wanyu/IteraTeR_full_sent huggingface dataset:
Original: For a given linear algebra problem, we consider those solution algorithms that are mathematically equivalent to one another, and that mostly consist of a sequence of callsto kernels from optimized libraries such as BLAS and LAPACK. Although equivalent (at least in exact precision) , those algorithms typically exhibit significant differences in terms of performance , and naturally, we are interested in finding the fastest one(s) . In practice, we often observe that multiple algorithms yield comparable performance characteristics.
Revised: In scientific computing, it is common that one target computation can be translated into many different sequences of library calls, each identifying an algorithm. Although mathematically equivalent , those algorithms typically exhibit significant differences in terms of performance , and naturally, we are interested in finding the fastest one(s) . In practice, we often observe that multiple algorithms yield comparable performance characteristics.
Edit intent: clarity
Original:  Although equivalent (at least in exact precision) , those algorithms typically exhibit significant differences in terms of performance , and naturally, we are interested in finding the fastest one(s) . In practice, we often observe that multiple algorithms yield comparable performance characteristics.
Revised:  Although equivalent (at least in exact precision) , those algorithms might exhibit significant differences in terms of performance , and naturally, we are interested in finding the fastest one(s) . In practice, we often observe that multiple algorithms yield comparable performance characteristics.
Edit intent: clarity
Original:  Although equivalent (at least in exact precision) , those algorithms typically exhibit significant differences in terms of performance , and naturally, we are interested in finding the fastest one(s) . In practice, we often observe that multiple algorithms yield comparable performance characteristics.
Revised:  Although equivalent (at least in exact precision) , those algorithms typically exhibit significant differences in terms of performance , and naturally, we are interested in finding the fastest one(s) . In practice, we observe that subsets of algorithms show comparable performance characteristics.
Edit intent: clarity
Original:   To this end, instead 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:  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. To this end, instead 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: meaning-changed
Original:  To address this, we propose viewmaker networks: generative models that learn to produce input-dependent views for contrastive learning. We train this network jointly with an encoder network to produce adversarial \ell_pperturbations for an input, which yields challenging yet useful views without extensive human tuning. Our learned views, when applied to CIFAR-10,  enable comparable transfer accuracy to the the well-studied augmentations used for the SimCLR model.
Revised:  To address this, we propose viewmaker networks: generative models that learn to produce useful views from a given input. Viewmakers are stochastic bounded adversaries: they produce views by generating and then adding an \ell_p-bounded perturbation to the input, and are trained adversarially with respect to the main encoder network. Remarkably, when pretraining on CIFAR-10, enable comparable transfer accuracy to the the well-studied augmentations used for the SimCLR model.
Edit intent: meaning-changed
Original:  Our learned views, when applied to CIFAR-10,  enable comparable transfer accuracy to the the well-studied augmentations used for the SimCLR model. Our views significantly outperforming baseline augmentations in speech (+9\% absolute ) and wearable sensor  (+17\% absolute)domains.
Revised:  Our learned views, when applied to CIFAR-10, enable comparable transfer accuracy to the well-tuned SimCLR augmentations -- despite not including transformations like cropping or color jitter. Furthermore, our learned views significantly outperform baseline augmentations on speech recordings (+9\% absolute ) and wearable sensor (+17\% absolute)domains.
Edit intent: meaning-changed
Original:  Our views significantly outperforming baseline augmentations in speech (+9\% absolute ) and wearable sensor  (+17\% absolute)domains. We also show how viewmaker views can be combined with handcrafted views to improve robustness to common image corruptions .
Revised:  Our views significantly outperforming baseline augmentations in speech (+9\% absolute ) and wearable sensor (+17\% points). Viewmakers can also be combined with handcrafted views to improve robustness to common image corruptions .
Edit intent: clarity
Original:  We also show how viewmaker views can be combined with handcrafted views to improve robustness to common image corruptions . Our method demonstrates that learned views are a promising way to reduce the amount of expertise and effort needed for unsupervised learning, potentially extending its benefits to a much wider set of domains. 
Revised:  We also show how viewmaker views can be combined with handcrafted views to improve robustness to common image corruptions and can increase transfer performance in cases where handcrafted views are less explored. These results suggest that viewmakers may provide a path towards more general representation learning algorithms -- reducing the domain expertise and effort needed for unsupervised learning, potentially extending its benefits to a much wider set of domains. 
Edit intent: meaning-changed
Original: End-to-end automatic speech recognition (ASR) systems are increasingly being favoured due to their direct treatment of the problem of speech to text conversion. However, these systems are known to be data hungry and hence underperform in low-resource settings. In this work , we propose a seemingly simple but effective technique to improve low-resource end-to-end ASR performance.
