wanyu/IteraTeR_v2 huggingface dataset:
Original:  Finally , we apply the concept of an assortment auction in online assortment problems.
Revised:  To conclude , we apply the concept of an assortment auction in online assortment problems.
Edit intent: clarity
Original:  Finally , we apply the concept of an assortment auction in online assortment problems.
Revised:  Finally , we apply our theory in online assortment problems.
Edit intent: clarity
Original:  We show that any personalized assortment policy is a special case of a truthful assortment auction, and that moreover, the optimal auction provides a tighter relaxation for online policies than the commonly-used ``deterministic LP'' . Using this fact, we improve many online assortmentpolicies, and derive the first approximation guarantees that strictly exceed 1-1/e.
Revised:  We show that any personalized assortment policy is a special case of a truthful assortment auction, and that moreover, the optimal auction provides a tighter benchmark than the commonly-used ``deterministic LP'' . Using this fact, we improve many online assortmentpolicies, and derive the first approximation guarantees that strictly exceed 1-1/e.
Edit intent: clarity
Original:  We show that any personalized assortment policy is a special case of a truthful assortment auction, and that moreover, the optimal auction provides a tighter relaxation for online policies than the commonly-used ``deterministic LP'' . Using this fact, we improve many online assortmentpolicies, and derive the first approximation guarantees that strictly exceed 1-1/e.
Revised:  We show that any personalized assortment policy is a special case of a truthful assortment auction, and that moreover, the optimal auction provides a tighter relaxation for online policies than the commonly-used ``deterministic LP'' for online assortment, leading to the first approximation guarantees that strictly exceed 1-1/e.
Edit intent: coherence
Original:  In this work, we first investigate this problem from a theoretical perspective and then provide a set of practical algorithms to identify and characterize such behavior in social media.
Revised:  In this work, we first look into this problem from a theoretical perspective and then provide a set of practical algorithms to identify and characterize such behavior in social media.
Edit intent: clarity
Original:  More specifically, we address the above problem from the perspective of sequential decision making and utility maximization.
Revised:  More specifically, we address the above problem from the viewpoint of sequential decision making and utility maximization.
Edit intent: fluency
Original:  For a wide family of utility functions, we first show that, to succeed, a user needs to actively trade off exploitation-- sharing stories which lead to more (positive) feedback--and exploration-- sharing stories to learn about her followers' preferences.
Revised:  For a wide variety of utility functions, we first show that, to succeed, a user needs to actively trade off exploitation-- sharing stories which lead to more (positive) feedback--and exploration-- sharing stories to learn about her followers' preferences.
Edit intent: clarity
Original: Finding or discovering data is a necessary precursor to being able to reuse data, although relatively little large-scale empirical evidence exists about how researchers discover, make sense of and (re)use data for research.
Revised: Finding data is a necessary precursor to being able to reuse data, although relatively little large-scale empirical evidence exists about how researchers discover, make sense of and (re)use data for research.
Edit intent: coherence
Original:  We examine the data needs and discovery strategies of respondents, propose a typology for data (re)use and probe the role of social interactions and other research practices in data discovery , with the aim of informing the design of community-centric solutions and policies .
Revised:  We examine the data needs and discovery strategies of respondents, propose a typology for data reuse and probe the role of social interactions and other research practices in data discovery , with the aim of informing the design of community-centric solutions and policies .
Edit intent: coherence
Original:  We examine the data needs and discovery strategies of respondents, propose a typology for data (re)use and probe the role of social interactions and other research practices in data discovery , with the aim of informing the design of community-centric solutions and policies .
Revised:  We examine the data needs and discovery strategies of respondents, propose a typology for data (re)use and probe the role of social interactions and literature search in data discovery , with the aim of informing the design of community-centric solutions and policies .
Edit intent: clarity
Original: We consider a two stage market mechanism for trading electricity including renewable generation as an alternative to the widely used multi-settlement market structure.
Revised: We consider a two-stage market mechanism for trading electricity including renewable generation as an alternative to the widely used multi-settlement market structure.
Edit intent: fluency
Original:  The two stage market structure allows for recourse decisions by the market operator, which is not possible in today's markets.
Revised:  The two-stage market structure allows for recourse decisions by the market operator, which is not possible in today's markets.
