wanyu/IteraTeR_v2 huggingface dataset:
Original: In scientific computing, it is common that one target computation can be translated into many different sequences of library calls , each identifying an algorithm .
Revised: In scientific computing, it is common that a mathematical expression can be computed by many different algorithms (sometimes over hundreds) , each identifying an algorithm .
Edit intent: clarity
Original: In scientific computing, it is common that one target computation can be translated into many different sequences of library calls , each identifying an algorithm .
Revised: In scientific computing, it is common that one target computation can be translated into many different sequences of library calls , each identifying a specific sequence of library calls .
Edit intent: clarity
Original:  In practice, we observe that subsets of algorithms show comparable performance characteristics .
Revised:  However in practice, due to fluctuations, there is not one algorithm that consistently performs noticeably better than the rest .
Edit intent: clarity
Original:  For this reason,  we aim to identify and separate not one algorithm, but the subset of algorithms , that are reliably faster than the rest.
Revised:  For this reason, we aim to identify not the one best algorithm, but the subset of algorithms , that are reliably faster than the rest.
Edit intent: clarity
Original:  For this reason,  we aim to identify and separate not one algorithm, but the subset of algorithms , that are reliably faster than the rest.
Revised:  For this reason, we aim to identify and separate not one algorithm, but the subset of algorithms that are reliably faster than the rest.
Edit intent: fluency
Original:  One of the motivations for this setup is that it makes it then possible to select an algorithm based on additional performance metrics such as those based on energy or scalability.
Edit intent: coherence
Original:  To this end, instead of using the usual methods of quantifying the performance of an algorithm in absolute terms, we present a measurement-based approach that assigns a relative score to the algorithms in comparison to one another.
Revised:  To this end, instead of using the usual approach of quantifying the performance of an algorithm in absolute terms, we present a measurement-based approach that assigns a relative score to the algorithms in comparison to one another.
Edit intent: clarity
Original:  The relative performance is encoded by sorting the algorithms based on pair-wise comparisons and by ranking them into equivalence (or performance) classes , so that multiple algorithms can obtain the same rank .
Revised:  The relative performance is encoded by sorting the algorithms based on pair-wise comparisons and by ranking them into equivalence (or performance) classes using pair-wise comparisons .
Edit intent: clarity
Original:  We show that this approach, based on relative performance, leads to robust identification of the fastest algorithms , that is, reliable identification even under noisy system conditions  .
Revised:  We show that this approach, based on relative performance, leads to robust identification of the fastest algorithms even under noisy system conditions .
Edit intent: coherence
Original:  We show that this approach, based on relative performance, leads to robust identification of the fastest algorithms , that is, reliable identification even under noisy system conditions  .
Revised:  We show that this approach, based on relative performance, leads to robust identification of the fastest algorithms , that is, reliable identification even under noisy system conditions . Furthermore, it enables the development of practical machine learning models for automatic algorithm selection .
Edit intent: coherence
Original:  Following some impossibility results, we restrict attention to matroid feasibility constraints that capture natural scenarios, such as the allocation of shifts to medical doctors or conference papers to referees.
Revised:  Following some impossibility results, we restrict attention to matroid feasibility constraints that capture natural scenarios, such as the allocation of shifts to medical doctors , and the allocation of conference papers to referees.
Edit intent: coherence
Original:  A major open problem is the existence of EF1 complete allocations among heterogeneous agents, where the heterogeneity is both in the agents' feasibility constraints and in their valuations.
Revised:  An open problem is the existence of EF1 complete allocations among heterogeneous agents, where the heterogeneity is both in the agents' feasibility constraints and in their valuations.
Edit intent: clarity
Original:  We adapt the Reeb graph edit distance of Landi et. al. to each of our categories and prove that both functors in our pipeline are 1-Lipschitz making our pipeline stable  .
Revised:  We adapt the Reeb graph edit distance to each of our categories and prove that both functors in our pipeline are 1-Lipschitz making our pipeline stable .
