wanyu/IteraTeR_v2 huggingface dataset:
Original:  To address environmental partial observability, a belief abstraction is employed at the high-level navigation planner to estimate the dynamic obstacles' location when they are out of the robot's local field of view .
Revised:  To address environmental partial observability, a belief abstraction is employed at the high-level navigation planner to estimate the dynamic obstacles' location .
Edit intent: clarity
Original:  Accordingly, a synthesized action planner sends a set of locomotion actions including walking step, step height, and heading angle change, to the middle-level motion planner, while incorporating safe locomotion specifications extracted from safety theorems based on a reduced-order model (ROM) of the locomotion process.
Revised:  Accordingly, a synthesized action planner sends a set of locomotion actions to the middle-level motion planner, while incorporating safe locomotion specifications extracted from safety theorems based on a reduced-order model (ROM) of the locomotion process.
Edit intent: clarity
Original:  A set of ROM-based hyperparameters are finally interpolated to design whole-body locomotion gaits generated by trajectory optimization and validate the viable deployment of the ROM-based TAMP to the full-body trajectory generation for a 20-degrees-of-freedom Cassie bipedal robot designed by Agility Robotics .
Revised:  A set of ROM-based hyperparameters are finally interpolated to design whole-body locomotion gaits generated by trajectory optimization and validate the viable deployment of the ROM-based TAMP on a 20-degrees-of-freedom Cassie bipedal robot designed by Agility Robotics .
Edit intent: clarity
Original:  A set of ROM-based hyperparameters are finally interpolated to design whole-body locomotion gaits generated by trajectory optimization and validate the viable deployment of the ROM-based TAMP to the full-body trajectory generation for a 20-degrees-of-freedom Cassie bipedal robot designed by Agility Robotics .
Revised:  A set of ROM-based hyperparameters are finally interpolated to design whole-body locomotion gaits generated by trajectory optimization and validate the viable deployment of the ROM-based TAMP to the full-body trajectory generation for a 20-degrees-of-freedom Cassie robot designed by Agility Robotics .
Edit intent: clarity
Original: In this paper , we highlight scenarios in General Lotto games where there exist incentives to reveal one's  intentions to an opponent .
Revised: Strategic decision-making in uncertain and adversarial environments is crucial for the security of modern systems and infrastructures. A salient feature of many optimal decision-making policies is a level of unpredictability, or randomness, which helps to keep an adversary uncertain about the system's behavior. This paper seeks to explore decision-making policies on the other end of the spectrum -- namely, whether there are benefits in revealing one's intentions to an opponent .
Edit intent: coherence
Original:  We study a multi-step extension where one player has the option to publicly pre-commit resources to battlefields before play begins.
Revised:  We study a multi-step extension where one of the players has the option to publicly pre-commit resources to battlefields before play begins.
Edit intent: clarity
Original:  In response, the opponent decides which of these battlefields to secure  by matching the pre-commitment with its own resources, and which of them to withdraw from entirely .
Revised:  In response, the opponent decides which of these battlefields to secure (or abandon) by matching the pre-commitment with its own resources, and which of them to withdraw from entirely .
Edit intent: clarity
Original:  In response, the opponent decides which of these battlefields to secure  by matching the pre-commitment with its own resources, and which of them to withdraw from entirely .
Revised:  In response, the opponent decides which of these battlefields to secure by matching the pre-commitment with its own assets .
Edit intent: clarity
Original:  On a simple, non-transfer sequential CNN, PVLU led to relative error decrease of 16.3\% and 11.3\%  without and with data augmentation , relative to ReLU . PVLU is also tested on transfer learning problems.
Revised:  On a simple, non-transfer sequential CNN, PVLU allowed for a relative error decrease of 16.3\% and 11.3\% without and with data augmentation , relative to ReLU . PVLU is also tested on transfer learning problems.
Edit intent: clarity
Original:  On a simple, non-transfer sequential CNN, PVLU led to relative error decrease of 16.3\% and 11.3\%  without and with data augmentation , relative to ReLU . PVLU is also tested on transfer learning problems.
