wanyu/IteraTeR_v2 huggingface dataset:
Original:  In this paper, we consider temporal property graphs (TPGs) and propose temporal regular path queries ( TRPQ ) that incorporate time into TPGs navigation.
Revised:  In this paper, we consider temporal property graphs (TPGs) and propose temporal regular path queries ( TRPQ ) that incorporate time into TPG navigation.
Edit intent: fluency
Original:  Our work on the syntax, and the positive complexity results, pave the way to implementations of TRPQs that are both usable and practical .
Revised:  Finally, we implement a fragment of the language in a state-of-the-art dataflow framework, and experimentally demonstrate that TRPQ can be evaluated efficiently .
Edit intent: coherence
Original:  1620 models were evaluated using 5-foldcross-validation by loss and DICE.
Revised:  1620 models were evaluated using 5-fold cross-validation by loss and DICE.
Edit intent: fluency
Original: In this work we theoretically and experimentally analyze Multi-Agent Advantage Actor-Critic (MA2C) and Independent Advantage Actor-Critic (IA2C), two recently proposed multi-agent reinforcement learning methods that can be applied to control traffic signals in urban areas.
Revised: In this work we analyze Multi-Agent Advantage Actor-Critic (MA2C) and Independent Advantage Actor-Critic (IA2C), two recently proposed multi-agent reinforcement learning methods that can be applied to control traffic signals in urban areas.
Edit intent: clarity
Original: In this work we theoretically and experimentally analyze Multi-Agent Advantage Actor-Critic (MA2C) and Independent Advantage Actor-Critic (IA2C), two recently proposed multi-agent reinforcement learning methods that can be applied to control traffic signals in urban areas.
Revised: In this work we theoretically and experimentally analyze Multi-Agent Advantage Actor-Critic (MA2C) a recently proposed multi-agent reinforcement learning methods that can be applied to control traffic signals in urban areas.
Edit intent: clarity
Original: In this work we theoretically and experimentally analyze Multi-Agent Advantage Actor-Critic (MA2C) and Independent Advantage Actor-Critic (IA2C), two recently proposed multi-agent reinforcement learning methods that can be applied to control traffic signals in urban areas.
Revised: In this work we theoretically and experimentally analyze Multi-Agent Advantage Actor-Critic (MA2C) and Independent Advantage Actor-Critic (IA2C), two recently proposed multi-agent reinforcement learning algorithm that can be applied to control traffic signals in urban areas.
Edit intent: clarity
Original:  Moreover, we analyze the efficacy and the robustness of the methods experimentally by testing them in two traffic areas in the Bologna (Italy) area, simulated by SUMO, a software tool.
Revised:  Moreover, we analyze the efficacy and the robustness of the method by testing it in two traffic areas in the Bologna (Italy) area, simulated by SUMO, a software tool.
Edit intent: coherence
Original:  Moreover, we analyze the efficacy and the robustness of the methods experimentally by testing them in two traffic areas in the Bologna (Italy) area, simulated by SUMO, a software tool.
Revised:  Moreover, we analyze the efficacy and the robustness of the methods experimentally by testing them in two traffic areas located in Bologna (Italy) area, simulated by SUMO, a software tool.
Edit intent: clarity
Original:  Moreover, we analyze the efficacy and the robustness of the methods experimentally by testing them in two traffic areas in the Bologna (Italy) area, simulated by SUMO, a software tool.
Revised:  Moreover, we analyze the efficacy and the robustness of the methods experimentally by testing them in two traffic areas in the Bologna (Italy) simulated in SUMO, a software tool.
Edit intent: clarity
Original:  The experimental results indicate that MA2C achieves the best performance in the majority of cases, outperforms the alternative method considered, and displays sufficient stability during the learning process .
Revised:  The experimental results indicate that MA2C , trained with pseudo-random vehicle flows, is a promising technique able to outperform the alternative methods .
Edit intent: clarity
Original:  This sublattice is the linear, higher order analogue of an invariant manifold for a vector field.
Edit intent: coherence
Original: Quantization based model compression serves as high performing and fast approach for inference that yields highly compressed models compared to their full-precision floating point counterparts.
