wanyu/IteraTeR_v2 huggingface dataset:
Original:  In this paper, we propose a framework to reformulate many point process based models into stochastic differential equations, which allows us to use and extend methods from stochastic control and reinforcement learning to address the user activity guiding problem.
Revised:  In this paper, we propose a framework to reformulate many point process based models into stochastic differential equations, which allows us to extend methods from stochastic control and reinforcement learning to address the user activity guiding problem.
Edit intent: coherence
Original:  In this paper, we propose a framework to reformulate many point process based models into stochastic differential equations, which allows us to use and extend methods from stochastic control and reinforcement learning to address the user activity guiding problem.
Revised:  In this paper, we propose a framework to reformulate many point process based models into stochastic differential equations, which allows us to use and extend methods from stochastic optimal control to address the user activity guiding problem.
Edit intent: clarity
Original:  In this paper, we propose a framework to reformulate many point process based models into stochastic differential equations, which allows us to use and extend methods from stochastic control and reinforcement learning to address the user activity guiding problem.
Revised:  In this paper, we propose a framework to reformulate many point process based models into stochastic differential equations, which allows us to use and extend methods from stochastic control and reinforcement learning to address the activity guiding problem.
Edit intent: clarity
Original:  For our experiments, we also designed an efficient online algorithm, and show that our algorithm can guide user activities to desired states more effectively than open loop approaches .
Revised:  We also design an efficient algorithm, and show that our algorithm can guide user activities to desired states more effectively than open loop approaches .
Edit intent: clarity
Original:  For our experiments, we also designed an efficient online algorithm, and show that our algorithm can guide user activities to desired states more effectively than open loop approaches .
Revised:  For our experiments, we also designed an efficient online algorithm, and show that our method guides user activities to desired states more effectively than open loop approaches .
Edit intent: clarity
Original:  For our experiments, we also designed an efficient online algorithm, and show that our algorithm can guide user activities to desired states more effectively than open loop approaches .
Revised:  For our experiments, we also designed an efficient online algorithm, and show that our algorithm can guide user activities to desired states more effectively than the state of the art .
Edit intent: clarity
Original:  We prove that two simple greedy policies for the problem are not near-optimal but the best between them is near-optimal .
Revised:  We prove that two simple greedy algorithms are not near-optimal but the best between them is near-optimal .
Edit intent: clarity
Original:  With this result, we propose a combined policy that is near-optimal with respect to the optimal worst-case policy that uses half of the budget.
Revised:  With this result, we propose a combined policy that is near-optimal with respect to the optimal algorithm that uses half of the budget.
Edit intent: clarity
Original:  We discuss applications of our theoretical results and also report experimental results comparing the greedy policies on the active learning problem.
Revised:  We discuss applications of our theoretical results and also report experiments comparing the greedy policies on the active learning problem.
Edit intent: fluency
Original:  We discuss applications of our theoretical results and also report experimental results comparing the greedy policies on the active learning problem.
Revised:  We discuss applications of our theoretical results and also report experimental results comparing the greedy algorithms on the active learning problem.
Edit intent: clarity
Original: In this work we give a comprehensive overview of the time consistency property of dynamic risk and performance measures, with focus on discrete time setup.
Revised: In this work we give a comprehensive overview of the time consistency property of dynamic risk and performance measures, focusing on a the discrete time setup.
Edit intent: fluency
Original:  The two key operational concepts used throughout are the notion of the LM-measure and the notion of the update rule that, we believe, are the key tools for studying the time consistency in a unified framework.
Revised:  The two key operational concepts used throughout are the notion of the LM-measure and the notion of the update rule that, we believe, are the key tools for studying time consistency in a unified framework.
Edit intent: fluency
Original: We investigate the effects of cooperation between two interacting infectious diseases that spread and stabilize in a host population.
Revised: We investigate the effects of cooperativity between contagion processes that spread and stabilize in a host population.
Edit intent: clarity
Original: We investigate the effects of cooperation between two interacting infectious diseases that spread and stabilize in a host population.
Revised: We investigate the effects of cooperation between two interacting infectious diseases that spread and persist in a host population.
Edit intent: clarity
Original:  While some of these new systems have gained in popularity, their formal semantics are generally still missing .
Revised:  While some of these new systems have gained in popularity, they lack a proper formalization, and a precise understanding of the expressiveness and the computational properties of the associated query languages .
Edit intent: clarity
Original:  In this paper, we consider the symptomatic case of MongoDB, a widely adopted document database , in which roughly speaking relational tables correspond to collections, and tuples to documents .
Revised:  In this paper, we aim at filling this gap, and we do so by considering MongoDB, a widely adopted document database , in which roughly speaking relational tables correspond to collections, and tuples to documents .
