wanyu/IteraTeR_v2 huggingface dataset:
Original:  In this regard we construct an n{2} + \lceil n{8} \rceil query exact quantum algorithm that is not a parity decision tree and evaluates a non-symmetric subclass of MM type Bent functions on n variables consisting of%DIFDELCMD < \left(%%%  2^{ %DIFDELCMD < \lfloor %%% \frac{n{4} }%DIFDELCMD < \rfloor%%% {4} \rfloor }} } !%DIFDELCMD < \right)\left(%%%  2 ^{\lceil \frac{n{4} \rceil}!}%DIFDELCMD < \right) %%% 2^{2^{\lfloor \frac{n{4} \rfloor}} functions.
Revised:  In this regard we construct an n{2} + \lceil n{8} \rceil query exact quantum algorithm that is not a parity decision tree and evaluates a non-symmetric subclass of MM type Bent functions on n variables consisting of%DIFDELCMD < \left(%%% 2^{ %DIFDELCMD < \lfloor %%% {4} }%DIFDELCMD < \rfloor%%% {4} \rfloor }} } !%DIFDELCMD < \right)\left(%%% 2 ^{\lceil \frac{n{4} \rceil}!}%DIFDELCMD < \right) %%% 2^{2^{\lfloor \frac{n{4} \rfloor}} functions.
Edit intent: fluency
Original:  In this regard we construct an n{2} + \lceil n{8} \rceil query exact quantum algorithm that is not a parity decision tree and evaluates a non-symmetric subclass of MM type Bent functions on n variables consisting of%DIFDELCMD < \left(%%%  2^{ %DIFDELCMD < \lfloor %%% \frac{n{4} }%DIFDELCMD < \rfloor%%% {4} \rfloor }} } !%DIFDELCMD < \right)\left(%%%  2 ^{\lceil \frac{n{4} \rceil}!}%DIFDELCMD < \right) %%% 2^{2^{\lfloor \frac{n{4} \rfloor}} functions.
Revised:  In this regard we construct an n{2} + \lceil n{8} \rceil query exact quantum algorithm that is not a parity decision tree and evaluates a non-symmetric subclass of MM type Bent functions on n variables consisting of%DIFDELCMD < \left(%%% 2^{ %DIFDELCMD < \lfloor %%% \frac{n{4} }%DIFDELCMD < \rfloor%%% 2^{\lfloor \frac{n{4} \rfloor }} } !%DIFDELCMD < \right)\left(%%% 2 ^{\lceil \frac{n{4} \rceil}!}%DIFDELCMD < \right) %%% 2^{2^{\lfloor \frac{n{4} \rfloor}} functions.
Edit intent: fluency
Original:  In this regard we construct an n{2} + \lceil n{8} \rceil query exact quantum algorithm that is not a parity decision tree and evaluates a non-symmetric subclass of MM type Bent functions on n variables consisting of%DIFDELCMD < \left(%%%  2^{ %DIFDELCMD < \lfloor %%% \frac{n{4} }%DIFDELCMD < \rfloor%%% {4} \rfloor }} } !%DIFDELCMD < \right)\left(%%%  2 ^{\lceil \frac{n{4} \rceil}!}%DIFDELCMD < \right) %%% 2^{2^{\lfloor \frac{n{4} \rfloor}} functions.
Revised:  In this regard we construct an n{2} + \lceil n{8} \rceil query exact quantum algorithm that is not a parity decision tree and evaluates a non-symmetric subclass of MM type Bent functions on n variables consisting of%DIFDELCMD < \left(%%% 2^{ %DIFDELCMD < \lfloor %%% \frac{n{4} }%DIFDELCMD < \rfloor%%% {4} \rfloor }} } %DIFDELCMD < \right)\left(%%% 2 ^{\lceil \frac{n{4} \rceil}!}%DIFDELCMD < \right) %%% 2^{2^{\lfloor \frac{n{4} \rfloor}} functions.
Edit intent: clarity
Original:  In this regard we construct an n{2} + \lceil n{8} \rceil query exact quantum algorithm that is not a parity decision tree and evaluates a non-symmetric subclass of MM type Bent functions on n variables consisting of%DIFDELCMD < \left(%%%  2^{ %DIFDELCMD < \lfloor %%% \frac{n{4} }%DIFDELCMD < \rfloor%%% {4} \rfloor }} } !%DIFDELCMD < \right)\left(%%%  2 ^{\lceil \frac{n{4} \rceil}!}%DIFDELCMD < \right) %%% 2^{2^{\lfloor \frac{n{4} \rfloor}} functions.