Revised: Quantization based model compression serves as high performing and fast approach for inference that yields models which are highly compressed when compared to their full-precision floating point counterparts.
Edit intent: clarity
Original:  This is achieved by approximating a multivariate binary state over the weights utilizing a deterministic and differentiable transformation of real-valued  continuous parameters.
Revised:  This is achieved by approximating a multivariate binary state over the weights utilizing a deterministic and differentiable transformation of real-valued , continuous parameters.
Edit intent: fluency
Original:  It is demonstrated that contrary to common assertions made in the literature,  binary weighted networks can train well with the same standard optimization techniques and similar hyperparameters settings as their full-precision counterparts, namely momentum SGD with large learning rates and L_2 regularization  .
Revised:  Contrary to common assertions made in the literature, binary weighted networks can train well with the same standard optimization techniques and similar hyperparameters settings as their full-precision counterparts, namely momentum SGD with large learning rates and L_2 regularization .
Edit intent: coherence
Original:  It is demonstrated that contrary to common assertions made in the literature,  binary weighted networks can train well with the same standard optimization techniques and similar hyperparameters settings as their full-precision counterparts, namely momentum SGD with large learning rates and L_2 regularization  .
Revised:  It is demonstrated that contrary to common assertions made in the literature, binary weighted networks can train well with the same standard optimization techniques and similar hyperparameter settings as their full-precision counterparts, namely momentum SGD with large learning rates and L_2 regularization .
Edit intent: fluency
Original:  It is demonstrated that contrary to common assertions made in the literature,  binary weighted networks can train well with the same standard optimization techniques and similar hyperparameters settings as their full-precision counterparts, namely momentum SGD with large learning rates and L_2 regularization  .
Revised:  It is demonstrated that contrary to common assertions made in the literature, binary weighted networks can train well with the same standard optimization techniques and similar hyperparameters settings as their full-precision counterparts, specifically momentum SGD with large learning rates and L_2 regularization .
Edit intent: fluency
Original: The multiple partners matching game is a cooperative profit-sharing game , which generalizes the classic matching game by allowing each player to have more than one partner.
Revised: The matching game is a cooperative profit-sharing game , which generalizes the classic matching game by allowing each player to have more than one partner.
Edit intent: clarity
Original:  The core is one of the most important concepts in cooperative game theory, which consists all possible ways of allocating the total profit of the game among individual players such that the grand coalition remains intact.
Revised:  The core is one of the most important concepts in cooperative game theory, which consists all possible ways of distributing the profit among individual players such that the grand coalition remains intact.
Edit intent: clarity
Original:  For the multiple partners matching game, the core may be empty in general [Deng et al., Algorithmic aspects of the core of combinatorial optimization games, Math.
Revised:  The core of multiple partners matching game, the core may be empty in general [Deng et al., Algorithmic aspects of the core of combinatorial optimization games, Math.
Edit intent: clarity
Original:  For the multiple partners matching game, the core may be empty in general [Deng et al., Algorithmic aspects of the core of combinatorial optimization games, Math.
Revised:  For the multiple partners matching games may be empty in general [Deng et al., Algorithmic aspects of the core of combinatorial optimization games, Math.
Edit intent: clarity
Original:  For the multiple partners matching game, the core may be empty in general [Deng et al., Algorithmic aspects of the core of combinatorial optimization games, Math.
Revised:  For the multiple partners matching game, the core may be empty [Deng et al., Algorithmic aspects of the core of combinatorial optimization games, Math.
Edit intent: clarity
Original:  Moreover, we show that the factor 2/3 is best possible in general, but can be improved depending on how severely constrained the players are .
Revised:  We also show that 2/3 is best possible in general, but can be improved depending on how severely constrained the players are .
Edit intent: clarity
Original:  Our result generalizes the recent work of Vazirani [Vazirani, The general graph matching game: approximate core, arXiv, 2021] from matching games to multiple partners matching games.
Revised:  Our result generalizes the work of Vazirani [Vazirani, The general graph matching game: approximate core, arXiv, 2021] from matching games to multiple partners matching games.