Revised:  On a simple, non-transfer sequential CNN, PVLU led to relative error decrease of 16.3\% and 11.3\% ( without and with data augmentation , relative to ReLU . PVLU is also tested on transfer learning problems.
Edit intent: fluency
Original:  Along with introducing nonlinearity and non-zero gradients across the entire real domain, PVLU allows for increased model generalization and robustness when implemented in the context of transfer learning.
Revised:  Along with introducing nonlinearity and non-zero gradients across the entire real domain, PVLU acts as a mechanism of fine-tuning when implemented in the context of transfer learning.
Edit intent: clarity
Original:  On a simple, non-transfer sequential CNN, PVLU allowed for a relative error decrease of 16.3\% and 11.3\% (without and with data augmentation) on CIFAR-10 . PVLU is also tested on transfer learning problems .
Revised:  On a simple, non-transfer sequential CNN, PVLU allowed for a relative error decrease of 16.3\% and 11.3\% (without and with data augmentation) on CIFAR-10 . PVLU is also tested on transfer learning models .
Edit intent: clarity
Original:  Most notably, PVLU fine tuning allows for relative error reductions up to and exceeding 10\% on near state-of-the-art ResNet models for both CIFAR-10 and CIFAR-100 .
Revised:  Most notably, fine-tuning using PVLU allows for relative error reductions up to and exceeding 10\% on near state-of-the-art ResNet models for both CIFAR-10 and CIFAR-100 .
Edit intent: clarity
Original:  Most notably, PVLU fine tuning allows for relative error reductions up to and exceeding 10\% on near state-of-the-art ResNet models for both CIFAR-10 and CIFAR-100 .
Revised:  Most notably, PVLU fine tuning allows for relative error reductions up to and exceeding 10\% for near state-of-the-art ResNet models for both CIFAR-10 and CIFAR-100 .
Edit intent: fluency
Original:  Most notably, PVLU fine tuning allows for relative error reductions up to and exceeding 10\% on near state-of-the-art ResNet models for both CIFAR-10 and CIFAR-100 .
Revised:  Most notably, PVLU fine tuning allows for relative error reductions up to and exceeding 10\% on near state-of-the-art residual neural network architectures on the CIFAR datasets .
Edit intent: clarity
Original:  In cultures where line or connect-the-dot figures were documented, these visual representations are constrained to the fixed background of stars, but are free in their choice of stars and lines to draw.
Revised:  In cultures where line or connect-the-dot figures , which are spatial networks constrained to the fixed background of stars, but are free in their choice of stars and lines to draw.
Edit intent: clarity
Original:  In cultures where line or connect-the-dot figures were documented, these visual representations are constrained to the fixed background of stars, but are free in their choice of stars and lines to draw.
Revised:  In cultures where line or connect-the-dot figures were documented, these visual representations are constrained to the fixed background of stars, but free in their choice of stars and lines to draw.
Edit intent: fluency
Original:  Over a dataset of 1591 constellation line figures from 50 astronomical cultures, we define metrics to measure the visual signature (or complexity) of a constellation , and answer two questions: (1) does the type of cultureassociate with the visual signature of constellations?
Revised:  Over a dataset of 1591 constellation line figures from 50 astronomical cultures, we define metrics to measure the visual signature of a constellation , and answer two questions: (1) does the type of cultureassociate with the visual signature of constellations?
Edit intent: clarity
Original:  We find clear clusters of cross-culture and cross-type similarityin visual signatures , with SE Asian traditions far apart from Mesopotamian, N and S American, Austronesian and Polynesian traditions , which are similar .
Revised:  We find clear clusters of cross-culture similarity , with SE Asian traditions far apart from Mesopotamian, N and S American, Austronesian and Polynesian traditions , which are similar .
Edit intent: clarity
Original:  We find clear clusters of cross-culture and cross-type similarityin visual signatures , with SE Asian traditions far apart from Mesopotamian, N and S American, Austronesian and Polynesian traditions , which are similar .
Revised:  We find clear clusters of cross-culture and cross-type similarityin visual signatures , with SE Asian traditions far apart from Mesopotamian, N and S American, Austronesian and Polynesian traditions .