Revised: This work presents a seemingly simple but effective technique to improve low-resource end-to-end ASR performance.
Edit intent: coherence
Original:  In this work , we propose a seemingly simple but effective technique to improve low-resource end-to-end ASR performance. We compress the output vocabulary of the end-to-end ASR  system using linguistically meaningful reductions and then reconstruct the original vocabulary using a standalone module.
Revised:  In this work , we propose a seemingly simple but effective technique to improve low-resource ASR system using linguistically meaningful reductions and then reconstruct the original vocabulary using a standalone module.
Edit intent: clarity
Original:  We compress the output vocabulary of the end-to-end ASR  system using linguistically meaningful reductions and then reconstruct the original vocabulary using a standalone module.
Revised:  We compress the output vocabulary of the end-to-end ASR systems for phonetic languages. By identifying sets of acoustically similar graphemes in these languages, we first reduce the output alphabet of the ASR system using linguistically meaningful reductions and then reconstruct the original vocabulary using a standalone module.
Edit intent: meaning-changed
Original:  Our objective is two-fold: to lessen the burden on the low-resource end-to-end ASR system by reducing the output vocabulary space and to design a powerful reconstruction module that recovers sequences in the original vocabulary from sequences in the reduced vocabulary .
Revised:  We demonstrate that this lessens the burden and improves the performance of low-resource end-to-end ASR system by reducing the output vocabulary space and to design a powerful reconstruction module that recovers sequences in the original vocabulary from sequences in the reduced vocabulary .
Edit intent: meaning-changed
Original:  Our objective is two-fold: to lessen the burden on the low-resource end-to-end ASR system by reducing the output vocabulary space and to design a powerful reconstruction module that recovers sequences in the original vocabulary from sequences in the reduced vocabulary .
Revised:  Our objective is two-fold: to lessen the burden on the low-resource end-to-end ASR systems (because only reduced-alphabet predictions are needed) and that it is possible to design a powerful reconstruction module that recovers sequences in the original vocabulary from sequences in the reduced vocabulary .
Edit intent: meaning-changed
Original:  Our objective is two-fold: to lessen the burden on the low-resource end-to-end ASR system by reducing the output vocabulary space and to design a powerful reconstruction module that recovers sequences in the original vocabulary from sequences in the reduced vocabulary .
Revised:  Our objective is two-fold: to lessen the burden on the low-resource end-to-end ASR system by reducing the output vocabulary space and to design a very simple but effective reconstruction module that recovers sequences in the original vocabulary from sequences in the reduced vocabulary .
Edit intent: meaning-changed
Original:  Our objective is two-fold: to lessen the burden on the low-resource end-to-end ASR system by reducing the output vocabulary space and to design a powerful reconstruction module that recovers sequences in the original vocabulary from sequences in the reduced vocabulary .
Revised:  Our objective is two-fold: to lessen the burden on the low-resource end-to-end ASR system by reducing the output vocabulary space and to design a powerful reconstruction module that recovers sequences in the original alphabet from sequences in the reduced vocabulary .
Edit intent: clarity
Original:  Our objective is two-fold: to lessen the burden on the low-resource end-to-end ASR system by reducing the output vocabulary space and to design a powerful reconstruction module that recovers sequences in the original vocabulary from sequences in the reduced vocabulary .
Revised:  Our objective is two-fold: to lessen the burden on the low-resource end-to-end ASR system by reducing the output vocabulary space and to design a powerful reconstruction module that recovers sequences in the original vocabulary from sequences in the reduced alphabet .
Edit intent: clarity
Original: Simulation-based training is an effective tool for acquiring practical skills, the question remains as to which methods should be utilized to optimize this process and for a better assessment of improved manual dexterity. Specifically , it is not fully understood which brain processes during simulation-based training will translate to better skill acquisition through practice.
Revised: Simulation-based training is an effective tool for acquiring practical skills, specifically to train new surgeons in a controlled and hazard-free environment , it is not fully understood which brain processes during simulation-based training will translate to better skill acquisition through practice.
Edit intent: meaning-changed
Original:  Specifically , it is not fully understood which brain processes during simulation-based training will translate to better skill acquisition through practice. As cognitive load decreases with better performance, we used a novel method for brain assessment that enables an extraction of a cognitive load neurological biomarker . 38 participants were assigned into 3 experiments examining their behavioral performance undergoing a task with the Simbionix LAP MENTO simulator, while their brain activity was measured using a single-electrode EEG by Aurora by Neurosteer . Each task was repeated 3 times with difference session setups.
