wanyu/IteraTeR_v2 huggingface dataset:
Original:  Note that optimizing multiple recommendation strategies jointly faces two challenges in  existing model-free RL model \mbox{ feng2018learning - (i) it requires huge amounts of user behavior data, and (ii) the distribution of reward (users' feedback) are extremely unbalanced.
Revised:  Note that optimizing multiple recommendation strategies jointly faces two challenges in the existing model-free RL model \mbox{ feng2018learning - (i) it requires huge amounts of user behavior data, and (ii) the distribution of reward (users' feedback) are extremely unbalanced.
Edit intent: fluency
Original:  Note that optimizing multiple recommendation strategies jointly faces two challenges in  existing model-free RL model \mbox{ feng2018learning - (i) it requires huge amounts of user behavior data, and (ii) the distribution of reward (users' feedback) are extremely unbalanced.
Revised:  Note that optimizing multiple recommendation strategies jointly faces two challenges in existing model-free RL model - (i) it requires huge amounts of user behavior data, and (ii) the distribution of reward (users' feedback) are extremely unbalanced.
Edit intent: coherence
Original:  In this paper, we introduce model-based reinforcement learning techniques to reduce the training data requirement and execute more accurate strategy updates.
Revised:  In this paper, we introduce model-based RL techniques to reduce the training data requirement and execute more accurate strategy updates.
Edit intent: clarity
Original:  The problem investigated in this paper arises in different applications such as impulsive noise cancellation from imagesand audios, and decomposition of low-rank and sparse components of matrices  .
Revised:  The problem investigated in this paper arises in different applications such as impulsive noise removal from images, audios and videos, decomposition of low-rank and sparse components of matrices .
Edit intent: clarity
Original:  The convergence analysis of the algorithm is also provided.
Revised:  The analysis of the algorithm is also provided.
Edit intent: clarity
Original:  Simulation results show that our algorithms is simple and fast, and it outperforms the other state-of-the-art methods in terms of reconstruction quality and/or complexity.
Revised:  Simulation results show that our algorithms is simple and fast, and it outperforms other state-of-the-art methods in terms of reconstruction quality and/or complexity.
Edit intent: fluency
Original:  Our experiment results indicate that our proposal manages to avoid bogus message spread, and a vehicle in our framework has to contribute to the traffic event detection to normally employ the traffic service.
Revised:  Our experiment results indicate that our proposal manages to avoid bogus event spread, and a vehicle in our framework has to contribute to the traffic event detection to normally employ the traffic service.
Edit intent: clarity
Original: Using an existing classification results for the 7- and 8-cycles in the pancake graph, we determine the number of permutations that require 4 pancake flips (prefix reversals) to be sorted.
Revised: Using existing classification results for the 7- and 8-cycles in the pancake graph, we determine the number of permutations that require 4 pancake flips (prefix reversals) to be sorted.
Edit intent: fluency
Original:  A similar characterization of the 8-cycles in the burnt pancake graph, due to the authors, is used to derive a formula for the number of signed permutations requiring 4  pancake flips to be sorted.
Revised:  A similar characterization of the 8-cycles in the burnt pancake graph, due to the authors, is used to derive a formula for the number of signed permutations requiring 4 (burnt) pancake flips to be sorted.
Edit intent: clarity
Original:  However, there is no theory defining the maximization performance in more realistic networks where edges are heterogeneously distributed within and between communities.
Revised:  However, there is no theory bounding the maximization performance in more realistic networks where edges are heterogeneously distributed within and between communities.
Edit intent: clarity
Original:  We establish the asymptotic theoretical bounds on the resolution parameter of generalized modularity using the random graph properties .
Revised:  Using the random graph properties, we establish asymptotic theoretical bounds on the resolution parameter of generalized modularity using the random graph properties .
Edit intent: fluency
Original:  Given a network produced by the stochastic block models, the communities for which the resolution parameter is larger than their densities are likely to be spread among multiple clusters ;
Revised:  Given a network produced by the stochastic block models, the communities for which the resolution parameter is larger than their densities are likely to be spread among multiple clusters ,
Edit intent: fluency
Original:  while communities for which the resolution parameter is smaller than their background inter-community edge density get merged into one large component.
