wanyu/IteraTeR_v2 huggingface dataset:
Original:  In this context, the paper focuses on the online stochastic gradient descent method , and establishes its convergence to the sequence of optimizers (within a bounded error) in expectation and in high probability  .
Revised:  In this context, we propose the use of an online stochastic gradient descent method , and establishes its convergence to the sequence of optimizers (within a bounded error) in expectation and in high probability .
Edit intent: clarity
Original:  In this context, the paper focuses on the online stochastic gradient descent method , and establishes its convergence to the sequence of optimizers (within a bounded error) in expectation and in high probability  .
Revised:  In this context, the paper focuses on the online stochastic gradient descent method to solve the optimization, and we provide explicit bounds in expectation and in high probability .
Edit intent: clarity
Original:  In particular, high-probability convergence results are derived by modeling the gradient error  as a sub-Weibull random variable  .
Revised:  In particular, we show that when the gradient error as a sub-Weibull random variable .
Edit intent: coherence
Original: The evolution and function of imitation in animal learning has always been associated with its crucial role in cultural transmission and cultural evolution.
Revised: The evolution and function of imitation have always been placed within the confines of animal learning and associated with its crucial role in cultural transmission and cultural evolution.
Edit intent: clarity
Original:  We investigate a model in which imitation is unbundled from cultural transmission: an organism's adult phenotype is plastically altered by its juvenile experiences of genetically determined juvenile traitswithin its cohort, and the only information transmitted between generations is genetic.
Revised:  We investigate a model in which imitation is unbundled from cultural transmission: an organism's adult phenotype is plastically altered by its experiences as a juvenile of other juveniles' genetically determined traits. The only information transmitted between generations is genetic.
Edit intent: clarity
Original:  Transmission of phenotypic information between generations is precluded by the population being semelparous with discrete, non-overlapping generations.
Edit intent: clarity
Original:  In a model of purifying selection for an extreme phenotype , selection for anti-imitation continues even at a mutation-selection balance  .
Revised:  In a model of purifying selection for an extreme phenotype is modeled, only selection for anti-imitation continues even at a mutation-selection balance .
Edit intent: clarity
Original:  In a model of purifying selection for an extreme phenotype , selection for anti-imitation continues even at a mutation-selection balance  .
Revised:  In a model of purifying selection for an extreme phenotype , selection for anti-imitation occurs, even at a mutation-selection balance .
Edit intent: clarity
Original:  More importantly, given the risk-aversity of the control prior, BCF ensures safe exploration and deployment, where the control prior naturally dominates the action distribution in states unknown to the policy.
Revised:  More importantly, given the risk-aversity of the control prior, BCF ensures safe exploration and deployment, where the control prior naturally dominates the action distribution in states unknown to the policy.
Edit intent: fluency
Original: This paper is concerned with the error estimates of the fully discrete generalized finite element method (GFEM) with optimal local approximation spaces for solving elliptic problems with heterogeneous coefficients.
Revised: This paper is concerned with error estimates of the fully discrete generalized finite element method (GFEM) with optimal local approximation spaces for solving elliptic problems with heterogeneous coefficients.
Edit intent: fluency
Original:  The experimental analysis is concluded by comparing PPO learned policy results with frontier-based exploration context for extended terrain sizes .
Revised:  The experimental analysis is concluded by evaluating PPO learned policy results with frontier-based exploration context for extended terrain sizes .
Edit intent: clarity
Original: Deep generative models have recently achieved impressive performance in speech synthesis and music generation .
Revised: Deep generative models have recently achieved impressive performance in speech and music synthesis .
Edit intent: clarity
Original:  However, compared to the generation of those domain-specific sounds, the generation of general sounds (such as car horn, dog barking, and gun shot ) has received less attention, despite their wide potential applications.
Revised:  However, compared to the generation of those domain-specific sounds, generating general sounds (such as car horn, dog barking, and gun shot ) has received less attention, despite their wide potential applications.
Edit intent: clarity
Original:  However, compared to the generation of those domain-specific sounds, the generation of general sounds (such as car horn, dog barking, and gun shot ) has received less attention, despite their wide potential applications.