Revised:  In this regard we construct an n{2} + \lceil n{8} \rceil query exact quantum algorithm that is not a parity decision tree and evaluates a non-symmetric subclass of MM type Bent functions on n variables consisting of%DIFDELCMD < \left(%%% 2^{ %DIFDELCMD < \lfloor %%% \frac{n{4} }%DIFDELCMD < \rfloor%%% {4} \rfloor }} } !%DIFDELCMD < \right)\left(%%% 2 {4} \rceil}!}%DIFDELCMD < \right) %%% 2^{2^{\lfloor \frac{n{4} \rfloor}} functions.
Edit intent: fluency
Original:  In this regard we construct an n{2} + \lceil n{8} \rceil query exact quantum algorithm that is not a parity decision tree and evaluates a non-symmetric subclass of MM type Bent functions on n variables consisting of%DIFDELCMD < \left(%%%  2^{ %DIFDELCMD < \lfloor %%% \frac{n{4} }%DIFDELCMD < \rfloor%%% {4} \rfloor }} } !%DIFDELCMD < \right)\left(%%%  2 ^{\lceil \frac{n{4} \rceil}!}%DIFDELCMD < \right) %%% 2^{2^{\lfloor \frac{n{4} \rfloor}} functions.
Revised:  In this regard we construct an n{2} + \lceil n{8} \rceil query exact quantum algorithm that is not a parity decision tree and evaluates a non-symmetric subclass of MM type Bent functions on n variables consisting of%DIFDELCMD < \left(%%% 2^{ %DIFDELCMD < \lfloor %%% \frac{n{4} }%DIFDELCMD < \rfloor%%% {4} \rfloor }} } !%DIFDELCMD < \right)\left(%%% 2 ^{\lceil \frac{n{4} \rceil}!}%DIFDELCMD < \right) %%% {4} \rfloor}} functions.
Edit intent: clarity
Original: The Exact Quantum Query model is the least explored query model, and almost all of the  functions for which non-trivial query algorithms exist are symmetric in nature.
Revised: In the Exact Quantum Query model is the least explored query model, and almost all of the functions for which non-trivial query algorithms exist are symmetric in nature.
Edit intent: fluency
Original: The Exact Quantum Query model is the least explored query model, and almost all of the  functions for which non-trivial query algorithms exist are symmetric in nature.
Revised: The Exact Quantum Query model , almost all of the functions for which non-trivial query algorithms exist are symmetric in nature.
Edit intent: clarity
Original:  The (classical) Deterministic Query Complexity ( D(f) ) of all functions in this class is n.
Revised:  The (classical) Deterministic Query Complexity D(f) ) of all functions in this class is n.
Edit intent: fluency
Original:  The (classical) Deterministic Query Complexity ( D(f) ) of all functions in this class is n.
Revised:  The (classical) Deterministic Query Complexity ( D(f) of all functions in this class is n.
Edit intent: fluency
Original:  In this regard we construct an n{2 + }%DIFDELCMD < \lceil %%% \frac{n{8} }%DIFDELCMD < \rceil %%% query family of exact quantum algorithms that are not parity decision trees to evaluate a subclass of MM type Bent functions consisting of \Omega(2^{2^{\lfloor n{4 \rfloor }}) non-PNP equivalent functions.
Revised:  + }%DIFDELCMD < \lceil %%% \frac{n{8} }%DIFDELCMD < \rceil %%% query family of exact quantum algorithms that are not parity decision trees to evaluate a subclass of MM type Bent functions consisting of \Omega(2^{2^{\lfloor n{4 \rfloor }}) non-PNP equivalent functions.
Edit intent: coherence
Original:  In this regard we construct an n{2 + }%DIFDELCMD < \lceil %%% \frac{n{8} }%DIFDELCMD < \rceil %%% query family of exact quantum algorithms that are not parity decision trees to evaluate a subclass of MM type Bent functions consisting of \Omega(2^{2^{\lfloor n{4 \rfloor }}) non-PNP equivalent functions.
Revised:  In this regard we construct an n{2 + }%DIFDELCMD < \lceil %%% {8} }%DIFDELCMD < \rceil %%% query family of exact quantum algorithms that are not parity decision trees to evaluate a subclass of MM type Bent functions consisting of \Omega(2^{2^{\lfloor n{4 \rfloor }}) non-PNP equivalent functions.
Edit intent: clarity
Original:  In this regard we construct an n{2 + }%DIFDELCMD < \lceil %%% \frac{n{8} }%DIFDELCMD < \rceil %%% query family of exact quantum algorithms that are not parity decision trees to evaluate a subclass of MM type Bent functions consisting of \Omega(2^{2^{\lfloor n{4 \rfloor }}) non-PNP equivalent functions.
