
Edit intent: clarity
Original:  Quantitative experiments and modeling suggest that these vortices create a physical tradeoff between feeding and swimming  , which manifests as distinct flow patterns or " eigenstrokes " representing each behavior---potentially implicating neuronal control of cilia.
Revised:  Quantitative experiments and modeling suggest that these vortices create a physical tradeoff between feeding and swimming , which manifests as distinct flow patterns or " eigen-strokes " representing each behavior---potentially implicating neuronal control of cilia.
Edit intent: fluency
Original:  This quantitative interplay between larval form and hydrodynamic function generalizes to other invertebrates , and demonstrates the potential of active boundary conditions in other biological and synthetic systems.
Revised:  This quantitative interplay between larval form and hydrodynamic function may generalize to other invertebrates , and demonstrates the potential of active boundary conditions in other biological and synthetic systems.
Edit intent: clarity
Original:  The 1-shortcut , however, is essentially equivalent to no shortcuts .
Revised:  The shortcut 1 , however, is essentially equivalent to no shortcuts .
Edit intent: clarity
Original:  We show that initializing the network to small weights with 2-shortcuts achieves significantly better results than random Gaussian (Xavier) initialization, orthogonal initialization, and shortcuts of deeper depth, from various perspectives ranging from final loss, learning dynamics and stability, to the behavior of the Hessian along the learning process.
Revised:  We show that initializing the network to small weights with shortcut 2 achieves significantly better results than random Gaussian (Xavier) initialization, orthogonal initialization, and shortcuts of deeper depth, from various perspectives ranging from final loss, learning dynamics and stability, to the behavior of the Hessian along the learning process.
Edit intent: clarity
Original:  Our paper contributes to the literature by taking into account the timing issue by studying when the papers were made free
Revised:  It is natural to wonder if this might reduce researchers' reliance on library subscriptions for access. To do so, we need to determine not just what papers researchers are citing to that are free today, but to estimate if the papers they were citing were freely available at the time they were citing it. We attempt to do so for a sample of citations made by researchers in the Singapore Management University in the field of Economics.
Edit intent: coherence
Original:  We then extend previous contributions by detailing three equivalent formulations of the Gaussian dynamic texture model.
Revised:  We extend previous contributions by detailing three equivalent formulations of the Gaussian dynamic texture model.
Edit intent: coherence
Original:  We then extend previous contributions by detailing three equivalent formulations of the Gaussian dynamic texture model.
Revised:  We then extend previous contributions by detailing three equivalent formulations of this texture model.
Edit intent: clarity
Original:  Second , these textures are cast as solutions to a stochastic partial differential equation (sPDE).
Revised:  Secondly , these textures are cast as solutions to a stochastic partial differential equation (sPDE).
Edit intent: coherence
Original:  This essential step enables real time, on-the-fly , texture synthesis using time-discretized auto- regressive processes.
Revised:  This essential step enables real time, on-the-fly texture synthesis using time-discretized auto- regressive processes.
Edit intent: fluency
Original:  This essential step enables real time, on-the-fly , texture synthesis using time-discretized auto- regressive processes.
Revised:  This essential step enables real time, on-the-fly , texture synthesis using time-discretized auto-regressive processes.
Edit intent: fluency
Original:  The log-likelihoods are finally essential for the construction of a Bayesian inference framework.
Revised:  The log-likelihoods are essential for the construction of a Bayesian inference framework.
Edit intent: clarity
Original:  We use the model to probe speed perception in humans psychophysically using zoom-like changes in stimulus spatial frequency content .
Revised:  We use the model to probe speed perception in humans using zoom-like changes in stimulus spatial frequency content .
Edit intent: clarity
Original:  We use the model to probe speed perception in humans psychophysically using zoom-like changes in stimulus spatial frequency content .
Revised:  We use the model to probe speed perception in humans psychophysically using zoom-like changes in the spatial frequency content .
Edit intent: clarity
Original:  The human data replicates previous findings that relative perceived speed is positively biased by spatial frequency increments.
Revised:  The human data replicates previous findings showing perceived speed to be positively biased by spatial frequency increments.
