wanyu/IteraTeR_v2 huggingface dataset:
Original:  We generalize the notion of lens by defining a category Lens _F for any category C and functor F : \colon C^{\rm op}\toCat, using a variant of the Grothendieck construction.
Revised:  We generalize the notion of lens by defining a category Lens _F for any category C and functor F \colon C^{\rm op}\toCat, using a variant of the Grothendieck construction.
Edit intent: coherence
Original:  Given n time windows to optimise, a maximum number of battery cycles C_{max first 'constrained' algorithm runs on a circuit of length O(p(n +%DIFDELCMD < \lfloor %%% \log_2 C_{max }%DIFDELCMD < \rfloor %%% + 1)) and needs O(n +%DIFDELCMD < \lfloor %%% \log_2 C_{max }%DIFDELCMD < \rfloor %%% + 1) qubits and enforces the constraint to be respected strictly .
Revised:  Given n time windows to optimise, a maximum number of battery cycles C_{max first 'constrained' %DIFDELCMD < \lfloor %%% \log_2 C_{max }%DIFDELCMD < \rfloor %%% + 1)) and needs O(n +%DIFDELCMD < \lfloor %%% \log_2 C_{max }%DIFDELCMD < \rfloor %%% + 1) qubits and enforces the constraint to be respected strictly .
Edit intent: clarity
Original:  Given n time windows to optimise, a maximum number of battery cycles C_{max first 'constrained' algorithm runs on a circuit of length O(p(n +%DIFDELCMD < \lfloor %%% \log_2 C_{max }%DIFDELCMD < \rfloor %%% + 1)) and needs O(n +%DIFDELCMD < \lfloor %%% \log_2 C_{max }%DIFDELCMD < \rfloor %%% + 1) qubits and enforces the constraint to be respected strictly .
Revised:  Given n time windows to optimise, a maximum number of battery cycles C_{max first 'constrained' algorithm runs on a circuit of length O(p(n +%DIFDELCMD < \lfloor %%% }%DIFDELCMD < \rfloor %%% + 1)) and needs O(n +%DIFDELCMD < \lfloor %%% \log_2 C_{max }%DIFDELCMD < \rfloor %%% + 1) qubits and enforces the constraint to be respected strictly .
Edit intent: fluency
Original:  Given n time windows to optimise, a maximum number of battery cycles C_{max first 'constrained' algorithm runs on a circuit of length O(p(n +%DIFDELCMD < \lfloor %%% \log_2 C_{max }%DIFDELCMD < \rfloor %%% + 1)) and needs O(n +%DIFDELCMD < \lfloor %%% \log_2 C_{max }%DIFDELCMD < \rfloor %%% + 1) qubits and enforces the constraint to be respected strictly .
Revised:  Given n time windows to optimise, a maximum number of battery cycles C_{max first 'constrained' algorithm runs on a circuit of length O(p(n +%DIFDELCMD < \lfloor %%% \log_2 C_{max }%DIFDELCMD < \rfloor %%% %DIFDELCMD < \lfloor %%% \log_2 C_{max }%DIFDELCMD < \rfloor %%% + 1) qubits and enforces the constraint to be respected strictly .
Edit intent: coherence
Original:  Given n time windows to optimise, a maximum number of battery cycles C_{max first 'constrained' algorithm runs on a circuit of length O(p(n +%DIFDELCMD < \lfloor %%% \log_2 C_{max }%DIFDELCMD < \rfloor %%% + 1)) and needs O(n +%DIFDELCMD < \lfloor %%% \log_2 C_{max }%DIFDELCMD < \rfloor %%% + 1) qubits and enforces the constraint to be respected strictly .
Revised:  Given n time windows to optimise, a maximum number of battery cycles C_{max first 'constrained' algorithm runs on a circuit of length O(p(n +%DIFDELCMD < \lfloor %%% \log_2 C_{max }%DIFDELCMD < \rfloor %%% + 1)) and needs O(n +%DIFDELCMD < \lfloor %%% }%DIFDELCMD < \rfloor %%% + 1) qubits and enforces the constraint to be respected strictly .
Edit intent: fluency
Original:  The second 'relaxed' algorithm is only of length O(p(\log  n)^3) and needs O(n \log n) qubits.