Edit intent: clarity
Original:  While work in algorithmic fairness to-date has primarily focused on addressing discrimination due to individually linked attributes, social science research elucidates how some properties we link to individuals can be conceptualized as having causes at population (e.g. structural /social) levels and it may be important to be fair to attributes at multiple levels.
Revised:  While work in algorithmic fairness to-date has primarily focused on addressing discrimination due to individually linked attributes, social science research elucidates how some properties we link to individuals can be conceptualized as having causes at macro (e.g. structural /social) levels and it may be important to be fair to attributes at multiple levels.
Edit intent: clarity
Original:  While work in algorithmic fairness to-date has primarily focused on addressing discrimination due to individually linked attributes, social science research elucidates how some properties we link to individuals can be conceptualized as having causes at population (e.g. structural /social) levels and it may be important to be fair to attributes at multiple levels.
Revised:  While work in algorithmic fairness to-date has primarily focused on addressing discrimination due to individually linked attributes, social science research elucidates how some properties we link to individuals can be conceptualized as having causes at population (e.g. structural ) levels, and it may be important to be fair to attributes at multiple levels.
Edit intent: coherence
Original:  For example, instead of simply considering race as a  protected attribute of an individual, it can be thought of as the perceived race of an individual which in turn may be affected by neighborhood-level factors.
Revised:  For example, instead of simply considering race as a protected attribute of an individual, it can be thought of as the perceived race of an individual which in turn can be affected by neighborhood-level factors.
Edit intent: fluency
Original:  This multi-level conceptualization is relevant to questions of fairness, as it may not only be important to take into account if the individual belonged to another demographic group, but also if the individual received advantaged treatment at the population-level .
Revised:  This multi-level conceptualization is relevant to questions of fairness, as it may not only be important to take into account if the individual belonged to another demographic group, but also if the individual received advantaged treatment at the macro-level .
Edit intent: clarity
Original:  Further, in the context of a real-world task of predicting income based on population and individual-level attributes, we demonstrate an approach for mitigating unfairness due to multi-level sensitive attributes.
Revised:  Further, in the context of a real-world task of predicting income based on macro and individual-level attributes, we demonstrate an approach for mitigating unfairness due to multi-level sensitive attributes.
Edit intent: clarity
Original:  Further, in the context of a real-world task of predicting income based on population and individual-level attributes, we demonstrate an approach for mitigating unfairness due to multi-level sensitive attributes.
Revised:  Further, in the context of a real-world task of predicting income based on population and individual-level attributes, we demonstrate an approach for mitigating unfairness , a result of multi-level sensitive attributes.
Edit intent: clarity
Original: Ant colony optimization is one of the potential solutions to tackle intractable NP-Hard discrete combinatorial optimization problems .
Revised: Ant colony optimization (ACO) is a commonly used meta-heuristic to solve complex combinatorial optimization problems .
Edit intent: clarity
Original:  Here, this approach is advanced by stating and proving equivalent conditions for second-order stochastic dominance, a widely used way of comparing probability distributions is by their spread.
Revised:  Here, this approach is advanced by stating and proving equivalent conditions for second-order stochastic dominance, a widely used way of comparing probability distributions by their spread.
Edit intent: coherence
Original:  What are the prerequisites and goals of the cognitive mechanism of trust, and how can we cause these prerequisites and goals , or assess whether they are being satisfied in a given interaction?
Revised:  What are the prerequisites and goals of the cognitive mechanism of trust, and how can we promote them , or assess whether they are being satisfied in a given interaction?
Edit intent: clarity
Original:  Numerical experiments are presented that confirm that our error estimates are formally optimal until the solution develops singularities .
Revised:  We present time-adaptive numerical simulations based on the a posteriori error estimators for solutions involving blow-up .
Edit intent: clarity
Original: We proposed a model for the  CSMT2020  data challenge of melody classification.
