wanyu/IteraTeR_full_sent huggingface dataset:
Original:  A stochastic control problem optimizing a long-run objective function is an ergodic control problem whose resolution can be achieved by solving an associated  Hamilton-Jacobi-Bellman (HJB) equation having an effective Hamiltonian.
Revised:  A stochastic control problem optimizing a long-run objective is an ergodic control problem whose resolution can be achieved by solving an associated Hamilton-Jacobi-Bellman (HJB) equation having an effective Hamiltonian.
Edit intent: clarity
Original:  A stochastic control problem optimizing a long-run objective function is an ergodic control problem whose resolution can be achieved by solving an associated  Hamilton-Jacobi-Bellman (HJB) equation having an effective Hamiltonian.
Revised:  A stochastic control problem optimizing a long-run objective function is an ergodic control problem whose resolution can be achieved by solving an associated non-local Hamilton-Jacobi-Bellman (HJB) equation having an effective Hamiltonian.
Edit intent: meaning-changed
Original:  However, this key topic has not been well-studied in the context of environmental management. Focusing on non-smooth sediment storage management as an engineering problem, we formulate  a new ergodic control problem under discrete observations: a natural assumption of realistic observations .
Revised:  Focusing on sediment storage management as an engineering problem, we formulate a new ergodic control problem under discrete observations: a natural assumption of realistic observations .
Edit intent: coherence
Original:  We give an analytical solution to a simple problem and verify optimality and uniqueness of the corresponding HJB equation . To manage HJB equationsin more general cases , we propose a fast sweep method resorting to neither pseudo-time integration nor vanishing discount.
Revised:  We give an analytical solution to a simple problem and verify optimality and uniqueness of the corresponding HJB equation having unique non-smoothness and discontinuity. To numerically compute HJB equations , we propose a fast sweep method resorting to neither pseudo-time integration nor vanishing discount.
Edit intent: meaning-changed
Original: I study the impact of corona populism -- politics aimed at denying or downplaying the danger posed by COVID-19 for strategic reasons -- on the evolution of the pandemic using regional data from Austria. The right-wing FPOE first vocalized strong support for strict lockdown measures, but made a corona populist turn at the end of the first wave of infections.
Revised: I study the impact of corona populism -- politics aimed at downplaying the threat of Covid-19. Exploiting a policy U-turn of a major Austrian right-wing FPOE first vocalized strong support for strict lockdown measures, but made a corona populist turn at the end of the first wave of infections.
Edit intent: clarity
Original:  The right-wing FPOE first vocalized strong support for strict lockdown measures, but made a corona populist turn at the end of the first wave of infections. Using panel regression analysis, I show that the vote share of the FPOE at the last national parliamentary elections is a strong predictor for the number of COVID-19 deaths per capita after the FPOE switched their policy stance, while there is no correlation before the policy switch.
Revised:  The right-wing party (FPOE), I show that the vote share of the FPOE at the last national parliamentary elections is a strong predictor for the number of COVID-19 deaths per capita after the FPOE switched their policy stance, while there is no correlation before the policy switch.
Edit intent: clarity
Original:  Using panel regression analysis, I show that the vote share of the FPOE at the last national parliamentary elections is a strong predictor for the number of COVID-19 deaths per capita after the FPOE switched their policy stance, while there is no correlation before the policy switch.
Revised:  Using panel regression analysis, I show that Covid-19 deaths per capita after the FPOE switched their policy stance, while there is no correlation before the policy switch.
Edit intent: clarity
Original:  Using panel regression analysis, I show that the vote share of the FPOE at the last national parliamentary elections is a strong predictor for the number of COVID-19 deaths per capita after the FPOE switched their policy stance, while there is no correlation before the policy switch.
Revised:  Using panel regression analysis, I show that the vote share of the FPOE at the last national parliamentary elections is a strong predictor for the number of COVID-19 deaths per capita are significantly positively correlated with support for the FPOE only after the turn using panel regressions. Paradoxically, there is no correlation before the policy switch.
Edit intent: meaning-changed
Original:  Using panel regression analysis, I show that the vote share of the FPOE at the last national parliamentary elections is a strong predictor for the number of COVID-19 deaths per capita after the FPOE switched their policy stance, while there is no correlation before the policy switch. Interestingly, I do not find a statistically significant correlation between the FPOE vote share and the reported number of infections.