Edit intent: clarity
Original:  We provide a formalization of the JSON-based data modeladopted by MongoDB , and of a core fragment  of the MongoDB aggregation query language, MUPGL, which includes the match, unwind, project, group, and lookup operators .
Revised:  We provide a formalization of the MongoDB data model , and of a core fragment of the MongoDB aggregation query language, MUPGL, which includes the match, unwind, project, group, and lookup operators .
Edit intent: clarity
Original:  We provide a formalization of the JSON-based data modeladopted by MongoDB , and of a core fragment  of the MongoDB aggregation query language, MUPGL, which includes the match, unwind, project, group, and lookup operators .
Revised:  We provide a formalization of the JSON-based data modeladopted by MongoDB , and of a core fragment of the MongoDB query language .
Edit intent: clarity
Original:  We further investigate the computational complexity of MUPGL and of significant fragments of it  .
Revised:  We further investigate the computational complexity of significant fragments of it .
Edit intent: clarity
Original:  While some of these new systems have gained in popularity, they lack a proper formalization, and a precise understanding of the expressiveness and the computational properties of the associated query languages.
Revised:  While some of these new systems have gained in popularity, they lack a proper formalization, and a precise understanding of the expressivity and the computational properties of the associated query languages.
Edit intent: fluency
Original:  We study the expressiveness of MQuery, showing its equivalence with nested relational algebra.
Revised:  We study the expressivity of MQuery, showing its equivalence with nested relational algebra.
Edit intent: fluency
Original: We present a new algorithm for the approximate nearest neighbor search based on navigable small world graphs with controllable hierarchy (Hierarchical NSW) admitting simple insertion, deletion and K-nearest neighbor queries.
Revised: We present a new algorithm for the approximate K-nearest neighbor search based on navigable small world graphs with controllable hierarchy (Hierarchical NSW) admitting simple insertion, deletion and K-nearest neighbor queries.
Edit intent: fluency
Original:  The Hierarchical NSW is a fully graph-based approach without a need for additional search structures (such as kd-trees or Cartesian concatenation) typically used at coarse search stage of the most proximity graph techniques.
Revised:  The Hierarchical NSW is a fully graph-based , without any need for additional search structures (such as kd-trees or Cartesian concatenation) typically used at coarse search stage of the most proximity graph techniques.
Edit intent: clarity
Original:  The Hierarchical NSW is a fully graph-based approach without a need for additional search structures (such as kd-trees or Cartesian concatenation) typically used at coarse search stage of the most proximity graph techniques.
Revised:  The Hierarchical NSW is a fully graph-based approach without a need for additional search structures which are typically used at coarse search stage of the most proximity graph techniques.
Edit intent: clarity
Original:  The algorithm incrementally builds a layered structure consisting from hierarchical set of proximity graphs (layers) for nested subsets of the stored elements.
Revised:  Hierarchical NSW incrementally builds multi-layer structure consisting from hierarchical set of proximity graphs (layers) for nested subsets of the stored elements.
Edit intent: clarity
Original:  Starting search from the upper layer instead of random seeds together with utilizing the scale separation boosts the performance compared to the NSW and allows a logarithmic complexity scaling.
Revised:  Starting search from the upper layer together with utilizing the scale separation boosts the performance compared to the NSW and allows a logarithmic complexity scaling.
Edit intent: clarity
Original:  Additional employment of a simple heuristic for selecting proximity graph neighbors  increases performance at high recall and in case of highly clustered data.
Revised:  Additional employment of a heuristic for selecting proximity graph neighbors increases performance at high recall and in case of highly clustered data.
Edit intent: clarity
Original:  Performance evaluation on a large number of datasets has demonstrated that the proposed general metric space method is able to strongly outperform many previous state-of-art vector-only approaches such as FLANN, FALCONN and Annoy .
Revised:  Performance evaluation has demonstrated that the proposed general metric space method is able to strongly outperform many previous state-of-art vector-only approaches such as FLANN, FALCONN and Annoy .
Edit intent: clarity
Original:  Performance evaluation on a large number of datasets has demonstrated that the proposed general metric space method is able to strongly outperform many previous state-of-art vector-only approaches such as FLANN, FALCONN and Annoy .
Revised:  Performance evaluation on a large number of datasets has demonstrated that the proposed general metric space method is able to strongly outperform many previous state-of-art vector-only approaches .
Edit intent: clarity
Original:  Similarity of the algorithm to a well-known 1D skip list structure allows straightforward efficient and balanced distributed implementation.
Revised:  Similarity of the algorithm to the skip list structure allows straightforward efficient and balanced distributed implementation.
Edit intent: clarity
Original:  Similarity of the algorithm to a well-known 1D skip list structure allows straightforward efficient and balanced distributed implementation.
Revised:  Similarity of the algorithm to a well-known 1D skip list structure allows straightforward balanced distributed implementation.