Revised: We proposed a model for the CSMT2020 ) data challenge of melody classification.
Edit intent: fluency
Original:  Given recent evidence that class selectivity may not be necessary for, and can even impair generalization, we investigated whether it also confers robustness (or vulnerability) to perturbations of input data.
Revised:  Given recent evidence that class selectivity may not be necessary for, and in some cases can impair generalization, we investigated whether it also confers robustness (or vulnerability) to perturbations of input data.
Edit intent: clarity
Original:  Given recent evidence that class selectivity may not be necessary for, and can even impair generalization, we investigated whether it also confers robustness (or vulnerability) to perturbations of input data.
Revised:  Given recent evidence that class selectivity may not be necessary for, and can even impair generalization, we investigate whether it also confers robustness (or vulnerability) to perturbations of input data.
Edit intent: fluency
Original:  Networks regularized to have lower levels of class selectivity are more robust to average-case  perturbations, while networks with higher class selectivity are more vulnerable.
Revised:  Networks regularized to have lower levels of class selectivity were more robust to average-case perturbations, while networks with higher class selectivity are more vulnerable.
Edit intent: fluency
Original:  In contrast, we found that class selectivity increases robustness to  worst-case (i.e. white box adversarial) perturbations, suggesting that while decreasing class selectivity is helpful for average-case robustness , it is harmful for worst-case robustness .
Revised:  In contrast, class selectivity increases robustness to worst-case (i.e. white box adversarial) perturbations, suggesting that while decreasing class selectivity is helpful for average-case robustness , it is harmful for worst-case robustness .
Edit intent: coherence
Original:  In contrast, we found that class selectivity increases robustness to  worst-case (i.e. white box adversarial) perturbations, suggesting that while decreasing class selectivity is helpful for average-case robustness , it is harmful for worst-case robustness .
Revised:  In contrast, we found that class selectivity increases robustness to worst-case (i.e. white box adversarial) perturbations, suggesting that while decreasing class selectivity is helpful for average-case perturbations , it is harmful for worst-case robustness .
Edit intent: fluency
Original:  In contrast, we found that class selectivity increases robustness to  worst-case (i.e. white box adversarial) perturbations, suggesting that while decreasing class selectivity is helpful for average-case robustness , it is harmful for worst-case robustness .
Revised:  In contrast, we found that class selectivity increases robustness to worst-case (i.e. white box adversarial) perturbations, suggesting that while decreasing class selectivity is helpful for average-case robustness , it is harmful for worst-case perturbations .
Edit intent: fluency
Original:  We also found that the input-unit gradient was more variable across samples and units in high-selectivity networks compared to low-selectivity networks.
Revised:  Furthermore, the input-unit gradient was more variable across samples and units in high-selectivity networks compared to low-selectivity networks.
Edit intent: coherence
Original:  We also found that the input-unit gradient was more variable across samples and units in high-selectivity networks compared to low-selectivity networks.
Revised:  We also found that the input-unit gradient is more variable across samples and units in high-selectivity networks compared to low-selectivity networks.
Edit intent: fluency
Original: Speaker extraction algorithm relies on a reference speech to focus its attention on a target speaker.
Revised: Speaker extraction algorithm relies on the speech sample from the target speaker as the reference point to focus its attention on a target speaker.
Edit intent: clarity
Original:  We believe that temporal synchronization between speech and lip movement is a useful cue, and target speaker embedding is also equally important .
Revised:  We believe that temporal synchronization between speech and lip movement also serves as an informative cue .
Edit intent: clarity
Original:  Motivated by this belief , we study a novel technique to use visual cues as the reference to extract target speaker embedding , without the need of pre-registered reference speech.
Revised:  Motivated by this idea , we study a novel technique to use visual cues as the reference to extract target speaker embedding , without the need of pre-registered reference speech.
Edit intent: clarity
Original:  Motivated by this belief , we study a novel technique to use visual cues as the reference to extract target speaker embedding , without the need of pre-registered reference speech.
