wanyu/IteraTeR_v2 huggingface dataset:
Original:  SRO is used to handle the experience inconsistency by decoupling the dynamics of the environment from the rewards to learn the option-value function under each agent's preference.
Revised:  SRO is used to handle the experience inconsistency by decoupling the dynamics of the environment from the rewards to learn the option-value under each agent's preference.
Edit intent: clarity
Original: Transfer Learning has shown great potential to enhance the single-agent Reinforcement Learning (RL) efficiency.
Revised: Transfer Learning has shown great potential to enhance single-agent Reinforcement Learning (RL) efficiency.
Edit intent: fluency
Original:  In this paper, we propose a novel Multiagent Option-based Policy Transfer (MAOPT) framework to improve MARL efficiency.
Revised:  In this paper, we propose a novel Multiagent Policy Transfer Framework (MAPTF) to improve MARL efficiency.
Edit intent: clarity
Original:  MAOPT learns what advice to provide and when to terminate it for each agent by modeling multiagent policy transfer as the option learning problem.
Revised:  MAOPT learns what advice to provide and when to terminate it by modeling multiagent policy transfer as the option learning problem.
Edit intent: clarity
Original:  The other is the local option advisor, which uses each agent's local experience when only each agent's local experiences can be obtained due to partial observability .
Revised:  The other is the local option advisor, which uses each agent's local experience when only each agent's local experiences for update due to the partial observability of the environment .
Edit intent: clarity
Original:  MAOPT can be easily combined with existing deep RL and MARL approaches, and experimental results show it significantly boosts the performance of existing methods in both discrete and continuous state spaces.
Revised:  MAPTF can be easily combined with existing deep RL and MARL approaches, and experimental results show it significantly boosts the performance of existing methods in both discrete and continuous state spaces.
Edit intent: clarity
Original: Despite progress in training neural networks for lossy image compression, current approaches fail to maintain both perceptual quality and high-level features at very low bitrates.
Revised: Despite progress in training neural networks for lossy image compression, current approaches fail to maintain both perceptual quality and abstract features at very low bitrates.
Edit intent: clarity
Original:  Encouraged by recent success in learning discrete representations with Vector Quantized Variational AutoEncoders (VQ-VAEs), we motivate the use of a hierarchy of VQ-VAEs to attain high factors of compression.
Revised:  Encouraged by recent success in learning discrete representations with Vector Quantized Variational Autoencoders (VQ-VAEs), we motivate the use of a hierarchy of VQ-VAEs to attain high factors of compression.
Edit intent: fluency
Original:  Our hierarchy produces a Markovian series of latent variables that reconstruct high-quality images which retain semantically meaningful features.
Revised:  Our hierarchy produces a Markovian series of latent variables that reconstruct images of high-perceptual quality which retain semantically meaningful features.
Edit intent: clarity
Original:  These latents can then be further used to generate realistic samples.
Edit intent: clarity
Original:  We provide qualitative and quantitative evaluations of reconstructions and samples on the CelebA and MNIST datasets.
Revised:  We provide qualitative and quantitative evaluations on the CelebA and MNIST datasets.
Edit intent: clarity
Original: Randomized smoothing is a recently proposed defense against adversarial attacks that has achieved state-of-the-art  provable robustness against \ell_2 perturbations.
Revised: Randomized smoothing is the current state-of-the-art provable robustness against \ell_2 perturbations.
Edit intent: clarity
Original:  however, for each geometry, substantial effort was needed to derive new robustness guarantees.
Revised:  however, substantial effort was needed to derive new robustness guarantees.
Edit intent: clarity
Original:  however, for each geometry, substantial effort was needed to derive new robustness guarantees.
Revised:  however, for each geometry, substantial effort was needed to derive such new guarantees.
Edit intent: clarity
Original:  In this work we propose a novel framework for devising and analyzing randomized smoothing schemes, and validate its effectiveness in practice.
Revised:  We propose a novel framework for devising and analyzing randomized smoothing schemes, and validate its effectiveness in practice.