Edit intent: clarity
Original:  Here we show that a subtle flaw in Web of Science can inflate the results of info collected, therefore compromising the exactness and, consequently, the effectiveness of Hirsch's proposal and its variations 
Revised:  Here we show that a subtle flaw in Web of Science can inflate the results of info collected, therefore compromising the exactness and, consequently, the effectiveness of Hirsch's proposal and its variations .
Edit intent: fluency
Original: Oblivious RAM (ORAM) is a cryptographic primitive which obfuscates the access patterns to a storage thereby preventing privacy leakage via access patterns . So far in the current literature only ' fully functional' ORAMs are widely studied which can protect, at a cost of considerable performance penalty, against the strong adversaries who have access to the memory address bus and can monitor all read and write operations.
Revised: Oblivious RAM (ORAM) is a cryptographic primitive which obfuscates the access patterns to a storage thereby preventing privacy leakage . So far in the current literature only ' fully functional' ORAMs are widely studied which can protect, at a cost of considerable performance penalty, against the strong adversaries who have access to the memory address bus and can monitor all read and write operations.
Edit intent: clarity
Original: Oblivious RAM (ORAM) is a cryptographic primitive which obfuscates the access patterns to a storage thereby preventing privacy leakage via access patterns . So far in the current literature only ' fully functional' ORAMs are widely studied which can protect, at a cost of considerable performance penalty, against the strong adversaries who have access to the memory address bus and can monitor all read and write operations.
Revised: Oblivious RAM (ORAM) is a cryptographic primitive which obfuscates the access patterns to a storage thereby preventing privacy leakage via access patterns . So far in the current literature , only ` fully functional' ORAMs are widely studied which can protect, at a cost of considerable performance penalty, against the strong adversaries who have access to the memory address bus and can monitor all read and write operations.
Edit intent: fluency
Original: Oblivious RAM (ORAM) is a cryptographic primitive which obfuscates the access patterns to a storage thereby preventing privacy leakage via access patterns . So far in the current literature only ' fully functional' ORAMs are widely studied which can protect, at a cost of considerable performance penalty, against the strong adversaries who have access to the memory address bus and can monitor all read and write operations.
Revised: Oblivious RAM (ORAM) is a cryptographic primitive which obfuscates the access patterns to a storage thereby preventing privacy leakage via access patterns . So far in the current literature only ' fully functional' ORAMs are widely studied which can protect, at a cost of considerable performance penalty, against the strong adversaries who can monitor all read and write operations.
Edit intent: coherence
Original:  A simple ' write-only' ORAM is sufficient for such adversaries , and, more interestingly, is preferred as it can offer far more performance and energy efficiency than the fully functional ORAM.
Revised:  A simple ' write-only' ORAM is sufficient , and, more interestingly, is preferred as it can offer far more performance and energy efficiency than the fully functional ORAM.
Edit intent: clarity
Original:  A simple ' write-only' ORAM is sufficient for such adversaries , and, more interestingly, is preferred as it can offer far more performance and energy efficiency than the fully functional ORAM.
Revised:  A simple ' write-only' ORAM is sufficient for such adversaries , and, more interestingly, is preferred as it can offer far more performance and energy efficiency than a fully functional ORAM.
Edit intent: fluency
Original:  In this work, we present Flat ORAM: a simplified and efficient write-only ORAM scheme for secure processors.
Revised:  In this work, we present Flat ORAM: an efficient write-only ORAM scheme for secure processors.
Edit intent: clarity
Original:  Specific to write-only ORAMs, we introduce a new ORAM structure called Occupancy Map (OccMap) which contains memory occupancy information vital for correctness and efficiency of our scheme .
Revised:  Specific to write-only ORAMs, we introduce a new ORAM structure called Occupancy Map (OccMap) which efficiently manages the memory occupancy information vital for correctness and efficiency of our scheme .
Edit intent: clarity
Original:  Specific to write-only ORAMs, we introduce a new ORAM structure called Occupancy Map (OccMap) which contains memory occupancy information vital for correctness and efficiency of our scheme .
Revised:  Specific to write-only ORAMs, we introduce a new ORAM structure called Occupancy Map (OccMap) which contains memory occupancy information resulting in far better performance .
Edit intent: clarity
Original:  Compared to the closest existing write-only ORAM scheme called HIVE, Flat ORAM offers %DIFDELCMD < \approx50%%%  \\%DIF < performance gain and 45-65\\% energy savings on average.