Revised:  while communities for which the resolution parameter is smaller than their background inter-community edge density will be merged into one large component.
Edit intent: clarity
Original:  For such networks, we propose a progressive agglomerative heuristic algorithm to detect statistically significant communities at multiple scales.
Revised:  For such networks, we propose a progressive agglomerative heuristic algorithm to detect practically significant communities at multiple scales.
Edit intent: clarity
Original:  This particular problem was first studied in Dru13 and referred to as the "density prediction game".
Revised:  This particular problem was first studied in Drucker (2013) and referred to as the "density prediction game".
Edit intent: clarity
Original: A large proportion of the basepairs in the long reads that third-generation sequencing technologies produce possess sequencing errors .
Revised: A large proportion of bps in these long reads are incorrectly identified .
Edit intent: clarity
Original:  Assembly polishing algorithms minimize  error propagation by polishing or fixing errors in the assembly by using information from alignments between reads and the assembly (i.e., read-to-assembly alignment  ).
Revised:  Assembly polishing algorithms minimize such error propagation by polishing or fixing errors in the assembly by using information from alignments between reads and the assembly (i.e., read-to-assembly alignment ).
Edit intent: clarity
Original:  Assembly polishing algorithms minimize  error propagation by polishing or fixing errors in the assembly by using information from alignments between reads and the assembly (i.e., read-to-assembly alignment  ).
Revised:  Assembly polishing algorithms minimize error propagation by polishing or fixing errors in the assembly by using information from alignments between reads and the assembly (i.e., read-to-assembly alignment information ).
Edit intent: clarity
Original:  However, current assembly polishing algorithms can only polish an assembly using reads either from a certain sequencing technology or from a small genome.
Revised:  However, assembly polishing algorithms can only polish an assembly using reads either from a certain sequencing technology or from a small genome.
Edit intent: clarity
Original:  This technology and genome-size dependency prevents assembly polishing algorithms from either (1) using all the available read sets from multiple sequencing technologies or (2) polishing large genomes.
Revised:  This technology and genome-size dependency prevents assembly polishing algorithms from either (1) using all the available read sets and polish large genomes.
Edit intent: clarity
Original:  We introduce Apollo, a new assembly polishing algorithm that can 1) scale to polish assemblies of large genomes and 2) use multiple sets of reads from any sequencing technology to polish an assembly.
Revised:  We introduce Apollo, a universal assembly polishing algorithm that can 1) scale to polish assemblies of large genomes and 2) use multiple sets of reads from any sequencing technology to polish an assembly.
Edit intent: clarity
Original:  Our goal is to provide a single algorithm that uses read sets from all  sequencing technologies to polish assemblies and that can polish large genomes.
Revised:  Our goal is to provide a single algorithm that uses read sets from all available sequencing technologies to polish assemblies and that can polish large genomes.
Edit intent: clarity
Original:  Our experiments with real read sets demonstrate that 1)
Revised:  Our experiments with real read sets demonstrate that 
Edit intent: clarity
Original:  Apollo is the only algorithm that can use reads from multiple sequencing technology within a single run and that can polish an assembly of any size, 2) using reads from multiple sequencing technologies produces a more accurate assembly compared to using reads from a single sequencing technology, and 3) Apollo performs better than or comparable to the state-of-the-art algorithms in terms of accuracy even when using reads from a single sequencing technology .
Revised:  Apollo is the only algorithm that 1) uses reads from any sequencing technology within a single run and that can polish an assembly of any size, 2) using reads from multiple sequencing technologies produces a more accurate assembly compared to using reads from a single sequencing technology, and 3) Apollo performs better than or comparable to the state-of-the-art algorithms in terms of accuracy even when using reads from a single sequencing technology .