Revised:  The second 'relaxed' algorithm is only of length O(p(\log n)^3) and needing O(n \log n) qubits.
Edit intent: fluency
Original:  The results of the simulation on IBM's simulator illustrate an exponential improvement over the number of depth levels , with and without penalty, with a slight quality decrease with larger numbers of time windows .
Revised:  Simulations reveal an exponential improvement over the number of depth levels , with and without penalty, with a slight quality decrease with larger numbers of time windows .
Edit intent: clarity
Original:  In this work, we investigate how to promote inter-agent coordination  and discuss two possible avenues based respectively on inter-agent modelling and guided synchronized sub-policies .
Revised:  In this work, we investigate how to promote inter-agent coordination and discuss two possible avenues respectively based on inter-agent modelling and guided synchronized sub-policies .
Edit intent: fluency
Original:  In this work, we investigate how to promote inter-agent coordination  and discuss two possible avenues based respectively on inter-agent modelling and guided synchronized sub-policies .
Revised:  In this work, we investigate how to promote inter-agent coordination and discuss two possible avenues based respectively on inter-agent modelling and synchronized sub-policy selection .
Edit intent: clarity
Original:  We test each approach in four challenging continuous control tasks with sparse rewards and compare them against three variants of MADDPG, a state-of-the-art multi-agent reinforcement learning algorithm.
Revised:  We test each approach in four challenging continuous control tasks with sparse rewards and compare them against three baselines including MADDPG, a state-of-the-art multi-agent reinforcement learning algorithm.
Edit intent: clarity
Original: A central challenge in multi-agent reinforcement learning is the induction of coordination between agentsof a team.
Revised: In multi-agent reinforcement learning is the induction of coordination between agentsof a team.
Edit intent: clarity
Original:  We test each approach in four challenging continuous control tasks with sparse rewards and compare them against three baselines including MADDPG, a state-of-the-art multi-agent reinforcement learning algorithm.
Revised:  We evaluate each approach on four challenging continuous control tasks with sparse rewards and compare them against three baselines including MADDPG, a state-of-the-art multi-agent reinforcement learning algorithm.
Edit intent: clarity
Original:  To ensure a fair comparison, we rely on a thorough hyper-parameter selection and training methodology that allows a fixed hyper-parameter search budget for each algorithm and environment.
Revised:  To ensure a fair comparison, we rely on a thorough hyper-parameter search budget for each algorithm and environment.
Edit intent: coherence
Original:  We consequently assess both the hyper-parameter sensitivity, sample-efficiency and asymptotic performance of each learning method .
Revised:  We consequently assess both the hyper-parameter variations .
Edit intent: clarity
Original:  We further analyse the effects of the proposed regularizations on the behaviors learned by the agents .
Revised:  We further analyse the effects of our proposed methods on the policies that our agents learn and we show that our methods successfully enforce the qualities that we propose as proxies for coordinated behaviors .
Edit intent: clarity
Original:  Our experiments show that our methods significantly improve performance on cooperative multi-agent problems and scale well when the number of agents is increased .
Revised:  Our experiments show improved performance across many cooperative multi-agent problems and scale well when the number of agents is increased .
Edit intent: clarity
Original:  Our experiments show that our methods significantly improve performance on cooperative multi-agent problems and scale well when the number of agents is increased .
Revised:  Our experiments show that our methods significantly improve performance on cooperative multi-agent problems .
Edit intent: clarity
Original:  Finally, we quantitatively analyze the effects of our proposed methods on the policies that our agents learn and we show that our methods successfully enforce the qualities that we propose as proxies for coordinated behaviors.
Revised:  Finally, we analyze the effects of our proposed methods on the policies that our agents learn and we show that our methods successfully enforce the qualities that we propose as proxies for coordinated behaviors.
Edit intent: clarity
Original:  Finally, we quantitatively analyze the effects of our proposed methods on the policies that our agents learn and we show that our methods successfully enforce the qualities that we propose as proxies for coordinated behaviors.
Revised:  Finally, we quantitatively analyze the effects of our proposed methods on the policies that our agents learn and show that our methods successfully enforce the qualities that we propose as proxies for coordinated behaviors.
Edit intent: fluency
Original:  However, it is still suffering from several issues, i.e., low sample efficiency and lack of awareness of the video quality information.