Revised:  Motivated by this belief , we study a novel technique to use visual cues as the reference to extract target speaker embedding , without the need of pre-recorded reference speech.
Edit intent: clarity
Original:  We propose a multi-modal speaker extraction network, named MuSE, that is conditioned only on a lip image sequence for target speaker extraction .
Revised:  We propose a multi-modal speaker extraction network, named MuSE, that is conditioned only on a lip image sequence .
Edit intent: coherence
Original:  MuSE not only improves over AV-ConvTasnet baseline in terms of SI-SDR and PESQ, but also shows superior robustness in cross-domain evaluations.
Revised:  MuSE not only outperforms other competitive baselines in terms of SI-SDR and PESQ, but also shows superior robustness in cross-domain evaluations.
Edit intent: clarity
Original:  MuSE not only outperforms other competitive baselines in terms of SI-SDR and PESQ, but also shows superior robustness in cross-domain evaluations.
Revised:  MuSE not only outperforms other competitive baselines in terms of SI-SDR and PESQ, but also shows consistent improvement in cross-dataset evaluations.
Edit intent: clarity
Original: Variational inequalities with monotone operators  capture many problems of interest, notably convex optimization and convex-concave saddle point problems.
Revised: Variational inequalities with monotone operators , which capture many problems of interest, notably convex optimization and convex-concave saddle point problems.
Edit intent: coherence
Original:  Our algorithms use a single operator evaluation per iteration and automatically adapt to  problem parameters such as smoothness .
Revised:  Our algorithms use a single operator evaluation per iteration and automatically adapt to unknown problem parameters such as smoothness .
Edit intent: clarity
Original: The COVID-19 pandemic has affected people's lives around the world at a unprecedented scale.
Revised: The COVID-19 pandemic has affected people's lives around the world on an unprecedented scale.
Edit intent: fluency
Original:  To investigate the hoarding behaviors in response to the pandemic , we propose a novel computational framework using large scale social media data.
Revised:  We intend to investigate hoarding behaviors in response to the pandemic , we propose a novel computational framework using large scale social media data.
Edit intent: clarity
Original:  To investigate the hoarding behaviors in response to the pandemic , we propose a novel computational framework using large scale social media data.
Revised:  To investigate the hoarding behaviors in response to the pandemic using large-scale social media data.
Edit intent: clarity
Original:  By comparing their anxiety scores with the typical Twitter anxiety score, we reveal further insights.
Revised:  By comparing their anxiety scores with the baseline Twitter anxiety score, we reveal further insights.
Edit intent: clarity
Original:  The LIWC anxiety mean for the hoarding related tweets is significantly higher than the general Twitter anxiety mean.
Revised:  The LIWC anxiety mean for the hoarding-related tweets is significantly higher than the general Twitter anxiety mean.
Edit intent: fluency
Original:  The LIWC anxiety mean for the hoarding related tweets is significantly higher than the general Twitter anxiety mean.
Revised:  The LIWC anxiety mean for the hoarding related tweets is significantly higher than the baseline Twitter anxiety mean.
Edit intent: clarity
Original:  One relevant problem that can be approach is how to build the models for the study of dynamical systems, and how to extract the relevant information to be able to answer the scientific questions of interest.
Revised:  One relevant problem that can be approached is how to build the models for the study of dynamical systems, and how to extract the relevant information to be able to answer the scientific questions of interest.
Edit intent: fluency
Original:  The purpose of the present work is to contribute to this aim by using a temporal processing task, in this case, a 3-bit Flip Flop memory, to show the modeling procedure in every step: from equations to the software code , using Tensorflow and Keras.
Revised:  The purpose of the present work is to contribute to this aim by using a temporal processing task, in this case, a 3-bit Flip Flop memory, to show the modeling procedure in every step: from equations to the software code using Tensorflow and Keras.