Edit intent: clarity
Original:  Apollo is the only algorithm that can use reads from multiple sequencing technology within a single run and that can polish an assembly of any size, 2) using reads from multiple sequencing technologies produces a more accurate assembly compared to using reads from a single sequencing technology, and 3) Apollo performs better than or comparable to the state-of-the-art algorithms in terms of accuracy even when using reads from a single sequencing technology .
Revised:  Apollo is the only algorithm that can use reads from multiple sequencing technology within a single run and 2) using reads from multiple sequencing technologies produces a more accurate assembly compared to using reads from a single sequencing technology, and 3) Apollo performs better than or comparable to the state-of-the-art algorithms in terms of accuracy even when using reads from a single sequencing technology .
Edit intent: coherence
Original:  Kinetic equations model transport and collisions of particles in a position-velocity phase-space.
Revised:  Kinetic equations model transport and collision of particles in a position-velocity phase-space.
Edit intent: fluency
Original:  We describe how to achieve the necessary correlation between simulation paths at different levels and demonstrate the potential of the approach via computational experiments.
Revised:  We describe how to achieve the necessary correlation between simulation paths at different levels and demonstrate the potential of the approach via numerical experiments.
Edit intent: clarity
Original: We present a sound and complete method to generate inductive invariants consisting of polynomial inequalities for programs with polynomial updates.
Revised: We consider the classical problem of invariant generation for programs with polynomial updates.
Edit intent: clarity
Original:  We also present experimental results on several academic examples that require polynomial invariants .
Revised:  We also present experimental results on several academic benchmarks .
Edit intent: clarity
Original: Given a string S of n integers in [0,\sigma), a range minimum query RMQ (i, j) asks for the index of the smallest integer in S[i \dots j].
Revised: Given a string S of n integers in [0,\sigma), a range minimum query RMQ (i, j) asks for the index of the smallest integer in S[i \dots j].
Edit intent: fluency
Original:  In this paper we show how to preprocess S into a %DIFDELCMD < {\em %%% compressed representation that allows fast range minimum queries.
Revised:  In this paper we show how to preprocess S into a %DIFDELCMD < {\em %%% compressed representation that allows fast range minimum queries.
Edit intent: fluency
Original:  This allows for %DIFDELCMD < {\em %%% sublinear size data structures with logarithmic query time.
Revised:  This allows for %DIFDELCMD < {\em %%% sublinear size data structures with logarithmic query time.
Edit intent: fluency
Original:  We investigate this approach using grammar compression.
Revised:  We investigate this approach in the context of grammar compression.
Edit intent: clarity
Original:  A scoring functions should be (strictly) consistent for the functional of interest, that is, the expected score should be minimised by the correctly specified functional value.
Revised:  A scoring function should be (strictly) consistent for the functional of interest, that is, the expected score should be minimised by the correctly specified functional value.
Edit intent: fluency
Original:  We first develop a general lower bound argument for estimation problems with differential privacy constraints, and then apply the lower bound argument to mean estimation and linear regression .
Revised:  We first develop a general lower bound argument for minimax risks with differential privacy constraints, and then apply the lower bound argument to mean estimation and linear regression .
Edit intent: clarity
Original:  We first develop a general lower bound argument for estimation problems with differential privacy constraints, and then apply the lower bound argument to mean estimation and linear regression .
Revised:  We first develop a general lower bound argument for estimation problems with differential privacy constraints, and apply this argument to high-dimensional mean estimation and linear regression .
Edit intent: clarity
Original:  For these statistical problems, we also design computationally efficient algorithms that match the minimax lower bound up to a logarithmic factor.
Revised:  For these statistical problems, we also design computationally efficient algorithms that attain the minimax lower bound up to a logarithmic factor.
Edit intent: clarity
Original:  For these statistical problems, we also design computationally efficient algorithms that match the minimax lower bound up to a logarithmic factor.
Revised:  For these statistical problems, we also design computationally efficient algorithms that match the minimax lower bounds up to a logarithmic factor.
Edit intent: fluency
Original:  Inspired by the theoretical computer science literature on "tracing adversaries" , we formulate a general lower bound argument for minimax risks with differential privacy constraints, and apply this argument to high-dimensional mean estimation and linear regression problems.