Revised:  Using panel regression analysis, I show that the vote share of the FPOE at the last national parliamentary elections is a strong predictor for the number of COVID-19 deaths per capita after the FPOE switched their policy stance, while there is no statistically significant correlation between the FPOE vote share and the reported number of infections.
Edit intent: coherence
Original:  I hypothesize that this can be traced back to a self-selection bias in testing . To explore this hypothesis , I extend the classical SIRD model to incorporate conditional quarantine and  two groups of agents : the majority and the corona sceptics, where the latter are less inclined to get tested and engage in social distancing.
Revised:  I hypothesize that this can be traced back to a self-selection bias in testing , which causes a higher dark figure in FPOE strongholds. I find empirical support for this hypothesis in individual-level data from a Covid-19 prevalence study showing a much higher share of (undetected) cases among "corona skeptics". I finally extend the classical SIRD model to incorporate conditional quarantine and two groups of agents : the majority and the corona sceptics, where the latter are less inclined to get tested and engage in social distancing.
Edit intent: meaning-changed
Original:  To explore this hypothesis , I extend the classical SIRD model to incorporate conditional quarantine and  two groups of agents : the majority and the corona sceptics, where the latter are less inclined to get tested and engage in social distancing.
Revised:  To explore this hypothesis , I extend the classical SIRD model to incorporate conditional quarantine and heterogeneous mixing of two groups of agents : the majority and the corona sceptics, where the latter are less inclined to get tested and engage in social distancing.
Edit intent: meaning-changed
Original:  To explore this hypothesis , I extend the classical SIRD model to incorporate conditional quarantine and  two groups of agents : the majority and the corona sceptics, where the latter are less inclined to get tested and engage in social distancing. Such a model can explain the puzzling empirics: if mixing is sufficiently homophilic , an increase in the share of corona sceptics can cause an increase in the number of deaths without increasing the number of reported infections .
Revised:  To explore this hypothesis , I extend the classical SIRD model to incorporate conditional quarantine and two groups of agents with behavioral differences and explore its partly non-trivial properties using thousands of numerical simulations. This model can explain the puzzling empirics: if mixing is sufficiently homophilic , an increase in the share of corona sceptics can cause an increase in the number of deaths without increasing the number of reported infections .
Edit intent: meaning-changed
Original:  Such a model can explain the puzzling empirics: if mixing is sufficiently homophilic , an increase in the share of corona sceptics can cause an increase in the number of deaths without increasing the number of reported infections .
Revised:  Such a model can explain the puzzling empirics: if the behavioral differences between the two groups are sufficiently different , an increase in the share of corona sceptics can cause an increase in the number of deaths without increasing the number of reported infections .
Edit intent: meaning-changed
Original:  Such a model can explain the puzzling empirics: if mixing is sufficiently homophilic , an increase in the share of corona sceptics can cause an increase in the number of deaths without increasing the number of reported infections .
Revised:  Such a model can explain the puzzling empirics: if mixing is sufficiently homophilic , an increase in the share of corona skeptics can cause an increase in the number of deaths without increasing the number of reported infections .
Edit intent: fluency
Original:  Such a model can explain the puzzling empirics: if mixing is sufficiently homophilic , an increase in the share of corona sceptics can cause an increase in the number of deaths without increasing the number of reported infections . I finally discuss the partly non-trivial implications of the interplay between group sizes, behavioral differences and the degree of homophily on public health outcomes within the theoretical model .
Revised:  Such a model can explain the puzzling empirics: if mixing is sufficiently homophilic , an increase in the share of corona sceptics can cause an increase in the number of deaths without increasing the number of reported infections .
Edit intent: coherence
Original:  Two well-designed techniques, namely the retrospective feed mechanism and the enhanced recurrence mechanism enable ERNIE-DOC with much longer effective context length  to capture the contextual information of a whole document.
Revised:  Two well-designed techniques, namely the retrospective feed mechanism and the enhanced recurrence mechanism , enable ERNIE-Doc, which has a much longer effective context length to capture the contextual information of a whole document.
Edit intent: coherence
Original:  Various experiments  on both English and Chinese document-level tasks are conducted. ERNIE-DOC achieves SOTA language modeling result of  16.8 ppl on WikiText-103 and outperforms competitive pretraining models  on most language understanding tasks  such as text classification , question answeringby a large margin .
Revised:  Various experiments on both English and Chinese document-level tasks . ERNIE-Doc improved the state-of-the-art language modeling result of 16.8 ppl on WikiText-103 and outperforms competitive pretraining models on most language understanding tasks such as text classification , question answeringby a large margin .