Edit intent: fluency
Original:  The code developed in this premier is provided to be used as a base for model other systems.
Revised:  The code developed in this work is provided to be used as a base for model other systems.
Edit intent: clarity
Original:  We show that EqSpike implemented in silicon neuromorphic technology could reduce the energy consumption of inference  and training by up to three orders of magnitude compared to GPUs.
Revised:  We show that EqSpike implemented in silicon neuromorphic technology could reduce the energy consumption of inference by up to three orders of magnitude and training by up to three orders of magnitude compared to GPUs.
Edit intent: fluency
Original:  So far, hardware-oriented studies of Equilibrium Propagation focused on rate-based networks.
Revised:  So far, hardware-oriented studies have so far focused on rate-based networks.
Edit intent: clarity
Original:  We show that EqSpike implemented in silicon neuromorphic technology could reduce the energy consumption of inference by up to three orders of magnitude and training by up to two orders of magnitude compared to GPUs.
Revised:  We show that EqSpike implemented in silicon neuromorphic technology could reduce the energy consumption of inference and training respectively by three orders and two orders of magnitude compared to GPUs.
Edit intent: clarity
Original:  Specifically, we demonstrate a potential fog-cloud combined IoT platform that can be used in the systematic and intelligent COVID-19 prevention and control, which involves five interventions including COVID-19 Symptom Diagnosis, Quarantine Monitoring, Contact Tracing \& Social Distancing, COVID-19 Outbreak Forecasting, and SARS-CoV-2 Mutation Tracking.
Revised:  Specifically, we demonstrate a potential fog-cloud combined IoT platform that can be used in the systematic and intelligent COVID-19 prevention and control, which involves five interventions including COVID-19 Symptom Diagnosis, Quarantine Monitoring, Contact Tracing Social Distancing, COVID-19 Outbreak Forecasting, and SARS-CoV-2 Mutation Tracking.
Edit intent: fluency
Original: We propose a reduced-order simulation and optimization technique for a type of digital materials which we denote as geometric meta-materials .
Revised: We analyze the performance of a reduced-order simulation and optimization technique for a type of digital materials which we denote as geometric meta-materials .
Edit intent: clarity
Original: We propose a reduced-order simulation and optimization technique for a type of digital materials which we denote as geometric meta-materials .
Revised: We propose a reduced-order simulation of geometric meta-materials .
Edit intent: clarity
Original:  They are planar cellular structures , which can be fabricated in 2d and folded in 3d space and thus well shaped into sophisticated 3d surfaces .
Revised:  They are planar cellular structures which can be fabricated in 2d and folded in 3d space and thus well shaped into sophisticated 3d surfaces .
Edit intent: fluency
Original:  They are planar cellular structures , which can be fabricated in 2d and folded in 3d space and thus well shaped into sophisticated 3d surfaces .
Revised:  They are planar cellular structures , which can be fabricated in 2d and folded in 3d space .
Edit intent: coherence
Original:  While the physical properties of the base material (i.e., the physical substance) of course influence the behavior as well, our goal is to factor them out .
Revised:  While the physical properties of the base material (i.e., the physical substance) influence the behavior as well, our goal is to factor them out .
Edit intent: coherence
Original:  While the physical properties of the base material (i.e., the physical substance) of course influence the behavior as well, our goal is to factor them out .
Revised:  While the physical properties of the base material (i.e., the physical substance) of course influence the behavior as well, but we essentially factor them out .
Edit intent: clarity
Original:  However, the simulation of such complex structures still comes with a high computational cost .
Revised:  However, the simulation of such complex geometric structures comes with a high computational cost .
Edit intent: clarity
Original:  We propose an approach to reduce this computational cost by abstracting the meso-structures and encoding the properties of their elastic deformation behavior into a different set of material parameters.
Revised:  We propose an approach to reduce it by abstracting the meso-structures and encoding the properties of their elastic deformation behavior into a different set of material parameters.
Edit intent: clarity