Revised:  Inspired by the theoretical computer science literature , we formulate a general lower bound argument for minimax risks with differential privacy constraints, and apply this argument to high-dimensional mean estimation and linear regression problems.
Edit intent: clarity
Original:  However, a systemic investigation of the relationship between online attention and market dynamics, across multiple digital currencies, is still lacking.
Revised:  However, a systematic investigation of the relationship between online attention and market dynamics, across multiple digital currencies, is still lacking.
Edit intent: fluency
Original:  Several tests on a kinetic alignment model with self propulsion validate the proposed methods both in the homogeneous and inhomogeneous setting, shading light on the influence of uncertainties in phase transition phenomena driven by noise such as their smoothing and confidence bands .
Revised:  Several tests on a kinetic alignment model with self propulsion validate the proposed methods both in the homogeneous and inhomogeneous setting, shading light on the influence of uncertainties in phase transition phenomena driven by noise such as their smoothing and confidence band .
Edit intent: fluency
Original:  Selfish nodes launching such attacks acquire unduly high quality of service (QoS) by assigning higher priority to source packets and lower priority to transit packets.
Revised:  Selfish nodes launching such attacks receive unjustifiably high quality of service (QoS) by assigning higher priority to source packets and lower priority to transit packets.
Edit intent: clarity
Original:  We present a formal model of opportunistic plausible TRAs and the corresponding one-shot  non-cooperative game . Using a heuristic rank-based payoff function, we propose a boundedly rational multistage attack strategy  that both selfish and non-selfish nodes are free to use, and that allows non-selfish nodes to respond in kind to TRAs.
Revised:  We present a formal model of plausible opportunistic TRAs and the corresponding one-shot non-cooperative game . Using a heuristic rank-based payoff function, we propose a boundedly rational multistage attack strategy that both selfish and non-selfish nodes are free to use, and that allows non-selfish nodes to respond in kind to TRAs.
Edit intent: fluency
Original:  We present a formal model of opportunistic plausible TRAs and the corresponding one-shot  non-cooperative game . Using a heuristic rank-based payoff function, we propose a boundedly rational multistage attack strategy  that both selfish and non-selfish nodes are free to use, and that allows non-selfish nodes to respond in kind to TRAs.
Revised:  We present a formal model of opportunistic plausible TRAs and the corresponding one-shot and multistage non-cooperative game . Using a heuristic rank-based payoff function, we propose a boundedly rational multistage attack strategy that both selfish and non-selfish nodes are free to use, and that allows non-selfish nodes to respond in kind to TRAs.
Edit intent: clarity
Original:  We present a formal model of opportunistic plausible TRAs and the corresponding one-shot  non-cooperative game . Using a heuristic rank-based payoff function, we propose a boundedly rational multistage attack strategy  that both selfish and non-selfish nodes are free to use, and that allows non-selfish nodes to respond in kind to TRAs.
Revised:  We present a formal model of opportunistic plausible TRAs and the corresponding one-shot non-cooperative games . Using a heuristic rank-based payoff function, we propose a boundedly rational multistage attack strategy that both selfish and non-selfish nodes are free to use, and that allows non-selfish nodes to respond in kind to TRAs.
Edit intent: fluency
Original:  Finally, we determine whether boundedly rational nodes are likely to follow alternative multistage behavior rather than the proposed multistage strategy .
Revised:  Therefore, REST can be considered an effective countermeasure to TRAs in multi-hop networks .
Edit intent: coherence
Original: Multi-hop ad hoc networks are susceptible to selfish misbehavior such as traffic remapping attacks (TRAs).
Revised: Multi-hop wireless networks with autonomous nodes are susceptible to selfish misbehavior such as traffic remapping attacks (TRAs).
Edit intent: clarity
Original: Multi-hop ad hoc networks are susceptible to selfish misbehavior such as traffic remapping attacks (TRAs).