Edit intent: fluency
Original:  The two stage market structure allows for recourse decisions by the market operator, which is not possible in today's markets.
Revised:  The two stage market structure allows for recourse decisions by the market operator, which are not possible in today's markets.
Edit intent: fluency
Original:  We allow for different  generation cost curves in the forward and the real-time stage .
Revised:  We allow for different generation cost curves in the forward and the real-time stages .
Edit intent: fluency
Original:  We have considered costs of demand response programs , and black outs but have ignored network structure for the sake of simplicity .
Revised:  We have considered costs of demand response programs and black outs but have ignored network structure for the sake of simplicity .
Edit intent: fluency
Original:  We then argue social welfare properties of such an SCEq . We then design a market mechanism that achieves social welfare maximization when the market participants are non-strategic  .
Revised:  We argue social welfare properties of such an SCEq . We then design a market mechanism that achieves social welfare maximization when the market participants are non-strategic .
Edit intent: fluency
Original:  We then argue social welfare properties of such an SCEq . We then design a market mechanism that achieves social welfare maximization when the market participants are non-strategic  .
Revised:  We then argue social welfare properties of such an SCEq , and then design a market mechanism that achieves social welfare maximization when the market participants are non-strategic .
Edit intent: coherence
Original:  These systems arise in satisfiability (SAT) solving , and allow inferences which preserve satisfiability but not logical implication .
Revised:  These systems arise in satisfiability (SAT) solving .
Edit intent: clarity
Original:  We focus on the systems that do not allow new variables to be introduced.
Revised:  We focus on restricted systems that do not allow new variables to be introduced.
Edit intent: clarity
Original:  Our first main result is that the systems DRAT ^-, DSPR%DIFDELCMD < {}%%% ^- and DPR ^-, which allow deletionbut not new variables, are polynomially equivalent.
Revised:  Our first main result is that the systems DRAT %DIFDELCMD < {}%%% ^- and DPR ^-, which allow deletionbut not new variables, are polynomially equivalent.
Edit intent: clarity
Original:  Our first main result is that the systems DRAT ^-, DSPR%DIFDELCMD < {}%%% ^- and DPR ^-, which allow deletionbut not new variables, are polynomially equivalent.
Revised:  Our first main result is that the systems DRAT ^-, DSPR%DIFDELCMD < {}%%% ^-, which allow deletionbut not new variables, are polynomially equivalent.
Edit intent: coherence
Original:  By earlier work of Kiesl, Rebola-Pardo and Heule, they are also equivalent to DBC ^- . Without deletion and without new variables , we show that SPR ^- can polynomially simulate PR%DIFDELCMD < {}%%% ^- provided only short clauses are inferred by SPR inferences.
Revised:  By earlier work of Kiesl, Rebola-Pardo and Heule, they are also equivalent to ^- . Without deletion and without new variables , we show that SPR ^- can polynomially simulate PR%DIFDELCMD < {}%%% ^- provided only short clauses are inferred by SPR inferences.
Edit intent: clarity
Original:  By earlier work of Kiesl, Rebola-Pardo and Heule, they are also equivalent to DBC ^- . Without deletion and without new variables , we show that SPR ^- can polynomially simulate PR%DIFDELCMD < {}%%% ^- provided only short clauses are inferred by SPR inferences.
Revised:  By earlier work of Kiesl, Rebola-Pardo and Heule, they are also equivalent to DBC DBC- . Without deletion and without new variables , we show that SPR ^- can polynomially simulate PR%DIFDELCMD < {}%%% ^- provided only short clauses are inferred by SPR inferences.
Edit intent: clarity
Original:  By earlier work of Kiesl, Rebola-Pardo and Heule, they are also equivalent to DBC ^- . Without deletion and without new variables , we show that SPR ^- can polynomially simulate PR%DIFDELCMD < {}%%% ^- provided only short clauses are inferred by SPR inferences.
Revised:  By earlier work of Kiesl, Rebola-Pardo and Heule, they are also equivalent to DBC ^- . Without deletion , we show that SPR ^- can polynomially simulate PR%DIFDELCMD < {}%%% ^- provided only short clauses are inferred by SPR inferences.