Revised:  However, compared to the generation of those domain-specific sounds, the generation of general sounds (such as car horn, dog barking, and gun shot ) has received less attention, despite their wide applications.
Edit intent: clarity
Original:  In our previous work, sounds are generated in the time domain using SampleRNN . However, it is difficult to capture long-range dependencies within sound recordings using this method .
Revised:  In previous work, sounds are generated in the time domain using SampleRNN . However, it is difficult to capture long-range dependencies within sound recordings using this method .
Edit intent: fluency
Original:  In our previous work, sounds are generated in the time domain using SampleRNN . However, it is difficult to capture long-range dependencies within sound recordings using this method .
Revised:  In our previous work, the SampleRNN method was considered for sound generation in the time domain using SampleRNN . However, it is difficult to capture long-range dependencies within sound recordings using this method .
Edit intent: clarity
Original:  In our previous work, sounds are generated in the time domain using SampleRNN . However, it is difficult to capture long-range dependencies within sound recordings using this method .
Revised:  In our previous work, sounds are generated in the time domain . However, it is difficult to capture long-range dependencies within sound recordings using this method .
Edit intent: coherence
Original:  In our previous work, sounds are generated in the time domain using SampleRNN . However, it is difficult to capture long-range dependencies within sound recordings using this method .
Revised:  In our previous work, sounds are generated in the time domain using SampleRNN . However, SampleRNN is potentially limited in capturing long-range dependencies within sound recordings using this method .
Edit intent: clarity
Original:  In this work, we propose to generate sounds conditioned on sound classes via neural discrete time-frequency representation learning  .
Revised:  In this work, we propose a method for generating sounds via neural discrete time-frequency representation learning .
Edit intent: clarity
Original:  This offers an advantage in  modelling long-range dependencies and retaining local fine-grained structure within a sound clip .
Revised:  This offers an advantage in efficiently modelling long-range dependencies and retaining local fine-grained structure within a sound clip .
Edit intent: clarity
Original:  This offers an advantage in  modelling long-range dependencies and retaining local fine-grained structure within a sound clip .
Revised:  This offers an advantage in modelling long-range dependencies and retaining local fine-grained structures within sound clips .
Edit intent: fluency
Original:  The proposed solution has the advantages of being (i) mathematically sound, (ii) generalisable to any infinitely divisible probability distribution, and (iii) of simple implementation in modern architectures.
Revised:  The proposed solution has the advantages of being generalisable to any infinitely divisible probability distribution, and (iii) of simple implementation in modern architectures.
Edit intent: clarity
Original:  The proposed solution has the advantages of being (i) mathematically sound, (ii) generalisable to any infinitely divisible probability distribution, and (iii) of simple implementation in modern architectures.
Revised:  The proposed solution has the advantages of being (i) mathematically sound, (ii) generalisable to any infinitely divisible probability distribution, and of simple implementation in modern architectures.
Edit intent: coherence
Original:  Codes and pre-trained weights will be made available upon paper acceptance.
Revised:  Code and pre-trained weights will be made available upon paper acceptance.
Edit intent: fluency
Original:  The code and pre-trained model will be available upon paper acceptance.
Revised:  Code and pre-trained model will be available upon paper acceptance.
Edit intent: clarity
Original: This paper presents a simple MLP-like architecture, CycleMLP, which is a versatile backbone for visual recognition and dense predictions , unlike modern MLP architectures, e.g., MLP-Mixer, ResMLP, and gMLP, whose architectures are correlated to image size and thus are infeasible in object detection and segmentation .
Revised: This paper presents a simple MLP-like architecture, CycleMLP, which is a versatile backbone for visual recognition and dense predictions . As compared to modern MLP architectures, e.g., MLP-Mixer, ResMLP, and gMLP, whose architectures are correlated to image size and thus are infeasible in object detection and segmentation .
Edit intent: coherence
Original: This paper presents a simple MLP-like architecture, CycleMLP, which is a versatile backbone for visual recognition and dense predictions , unlike modern MLP architectures, e.g., MLP-Mixer, ResMLP, and gMLP, whose architectures are correlated to image size and thus are infeasible in object detection and segmentation .