Revised:  Compared to HIVE, Flat ORAM offers %DIFDELCMD < \approx50%%% \\%DIF < performance gain and 45-65\\% energy savings on average.
Edit intent: clarity
Original:  Compared to the closest existing write-only ORAM scheme called HIVE, Flat ORAM offers %DIFDELCMD < \approx50%%%  \\%DIF < performance gain and 45-65\\% energy savings on average.
Revised:  Compared to the closest existing write-only ORAM scheme called HIVE, Flat ORAM offers %DIFDELCMD < \approx50%%% \\%DIF < performance gain and 45-65\\% energy savings 
Edit intent: clarity
Original:  Our CIFAR-10 model achieves a test error rate of 3.84 , which is only 0.1 percent worse and 1.2 x faster than the current state-of-the-art model  .
Revised:  Our CIFAR-10 model achieves a test error rate of 3.84 , which is only 0.1 percent worse and 1.2 x faster than the previous state-of-the-art model .
Edit intent: clarity
Original: One of the most important fields in robotics is the optimization of controllers.
Revised: An important field in robotics is the optimization of controllers.
Edit intent: clarity
Original:  Currently, robots are  treated as a black box in this optimization process, which is the reason why derivative-free optimization methods such as evolutionary algorithms or reinforcement learning are omnipresent.
Revised:  Currently, robots are often treated as a black box in this optimization process, which is the reason why derivative-free optimization methods such as evolutionary algorithms or reinforcement learning are omnipresent.
Edit intent: coherence
Original:  We propose an implementation of a modern physics engine, which has the ability to differentiate control parameters.
Revised:  We propose an implementation of a modern physics engine, which can differentiate control parameters.
Edit intent: clarity
Original:  This has been implemented on both CPU and GPU.
Revised:  This engine is implemented for both CPU and GPU.
Edit intent: clarity
Original:  We show how this speeds up the optimization process, even for small problems , and why it will scale to bigger problems.
Revised:  Firstly, this paper shows how such an engine speeds up the optimization process, even for small problems , and why it will scale to bigger problems.
Edit intent: clarity
Original:  Lastly , we argue that this is a big step for deep learning in robotics, as it opens up new possibilities to optimize robots, both in hardware and software.
Revised:  Finally , we argue that this is a big step for deep learning in robotics, as it opens up new possibilities to optimize robots, both in hardware and software.
Edit intent: fluency
Original:  It also handles missing data more handsomely . Lastly, as side information, it provides interesting insights on the test subjects and video contents.
Revised:  It also handles missing data more gracefully . Lastly, as side information, it provides interesting insights on the test subjects and video contents.
Edit intent: clarity
Original:  Lastly , as side information, it provides interesting insights on the test subjects and video contents.
Revised:  Finally , as side information, it provides interesting insights on the test subjects and video contents.
Edit intent: fluency
Original:  In this paper, using the well-known Hegselmann-Krause (HK) model, we design a quite simple strategy that could resolve the opinion difference of the system in finite time and induce the opinions synchronized to the targeted value.
Revised:  In this paper, using the well-known Hegselmann-Krause (HK) model, we design a quite simple strategy that could resolve the opinion difference of the system in finite time and induce the opinions synchronized to a targeted value.
Edit intent: fluency
Original:  We implemented and instantiated our approach to the task of learning a points-to analysis for JavaScript, a challenging yet important problem that has received significant research attention.
Revised:  We implemented and instantiated our approach to the task of learning a points-to analysis for JavaScript, a challenging yet important problems that have received significant research attention.
Edit intent: fluency
Original:  We show that our approach is effective: our system automatically discovered practical and useful inference rules for many corner cases that are tricky to manually identify and are missed by state-of-the-art, manually tuned solutions .
Revised:  We show that our approach is effective: our system automatically discovered practical and useful inference rules for many cases that are tricky to manually identify and are missed by state-of-the-art, manually tuned solutions .
Edit intent: clarity
Original:  We show that our approach is effective: our system automatically discovered practical and useful inference rules for many corner cases that are tricky to manually identify and are missed by state-of-the-art, manually tuned solutions .
Revised:  We show that our approach is effective: our system automatically discovered practical and useful inference rules for many corner cases that are tricky to manually identify and are missed by state-of-the-art, manually tuned analyzers .