Edit intent: clarity
Original:  The proposed approach is fully graph-based, without any need for additional search structures  which are typically used at  coarse search stage of the most proximity graph techniques.
Revised:  The proposed approach is fully graph-based, without any need for additional search structures , which are typically used at coarse search stage of the most proximity graph techniques.
Edit intent: fluency
Original:  The proposed approach is fully graph-based, without any need for additional search structures  which are typically used at  coarse search stage of the most proximity graph techniques.
Revised:  The proposed approach is fully graph-based, without any need for additional search structures which are typically used at the coarse search stage of the most proximity graph techniques.
Edit intent: fluency
Original:  The maximum layer in which an element is present is selected randomly with  exponentially decaying probability distribution.
Revised:  The maximum layer in which an element is present is selected randomly with an exponentially decaying probability distribution.
Edit intent: fluency
Original:  Starting search from the upper layer together with utilizing the scale separation boosts the performance compared to the NSW and allows a logarithmic complexity scaling.
Revised:  Starting search from the upper layer together with utilizing the scale separation boosts the performance compared to NSW and allows a logarithmic complexity scaling.
Edit intent: fluency
Original:  Performance evaluation has demonstrated that the proposed general metric space method is able to strongly outperform many previous state-of-art vector-only approaches.
Revised:  Performance evaluation has demonstrated that the proposed general metric space search index is able to strongly outperform many previous state-of-art vector-only approaches.
Edit intent: clarity
Original:  Performance evaluation has demonstrated that the proposed general metric space method is able to strongly outperform many previous state-of-art vector-only approaches.
Revised:  Performance evaluation has demonstrated that the proposed general metric space method is able to strongly outperform many previous state-of-the-art vector-only approaches.
Edit intent: fluency
Original: We present a new algorithm for the approximate K-nearest neighbor search based on navigable small world graphs with controllable hierarchy (Hierarchical NSW  ).
Revised: We present a new approach for the approximate K-nearest neighbor search based on navigable small world graphs with controllable hierarchy (Hierarchical NSW ).
Edit intent: clarity
Original:  The proposed approach is fully graph-based, without any need for additional search structures, which are typically used at the coarse search stage of the most proximity graph techniques.
Revised:  The proposed solution is fully graph-based, without any need for additional search structures, which are typically used at the coarse search stage of the most proximity graph techniques.
Edit intent: clarity
Original:  Hierarchical NSW incrementally builds  multi-layer structure consisting from hierarchical set of proximity graphs (layers) for nested subsets of the stored elements.
Revised:  Hierarchical NSW incrementally builds a multi-layer structure consisting from hierarchical set of proximity graphs (layers) for nested subsets of the stored elements.
Edit intent: fluency
Original:  Performance evaluation has demonstrated that the proposed general metric space search index is able to strongly outperform many previous state-of-the-art vector-only approaches.
Revised:  Performance evaluation has demonstrated that the proposed general metric space search index is able to strongly outperform previous opensource state-of-the-art vector-only approaches.
Edit intent: clarity
Original:  Intriguingly, we show that with stochastic depth we can increase the depth of residual networks even beyond 1200 layers and still yield meaningful improvements in test error (4.91\%) on CIFAR-10.
Revised:  Intriguingly, with stochastic depth we can increase the depth of residual networks even beyond 1200 layers and still yield meaningful improvements in test error (4.91\%) on CIFAR-10.
Edit intent: coherence
Original: Very deep convolutional networks with hundreds or more layers have lead to significant reductions in error on competitive benchmarks like the ImageNet or COCO tasks .
Revised: Very deep convolutional networks with hundreds of layers have led to significant reductions in error on competitive benchmarks like the ImageNet or COCO tasks .
Edit intent: clarity
Original: Very deep convolutional networks with hundreds or more layers have lead to significant reductions in error on competitive benchmarks like the ImageNet or COCO tasks .
Revised: Very deep convolutional networks with hundreds or more layers have lead to significant reductions in error on competitive benchmarks .
Edit intent: clarity
Original:  Although the unmatched expressiveness of the many deep layers can be highly desirable at test time, training very deep networks comes with its own set of challenges.
Revised:  Although the unmatched expressiveness of the many layers can be highly desirable at test time, training very deep networks comes with its own set of challenges.
Edit intent: fluency
Original:  The gradients can vanish, the forward flow often diminishes  and the training time can be painfully slow even on modern computers.
Revised:  The gradients can vanish, the forward flow often diminishes , and the training time can be painfully slow even on modern computers.
Edit intent: fluency
Original:  We show that this approach successfully addresses the training difficulties of deep networks and complements the recent success of Residual and Highway Networks .
Revised:  We show that this approach successfully addresses the training difficulties of deep networks and complements the recent success of residual networks .
Edit intent: clarity
Original:  It reduces training time substantially and improves the test errors on almost all data sets significantly (CIFAR-10, CIFAR-100, SVHN).