Edit intent: coherence
Original:  We also find (2) more diversity of constellation signature per sky region than expected, with diverse designs around the majority of popular stars.
Revised:  We also find broad visual signatures in many sky regions: there are diverse line designs around the majority of popular stars.
Edit intent: clarity
Original:  We also find (2) more diversity of constellation signature per sky region than expected, with diverse designs around the majority of popular stars.
Revised:  We also find (2) more diversity of constellation signature per sky region than expected, with diverse designs around the majority of widely used stars.
Edit intent: clarity
Original:  Despite many elegant demonstrations of RL-enabled decision-making, current research mainly focuses on the pure vehicle driving environment while ignoring other traffic participants like bicycles and pedestrians.
Revised:  Despite many elegant demonstrations of RL-enabled decision-making, current research mainly focuses on the simplified traffic conditions while ignoring the existence of mixed traffic flows, i.e., vehicles, cyclists and pedestrians.
Edit intent: clarity
Original:  For urban roads, the interaction of mixed traffic flows leads to a quite dynamic and complex relationship, which poses great difficulty to learn a safe and intelligent policy.
Revised:  For urban roads, different participants leads to a quite dynamic and complex relationship, which poses great difficulty to learn a safe and intelligent policy.
Edit intent: clarity
Original:  For urban roads, the interaction of mixed traffic flows leads to a quite dynamic and complex relationship, which poses great difficulty to learn a safe and intelligent policy.
Revised:  For urban roads, the interaction of mixed traffic flows leads to a quite dynamic and complex interaction, posing great difficulty to learn a safe and intelligent policy.
Edit intent: clarity
Original:  For urban roads, the interaction of mixed traffic flows leads to a quite dynamic and complex relationship, which poses great difficulty to learn a safe and intelligent policy.
Revised:  For urban roads, the interaction of mixed traffic flows leads to a quite dynamic and complex relationship, which poses great difficulty to learn an intelligent policy.
Edit intent: clarity
Original:  This paper proposes the encoding integrated decision and control ( E-IDC ) to handle complicated driving tasks with mixed traffic flows , which composes of an encoding function  to construct driving states , a value function to choose the optimal path as well as a policy function to output the control command of ego vehicle.
Revised:  This paper proposes the encoding integrated decision and control ( IDC ) to handle complicated driving tasks with mixed traffic flows , which composes of an encoding function to construct driving states , a value function to choose the optimal path as well as a policy function to output the control command of ego vehicle.
Edit intent: clarity
Original:  The verification is conducted on the intersection scenario with mixed traffic flows and result shows that E-IDC can enhance the driving performance , including the tracking performance and safety constraint requirements with a large margin.
Revised:  The verification is conducted on the intersection scenario with mixed traffic flows and result shows that E-IDC can enhance the driving performance of IDC, including comfort, decision compliance and safety with a large margin.
Edit intent: clarity
Original:  The online application indicates that E-IDC can realize efficient and smooth driving in the complex intersection, guaranteeing the intelligence and safety simultaneously.
Revised:  The trained driving policy can realize efficient and smooth driving in the complex intersection, guaranteeing the intelligence and safety simultaneously.
Edit intent: clarity
Original:  The online application indicates that E-IDC can realize efficient and smooth driving in the complex intersection, guaranteeing the intelligence and safety simultaneously.
Revised:  The online application indicates that E-IDC can realize efficient and smooth passing in the complex intersection, guaranteeing the intelligence and safety simultaneously.
Edit intent: clarity
Original:  The online application indicates that E-IDC can realize efficient and smooth driving in the complex intersection, guaranteeing the intelligence and safety simultaneously.
Revised:  The online application indicates that E-IDC can realize efficient and smooth driving in the complex intersection, guaranteeing driving intelligence and safety simultaneously.
Edit intent: clarity
Original: Recently,  automatic configuration tuning has attracted intensive interests from the database community to improve the performance of modern database management systems ( DBMS) . As a result, a line of configuration tuning systems with new algorithms and advanced features have been developed.
Revised: Recently, using automatic configuration tuning has attracted intensive interests from the database community to improve the performance of modern database management systems ( DBMS) . As a result, a line of configuration tuning systems with new algorithms and advanced features have been developed.