Edit intent: clarity
Original:  As a result, each SCC iteration only samples one random vector without having to compute all the orbitals.
Revised:  As a result, each SCF iteration only samples one random vector without having to compute all the orbitals.
Edit intent: clarity
Original:  We consider SCC iterations with damping and mixing , and we show with appropriate assumptions that the iterations converge in the mean-square sense, when the stochastic error has an almost sure bound.
Revised:  We consider the common practice of SCF iterations with damping and mixing , and we show with appropriate assumptions that the iterations converge in the mean-square sense, when the stochastic error has an almost sure bound.
Edit intent: clarity
Original:  We consider SCC iterations with damping and mixing , and we show with appropriate assumptions that the iterations converge in the mean-square sense, when the stochastic error has an almost sure bound.
Revised:  We consider SCC iterations with damping and mixing . We prove with appropriate assumptions that the iterations converge in the mean-square sense, when the stochastic error has an almost sure bound.
Edit intent: clarity
Original:  Otherwise, the convergence in probability is established .
Revised:  Otherwise, the convergence in probability .
Edit intent: clarity
Original: We present a new fast algorithm for computing the Boys function using  nonlinear approximation of the integrand via exponentials.
Revised: We present a new fast algorithm for computing the Boys function using a nonlinear approximation of the integrand via exponentials.
Edit intent: fluency
Original:  Specifically, we (1) fully describe the irreducible components of the zero-eigenvariety of a loose 3-hyperpath (its "nullvariety" ), (2) use recent results of Bao-Fan-Wang-Zhu to compute the corresponding algebraic multiplicity of zero (its "nullity" ), and then (3) for this special class of hypergraphs, verify a conjecture of Hu-Ye about the relationship between the geometric (multi-)dimension of the nullvariety and the nullity.
Revised:  Specifically, we (1) fully describe the irreducible components of the zero-eigenvariety of a loose 3-hyperpath (its ``nullvariety'' ), (2) use recent results of Bao-Fan-Wang-Zhu to compute the corresponding algebraic multiplicity of zero (its "nullity" ), and then (3) for this special class of hypergraphs, verify a conjecture of Hu-Ye about the relationship between the geometric (multi-)dimension of the nullvariety and the nullity.
Edit intent: fluency
Original:  Specifically, we (1) fully describe the irreducible components of the zero-eigenvariety of a loose 3-hyperpath (its "nullvariety" ), (2) use recent results of Bao-Fan-Wang-Zhu to compute the corresponding algebraic multiplicity of zero (its "nullity" ), and then (3) for this special class of hypergraphs, verify a conjecture of Hu-Ye about the relationship between the geometric (multi-)dimension of the nullvariety and the nullity.
Revised:  Specifically, we (1) fully describe the irreducible components of the zero-eigenvariety of a loose 3-hyperpath (its "nullvariety" ), (2) use recent results of Bao-Fan-Wang-Zhu to compute the corresponding algebraic multiplicity of zero (its ``nullity'' ), and then (3) for this special class of hypergraphs, verify a conjecture of Hu-Ye about the relationship between the geometric (multi-)dimension of the nullvariety and the nullity.
Edit intent: fluency
Original:  Specifically, we (1) fully describe the irreducible components of the zero-eigenvariety of a loose 3-hyperpath (its ``nullvariety'' ), (2) use recent results of Bao-Fan-Wang-Zhu to compute the corresponding algebraic multiplicity of zero (its ``nullity'' ), and then (3) for this special class of hypergraphs, verify a conjecture of Hu-Ye about the relationship between the geometric (multi-)dimension of the nullvariety and the nullity.
Revised:  Specifically, we (1) fully describe the irreducible components of the zero-eigenvariety of a loose 3-hyperpath (its "nullvariety" ), (2) use recent results of Bao-Fan-Wang-Zhu to compute the corresponding algebraic multiplicity of zero (its ``nullity'' ), and then (3) for this special class of hypergraphs, verify a conjecture of Hu-Ye about the relationship between the geometric (multi-)dimension of the nullvariety and the nullity.