Revised:  In this regard we construct an n{2 + }%DIFDELCMD < \lceil %%% \frac{n{8} }%DIFDELCMD < \rceil %%% We design a family of exact quantum algorithms that are not parity decision trees to evaluate a subclass of MM type Bent functions consisting of \Omega(2^{2^{\lfloor n{4 \rfloor }}) non-PNP equivalent functions.
Edit intent: clarity
Original:  We show that in this case the algorithms designed by us }  require \lfloor 3n{4} \rfloor queries and  our family of algorithms is optimal, outperforming any possible  parity decision tree technique.
Revised:  We show that in this case the algorithms designed by us } require \lfloor 3n{4} \rfloor queries and we show that and our family of algorithms is optimal, outperforming any possible parity decision tree technique.
Edit intent: coherence
Original: In the Exact Quantum Query model, almost all of the Boolean functions for which non-trivial query algorithms exist are symmetric in nature.
Revised: In Exact Quantum Query model, almost all of the Boolean functions for which non-trivial query algorithms exist are symmetric in nature.
Edit intent: fluency
Original:  The most well known quantum algorithms in this domain are parity decision trees, in which the parity of two bits can be obtained using a single query.
Revised:  The most well known techniques in this domain are parity decision trees, in which the parity of two bits can be obtained using a single query.
Edit intent: clarity
Original:  The most well known quantum algorithms in this domain are parity decision trees, in which the parity of two bits can be obtained using a single query.
Revised:  The most well known quantum algorithms in this domain exploit parity decision trees, in which the parity of two bits can be obtained using a single query.
Edit intent: clarity
Original:  The most well known quantum algorithms in this domain are parity decision trees, in which the parity of two bits can be obtained using a single query.
Revised:  The most well known quantum algorithms in this domain are parity decision trees, in which the parity of two bits can be obtained by a single query.
Edit intent: clarity
Original:  To the best of our knowledge, this is the first family of algorithms beyond generalized parity (and thus parity) for a general class of non-symmetric functions  .
Revised:  To the best of our knowledge, this is the first family of algorithms beyond generalized parity (and thus parity) for a large class of non-symmetric functions .
Edit intent: clarity
Original:  As our error bound depends on a computable approximation of the failure probability, it is applicable in practicable reliability analyses and, for instance, in multilevel methods.
Revised:  This relationship can be used to guide practicable reliability analyses and, for instance, in multilevel methods.
Edit intent: clarity
Original:  As our error bound depends on a computable approximation of the failure probability, it is applicable in practicable reliability analyses and, for instance, in multilevel methods.
Revised:  As our error bound depends on a computable approximation of the failure probability, it is applicable in practicable reliability analyses and, for instance, multilevel methods.
Edit intent: fluency
Original:  Next, we introduce a bias alleviation mechanism  to mitigate the effect of bias in training set during the fine-tuning of our pre-trained BERT-based model for hate speech detection .
Revised:  Next, we introduce a bias alleviation mechanism to mitigate the effect of bias in training set during the fine-tuning of our pre-trained BERT-based model .
Edit intent: coherence
Original: In this paper, we introduce a deep learning technique for consolidating and sharp feature generation of point clouds using only the input point cloud itself.
Revised: We introduce a novel technique for neural point cloud consolidation which learns from only the input point cloud itself.
Edit intent: clarity
Original:  During test time , the network is repeatedly fed a random subset of points from the input and displaces them to generate an arbitrarily large setof novel sharp feature points.
Revised:  During test time , the network is fed with random subsets of points from the input and displaces them to generate an arbitrarily large setof novel sharp feature points.
Edit intent: clarity
Original:   We demonstrate the ability to generate coherent sets of sharp feature points on a variety of shapes, while eliminating outliers and noise.
Revised:  We demonstrate the ability to consolidate point sets from a variety of shapes, while eliminating outliers and noise.
Edit intent: clarity
Original:  This suggests that in computations, quantum scrap space is more valuable than analogous classical space  and calls for an in-depth exploration of space-time tradeoffs in quantum circuits.
Revised:  This suggests that in computations, quantum scrap space is more valuable than analogous classical space -- and calls for an in-depth exploration of space-time tradeoffs in quantum circuits.
Edit intent: fluency
Original: Data-parallel problems , commonly found in data analytics, machine learning, and scientific computing demand ever growing floating-point  operations per second under tight area- and energy-efficiency constraints.
Revised: Data-parallel problems demand ever growing floating-point operations per second under tight area- and energy-efficiency constraints.