Revised:  However, it typically suffers from several issues, i.e., low sample efficiency and lack of awareness of the video quality information.
Edit intent: clarity
Original:  As a proof of concept, OSMO is employed to describe a leading-edge application scenario of the TaLPas workflow management system  .
Revised:  As a proof of concept, OSMO is employed to describe a use case of the TaLPas workflow management system .
Edit intent: clarity
Original:  The heuristic produces relative prices for options, with for sole parameter the tail index alpha under some mild arbitrage constraints.
Revised:  The heuristic produces relative prices for options, with for sole parameter the tail index \alpha, under some mild arbitrage constraints.
Edit intent: fluency
Original: Herman et al. (2007, 2010) pointed out that the insertion of run-time checks into a gradually typed program could hamper tail-call optimization and, as a result, worsen the space complexity of the program.
Revised: Herman et al. pointed out that the insertion of run-time checks into a gradually typed program could hamper tail-call optimization and, as a result, worsen the space complexity of the program.
Edit intent: coherence
Original:  To address the problem, they proposed a space-efficient coercion calculus, which was subsequently improved by Garcia, et al. (2009) and Siek et al. (2015).
Revised:  To address the problem, they proposed a space-efficient coercion calculus, which was subsequently improved by Siek et al. (2015).
Edit intent: coherence
Original:  To address the problem, they proposed a space-efficient coercion calculus, which was subsequently improved by Garcia, et al. (2009) and Siek et al. (2015).
Revised:  To address the problem, they proposed a space-efficient coercion calculus, which was subsequently improved by Garcia, et al. (2009) and Siek et al. 
Edit intent: coherence
Original:  A program in coercion-passing style passes "the rest of  run-time checks" around---just like continuation-passing style (CPS), in which "the rest of  computation" has been passed around---and (unlike CPS) composes coercions eagerly.
Revised:  A program in coercion-passing style passes "the rest of the run-time checks" around---just like continuation-passing style (CPS), in which "the rest of computation" has been passed around---and (unlike CPS) composes coercions eagerly.
Edit intent: fluency
Original:  A program in coercion-passing style passes "the rest of  run-time checks" around---just like continuation-passing style (CPS), in which "the rest of  computation" has been passed around---and (unlike CPS) composes coercions eagerly.
Revised:  A program in coercion-passing style passes "the rest of run-time checks" around---just like continuation-passing style (CPS), in which "the rest of the computation" has been passed around---and (unlike CPS) composes coercions eagerly.
Edit intent: fluency
Original:  A program in coercion-passing style passes "the rest of  run-time checks" around---just like continuation-passing style (CPS), in which "the rest of  computation" has been passed around---and (unlike CPS) composes coercions eagerly.
Revised:  A program in coercion-passing style passes "the rest of run-time checks" around---just like continuation-passing style (CPS), in which "the rest of computation" is passed around---and (unlike CPS) composes coercions eagerly.
Edit intent: clarity
Original: Queuing systems with redundant requests have drawn great attention because of their promise to reduce the job completion time and its variability.
Revised: Queuing systems with redundant requests have drawn great attention because of their promise to reduce the job completion time and variability.
Edit intent: clarity
Original:  Despite a large body of work on this topic, we are still far from fully understanding the benefits of redundancy in practice.
Revised:  Despite a large body of work on the topic, we are still far from fully understanding the benefits of redundancy in practice.
Edit intent: fluency
Original:  Such distributions have been observed in practical systems , as can be seen in  Google cluster traces.
Revised:  Such distributions have been observed in practice , as can be seen in Google cluster traces.
Edit intent: clarity
Original:  Such distributions have been observed in practical systems , as can be seen in  Google cluster traces.
Revised:  Such distributions have been observed in practical systems , as can be seen in , e.g., Google cluster traces.
Edit intent: clarity
Original:  In particular, we introduce new performance metrics in the analogous model, and argue that they are good indicators of the queuing time performance of non-adaptive scheduling policies.
Revised:  We introduce new performance metrics in the analogous model, and argue that they are good indicators of the queuing time performance of non-adaptive scheduling policies.
Edit intent: coherence
Original:  In particular, we introduce new performance metrics in the analogous model, and argue that they are good indicators of the queuing time performance of non-adaptive scheduling policies.