Edit intent: fluency
Original:  Specifically, we (1) fully describe the irreducible components of the zero-eigenvariety of a loose 3-hyperpath (its ``nullvariety'' ), (2) use recent results of Bao-Fan-Wang-Zhu to compute the corresponding algebraic multiplicity of zero (its ``nullity'' ), and then (3) for this special class of hypergraphs, verify a conjecture of Hu-Ye about the relationship between the geometric (multi-)dimension of the nullvariety and the nullity.
Revised:  Specifically, we (1) fully describe the irreducible components of the zero-eigenvariety of a loose 3-hyperpath (its ``nullvariety'' ), (2) use recent results of Bao-Fan-Wang-Zhu to compute the corresponding algebraic multiplicity of zero (its "nullity" ), and then (3) for this special class of hypergraphs, verify a conjecture of Hu-Ye about the relationship between the geometric (multi-)dimension of the nullvariety and the nullity.
Edit intent: fluency
Original:  Our experimental results and ablation show that our proposed method outperforms the existing methods on real-world benchmark datasets  .
Revised:  Our experimental results and ablation show that our proposed method is competitive with the existing methods on real-world benchmark datasets .
Edit intent: clarity
Original: 6D grasping in cluttered scenes is a longstanding robotic manipulation problem .
Revised: 6D grasping in cluttered scenes is a longstanding problem in robotic manipulation .
Edit intent: clarity
Original:  Open-loop manipulation pipelines can fail due to modularity and error sensitivity while most end-to-end grasping policies with raw perception inputs have not yet scaled to complex scenes with obstacles.
Revised:  Open-loop manipulation pipelines may fail due to modularity and error sensitivity while most end-to-end grasping policies with raw perception inputs have not yet scaled to complex scenes with obstacles.
Edit intent: clarity
Original:  Open-loop manipulation pipelines can fail due to modularity and error sensitivity while most end-to-end grasping policies with raw perception inputs have not yet scaled to complex scenes with obstacles.
Revised:  Open-loop manipulation pipelines can fail due to inaccurate state estimation, while most end-to-end grasping policies with raw perception inputs have not yet scaled to complex scenes with obstacles.
Edit intent: clarity
Original:  Open-loop manipulation pipelines can fail due to modularity and error sensitivity while most end-to-end grasping policies with raw perception inputs have not yet scaled to complex scenes with obstacles.
Revised:  Open-loop manipulation pipelines can fail due to modularity and error sensitivity while most end-to-end grasping methods have not yet scaled to complex scenes with obstacles.
Edit intent: clarity
Original:  In this work, we propose a new method to close the gap through sampling and selecting plans in the latent space .
Revised:  In this work, we propose a new method for end-to-end learning of 6D grasping in cluttered scenes .
Edit intent: clarity
Original:  Our method learns an embedding space to represent expert grasping plans  and a variational autoencoder to sample diverse latent plans at inference time.
Revised:  We learn an embedding space to represent expert grasping plans and a variational autoencoder to sample diverse latent plans at inference time.
Edit intent: clarity
Original:  Our method learns an embedding space to represent expert grasping plans  and a variational autoencoder to sample diverse latent plans at inference time.
Revised:  Our method learns an embedding space to encode expert grasping plans and a variational autoencoder to sample diverse latent plans at inference time.
Edit intent: clarity
Original:  Our method learns an embedding space to represent expert grasping plans  and a variational autoencoder to sample diverse latent plans at inference time.
Revised:  Our method learns an embedding space to represent expert grasping plans during training and a variational autoencoder to sample diverse latent plans at inference time.
Edit intent: clarity
Original:  Furthermore, we train a latent plan critic for plan selection and an option classifier for switching to an instance grasping policy through hierarchical reinforcement learning.
Revised:  Furthermore, we train a critic network for plan selection and an option classifier for switching to an instance grasping policy through hierarchical reinforcement learning.
Edit intent: clarity
Original:  Surprisingly, up to date, there are no results related to the uniqueness of the optimal trading strategy.
Edit intent: coherence
Original:  A simple nonlinear example are given to demonstrate the efficiency of this framework.