Edit intent: clarity
Original:  Application-specific architectures and accelerators, while efficient at a given task, are hard to adjust to algorithmic changes.
Edit intent: coherence
Original:  In this work, we present Manticore, a general-purpose, ultra-efficient , RISC-V, chiplet-based architecture for data-parallel floating-point workloads.
Revised:  In this work, we present Manticore, a general-purpose, ultra-efficient , RISC-V, chiplet-based architecture for data-parallel FP workloads.
Edit intent: clarity
Original:  We have manufactured a 9\text{mm prototype of the chiplet's computational core in Globalfoundries 22nm FD-SOI process and demonstrate more than 2.5\times improvement in energy efficiency on floating-point intensive workloads compared to high performance compute engines ( CPUs and GPUs ), despite their more advanced FinFET process.
Revised:  We have manufactured a prototype of the chiplet's computational core in Globalfoundries 22nm FD-SOI process and demonstrate more than 2.5\times improvement in energy efficiency on floating-point intensive workloads compared to high performance compute engines ( CPUs and GPUs ), despite their more advanced FinFET process.
Edit intent: clarity
Original:  We have manufactured a 9\text{mm prototype of the chiplet's computational core in Globalfoundries 22nm FD-SOI process and demonstrate more than 2.5\times improvement in energy efficiency on floating-point intensive workloads compared to high performance compute engines ( CPUs and GPUs ), despite their more advanced FinFET process.
Revised:  We have manufactured a 9\text{mm prototype of the chiplet's computational core in Globalfoundries 22nm FD-SOI process and demonstrate more than 2.5\times improvement in energy efficiency on floating-point intensive workloads compared to CPUs and GPUs ), despite their more advanced FinFET process.
Edit intent: clarity
Original:  The compute capability at high energy and area efficiency is provided by Snitch clusters . Each cluster contains eight small (20kGE) 32-bit integer RISC-V cores, each controlling a large double-precision floating-point unit (120kGE).
Revised:  The compute capability at high energy and area efficiency is provided by Snitch clusters containing eight small integer cores, each controlling a large double-precision floating-point unit (120kGE).
Edit intent: clarity
Original:  Each core supports two custom RISC-V ISA extensions: FREP and SSR. The SSR extension elides explicit load and store instructions by encoding them as register reads and writes.
Revised:  Each core supports two custom ISA extensions: FREP and SSR. The SSR extension elides explicit load and store instructions by encoding them as register reads and writes.
Edit intent: clarity
Original:  Each core supports two custom RISC-V ISA extensions: FREP and SSR. The SSR extension elides explicit load and store instructions by encoding them as register reads and writes.
Revised:  Each core supports two custom RISC-V ISA extensions: The SSR extension elides explicit load and store instructions by encoding them as register reads and writes.
Edit intent: clarity
Original:  The FREP extension mostly decouples the integer core from the FPU by allowing a sequence buffer to issue instructions to the FPU independently.
Revised:  The FREP extension decouples the integer core from the FPU by allowing a sequence buffer to issue instructions to the FPU independently.
Edit intent: clarity
Original:  Both extensions allow the tiny, single-issue , integer core to saturate the instruction bandwidth of the FPU and achieve FPU utilization above 90\%, with more than 80 \% of core area dedicated to the FPU.
Revised:  Both extensions allow the single-issue , integer core to saturate the instruction bandwidth of the FPU and achieve FPU utilization above 90\%, with more than 80 \% of core area dedicated to the FPU.
Edit intent: clarity
Original:  Both extensions allow the tiny, single-issue , integer core to saturate the instruction bandwidth of the FPU and achieve FPU utilization above 90\%, with more than 80 \% of core area dedicated to the FPU.
Revised:  Both extensions allow the tiny, single-issue , integer core to saturate the instruction bandwidth of the FPU , achieving FPU utilization above 90\%, with more than 80 \% of core area dedicated to the FPU.
Edit intent: coherence
Original: Various intervention methods have been introduced worldwide to slow down the spread of the SARS-CoV-2 virus , by limiting human mobility in different ways.
Revised: Major interventions have been introduced worldwide to slow down the spread of the SARS-CoV-2 virus , by limiting human mobility in different ways.
Edit intent: clarity
Original:  While large scale lockdown strategies are effective in reducing the spread rate, they come at a cost of significantly limited societal functions.
Revised:  While large scale lockdown strategies are effective in reducing the spread , but they come at a cost of significantly limited societal functions.
Edit intent: clarity
Original:  We show that natural human mobility has high diversity and heterogeneity such that a small group of  individuals and gathering venues play an important role in the spread of the disease.