Revised:  In particular, we introduce new performance indicators in the analogous model, and argue that they are good indicators of the queuing time performance of non-adaptive scheduling policies.
Edit intent: clarity
Original:  In particular, we introduce new performance metrics in the analogous model, and argue that they are good indicators of the queuing time performance of non-adaptive scheduling policies.
Revised:  In particular, we introduce new performance metrics in the analogous model, and argue that they are good predictors of the queuing time performance of non-adaptive scheduling policies.
Edit intent: clarity
Original:  In particular, we introduce new performance metrics in the analogous model, and argue that they are good indicators of the queuing time performance of non-adaptive scheduling policies.
Revised:  In particular, we introduce new performance metrics in the analogous model, and argue that they are good indicators of the queuing time in non-adaptive scheduling policies.
Edit intent: clarity
Original:  We then propose a new non-adaptive scheduling policy that is based on combinatorial designs, and show that it improves our performance metrics.
Revised:  We then propose a non-adaptive scheduling policy that is based on combinatorial designs, and show that it improves our performance metrics.
Edit intent: clarity
Original:  We observe in simulation that the proposed scheduling policy, as the performance metrics indicate , reduces the queuing times up to 25\% compared to random scheduling and up to 100\% compared round-robin scheduling.
Revised:  We observe in simulation that the proposed scheduling policy, as the performance metrics indicate , reduces the queuing times up to 25\% compared to random and round-robin scheduling.
Edit intent: clarity
Original:  The theory developed in this paper  requires only the number of trainable parameters to increase linearly as the number of training samples increases.
Revised:  The theory developed in this paper requires the number of trainable parameters to increase linearly as the number of training samples increases.
Edit intent: clarity
Original: We construct an epidemic model for the transmission of dengue fever with  early-life stage in the vector dynamics and age-structure within hosts.
Revised: We construct an epidemic model for the transmission of dengue fever with an early-life stage in the vector dynamics and age-structure within hosts.
Edit intent: fluency
Original:  Although, in recent years, extensive studies have been carried out about images based RDH-ED, little attention is paid to RDH-ED in 3D mesh models due to its complex data structure and irregular geometry.
Revised:  Although, in recent years, extensive studies have been carried out about images based RDH-ED, little attention is paid to RDH-ED in 3D meshes due to its complex data structure and irregular geometry.
Edit intent: clarity
Original:  We propose a separable RDH-ED method for 3D mesh models based on MSB ( most significant bit) prediction.
Revised:  In this paper, we propose a separable RDH-ED method for 3D mesh models based on MSB ( most significant bit) prediction.
Edit intent: clarity
Original:  Then, bit-stream encryption is used to encrypt the mesh . Finally,  data is embedded by replacing the MSB of the encrypted vertex coordinates of the "embedded" set by the additional data bits.
Revised:  Then, bit-stream encryption technique will be executed . Finally, data is embedded by replacing the MSB of the encrypted vertex coordinates of the "embedded" set by the additional data bits.
Edit intent: clarity
Original:  Then, bit-stream encryption is used to encrypt the mesh . Finally,  data is embedded by replacing the MSB of the encrypted vertex coordinates of the "embedded" set by the additional data bits.
Revised:  Then, bit-stream encryption is used to encrypt the mesh . Finally, additional data is embedded by replacing the MSB of the encrypted vertex coordinates of the "embedded" set by the additional data bits.
Edit intent: clarity
Original:  Then, bit-stream encryption is used to encrypt the mesh . Finally,  data is embedded by replacing the MSB of the encrypted vertex coordinates of the "embedded" set by the additional data bits.
Revised:  Then, bit-stream encryption is used to encrypt the mesh . Finally, data is embedded by replacing the Multi-MSB of the encrypted vertex coordinates of the "embedded" set by the additional data bits.
Edit intent: clarity
Original:  Experimental results show that the proposed method has higher embedding capacity and higher quality of the recovered meshes compared to the existing RDH-ED method for 3D meshes based on symmetric encryption .
Revised:  Experimental results show that the proposed method has higher embedding capacity and higher quality of the recovered meshes compared to the state-of-art methods .
Edit intent: clarity
Original:  The method relies on implicit representations of the coboundary operator and of the filtration order of the simplices, avoiding the explicit construction and storage of the filtration coboundary matrix  .