Revised:  A simple nonlinear example is given to demonstrate the efficiency of this framework.
Edit intent: fluency
Original: In this paper, a new framework, named as graphical state space model, is proposed for the real time optimal estimation of one kind of nonlinear state space model.
Revised: In this paper, a new framework, named as graphical state space model, is proposed for the real time optimal estimation of a class of nonlinear state space model.
Edit intent: clarity
Original: This paper presents a new family of linear codes, namely the expanded Gabidulin codes  . Exploiting the existing fast decoder of Gabidulin codes, we propose an efficient algorithm to decode these new codes when the noise vector satisfies a certain condition.
Revised: This paper presents a new family of linear codes, namely the expanded Gabidulin codes . Exploiting the fast decoder of Gabidulin codes, we propose an efficient algorithm to decode these new codes when the noise vector satisfies a certain condition.
Edit intent: coherence
Original:  Furthermore , these new codes enjoy an excellent error-correcting capability because of the optimality of their parent Gabidulin codes.
Revised:  Additionally , these new codes enjoy an excellent error-correcting capability because of the optimality of their parent Gabidulin codes.
Edit intent: fluency
Original:  Furthermore , these new codes enjoy an excellent error-correcting capability because of the optimality of their parent Gabidulin codes.
Revised:  Furthermore , these new codes have an excellent error-correcting capability because of the optimality of their parent Gabidulin codes.
Edit intent: clarity
Original:  According to our analysis, both of these two cryptosystems can  resist the existing structural attacks.
Revised:  According to our analysis, these two cryptosystems can resist the existing structural attacks.
Edit intent: clarity
Original:  According to our analysis, both of these two cryptosystems can  resist the existing structural attacks.
Revised:  According to our analysis, both of these two cryptosystems can both resist the existing structural attacks.
Edit intent: clarity
Original:  Our proposals have an obvious advantage in public-key representation without using the cyclic or quasi-cyclic structure compared to some other code-based cryptosystems  .
Revised:  Furthermore, our proposals also have an obvious advantage in public-key representation without using the cyclic or quasi-cyclic structure compared to some other code-based cryptosystems .
Edit intent: coherence
Original: Deep image colorization networks often suffer from the color-bleeding artifact, a problematic color spreading near the boundaries between adjacent objects.
Revised: Deep neural networks for automatic image colorization often suffer from the color-bleeding artifact, a problematic color spreading near the boundaries between adjacent objects.
Edit intent: clarity
Original:  The color-bleeding artifacts debase the reality of generated outputs, limiting the applicability of colorization models on a practical application .
Revised:  Such color-bleeding artifacts debase the reality of generated outputs, limiting the applicability of colorization models on a practical application .
Edit intent: fluency
Original:  The color-bleeding artifacts debase the reality of generated outputs, limiting the applicability of colorization models on a practical application .
Revised:  The color-bleeding artifacts debase the reality of generated outputs, limiting the applicability of colorization models in practice .
Edit intent: clarity
Original:  Although previous approaches have tackled this problem in an automatic manner, they often generate imperfect outputs because their enhancements are available only in limited cases , such as having a high contrast of gray-scale value in an input image.
Revised:  Although previous approaches have attempted to address this problem in an automatic manner, they often generate imperfect outputs because their enhancements are available only in limited cases , such as having a high contrast of gray-scale value in an input image.
Edit intent: clarity
Original:  Although previous approaches have tackled this problem in an automatic manner, they often generate imperfect outputs because their enhancements are available only in limited cases , such as having a high contrast of gray-scale value in an input image.
Revised:  Although previous approaches have tackled this problem in an automatic manner, they tend to work only in limited cases , such as having a high contrast of gray-scale value in an input image.
Edit intent: clarity
Original:  Although previous approaches have tackled this problem in an automatic manner, they often generate imperfect outputs because their enhancements are available only in limited cases , such as having a high contrast of gray-scale value in an input image.
Revised:  Although previous approaches have tackled this problem in an automatic manner, they often generate imperfect outputs because their enhancements are available only in limited cases where a high contrast of gray-scale value in an input image.
Edit intent: clarity