Revised:  We show that natural human movements are statistically diverse, and the spread of the disease is significantly influenced by a small group of individuals and gathering venues play an important role in the spread of the disease.
Edit intent: clarity
Original:  We discover that interventions that focus on protecting the most active individuals and most popular venues can significantly reduce the peak infection rate and the total number of infected people while retaining high levels of social activity overall.
Revised:  We discover that interventions that focus on protecting the most active individuals and most popular venues can significantly reduce the peak infection rate and the total infected population while retaining high levels of social activity overall.
Edit intent: clarity
Original:  Large scale lockdown of human movements are effective in reducing the spread, but they come at a cost of significantly limited societal functions.
Revised:  Large-scale lockdowns of human movements are effective in reducing the spread, but they come at a cost of significantly limited societal functions.
Edit intent: fluency
Original:  We find that interventions focused on these most mobile individuals and popular venues reduce both the peak infection rate and the total infected population while retaining high levels of social activity .
Revised:  We find that interventions focused on these most mobile individuals and popular venues reduce both the peak infection rate and the total infected population while retaining high social activity levels .
Edit intent: clarity
Original:  The observation implies that compared to broad sweeping interventions, more targeted strategies based on the network effects in human mobility provide a better balance between pandemic control and normal social activities.
Revised:  The observation implies that compared to broad sweeping interventions, more targeted strategies based on the network effects in human mobility provide a better balance between pandemic control and regular social activities.
Edit intent: clarity
Original:  To reduce this computational complexity, we decompose the large-scale LQR design problem into multiple sets of smaller-size LQR design problems.
Revised:  To reduce this computational complexity, we decompose the large-scale LQR design problem into multiple smaller-size LQR design problems.
Edit intent: clarity
Original:  The graph is decomposed into two parts, one consisting of multiple decoupled subgroups of connected components, and the other containing edges that connect the different subgroups .
Revised:  The graph is decomposed into two parts, one consisting of multiple decoupled subgroups of connected components, and the other containing edges that connect different clusters .
Edit intent: clarity
Original:  The first component optimizes the performance of each decoupled subgroup by solving the smaller-size LQR design problem in a model-free way using an RL algorithm.
Revised:  The first component optimizes the performance of each independent cluster by solving the smaller-size LQR design problem in a model-free way using an RL algorithm.
Edit intent: clarity
Original:  Although suboptimal, the hierarchical controller adheres to a particular structure as specified by the inter-agent coupling in the objective function and by the decomposition strategy.
Revised:  Although suboptimal, the hierarchical controller adheres to a particular structure as specified by inter-agent coupling in the objective function and by the decomposition strategy.
Edit intent: fluency
Original:  Although suboptimal, the hierarchical controller adheres to a particular structure as specified by the inter-agent coupling in the objective function and by the decomposition strategy.
Revised:  Although suboptimal, the hierarchical controller adheres to a particular structure as specified by the inter-agent couplings in the objective function and by the decomposition strategy.
Edit intent: fluency
Original:  Mathematical formulations are established to find a decomposition that minimizes  required communication links or reduces the optimality gap.
Revised:  Mathematical formulations are established to find a decomposition that minimizes the number of required communication links or reduces the optimality gap.
Edit intent: clarity
Original:  Finally, we provide a testing protocol for practitioners to use these group testing methods in the COVID-19 pandemic .
Revised:  Finally, we provide a testing protocol practitioners can use for mitigating COVID-19 pandemic .
Edit intent: clarity
Original: We show analytically that training a neural network by  stochastic mutation or "neuroevolution " of its weights is equivalent, in the limit of small mutations, to gradient descent on the loss function in the presence of Gaussian white noise.
Revised: We show analytically that training a neural network by stochastic mutation or neuroevolution of its weights is equivalent, in the limit of small mutations, to gradient descent on the loss function in the presence of Gaussian white noise.
Edit intent: fluency
Original:  Our results provide a connection between two distinct types of neural-network training , and provide justification for the empirical success of neuroevolution .
Revised:  Our results provide a connection between two families of neural-network training , and provide justification for the empirical success of neuroevolution .
Edit intent: clarity
Original:  In this work, we consider computerized tomography (CT) with fan-beam geometry and equipped with such cameras.
Revised:  In this work, we consider computerized tomography (CT) with fan beam geometry and equipped with such cameras.
Edit intent: fluency
Original:  The review also covers the probable crash scenarios by red-light running and turning and analyses the innovation of counter-crash technologies with future research directions .
Revised:  The review also covers the probable crash scenarios by red-light running and stop-and-go associated driving behaviour and subsequently implement countermeasures to combat such risky behaviour and improve the associated safety .
Edit intent: clarity