Edit intent: coherence
Original:  By earlier work of Kiesl, Rebola-Pardo and Heule, they are also equivalent to DBC ^- . Without deletion and without new variables , we show that SPR ^- can polynomially simulate PR%DIFDELCMD < {}%%% ^- provided only short clauses are inferred by SPR inferences.
Revised:  By earlier work of Kiesl, Rebola-Pardo and Heule, they are also equivalent to DBC ^- . Without deletion and without new variables , we show that ^- can polynomially simulate PR%DIFDELCMD < {}%%% ^- provided only short clauses are inferred by SPR inferences.
Edit intent: fluency
Original:  By earlier work of Kiesl, Rebola-Pardo and Heule, they are also equivalent to DBC ^- . Without deletion and without new variables , we show that SPR ^- can polynomially simulate PR%DIFDELCMD < {}%%% ^- provided only short clauses are inferred by SPR inferences.
Revised:  By earlier work of Kiesl, Rebola-Pardo and Heule, they are also equivalent to DBC ^- . Without deletion and without new variables , we show that SPR %DIFDELCMD < {}%%% ^- provided only short clauses are inferred by SPR inferences.
Edit intent: clarity
Original:  By earlier work of Kiesl, Rebola-Pardo and Heule, they are also equivalent to DBC ^- . Without deletion and without new variables , we show that SPR ^- can polynomially simulate PR%DIFDELCMD < {}%%% ^- provided only short clauses are inferred by SPR inferences.
Revised:  By earlier work of Kiesl, Rebola-Pardo and Heule, they are also equivalent to DBC ^- . Without deletion and without new variables , we show that SPR ^- can polynomially simulate PR%DIFDELCMD < {}%%% SPR- can simulate PR- provided only short clauses are inferred by SPR inferences.
Edit intent: clarity
Original:  Our next main result is that many of the well-known "hard" principles have polynomial size SPR ^- refutations(without deletions or new variables) .
Revised:  We also show that many of the well-known "hard" principles have polynomial size SPR ^- refutations(without deletions or new variables) .
Edit intent: coherence
Original:  Our final result is an exponential size lower bound for RAT ^- refutations, giving exponential separations between RAT ^- and both DRAT%DIFDELCMD < {}%%% ^- and SPR ^- .
Revised:  Our final result is an exponential size lower bound for ^- refutations, giving exponential separations between RAT ^- and both DRAT%DIFDELCMD < {}%%% ^- and SPR ^- .
Edit intent: fluency
Original:  Our final result is an exponential size lower bound for RAT ^- refutations, giving exponential separations between RAT ^- and both DRAT%DIFDELCMD < {}%%% ^- and SPR ^- .
Revised:  Our final result is an exponential size lower bound for RAT RAT- refutations, giving exponential separations between RAT ^- and both DRAT%DIFDELCMD < {}%%% ^- and SPR ^- .
Edit intent: clarity
Original:  Our final result is an exponential size lower bound for RAT ^- refutations, giving exponential separations between RAT ^- and both DRAT%DIFDELCMD < {}%%% ^- and SPR ^- .
Revised:  Our final result is an exponential size lower bound for RAT ^- refutations, giving exponential separations between ^- and both DRAT%DIFDELCMD < {}%%% ^- and SPR ^- .
Edit intent: fluency
Original:  Our final result is an exponential size lower bound for RAT ^- refutations, giving exponential separations between RAT ^- and both DRAT%DIFDELCMD < {}%%% ^- and SPR ^- .
Revised:  Our final result is an exponential size lower bound for RAT ^- refutations, giving exponential separations between RAT %DIFDELCMD < {}%%% ^- and SPR ^- .
Edit intent: clarity
Original:  Our final result is an exponential size lower bound for RAT ^- refutations, giving exponential separations between RAT ^- and both DRAT%DIFDELCMD < {}%%% ^- and SPR ^- .
Revised:  Our final result is an exponential size lower bound for RAT ^- refutations, giving exponential separations between RAT ^- and both DRAT%DIFDELCMD < {}%%% ^- .
Edit intent: coherence
Original:  In increasing order of strength the rules are BC, RAT, SPR and PR (respectively short for blocked clauses, resolution asymmetric tautologies, subset propagation redundancy and propagation redundancy).