Edit intent: clarity
Original:  Our theoretical contributions are as follows : (1) We show that for an appropriate notion of "optimal", the optimal smoothing distributions for any "nice" norm have level sets given by the  *Wulff Crystal* of that norm.
Revised:  Our theoretical contributions are : (1) We show that for an appropriate notion of "optimal", the optimal smoothing distributions for any "nice" norm have level sets given by the *Wulff Crystal* of that norm.
Edit intent: clarity
Original:  Our theoretical contributions are as follows : (1) We show that for an appropriate notion of "optimal", the optimal smoothing distributions for any "nice" norm have level sets given by the  *Wulff Crystal* of that norm.
Revised:  Our theoretical contributions are as follows : (1) we show that for an appropriate notion of "optimal", the optimal smoothing distributions for any "nice" norm have level sets given by the *Wulff Crystal* of that norm.
Edit intent: fluency
Original:  Our theoretical contributions are as follows : (1) We show that for an appropriate notion of "optimal", the optimal smoothing distributions for any "nice" norm have level sets given by the  *Wulff Crystal* of that norm.
Revised:  Our theoretical contributions are as follows : (1) We show that for an appropriate notion of "optimal", the optimal smoothing distributions for any "nice" norms have level sets given by the *Wulff Crystal* of that norm.
Edit intent: clarity
Original:  Our theoretical contributions are as follows : (1) We show that for an appropriate notion of "optimal", the optimal smoothing distributions for any "nice" norm have level sets given by the  *Wulff Crystal* of that norm.
Revised:  Our theoretical contributions are as follows : (1) We show that for an appropriate notion of "optimal", the optimal smoothing distributions for any "nice" norm have level sets given by the norm's *Wulff Crystal* of that norm.
Edit intent: clarity
Original:  Our theoretical contributions are as follows : (1) We show that for an appropriate notion of "optimal", the optimal smoothing distributions for any "nice" norm have level sets given by the  *Wulff Crystal* of that norm.
Revised:  Our theoretical contributions are as follows : (1) We show that for an appropriate notion of "optimal", the optimal smoothing distributions for any "nice" norm have level sets given by the *Wulff Crystal* ;
Edit intent: clarity
Original:  (2) We propose two novel and complementary methods for deriving provably robust radii for any smoothing distribution .
Revised:  (2) we propose two novel and complementary methods for deriving provably robust radii for any smoothing distribution .
Edit intent: fluency
Original:  On the other hand, using (3) , we show that , without more information than label statistics under random input perturbations, randomized smoothing cannot achieve nontrivial certified accuracy against perturbations of \ell_p-norm \Omega(\min(1, d^{\frac{1}{p} - \frac{1}{2}})), when the input dimension d is large.
Revised:  Meanwhile, we show using (3) , we show that , without more information than label statistics under random input perturbations, randomized smoothing cannot achieve nontrivial certified accuracy against perturbations of \ell_p-norm \Omega(\min(1, d^{\frac{1}{p} - \frac{1}{2}})), when the input dimension d is large.
Edit intent: coherence
Original: In this paper, we show that all finitary 1-truncated higher inductive types (HITs)  can be constructed from the groupoid quotient.
Revised: In this paper, we study finitary 1-truncated higher inductive types (HITs) can be constructed from the groupoid quotient.
Edit intent: clarity
Original:  We start by defining internally a notion of signatures for HITs, and for each signature, we construct a bicategory of algebras in 1-types and in groupoids.
Revised:  We define an internal notion of signatures for HITs, and for each signature, we construct a bicategory of algebras in 1-types and in groupoids.
Edit intent: coherence
Original:  We finish by constructing a biinitial object in the bicategory of algebras in groupoids  .
Revised:  Then we construct a biinitial object in the bicategory of algebras in groupoids .
Edit intent: clarity
Original: In this paper, we propose an efficient and accurate numerical method, which combine the high order adaptive virtual element method (VEM) and spectral deferred correction (SDC) scheme together, to simulate the self-consistent field theory (SCFT) model on arbitrary domains.