Revised:  The method relies on implicit representations of the coboundary operator and the filtration order of the simplices, avoiding the explicit construction and storage of the filtration coboundary matrix .
Edit intent: fluency
Original: A collection of U \: (\in N) data vectors is called a U-tuple, and the association strength among the vectors of a tuple is termed as the hyperlink weight , that is assumed to be symmetric with respect to permutation of the entries in the index.
Revised: A collection of U \: (\in N) data vectors is called a U-tuple, and the association strength among the vectors of a tuple is termed as the hyperlink weight , that is assumed to be symmetric with respect to permutation of the entries in the index.
Edit intent: fluency
Original:  BHLR is based on Bregman divergence (BD) and encompasses various existing methods  such as logistic regression (U=1), Poisson regression (U=1),  graph embedding (U=2), matrix factorization (U=2), tensor factorization (U \geq 2), and their variants equipped with arbitrary BD.
Revised:  BHLR is based on Bregman divergence (BD) and encompasses various existing methods , such as logistic regression (U=1), Poisson regression (U=1), graph embedding (U=2), matrix factorization (U=2), tensor factorization (U \geq 2), and their variants equipped with arbitrary BD.
Edit intent: fluency
Original:  We demonstrate that, regardless of the choice of BD and U \in N , the proposed BHLR is generally (P-1)
Revised:  We demonstrate that, regardless of the choice of BD and U \in N is (P-1)
Edit intent: clarity
Original:  robust against the distributional misspecification , that is, it asymptotically recovers the underlying true conditional expectation of hyperlink weights given data vectors regardless of its conditional distribution , and (P-2) computationally tractable, that is, it is efficiently computed by stochastic optimization algorithms using a novel generalized minibatch sampling procedure for hyper-relational data.
Revised:  statistically consistent , that is, it asymptotically recovers the underlying true conditional expectation of hyperlink weights given data vectors regardless of its conditional distribution , and (P-2) computationally tractable, that is, it is efficiently computed by stochastic optimization algorithms using a novel generalized minibatch sampling procedure for hyper-relational data.
Edit intent: clarity
Original:  robust against the distributional misspecification , that is, it asymptotically recovers the underlying true conditional expectation of hyperlink weights given data vectors regardless of its conditional distribution , and (P-2) computationally tractable, that is, it is efficiently computed by stochastic optimization algorithms using a novel generalized minibatch sampling procedure for hyper-relational data.
Revised:  robust against the distributional misspecification , that is, it asymptotically recovers the underlying true conditional expectation of hyperlink weights given data vectors , and (P-2) computationally tractable, that is, it is efficiently computed by stochastic optimization algorithms using a novel generalized minibatch sampling procedure for hyper-relational data.
Edit intent: clarity
Original: Many real networks in  social, biological or computer sciences have an inherent structure of a simplicial complex, which reflects the multi interactions among agents (and groups of agents) and constitutes the basics of Topological Data Analysis.
Revised: Many real networks in the social, biological or computer sciences have an inherent structure of a simplicial complex, which reflects the multi interactions among agents (and groups of agents) and constitutes the basics of Topological Data Analysis.
Edit intent: fluency
Original:  We propose new notions of higher order lower, upper and generalised adjacency degrees for simplices in a simplicial complex, allowing any dimensional comparison among them and their faces .
Revised:  We propose new notions of higher-order degrees of adjacency for simplices in a simplicial complex, allowing any dimensional comparison among them and their faces .
Edit intent: clarity
Original:  New multi parameter boundary and coboundary operators in an oriented simplicial complex are also given and a novel multi combinatorial Laplacian is defined .
Revised:  New multi parameter boundary and coboundary operators in an oriented simplicial complex and also a novel multi-combinatorial Laplacian is defined .
Edit intent: coherence
Original:  The results confirm that the proposed audio-visual CVAE effectively fuse audio and visual information, and it improves the speech enhancement performance compared with the audio-only VAE model, especially when the speech signal is highly corrupted by noise.
Revised:  The results confirm that the proposed audio-visual CVAE effectively fuses audio and visual information, and it improves the speech enhancement performance compared with the audio-only VAE model, especially when the speech signal is highly corrupted by noise.
Edit intent: fluency