Edit intent: clarity
Original: Recently,  automatic configuration tuning has attracted intensive interests from the database community to improve the performance of modern database management systems ( DBMS) . As a result, a line of configuration tuning systems with new algorithms and advanced features have been developed.
Revised: Recently, automatic configuration tuning to improve the performance of modern database management systems ( DBMS) . As a result, a line of configuration tuning systems with new algorithms and advanced features have been developed.
Edit intent: clarity
Original:  It remains unclear to identify the best combination of algorithm designs for database configuration tuning in practice, given the large body of solutions and the expensive evaluations .
Revised:  It remains unclear to identify the best combination of algorithm designs for database configuration tuning , considering the large body of solutions and the expensive evaluations .
Edit intent: clarity
Original:  It remains unclear to identify the best combination of algorithm designs for database configuration tuning in practice, given the large body of solutions and the expensive evaluations .
Revised:  It remains unclear to identify the best combination of algorithm designs for database configuration tuning in practice, given the large body of algorithm choices .
Edit intent: clarity
Original:  In addition, when jumping out of the database community , we could find even more underlying solutions that are designed for configuration tuning.
Revised:  In addition, beyond the applications on database systems , we could find even more underlying solutions that are designed for configuration tuning.
Edit intent: clarity
Original:  In addition, when jumping out of the database community , we could find even more underlying solutions that are designed for configuration tuning.
Revised:  In addition, when jumping out of the database community , we could find more potential algorithms designed for configuration tuning.
Edit intent: clarity
Original:  To this end, this paper provides a comprehensive evaluation of configuration tuning techniques from a broader domain, not limited to database community.
Revised:  To this end, this paper provides a comprehensive evaluation of configuration tuning techniques from a broader perspective, hoping to better benefit the database community.
Edit intent: clarity
Original:  In particular, we present a unified pipeline of database knob tuning with three key components and evaluate the fine-grained intra-algorithms in various and challenging scenarios .
Revised:  In particular, we summarize three key modules of database configuration tuning systems and conduct extensive ablation studies using various challenging cases .
Edit intent: clarity
Original:  Our evaluation has demonstrated that the hype-parameter optimization techniques can be borrowed to facilitate the database configuration tuning and we further identify the best solution ``path'' in different scenarios.
Revised:  Our evaluation demonstrates that the hyper-parameter optimization algorithms can be borrowed to facilitate the database configuration tuning and we further identify the best solution ``path'' in different scenarios.
Edit intent: clarity
Original:  Our evaluation has demonstrated that the hype-parameter optimization techniques can be borrowed to facilitate the database configuration tuning and we further identify the best solution ``path'' in different scenarios.
Revised:  Our evaluation has demonstrated that the hype-parameter optimization techniques can be borrowed to further enhance the database configuration tuning and we further identify the best solution ``path'' in different scenarios.
Edit intent: clarity
Original:  Our evaluation has demonstrated that the hype-parameter optimization techniques can be borrowed to facilitate the database configuration tuning and we further identify the best solution ``path'' in different scenarios.
Revised:  Our evaluation has demonstrated that the hype-parameter optimization techniques can be borrowed to facilitate the database configuration tuning . Moreover, we identify the best solution ``path'' in different scenarios.
Edit intent: coherence
Original:  Beyond the comprehensive evaluations, we offer an efficient and unified benchmark via surrogate that reduces the evaluation cost to a minimum, allowing for extensive runs and analysis of new optimizers .
Revised:  Beyond the comprehensive evaluations, we offer an efficient and unified benchmark via surrogate that reduces the evaluation cost to a minimum, allowing for extensive runs and analysis of new techniques .
Edit intent: clarity
Original:  When tested against large transformer models with 12--100 billion parameters on 48--384 NVIDIA Tesla V100 GPUs, Myelin achieves a per-GPU throughput of 49.4 --54.78 \% of theoretical peak and reduces the training time by 22-37 days ( 15--25 \% speedup) as compared to the state-of-the-art.