Revised: In this paper, we develop a high-order adaptive virtual element method (VEM) and spectral deferred correction (SDC) scheme together, to simulate the self-consistent field theory (SCFT) model on arbitrary domains.
Edit intent: clarity
Original: In this paper, we propose an efficient and accurate numerical method, which combine the high order adaptive virtual element method (VEM) and spectral deferred correction (SDC) scheme together, to simulate the self-consistent field theory (SCFT) model on arbitrary domains.
Revised: In this paper, we propose an efficient and accurate numerical method, which combine the high order adaptive virtual element method (VEM) to simulate the self-consistent field theory (SCFT) model on arbitrary domains.
Edit intent: clarity
Original: In this paper, we propose an efficient and accurate numerical method, which combine the high order adaptive virtual element method (VEM) and spectral deferred correction (SDC) scheme together, to simulate the self-consistent field theory (SCFT) model on arbitrary domains.
Revised: In this paper, we propose an efficient and accurate numerical method, which combine the high order adaptive virtual element method (VEM) and spectral deferred correction (SDC) scheme together, to simulate the self-consistent field theory (SCFT) model in arbitrary domains.
Edit intent: fluency
Original: In this note, we construct an algorithm that, on input of a description of a structurally stable planar dynamical flow  defined on the  unit disk, outputs the exact number of the (hyperbolic) equilibrium points as well the locations of all equilibriums with arbitrary precision .
Revised: In this note, we construct an algorithm that, on input of a description of a structurally stable planar dynamical flow defined on the unit disk, outputs the exact number of the (hyperbolic) equilibrium points and their locations with arbitrary accuracy .
Edit intent: clarity
Original:  As a consequence, we obtain a root-finding algorithm that computes the set of all zeros of a continuously differentiable function f defined on the  unit ball of R^{d} with arbitrary accuracy , provided that the Jacobian of f is invertible at each zero of f;
Revised:  As a consequence, we obtain a root-finding algorithm that computes the set of all zeros of a continuously differentiable function f defined on the unit ball of R^{d} , provided that the Jacobian of f is invertible at each zero of f;
Edit intent: clarity
Original:  Our model implementation is public and can be found at github.com/amanshenoy/multilogue-net
Edit intent: coherence
Original: Sentiment Analysis and Emotion Detection in conversation is key in a number of real-world applications, with different applications leveraging different kinds of data to be able to achieve reasonably accurate predictions.
Revised: Sentiment Analysis and Emotion Detection in conversation is key in several real-world applications, with different applications leveraging different kinds of data to be able to achieve reasonably accurate predictions.
Edit intent: clarity
Original:  in the conversation , and the relevance and relationship between the available modalities through an adequate fusion mechanism .
Revised:  in the conversation , and the relevance and relationship between the available modalities .
Edit intent: clarity
Original:  In this paper, we propose a recurrent neural network architecture that attempts to take into account all the mentioned drawbacks , and keeps track of the context of the conversation, interlocutor states, and the emotions conveyed by the speakers in the conversation .
Revised:  In this paper, we propose a recurrent neural network architecture that attempts to take into account all the mentioned drawbacks .
Edit intent: coherence
Original:  Our proposed model out performs the state of the art on two benchmark datasets on a variety of accuracy and regression metrics.
Revised:  Our proposed model out performs the state of the art on a benchmark dataset on a variety of accuracy and regression metrics.
Edit intent: clarity
Original:  Moreover, we demonstrate the advantages of such a model by providing a subexponential-time algorithm  solving the MaxCut problem on mixed unit interval graphs using our extended version of the bubble model .
Revised:  Moreover, we demonstrate the advantages of this generalized model by providing a subexponential-time algorithm solving the MaxCut problem on mixed unit interval graphs using our extended version of the bubble model .
Edit intent: clarity
Original:  Moreover, we demonstrate the advantages of such a model by providing a subexponential-time algorithm  solving the MaxCut problem on mixed unit interval graphs using our extended version of the bubble model .
Revised:  Moreover, we demonstrate the advantages of such a model by providing a subexponential-time algorithm for solving the MaxCut problem on mixed unit interval graphs using our extended version of the bubble model .