Revised: This paper presents a simple MLP-like architecture, CycleMLP, which is a versatile backbone for visual recognition and dense predictions , unlike modern MLP architectures, e.g., MLP-Mixer, ResMLP, and gMLP, whose architectures are correlated to image size and thus are infeasible in object detection and segmentation ,
Edit intent: fluency
Original:  We build a family of models that surpass existing MLPs and achieve a comparable accuracy (83.2\%) on ImageNet-1K classification compared to the state-of-the-art Transformer such as Swin Transformer(83.3\%) but using fewer parameters and FLOPs.
Revised:  We build a family of models which surpass existing MLPs and achieve a comparable accuracy (83.2\%) on ImageNet-1K classification compared to the state-of-the-art Transformer such as Swin Transformer(83.3\%) but using fewer parameters and FLOPs.
Edit intent: fluency
Original:  We build a family of models that surpass existing MLPs and achieve a comparable accuracy (83.2\%) on ImageNet-1K classification compared to the state-of-the-art Transformer such as Swin Transformer(83.3\%) but using fewer parameters and FLOPs.
Revised:  We build a family of models that surpass existing MLPs and even state-of-the-art Transformer such as Swin Transformer(83.3\%) but using fewer parameters and FLOPs.
Edit intent: clarity
Original:  We build a family of models that surpass existing MLPs and achieve a comparable accuracy (83.2\%) on ImageNet-1K classification compared to the state-of-the-art Transformer such as Swin Transformer(83.3\%) but using fewer parameters and FLOPs.
Revised:  We build a family of models that surpass existing MLPs and achieve a comparable accuracy (83.2\%) on ImageNet-1K classification compared to the state-of-the-art Transformer-based models, e.g., Swin Transformer, while using fewer parameters and FLOPs.
Edit intent: clarity
Original:  CycleMLP aims to provide a competitive baseline on object detection, instance segmentation, and semantic segmentation for MLP models .
Revised:  CycleMLP achieves competitive results on object detection, instance segmentation, and semantic segmentation for MLP models .
Edit intent: clarity
Original:  CycleMLP aims to provide a competitive baseline on object detection, instance segmentation, and semantic segmentation for MLP models .
Revised:  CycleMLP aims to provide a competitive baseline on object detection, instance segmentation, and semantic segmentation .
Edit intent: clarity
Original: The motivation of this paper is to introduce a cell-free adaptation of the strongest-user collision resolution (SUCRe) protocol originally proposed for cellular massive multiple-input multiple-output ( MIMO) networks.
Revised: In a cell-free adaptation of the strongest-user collision resolution (SUCRe) protocol originally proposed for cellular massive multiple-input multiple-output ( MIMO) networks.
Edit intent: coherence
Original: The motivation of this paper is to introduce a cell-free adaptation of the strongest-user collision resolution (SUCRe) protocol originally proposed for cellular massive multiple-input multiple-output ( MIMO) networks.
Revised: The motivation of this paper is to introduce a cell-free massive multiple-input multiple-output ( MIMO) networks.
Edit intent: clarity
Original:  We consider how the problem of random access (RA) to pilots can be addressed by such a network under the occurrence of pilot collisions.
Revised:  We consider how the random access (RA) to pilots can be addressed by such a network under the occurrence of pilot collisions.
Edit intent: clarity
Original:  We consider how the problem of random access (RA) to pilots can be addressed by such a network under the occurrence of pilot collisions.
Revised:  We consider how the problem of random access (RA) problem can be addressed by such a network under the occurrence of pilot collisions.
Edit intent: clarity
Original:  To find a solution, we embrace the user-centric perspective, which basically dictates that only a preferred subset of APs needs to service a UE.
Revised:  To find a solution, we embrace the user-centric perspective, which basically dictates that only a preferred set of APs needs to service a UE.
Edit intent: fluency
Original:  To find a solution, we embrace the user-centric perspective, which basically dictates that only a preferred subset of APs needs to service a UE.
Revised:  To find a solution, we embrace the user-centric perspective, which basically dictates that only a preferred subset of APs needs to serve a UE.