Edit intent: meaning-changed
Original:  ERNIE-DOC achieves SOTA language modeling result of  16.8 ppl on WikiText-103 and outperforms competitive pretraining models  on most language understanding tasks  such as text classification , question answeringby a large margin .
Revised:  ERNIE-DOC achieves SOTA language modeling result of perplexity to 16.8 ppl on WikiText-103 and outperforms competitive pretraining models on most language understanding tasks such as text classification , question answeringby a large margin .
Edit intent: meaning-changed
Original:  ERNIE-DOC achieves SOTA language modeling result of  16.8 ppl on WikiText-103 and outperforms competitive pretraining models  on most language understanding tasks  such as text classification , question answeringby a large margin .
Revised:  ERNIE-DOC achieves SOTA language modeling result of 16.8 on WikiText-103 and outperforms competitive pretraining models on most language understanding tasks such as text classification , question answeringby a large margin .
Edit intent: clarity
Original:  ERNIE-DOC achieves SOTA language modeling result of  16.8 ppl on WikiText-103 and outperforms competitive pretraining models  on most language understanding tasks  such as text classification , question answeringby a large margin .
Revised:  ERNIE-DOC achieves SOTA language modeling result of 16.8 ppl on WikiText-103 . Moreover, it outperformed competitive pretraining models on most language understanding tasks such as text classification , question answeringby a large margin .
Edit intent: coherence
Original:  ERNIE-DOC achieves SOTA language modeling result of  16.8 ppl on WikiText-103 and outperforms competitive pretraining models  on most language understanding tasks  such as text classification , question answeringby a large margin .
Revised:  ERNIE-DOC achieves SOTA language modeling result of 16.8 ppl on WikiText-103 and outperforms competitive pretraining models by a large margin on most language understanding tasks such as text classification , question answeringby a large margin .
Edit intent: fluency
Original:  ERNIE-DOC achieves SOTA language modeling result of  16.8 ppl on WikiText-103 and outperforms competitive pretraining models  on most language understanding tasks  such as text classification , question answeringby a large margin .
Revised:  ERNIE-DOC achieves SOTA language modeling result of 16.8 ppl on WikiText-103 and outperforms competitive pretraining models on most language understanding tasks , such as text classification , question answeringby a large margin .
Edit intent: fluency
Original:  ERNIE-DOC achieves SOTA language modeling result of  16.8 ppl on WikiText-103 and outperforms competitive pretraining models  on most language understanding tasks  such as text classification , question answeringby a large margin .
Revised:  ERNIE-DOC achieves SOTA language modeling result of 16.8 ppl on WikiText-103 and outperforms competitive pretraining models on most language understanding tasks such as text classification and question answering .
Edit intent: clarity
Original:  The  proposed approach is more general than existing methods as it is able to handle unmatched uncertainties while only requiring the system be nominally contracting in closed-loop.
Revised:  The analysis is first presented under the lens of contraction theory, and then expanded to general Lyapunov functions which can be synthesized via feedback linearization, backstepping, or optimization-based techniques. The proposed approach is more general than existing methods as it is able to handle unmatched uncertainties while only requiring the system be nominally contracting in closed-loop.
Edit intent: meaning-changed
Original:  The  proposed approach is more general than existing methods as it is able to handle unmatched uncertainties while only requiring the system be nominally contracting in closed-loop. Additionally, it can be used with learned feedback policies that are known to be contracting in some metric , facilitating transfer learning and bridging the sim2real gap.
Revised:  The proposed approach is more general than existing methods as the uncertainties can be unmatched and the system only needs to be stabilizable. The developed algorithm can be combined with learned feedback policies that are known to be contracting in some metric , facilitating transfer learning and bridging the sim2real gap.
Edit intent: meaning-changed
Original:  While quantization can be a viable solution to this, previous work on quantizing Transformer based models uses floating-point arithmetic during inference, thus limiting model deployment on many edge processors.
Revised:  While quantization can be a viable solution to this, previous work on quantizing Transformer based models uses floating-point arithmetic during inference, which cannot efficiently utilize integer-only logical units such as the recent Turing Tensor Cores, or traditional integer-only ARM processors.
Edit intent: meaning-changed
Original:  In this work, we propose a novel integer-only quantization scheme for Transformer based models that quantizes the entire inference process. In particular, we demonstrate how to approximate nonlinear operationsin Transformer architectures , e.g., GELU, Softmax, and Layer Normalization, with lightweight integer computations.