Revised:  When tested against large transformer models with 12-100 billion parameters on 48--384 NVIDIA Tesla V100 GPUs, Myelin achieves a per-GPU throughput of 49.4 --54.78 \% of theoretical peak and reduces the training time by 22-37 days ( 15--25 \% speedup) as compared to the state-of-the-art.
Edit intent: fluency
Original:  When tested against large transformer models with 12--100 billion parameters on 48--384 NVIDIA Tesla V100 GPUs, Myelin achieves a per-GPU throughput of 49.4 --54.78 \% of theoretical peak and reduces the training time by 22-37 days ( 15--25 \% speedup) as compared to the state-of-the-art.
Revised:  When tested against large transformer models with 12--100 billion parameters on 48-384 NVIDIA Tesla V100 GPUs, Myelin achieves a per-GPU throughput of 49.4 --54.78 \% of theoretical peak and reduces the training time by 22-37 days ( 15--25 \% speedup) as compared to the state-of-the-art.
Edit intent: fluency
Original:  When tested against large transformer models with 12--100 billion parameters on 48--384 NVIDIA Tesla V100 GPUs, Myelin achieves a per-GPU throughput of 49.4 --54.78 \% of theoretical peak and reduces the training time by 22-37 days ( 15--25 \% speedup) as compared to the state-of-the-art.
Revised:  When tested against large transformer models with 12--100 billion parameters on 48--384 NVIDIA Tesla V100 GPUs, Myelin achieves a per-GPU throughput of 49.4 --54.78 \% of theoretical peak and reduces the training time by 22-37 days ( 15-25 \% speedup) as compared to the state-of-the-art.
Edit intent: fluency
Original:  Utilizing machine learning on knowledge graph for drug similarity and recommendation will be less costly and less time consuming with higher scalability as compare to traditional biomedical methods due to the dependency on costly medical equipment and experts by the later ones.
Revised:  Utilizing machine learning on knowledge graph for drug similarity and recommendation will be less costly and less time consuming with higher scalability as compared to traditional biomedical methods due to the dependency on costly medical equipment and experts by the later ones.
Edit intent: fluency
Original:  Utilizing machine learning on knowledge graph for drug similarity and recommendation will be less costly and less time consuming with higher scalability as compare to traditional biomedical methods due to the dependency on costly medical equipment and experts by the later ones.
Revised:  Utilizing machine learning on knowledge graph for drug similarity and recommendation will be less costly and less time consuming with higher scalability as compare to traditional biomedical methods due to the dependency on costly medical equipment and experts of the latter ones.
Edit intent: clarity
Original:  Similar to the idea of self-taught learning used in transfer learning, many domains are rich with similar unlabeled datasets that could be leveraged as a proxy for out-of-distribution samples.
Revised:  Similar to the idea of self-taught learning used in transfer learning, many domains are rich with unlabeled datasets that could be leveraged as a proxy for out-of-distribution samples.
Edit intent: clarity
Original:  Similar to the idea of self-taught learning used in transfer learning, many domains are rich with similar unlabeled datasets that could be leveraged as a proxy for out-of-distribution samples.
Revised:  Similar to the idea of self-taught learning used in transfer learning, many domains are rich with similar similar unlabelled datasets that could be leveraged as a proxy for out-of-distribution samples.
Edit intent: fluency
Original:  In this paper we introduce Latent-Insensitive Autoencoder (LIS-AE) where unlabeled data from a similar domain is utilized as negative examples to shape the latent layer (bottleneck) of a regular autoencoder such that it is only capable of reconstructing one task.
Revised:  In this paper we introduce Latent-Insensitive autoencoder (LIS-AE) where unlabeled data from a similar domain is utilized as negative examples to shape the latent layer (bottleneck) of a regular autoencoder such that it is only capable of reconstructing one task.
Edit intent: fluency
Original:  We test our model in multiple anomaly detection and class-incremental settings presenting quantitative and qualitative analysis showcasing the accuracy and the flexibility of our model for both anomaly detection and class-incremental learning .
Revised:  We test our model in multiple anomaly detection settings presenting quantitative and qualitative analysis showcasing the accuracy and the flexibility of our model for both anomaly detection and class-incremental learning .
Edit intent: fluency