Edit intent: fluency
Original:  During the extension process, we observe that the user-centric perspective naturally equips a cell-free network with a method for resolving collisions.
Revised:  We establish that the user-centric perspective naturally equips a cell-free network with a method for resolving collisions.
Edit intent: clarity
Original:  During the extension process, we observe that the user-centric perspective naturally equips a cell-free network with a method for resolving collisions.
Revised:  During the extension process, we observe that the user-centric perspective naturally equips a CF network with robust fundamentals for resolving collisions.
Edit intent: clarity
Original:  We refer to this method as spatial separability, which comes from the macro-diversity brought about by the additional AP dimension .
Revised:  We refer to this foundation as spatial separability, which comes from the macro-diversity brought about by the additional AP dimension .
Edit intent: clarity
Original:  We then propose two novel RA protocols for cell-free mMIMO : i) the baseline cell-free (BCF) that resolves collisions with the concept of separability alone and ii) the cell-free SUCRe (CF-SUCRe) that combines SUCRe and spatial separability  to resolve collisions.
Revised:  We then propose two novel RA protocols for CF-mMIMO : i) the baseline cell-free (BCF) that resolves collisions with the concept of separability alone and ii) the cell-free SUCRe (CF-SUCRe) that combines SUCRe and spatial separability to resolve collisions.
Edit intent: fluency
Original:  We then propose two novel RA protocols for cell-free mMIMO : i) the baseline cell-free (BCF) that resolves collisions with the concept of separability alone and ii) the cell-free SUCRe (CF-SUCRe) that combines SUCRe and spatial separability  to resolve collisions.
Revised:  We then propose two novel RA protocols for cell-free mMIMO : i) the baseline cell-free (BCF) that resolves collisions with the concept of spatial separability alone, and ii) the cell-free SUCRe (CF-SUCRe) that combines SUCRe and spatial separability to resolve collisions.
Edit intent: fluency
Original:  The BCF and CF-SUCRe perform 6x to 2x better on average compared to the Ce-SUCRe with an average energy efficiency gain  of 45x to 125x, respectively.
Revised:  The BCF and CF-SUCRe support 6x to 2x better on average compared to the Ce-SUCRe with an average energy efficiency gain of 45x to 125x, respectively.
Edit intent: clarity
Original:  The BCF and CF-SUCRe perform 6x to 2x better on average compared to the Ce-SUCRe with an average energy efficiency gain  of 45x to 125x, respectively.
Revised:  The BCF and CF-SUCRe perform 6x and 2x better on average compared to the Ce-SUCRe with an average energy efficiency gain of 45x to 125x, respectively.
Edit intent: fluency
Original:  The BCF and CF-SUCRe perform 6x to 2x better on average compared to the Ce-SUCRe with an average energy efficiency gain  of 45x to 125x, respectively.
Revised:  The BCF and CF-SUCRe perform 6x to 2x better on average compared to the Ce-SUCRe with an average energy efficiency gain of 45x and 125x, respectively.
Edit intent: fluency
Original:  Among our methods, even with a higher overhead, the CF-SUCRe is superior to BCF  because the combination of methods for collision resolution allows many APs to be disconnected from RA without sacrificing much  performance.
Revised:  Among our methods, even with a higher overhead, the CF-SUCRe is superior to BCF because the combination of methods for collision resolution allows many APs to be disconnected from the RA process without sacrificing much performance.
Edit intent: clarity
Original:  Among our methods, even with a higher overhead, the CF-SUCRe is superior to BCF  because the combination of methods for collision resolution allows many APs to be disconnected from RA without sacrificing much  performance.
Revised:  Among our methods, even with a higher overhead, the CF-SUCRe is superior to BCF because the combination of methods for collision resolution allows many APs to be disconnected from RA without sacrificing much the performance.
Edit intent: clarity
Original: In this paper, we propose a computational framework to estimate the physical tissue properties that govern the thermal response of laser-irradiated tissue.
Revised: In this paper, we propose a computational framework to estimate the physical properties that govern the thermal response of laser-irradiated tissue.
Edit intent: fluency
Original:  Unlike prior approaches, in this work we estimate the tissue optical properties based on the observed surface thermal response to laser irradiation.