Revised:  Specifically , it is however important to measure participants cognitive load to decide whether they are ready to go into a real surgery. In the present study we measured performance on a surgery simulator of medical students and interns, while their brain activity was monitored by a mobile EEG device . 38 participants were assigned into 3 experiments examining their behavioral performance undergoing a task with the Simbionix LAP MENTO simulator, while their brain activity was measured using a single-electrode EEG by Aurora by Neurosteer . Each task was repeated 3 times with difference session setups.
Edit intent: coherence
Original:  As cognitive load decreases with better performance, we used a novel method for brain assessment that enables an extraction of a cognitive load neurological biomarker . 38 participants were assigned into 3 experiments examining their behavioral performance undergoing a task with the Simbionix LAP MENTO simulator, while their brain activity was measured using a single-electrode EEG by Aurora by Neurosteer . Each task was repeated 3 times with difference session setups.
Revised:  As cognitive load decreases with better performance, we used a novel method for brain assessment that enables an extraction of a cognitive load neurological biomarker . 38 medical studentswere underwent 3 experiments examining their behavioral performance undergoing a task with the Simbionix LAP MENTO simulator, while their brain activity was measured using a single-electrode EEG by Aurora by Neurosteer . Each task was repeated 3 times with difference session setups.
Edit intent: meaning-changed
Original:  As cognitive load decreases with better performance, we used a novel method for brain assessment that enables an extraction of a cognitive load neurological biomarker . 38 participants were assigned into 3 experiments examining their behavioral performance undergoing a task with the Simbionix LAP MENTO simulator, while their brain activity was measured using a single-electrode EEG by Aurora by Neurosteer . Each task was repeated 3 times with difference session setups.
Revised:  As cognitive load decreases with better performance, we used a novel method for brain assessment that enables an extraction of a cognitive load neurological biomarker . 38 participants were assigned into 3 experiments undergoing a task with the Simbionix LAP MENTO simulator, while their brain activity was measured using a single-electrode EEG by Aurora by Neurosteer . Each task was repeated 3 times with difference session setups.
Edit intent: clarity
Original:  As cognitive load decreases with better performance, we used a novel method for brain assessment that enables an extraction of a cognitive load neurological biomarker . 38 participants were assigned into 3 experiments examining their behavioral performance undergoing a task with the Simbionix LAP MENTO simulator, while their brain activity was measured using a single-electrode EEG by Aurora by Neurosteer . Each task was repeated 3 times with difference session setups.
Revised:  As cognitive load decreases with better performance, we used a novel method for brain assessment that enables an extraction of a cognitive load neurological biomarker . 38 participants were assigned into 3 experiments examining their behavioral performance undergoing a task with Simbionix simulator, while their brain activity was measured using a single-electrode EEG by Aurora by Neurosteer . Each task was repeated 3 times with difference session setups.
Edit intent: clarity
Original:  As cognitive load decreases with better performance, we used a novel method for brain assessment that enables an extraction of a cognitive load neurological biomarker . 38 participants were assigned into 3 experiments examining their behavioral performance undergoing a task with the Simbionix LAP MENTO simulator, while their brain activity was measured using a single-electrode EEG by Aurora by Neurosteer . Each task was repeated 3 times with difference session setups.
Revised:  As cognitive load decreases with better performance, we used a novel method for brain assessment that enables an extraction of a cognitive load neurological biomarker . 38 participants were assigned into 3 experiments examining their behavioral performance undergoing a task with the Simbionix LAP MENTO simulator, while their brain activity was measured using a single-channel EEG device ( Aurora by Neurosteer . Each task was repeated 3 times with difference session setups.
Edit intent: clarity
Original:  As cognitive load decreases with better performance, we used a novel method for brain assessment that enables an extraction of a cognitive load neurological biomarker . 38 participants were assigned into 3 experiments examining their behavioral performance undergoing a task with the Simbionix LAP MENTO simulator, while their brain activity was measured using a single-electrode EEG by Aurora by Neurosteer . Each task was repeated 3 times with difference session setups.
Revised:  As cognitive load decreases with better performance, we used a novel method for brain assessment that enables an extraction of a cognitive load neurological biomarker . 38 participants were assigned into 3 experiments examining their behavioral performance undergoing a task with the Simbionix LAP MENTO simulator, while their brain activity was measured using a single-electrode EEG by Aurora by Neurosteer ). On each experiment, participants performed 3 times with difference session setups.
Edit intent: clarity
Original:  As cognitive load decreases with better performance, we used a novel method for brain assessment that enables an extraction of a cognitive load neurological biomarker . 38 participants were assigned into 3 experiments examining their behavioral performance undergoing a task with the Simbionix LAP MENTO simulator, while their brain activity was measured using a single-electrode EEG by Aurora by Neurosteer . Each task was repeated 3 times with difference session setups. Correlations between a cognitive biomarker (VC9) and behavioral performance measurements (e. g. accuracy, economy of movement and time to exceed the task). Exp 1 results exhibited an improvement in behavioral performance with no correlations to VC9.