Revised:  These inference rules include BC, RAT, SPR and PR (respectively short for blocked clauses, resolution asymmetric tautologies, subset propagation redundancy and propagation redundancy).
Edit intent: clarity
Original:  Meanwhile, Artificial Intelligence (AI) applications are thriving with the breakthroughs in deep learning and the upgrade of hardware architectures.
Revised:  Meanwhile, Artificial Intelligence (AI) applications are thriving with the breakthroughs in deep learning and the many improvements in hardware architectures.
Edit intent: clarity
Original:  Billions of bytes of data , generated at the network edge, put great demands on data processing and structural optimization.
Revised:  Billions of data bytes , generated at the network edge, put great demands on data processing and structural optimization.
Edit intent: fluency
Original:  Billions of bytes of data , generated at the network edge, put great demands on data processing and structural optimization.
Revised:  Billions of bytes of data , generated at the network edge, put massive demands on data processing and structural optimization.
Edit intent: clarity
Original:  Therefore , there exists a strong demand to integrate Edge Computing and AI, which gives birth to Edge Intelligence.
Revised:  Thus , there exists a strong demand to integrate Edge Computing and AI, which gives birth to Edge Intelligence.
Edit intent: fluency
Original:  In this article , we divide Edge Intelligence into AI for edge (Intelligence-enabled Edge Computing) and AI on edge (Artificial Intelligence on Edge).
Revised:  In this paper , we divide Edge Intelligence into AI for edge (Intelligence-enabled Edge Computing) and AI on edge (Artificial Intelligence on Edge).
Edit intent: fluency
Original:  The former focuses on providing a more optimal solution to the key concerns in Edge Computing with the help of popular and effective AI technologies while the latter studies how to carry out the entire process of building AI models, i.e., model training and inference, on  edge.
Revised:  The former focuses on providing more optimal solutions to key problems in Edge Computing with the help of popular and effective AI technologies while the latter studies how to carry out the entire process of building AI models, i.e., model training and inference, on edge.
Edit intent: clarity
Original:  The former focuses on providing a more optimal solution to the key concerns in Edge Computing with the help of popular and effective AI technologies while the latter studies how to carry out the entire process of building AI models, i.e., model training and inference, on  edge.
Revised:  The former focuses on providing a more optimal solution to the key concerns in Edge Computing with the help of popular and effective AI technologies while the latter studies how to carry out the entire process of building AI models, i.e., model training and inference, on the edge.
Edit intent: fluency
Original:  This article focuses on giving insights into this new inter-disciplinary field from a broader vision and perspective.
Revised:  This paper provides insights into this new inter-disciplinary field from a broader vision and perspective.
Edit intent: clarity
Original:  This article focuses on giving insights into this new inter-disciplinary field from a broader vision and perspective.
Revised:  This article focuses on giving insights into this new inter-disciplinary field from a broader perspective.
Edit intent: clarity
Original:  It discusses the core concepts and the research road-map, which should provide the necessary background for potential future research programs in Edge Intelligence.
Revised:  It discusses the core concepts and the research road-map, which should provide the necessary background for potential future research initiatives in Edge Intelligence.
Edit intent: clarity
Original: In this paper, we propose a full discretization for d-dimensional stochastic wave equation with both polynomial nonlinearity and additive noise , which is based on the spectral Galerkin method in spatial direction and splitting averaged vector field method in temporal direction.
Revised: In this paper, we propose a full discretization for d-dimensional stochastic wave equation with both polynomial nonlinearity and additive noise . We first apply the spectral Galerkin method in spatial direction and splitting averaged vector field method in temporal direction.
Edit intent: coherence
Original:  Based on these regularity estimates and exponential integrability properties, the  strong convergence order in both spatial and temporal direction are obtained . Numerical experiments are presented to verify these theoretical results.
Revised:  Based on these regularity estimates and exponential integrability properties, the strong convergence order in both spatial and temporal direction are obtained . Numerical experiments coincide with these theoretical results.
Edit intent: clarity
Original:  We construct a `` test function operator function '' T(\cdot) so that A(\lambda) is weakly T(\lambda)-coercive for all suitable \lambda, i.e. T(\lambda)^*A(\lambda) is a compact perturbation of a coercive operator.