Revised:  It reduces training time substantially and improves the test error significantly on almost all data sets significantly (CIFAR-10, CIFAR-100, SVHN).
Edit intent: clarity
Original:  Intriguingly, with stochastic depth we can increase the depth of residual networks even beyond 1200 layers and still yield meaningful improvements in test error (4.91\% ) on CIFAR-10  .
Revised:  Intriguingly, with stochastic depth we can increase the depth of residual networks even beyond 1200 layers and still yield meaningful improvements in test error (4.91\% on CIFAR-10 .
Edit intent: fluency
Original:  Intriguingly, with stochastic depth we can increase the depth of residual networks even beyond 1200 layers and still yield meaningful improvements in test error (4.91\% ) on CIFAR-10  .
Revised:  Intriguingly, with stochastic depth we can increase the depth of residual networks even beyond 1200 layers and still yield meaningful improvements in test error (4.91\% ) on CIFAR-10 ) .
Edit intent: fluency
Original:  Here  I extend this analysis, deriving the minimal free energy required by an organism to run a given (stochastic) map \pi from its sensor inputs to its actuator outputs.
Revised:  Here , I extend this analysis, deriving the minimal free energy required by an organism to run a given (stochastic) map \pi from its sensor inputs to its actuator outputs.
Edit intent: fluency
Original:  I end with  general discussion of the limits imposed on the rate of the terrestrial biosphere's information processing by the flux of sunlight on the Earth.
Revised:  I end with a general discussion of the limits imposed on the rate of the terrestrial biosphere's information processing by the flux of sunlight on the Earth.
Edit intent: fluency
Original: Support for an extremist entity such as Islamic State (ISIS) somehow manages to survive globally online despite significant external pressure, and may ultimately inspire acts by individuals who have no prior history of extremism, formal cell membership or direct links to leadership.
Revised: Support for an extremist entity somehow manages to survive globally online despite significant external pressure, and may ultimately inspire acts by individuals who have no prior history of extremism, formal cell membership or direct links to leadership.
Edit intent: clarity
Original: Support for an extremist entity somehow manages to survive globally online despite significant external pressure, and may ultimately inspire  acts by individuals who have no prior history of extremism , formal cell membership or direct links to leadership.
Revised: Support for extremist entities - whether from the far right, or far left - often manages to survive globally online despite significant external pressure, and may ultimately inspire acts by individuals who have no prior history of extremism , formal cell membership or direct links to leadership.
Edit intent: clarity
Original: Support for an extremist entity somehow manages to survive globally online despite significant external pressure, and may ultimately inspire  acts by individuals who have no prior history of extremism , formal cell membership or direct links to leadership.
Revised: Support for an extremist entity somehow manages to survive globally online despite significant external pressure, and may ultimately inspire violent acts by individuals who have no prior history of extremism , formal cell membership or direct links to leadership.
Edit intent: clarity
Original: Support for an extremist entity somehow manages to survive globally online despite significant external pressure, and may ultimately inspire  acts by individuals who have no prior history of extremism , formal cell membership or direct links to leadership.
Revised: Support for an extremist entity somehow manages to survive globally online despite significant external pressure, and may ultimately inspire acts by individuals having no obvious prior history of extremism , formal cell membership or direct links to leadership.
Edit intent: clarity
Original: Noticeable performance degradation is often observed in text-independent speaker recognition with short test utterances .
Revised: For text-independent speaker recognition with short test utterances .
Edit intent: clarity
Original:  This paper presents a combination approach to improve short utterance speaker recognition (SUSR ), where two phonetic-aware systems are combined together : one is the DNN-based i-vector system and the other is the subregion-based GMM-UBM system proposed by us recently .
Revised:  This paper presents a combination approach to the SUSR tasks with two phonetic-aware systems are combined together : one is the DNN-based i-vector system and the other is the subregion-based GMM-UBM system proposed by us recently .
Edit intent: clarity
Original:  This paper presents a combination approach to improve short utterance speaker recognition (SUSR ), where two phonetic-aware systems are combined together : one is the DNN-based i-vector system and the other is the subregion-based GMM-UBM system proposed by us recently .
Revised:  This paper presents a combination approach to improve short utterance speaker recognition (SUSR ), where two phonetic-aware systems : one is the DNN-based i-vector system and the other is the subregion-based GMM-UBM system proposed by us recently .
Edit intent: clarity
Original:  This paper presents a combination approach to improve short utterance speaker recognition (SUSR ), where two phonetic-aware systems are combined together : one is the DNN-based i-vector system and the other is the subregion-based GMM-UBM system proposed by us recently .
Revised:  This paper presents a combination approach to improve short utterance speaker recognition (SUSR ), where two phonetic-aware systems are combined together : one is the DNN-based i-vector system and the other is the subregion-based GMM-UBM system .
Edit intent: coherence