Edit intent: clarity
Original:  The first strongly polynomial algorithm for this problem was given in [V\'egh16] ;
Revised:  The first strongly polynomial algorithm [V\'egh16] ;
Edit intent: clarity
Original:  The complexity bound O(  (m+n\log n) mn \log (n^2/m))  improves on the previous estimate in V\'egh16 by almost a factor O(n^2).
Revised:  The complexity bound O( mn (m+n\log n) mn \log (n^2/m)) improves on the previous estimate in V\'egh16 by almost a factor O(n^2).
Edit intent: fluency
Original:  The complexity bound O(  (m+n\log n) mn \log (n^2/m))  improves on the previous estimate in V\'egh16 by almost a factor O(n^2).
Revised:  The complexity bound O( (m+n\log n) \log (n^2/m)) improves on the previous estimate in V\'egh16 by almost a factor O(n^2).
Edit intent: clarity
Original:  The complexity bound O(  (m+n\log n) mn \log (n^2/m))  improves on the previous estimate in V\'egh16 by almost a factor O(n^2).
Revised:  The complexity bound O( (m+n\log n) mn \log (n^2/m)) improves on the previous estimate V\'egh16 by almost a factor O(n^2).
Edit intent: clarity
Original:  Even for small numerical parameter values, our algorithm is essentially as fast as the best weakly polynomial algorithms.
Revised:  Even for small numerical parameter values, our running time bound is comparable to the best weakly polynomial algorithms.
Edit intent: clarity
Original:  The key new technical idea is relaxing  primal feasibility conditions.
Revised:  The key new technical idea is relaxing the primal feasibility conditions.
Edit intent: fluency
Original:  The complexity bound O(mn(m+n\log n)\log (n^2/m)) for the uncapacitated problem formulation improves on the previous estimate by almost a factor O(n^2).
Revised:  For the uncapacitated problem formulation, the complexity bound O(mn(m+n\log n)\log (n^2/m)) for the uncapacitated problem formulation improves on the previous estimate by almost a factor O(n^2).
Edit intent: clarity
Original:  The complexity bound O(mn(m+n\log n)\log (n^2/m)) for the uncapacitated problem formulation improves on the previous estimate by almost a factor O(n^2).
Revised:  The complexity bound O(mn(m+n\log n)\log (n^2/m)) improves on the previous estimate by almost a factor O(n^2).
Edit intent: clarity
Original:  Sketches annotate each task with a sequence of named subtasks, providing  high-level structural relationships among tasks , but not providing the detailed guidance required by previous work on learning policy abstractions for RL (e.g. intermediate rewards, subtask completion signals, or intrinsic motivations).
Revised:  Sketches annotate tasks with sequences of named subtasks, providing high-level structural relationships among tasks , but not providing the detailed guidance required by previous work on learning policy abstractions for RL (e.g. intermediate rewards, subtask completion signals, or intrinsic motivations).
Edit intent: clarity
Original:  Sketches annotate each task with a sequence of named subtasks, providing  high-level structural relationships among tasks , but not providing the detailed guidance required by previous work on learning policy abstractions for RL (e.g. intermediate rewards, subtask completion signals, or intrinsic motivations).
Revised:  Sketches annotate each task with a sequence of named subtasks, providing information about high-level structural relationships among tasks , but not providing the detailed guidance required by previous work on learning policy abstractions for RL (e.g. intermediate rewards, subtask completion signals, or intrinsic motivations).
Edit intent: clarity
Original:  Sketches annotate each task with a sequence of named subtasks, providing  high-level structural relationships among tasks , but not providing the detailed guidance required by previous work on learning policy abstractions for RL (e.g. intermediate rewards, subtask completion signals, or intrinsic motivations).
Revised:  Sketches annotate each task with a sequence of named subtasks, providing high-level structural relationships among tasks , but not providing the detailed guidance used by much previous work on learning policy abstractions for RL (e.g. intermediate rewards, subtask completion signals, or intrinsic motivations).
Edit intent: clarity
Original:  Our approach associates every subtask with its own modular subpolicy, and jointly optimizes over full task-specific policies by tying parameters across shared subpolicies.
Revised:  Our approach associates every subtask with a modular subpolicy, and jointly optimizes over full task-specific policies by tying parameters across shared subpolicies.
Edit intent: clarity