Edit intent: fluency
Original:  Moreover, we demonstrate the advantages of such a model by providing a subexponential-time algorithm  solving the MaxCut problem on mixed unit interval graphs using our extended version of the bubble model .
Revised:  Moreover, we demonstrate the advantages of such a model by providing a subexponential-time algorithm solving the MaxCut problem on mixed unit interval graphs .
Edit intent: clarity
Original:  In addition, it gives us a polynomial-time algorithm for specific mixed unit interval graphs ;
Revised:  In addition, we derive a polynomial-time algorithm for specific mixed unit interval graphs ;
Edit intent: clarity
Original:  Clique-width is one of the most general structural graph parameters, where a large group of natural problems is still solvable in the tracktable time when an efficient representation is given.
Revised:  Clique-width is one of the most general structural graph parameters, where a large group of natural problems is still solvable in the tractable time when an efficient representation is given.
Edit intent: clarity
Original:  Unfortunately, the exact computation of the clique-width representation is NP-hard \NP . Therefore, good upper-bounds on clique-width are highly appreciated  .
Revised:  Unfortunately, the exact computation of the clique-width representation is \NP . Therefore, good upper-bounds on clique-width are highly appreciated .
Edit intent: clarity
Original: Amdahl's Law is generating debates in the community of experts dealing with parallel processing since it was suggested.
Edit intent: coherence
Original:  The paper explains why Amdahl's Law shall be interpreted specifically for distributed parallel systems and why it generated so many debates, discussions  and abuses.
Revised:  The paper explains why Amdahl's Law shall be interpreted specifically for distributed parallel systems and why it generated so many debates, discussions , and abuses.
Edit intent: fluency
Original:  It is clarified that using the right interpretation of terms, Amdahl's Law is the governing law of all kinds of parallel processing.
Revised:  We clarify that when using the right interpretation of terms, Amdahl's Law is the governing law of all kinds of parallel processing.
Edit intent: clarity
Original:  To study the algorithm we first eliminate the coefficient from the Helmholtz equation using a change of variables.
Revised:  First, we eliminate the coefficient from the Helmholtz equation using a change of variables.
Edit intent: coherence
Original:  Then using a truncated Fourier expansion for the wave field we approximately reformulate the inverse problem as a system of quasilinear elliptic PDEs, which can be numerically solved by a  quasi-reversibility approach.
Revised:  Next, using a truncated Fourier expansion for the wave field we approximately reformulate the inverse problem as a system of quasilinear elliptic PDEs, which can be numerically solved by a quasi-reversibility approach.
Edit intent: fluency
Original:  The cost functional for the  quasi-reversibility method is constructed as a Tikhonov-like functional that involves a Carleman weight function .
Revised:  The cost functional for the quasi-reversibility method is constructed as a Tikhonov-like functional that involves a Carleman Weight Function .
Edit intent: fluency
Original:  Our numerical study shows that using a method of gradient descent type one can find the minimizer of this Tikhonov-like functional without any advanced a priori knowledge about it.
Revised:  Our numerical study shows that , using a version of the gradient descent method, one can find the minimizer of this Tikhonov-like functional without any advanced a priori knowledge about it.
Edit intent: clarity
Original:  Our numerical study shows that using a method of gradient descent type one can find the minimizer of this Tikhonov-like functional without any advanced a priori knowledge about it.
Revised:  Our numerical study shows that using a method of gradient descent type one can find the minimizer of this Tikhonov-like functional without any advanced a priori knowledge about it.
Edit intent: fluency
Original:  On the side of computational complexity, we show that computing a 1.152-optimal solution for guarding a perimeter or a region is NP-hard, \% i.e., the problem is hard to approximate.
Revised:  On the side of computational complexity, we show that computing a 1.152-optimal solution for guarding a perimeter or a region is NP-hard, i.e., the problem is hard to approximate.
Edit intent: coherence
Original:  Thus, a BS unit can act as a self-powered BS.