Revised:  Unlike prior approaches, in this work we estimate the tissue optical properties based on observations of the tissue thermal response to laser irradiation.
Edit intent: clarity
Original:  Through preliminary evaluation in simulation , we demonstrate the ability of the proposed technique to identify the tissue optical properties and track their dynamic changes during laser exposure, while simultaneously tracking changes in the tissue temperature at locations beneath the surface  .
Revised:  Through simulated experimental studies , we demonstrate the ability of the proposed technique to identify the tissue optical properties and track their dynamic changes during laser exposure, while simultaneously tracking changes in the tissue temperature at locations beneath the surface .
Edit intent: clarity
Original:  During inference, based on user-controlled parameters, it can find a suitable trade-off between tracking accuracy and speed by adapting frame sizes at run time.
Revised:  During inference, based on user-controlled parameters.
Edit intent: clarity
Original:  Compared to a state-of-the-art tracker, DeepScale++, a variant of DeepScale achieves 1.57X accelerated with only moderate degradation ( ~2.3 \%) in tracking accuracy on the MOT15 dataset in one configuration  .
Revised:  Compared to a state-of-the-art tracker, DeepScale++, a variant of DeepScale achieves 1.57X accelerated with only moderate degradation ~2.3 \%) in tracking accuracy on the MOT15 dataset in one configuration .
Edit intent: fluency
Original:  Compared to a state-of-the-art tracker, DeepScale++, a variant of DeepScale achieves 1.57X accelerated with only moderate degradation ( ~2.3 \%) in tracking accuracy on the MOT15 dataset in one configuration  .
Revised:  Compared to a state-of-the-art tracker, DeepScale++, a variant of DeepScale achieves 1.57X accelerated with only moderate degradation ( ~2.3 \ in tracking accuracy on the MOT15 dataset in one configuration .
Edit intent: coherence
Original:  Aside from greater generality, the advantage of our algorithms over alternatives is that they resolve some long-standing convergence difficulties of the `` natural" policy iteration algorithm, which have been known since the Pollatschek and Avi-Itzhak method [PoA69] for finite-state Markov games.
Revised:  Aside from greater generality, the advantage of our algorithms over alternatives is that they resolve some long-standing convergence difficulties of the " natural" policy iteration algorithm, which have been known since the Pollatschek and Avi-Itzhak method [PoA69] for finite-state Markov games.
Edit intent: fluency
Original:  Mathematically, this `` natural" algorithm is a form of Newton's method for solving Bellman's equation, but Newton's method, contrary to the case of single-player DP problems, is not globally convergent in the case of a minimax problem, because the Bellman operator may have components that are neither convex nor concave.
Revised:  Mathematically, this " natural" algorithm is a form of Newton's method for solving Bellman's equation, but Newton's method, contrary to the case of single-player DP problems, is not globally convergent in the case of a minimax problem, because the Bellman operator may have components that are neither convex nor concave.
Edit intent: fluency
Original:  To address this issue, we have designed and held a location trace anonymization contest that deals with a long trace (400 events per user) and fine-grained locations (1024 regions).
Revised:  To address this issue, we have designed and held a location trace anonymization contest . Our contest deals with a long trace (400 events per user) and fine-grained locations (1024 regions).
Edit intent: clarity
Original:  In our contest, each team anonymizes her original traces, and then the other teams perform privacy attacks against the anonymized traces (i.e., both defense and attack compete together) in a partial-knowledge attacker model where the adversary does not know the original traces.
Revised:  In our contest, each team anonymizes her original traces, and then the other teams perform privacy attacks against the anonymized traces in a partial-knowledge attacker model where the adversary does not know the original traces.
Edit intent: coherence
Original:  To realize such a contest, we propose a novel location synthesizer that has diversity in that synthetic traces for each team are different from those for the other teams and utility in that synthetic traces preserve various statistical features of real traces.
Revised:  To realize such a contest, we propose a location synthesizer that has diversity in that synthetic traces for each team are different from those for the other teams and utility in that synthetic traces preserve various statistical features of real traces.
Edit intent: clarity