Revised: Multi-hop ad hoc networks are susceptible to selfish traffic remapping attacks (TRAs).
Edit intent: clarity
Original:  Selfish nodes launching such attacks receive unjustifiably high quality of service (QoS) by assigning higher priority to source packets and lower priority to transit packets . TRAs are easy to execute, impossible to prevent, difficult to detect, and detrimental to the QoS of non-selfish nodes.
Revised:  Selfish nodes launching such attacks receive unjustifiably high quality of service (QoS) for packet flows traversing source-to-destination routes . TRAs are easy to execute, impossible to prevent, difficult to detect, and detrimental to the QoS of non-selfish nodes.
Edit intent: clarity
Original:  Selfish nodes launching such attacks receive unjustifiably high quality of service (QoS) by assigning higher priority to source packets and lower priority to transit packets . TRAs are easy to execute, impossible to prevent, difficult to detect, and detrimental to the QoS of non-selfish nodes.
Revised:  Selfish nodes launching such attacks receive unjustifiably high quality of service (QoS) by assigning higher priority to source packets and lower priority to transit packets . TRAs are easy to execute, impossible to prevent, difficult to detect, and harmful to the QoS of non-selfish nodes.
Edit intent: clarity
Original:  Most traditional TOuU methods use gradient-based optimization algorithms and rely on accurate estimates of the statistical moments and their gradients, e.g  , via adjoint calculations.
Revised:  Most traditional TOuU methods use gradient-based optimization algorithms and rely on accurate estimates of the statistical moments and their gradients, e.g . , via adjoint calculations.
Edit intent: fluency
Original:  The optimization procedure itself often requires a large number of iterations, which may render the ToUU problem computationally expensive, if not infeasible , due to the overall large number of required adjoint (and/or forward) solves .
Revised:  The optimization procedure itself often requires a large number of iterations, which may render TOuU computationally expensive, if not infeasible , due to the overall large number of required adjoint (and/or forward) solves .
Edit intent: clarity
Original:  The optimization procedure itself often requires a large number of iterations, which may render the ToUU problem computationally expensive, if not infeasible , due to the overall large number of required adjoint (and/or forward) solves .
Revised:  The optimization procedure itself often requires a large number of iterations, which may render the ToUU problem computationally expensive, if not infeasible .
Edit intent: coherence
Original:  To tackle this difficulty, we here propose an optimization approach that generates a stochastic approximation of the objective, constraints, and their gradients via a small number of adjoint (and/or forward) solves, per optimization iteration.
Revised:  To tackle this difficulty, we here propose an optimization approach that generates a stochastic approximation of the objective, constraints, and their gradients via a small number of adjoint (and/or forward) solves, per iteration.
Edit intent: fluency
Original:  This approach results in a total cost that is a small factor larger than that of the corresponding deterministic TO problem.
Revised:  The total cost of this approach is only a small factor larger than that of the corresponding deterministic TO problem.
Edit intent: clarity
Original:  Second, we study the use of  stochastic approximation approach within conventional nonlinear programming methods, focusing on the Globally Convergent Method of Moving Asymptotes (GCMMA) , a widely utilized scheme in deterministic TO .
Revised:  Second, we study the use of stochastic approximation approach within conventional nonlinear programming methods, focusing on the Globally Convergent Method of Moving Asymptotes (GCMMA) .
Edit intent: clarity
Original:  The performance of these algorithms is investigated with structural design problems utilizing Solid Isotropic Material with Penalization (SIMP) based optimization , as well as an explicit level set method.
Revised:  The performance of these algorithms is investigated with structural design optimization problems utilizing a Solid Isotropic Material with Penalization (SIMP) based optimization , as well as an explicit level set method.
Edit intent: clarity
Original:  The performance of these algorithms is investigated with structural design problems utilizing Solid Isotropic Material with Penalization (SIMP) based optimization , as well as an explicit level set method.
Revised:  The performance of these algorithms is investigated with structural design problems utilizing Solid Isotropic Material with Penalization (SIMP) , as well as an explicit level set method.
Edit intent: clarity