Revised:  We construct a " test function operator function '' T(\cdot) so that A(\lambda) is weakly T(\lambda)-coercive for all suitable \lambda, i.e. T(\lambda)^*A(\lambda) is a compact perturbation of a coercive operator.
Edit intent: fluency
Original:  We construct a `` test function operator function '' T(\cdot) so that A(\lambda) is weakly T(\lambda)-coercive for all suitable \lambda, i.e. T(\lambda)^*A(\lambda) is a compact perturbation of a coercive operator.
Revised:  We construct a `` test function operator function " T(\cdot) so that A(\lambda) is weakly T(\lambda)-coercive for all suitable \lambda, i.e. T(\lambda)^*A(\lambda) is a compact perturbation of a coercive operator.
Edit intent: fluency
Original:  Convergent-cross mapping (CCM),  developed for deterministic dynamical systems, has been suggested as an alternative , although less grounded in statistical theory .
Revised:  Convergent-cross mapping (CCM), developed for deterministic dynamical systems, has been suggested as an alternative .
Edit intent: clarity
Original:  Here, we show that linear GC and CCM are able to uncover interactions with surprisingly similar performance, for predator-prey cycles, 2-species deterministic (chaotic) or stochastic competition, as well  10- and 20-species interaction networks.
Revised:  Here, we show that linear GC and CCM are able to uncover interactions with surprisingly similar performance, for predator-prey cycles, 2-species deterministic (chaotic) or stochastic competition, as well as 10- and 20-species interaction networks.
Edit intent: fluency
Original:  Our response is iCam, a runtime for autonomous cameras, that is capable of producing useful analytics results with frugal camera resources. iCam is built atop two novel techniques: (1) For the first time, iCam explores the joint tradeoff from both sampling strategy and wide selection of NN choices, and unifies the errors from both sources into one single bounded error.
Revised:  Our response is iCam, a runtime for autonomous cameras, that is capable of producing useful analytics results with frugal camera resources. iCam is built atop two novel techniques: (1) Elf explores the rich action space spanned by the number of sample image frames and the choice of per-frame object counters; it unifies errors from both sources into one single bounded error.
Edit intent: clarity
Original:  (2) Observing the disparate video characteristics across different timewindows, iCam employs a learning-based planner that judiciously decides the sampling action at runtime.
Revised:  (2) To decide count actions at run time, Elf employs a learning-based planner that judiciously decides the sampling action at runtime.
Edit intent: clarity
Original:  On typical embedded hardware, iCam continuously generates object counts that are only within 11\% of the true counts  .
Revised:  On typical embedded hardware, iCam continuously generates object counts within only 11\% of the true counts .
Edit intent: clarity
Original: When EAs are unlikely to locate precise global optimal solutions with satisfactory performances, it is important to substitute the hitting time/running time analysis with another available theoretical routine .
Revised: When EAs are unlikely to locate precise global optimal solutions with satisfactory performances, it is important to substitute the hitting time/running time .
Edit intent: clarity
Original:  In order to bring theories and applications closer , this paper is dedicated to perform an analysis on approximation error of EAs.
Revised:  In order to narrow the gap between theories and applications closer , this paper is dedicated to perform an analysis on approximation error of EAs.
Edit intent: clarity
Original:  In order to bring theories and applications closer , this paper is dedicated to perform an analysis on approximation error of EAs.
Revised:  In order to bring theories and applications , this paper is dedicated to perform an analysis on approximation error of EAs.
Edit intent: clarity
Original: When evolutionary algorithms (EAs) are unlikely to locate precise global optimal solutions with satisfactory performances, it is important to substitute alternative theoretical routine for the analysis of hitting time/running time .
Revised: When evolutionary algorithms (EAs) are unlikely to locate precise global optimal solutions with satisfactory performances, hitting time/running time .
Edit intent: clarity
Original: When random search heuristics (RSH) cannot locate precise globally optimal solutions with satisfactory performances, hitting time/running time analysis method is not flexible enough to accommodate the requirement of theoretical performance study .
Revised: When globally optimal solutions with satisfactory performances, hitting time/running time analysis method is not flexible enough to accommodate the requirement of theoretical performance study .
Edit intent: clarity