Revised:  Thus, a base station (BS) unit can act as a self-powered BS.
Edit intent: clarity
Original: The orthogonality dimension of a graph G=(V,E) over a field F is the smallest integer t for which there exists an assignment of a vector u_v \in F^t with \langle u_v,u_v \rangle \neq 0 to every vertex v \in V, such that \langle u_v, u_{v'} \rangle = 0 whenever v and v' are adjacent vertices in G. The study of the orthogonality dimension of graphs is motivated by various application in information theory and in theoretical computer science.
Revised: The orthogonality dimension of a graph G=(V,E) over a field F is the smallest integer t for which there exists an assignment of a vector u_v \in F^t with \langle u_v,u_v \rangle \neq 0 to every vertex v \in V, such that \langle u_v, u_{v'} \rangle = 0 whenever v and v' are adjacent vertices in G. The study of the orthogonality dimension of graphs is motivated by various applications in information theory and in theoretical computer science.
Edit intent: fluency
Original:  The contribution of the present work is two-folded .
Revised:  The contribution of the present work is two-fold .
Edit intent: fluency
Original:  We introduce an infinite-dimensional framework for high-resolution estimation of a random field from its low-resolution indirect measurements as well as the high-resolution measurements of training observations by merging the existing frameworks of generalized sampling and functional principal component analysis.
Revised:  We introduce an infinite-dimensional framework for high-resolution approximation of an unknown function from its low-resolution indirect measurements as well as the high-resolution measurements of training observations by merging the existing frameworks of generalized sampling and functional principal component analysis.
Edit intent: clarity
Original:  We introduce an infinite-dimensional framework for high-resolution estimation of a random field from its low-resolution indirect measurements as well as the high-resolution measurements of training observations by merging the existing frameworks of generalized sampling and functional principal component analysis.
Revised:  We introduce an infinite-dimensional framework for high-resolution estimation of a random field from its low-resolution indirect measurements as well as high-resolution measurements of training observations by merging the existing frameworks of generalized sampling and functional principal component analysis.
Edit intent: clarity
Original:  We introduce an infinite-dimensional framework for high-resolution estimation of a random field from its low-resolution indirect measurements as well as the high-resolution measurements of training observations by merging the existing frameworks of generalized sampling and functional principal component analysis.
Revised:  We introduce an infinite-dimensional framework for high-resolution estimation of a random field from its low-resolution indirect measurements as well as the high-resolution training observations by merging the existing frameworks of generalized sampling and functional principal component analysis.
Edit intent: clarity
Original:  We introduce an infinite-dimensional framework for high-resolution estimation of a random field from its low-resolution indirect measurements as well as the high-resolution measurements of training observations by merging the existing frameworks of generalized sampling and functional principal component analysis.
Revised:  We introduce an infinite-dimensional framework for high-resolution estimation of a random field from its low-resolution indirect measurements as well as the high-resolution measurements of training observations by merging the frameworks of generalized sampling and functional principal component analysis.
Edit intent: clarity
Original:   We study the statistical performance of the resulting estimation procedure and show that high-resolution recovery is indeed possible provided appropriate low-rank and angle conditions hold and provided the training set is sufficiently large relative to the desired resolution.
Revised:  We study the performance of the resulting estimation procedure and show that high-resolution recovery is indeed possible provided appropriate low-rank and angle conditions hold and provided the training set is sufficiently large relative to the desired resolution.
Edit intent: clarity
Original:  We also consider sparse representations of the principle components, which can reduce the required size of the training set  .
Revised:  Moreover, we show that the size of the training set .
Edit intent: coherence
Original:  Furthermore, the effectiveness of the proposed procedure is investigated in various numerical examples.
Revised:  Furthermore, the effectiveness of the proposed reconstruction procedure is illustrated by various numerical examples.
Edit intent: clarity
Original:  The key idea behind our approach is to tease apart---without annotation---the representations of linguistic content and speaker identity.
Revised:  The key idea behind our approach is to tease apart--without annotation--the representations of linguistic content and speaker identity.
Edit intent: fluency