Revised:  As cognitive load decreases with better performance, we used a novel method for brain assessment that enables an extraction of a cognitive load neurological biomarker . 38 participants were assigned into 3 experiments examining their behavioral performance undergoing a task with the Simbionix LAP MENTO simulator, while their brain activity was measured using a single-electrode EEG by Aurora by Neurosteer . Each task was repeated 3 repeats of a simulator task using laparoscopic hands. The retention between tasks was different on each experiment, to examine changes in performance and cognitive load biomarkers that occur during the task or as a results of night sleep consolidation. The participants behavioral performance improved with trial repetition in all 3 experiments. In Exps. 1 results exhibited an improvement in behavioral performance with no correlations to VC9.
Edit intent: meaning-changed
Original:  Exp 1 results exhibited an improvement in behavioral performance with no correlations to VC9. As a result of prolonging session time to three trials, VC9 activity significantly decreased with higher participants performance both in Exp.2 and in Exp. 3. Altogether , VC9 is found to be an effective biological measurement for the assessment of cognitive load while performing laparoscopic tasks using the surgical simulator.
Revised:  Exp 1 2, the theta band activity significantly decreased with better individual performance, as exhibited by some of the behavioral measurements of the simulator. The novel VC9 activity significantly decreased with higher participants performance both in Exp.2 and in Exp. 3. Altogether , VC9 is found to be an effective biological measurement for the assessment of cognitive load while performing laparoscopic tasks using the surgical simulator.
Edit intent: meaning-changed
Original:  As a result of prolonging session time to three trials, VC9 activity significantly decreased with higher participants performance both in Exp.2 and in Exp. 3. Altogether , VC9 is found to be an effective biological measurement for the assessment of cognitive load while performing laparoscopic tasks using the surgical simulator.
Revised:  As a result of prolonging session time to three trials, VC9 biomarker (previously shown to correlate with cognitive load), exhibited a significant decrease with better individual performance shown by all behavioral measurements. In correspondence with previous research, theta decreased with lower cognitive load and higher performance and the novel biomarker , VC9 is found to be an effective biological measurement for the assessment of cognitive load while performing laparoscopic tasks using the surgical simulator.
Edit intent: meaning-changed
Original:  As a result of prolonging session time to three trials, VC9 activity significantly decreased with higher participants performance both in Exp.2 and in Exp. 3. Altogether , VC9 is found to be an effective biological measurement for the assessment of cognitive load while performing laparoscopic tasks using the surgical simulator.
Revised:  As a result of prolonging session time to three trials, VC9 activity significantly decreased with higher participants performance both in Exp.2 and in Exp. 3. Altogether , VC9 , showed higher sensitivity to load changes. Together, these measurements might be for neuroimaging assessment of cognitive load while performing laparoscopic tasks using the surgical simulator.
Edit intent: meaning-changed
Original:  As a result of prolonging session time to three trials, VC9 activity significantly decreased with higher participants performance both in Exp.2 and in Exp. 3. Altogether , VC9 is found to be an effective biological measurement for the assessment of cognitive load while performing laparoscopic tasks using the surgical simulator. As surgical simulations allow to gain important skills and experience needed to perform procedures without any patient risk, it is crucial to fully evaluate and optimize the effect of these simulations on medical staff.
Revised:  As a result of prolonging session time to three trials, VC9 activity significantly decreased with higher participants performance both in Exp.2 and in Exp. 3. Altogether , VC9 is found to be an effective biological measurement for the assessment of cognitive load while performing simulator laparoscopic tasks.
Edit intent: coherence
Original: We continue to analyze matching of some basic constraints on human's decision making with quantum theory of measurement. As was found, quantum measurement theory based on the projection postulate does not match with combination of the question order effect (QOE) and the response replicability effect (RRE).
Revised: We continue to analyze matching of some basic constraints on the human decision making from the viewpoint of quantum measurement theory (QMT). As it has been found, the conventional QMT based on the projection postulate does not match with combination of the question order effect (QOE) and the response replicability effect (RRE).
Edit intent: clarity
Original:  This equality was derived by Busemeyer and Wang and it was shown (in the joint paper with Solloway and Shiffrin) that statistical data from many social opinion polls satisfies it. Now, we construct quantum instruments satisfying QQE, RRE , and QQ-inequality.
Revised:  This equality was derived by Busemeyer and Wang and it was shown (in the joint paper with Solloway and Shiffrin) that statistical data from many social opinion polls satisfy it. Here we construct quantum instruments satisfying QQE, RRE , and QQ-inequality.
Edit intent: coherence