Revised:  In this work, we propose a novel integer-only quantization scheme for Transformer based models that quantizes the entire inference with integer-only arithmetic. Based on lightweight integer-only approximation methods for nonlinear operations , e.g., GELU, Softmax, and Layer Normalization, with lightweight integer computations.
Edit intent: clarity
Original:  In particular, we demonstrate how to approximate nonlinear operationsin Transformer architectures , e.g., GELU, Softmax, and Layer Normalization, with lightweight integer computations. We use those approximations in our method, I-BERT , with an end-to-end integer-only inference, and without any floating point calculation.
Revised:  In particular, we demonstrate how to approximate nonlinear operationsin Transformer architectures , e.g., GELU, Softmax, and Layer Normalization, I-BERT , with an end-to-end integer-only inference, and without any floating point calculation.
Edit intent: clarity
Original:  We test our approach on GLUE downstream tasks using RoBERTa-Base and RoBERTa-Large. For both cases, with an 8-bit integer-only quantization scheme, I-BERT achieves similar  accuracy as compared to the full-precision baseline  .
Revised:  We test our approach on GLUE downstream tasks using RoBERTa-Base /Large. We show that for both cases, with an 8-bit integer-only quantization scheme, I-BERT achieves similar accuracy as compared to the full-precision baseline .
Edit intent: coherence
Original:  For both cases, with an 8-bit integer-only quantization scheme, I-BERT achieves similar  accuracy as compared to the full-precision baseline  .
Revised:  For both cases, with an 8-bit integer-only quantization scheme, I-BERT achieves similar accuracy as compared to the full-precision baseline . Furthermore, our preliminary implementation of I-BERT shows a speedup of 2.4 - 4.0x for INT8 inference on a T4 GPU system as compared to FP32 inference. The framework has been developed in PyTorch and has been open-sourced .
Edit intent: meaning-changed
Original:  As a result, the research questions concerning the safety and reliability of learning-based perception are gaining increased importance. Although there is an established field that studies safety certification and convergence guarantee of complex software systems for decision-making during design-time , the uncertainty in run-time conditions and the unknown future deployment environments of autonomous systems as well as the complexity of learning-based perception systems make the generalisation of the verification results from design-time  to run-time problematic.
Revised:  As a result, the research questions concerning the safety and reliability of learning-based perception systems. There is an established field that studies safety certification and convergence guarantee of complex software systems for decision-making during design-time , the uncertainty in run-time conditions and the unknown future deployment environments of autonomous systems as well as the complexity of learning-based perception systems make the generalisation of the verification results from design-time to run-time problematic.
Edit intent: clarity
Original:  Although there is an established field that studies safety certification and convergence guarantee of complex software systems for decision-making during design-time , the uncertainty in run-time conditions and the unknown future deployment environments of autonomous systems as well as the complexity of learning-based perception systems make the generalisation of the verification results from design-time  to run-time problematic.
Revised:  Although there is an established field that studies safety certification and convergence guarantees of complex software systems for decision-making during design-time , the uncertainty in run-time conditions and the unknown future deployment environments of autonomous systems as well as the complexity of learning-based perception systems make the generalisation of the verification results from design-time to run-time problematic.
Edit intent: fluency
Original:  Although there is an established field that studies safety certification and convergence guarantee of complex software systems for decision-making during design-time , the uncertainty in run-time conditions and the unknown future deployment environments of autonomous systems as well as the complexity of learning-based perception systems make the generalisation of the verification results from design-time  to run-time problematic.
Revised:  Although there is an established field that studies safety certification and convergence guarantee of complex software systems at design-time , the uncertainty in run-time conditions and the unknown future deployment environments of autonomous systems as well as the complexity of learning-based perception systems make the generalisation of the verification results from design-time to run-time problematic.
Edit intent: clarity
Original:  Although there is an established field that studies safety certification and convergence guarantee of complex software systems for decision-making during design-time , the uncertainty in run-time conditions and the unknown future deployment environments of autonomous systems as well as the complexity of learning-based perception systems make the generalisation of the verification results from design-time  to run-time problematic.
Revised:  Although there is an established field that studies safety certification and convergence guarantee of complex software systems for decision-making during design-time . However, the unknown future deployment environments of autonomous systems as well as the complexity of learning-based perception systems make the generalisation of the verification results from design-time to run-time problematic.
Edit intent: coherence
Original:  Although there is an established field that studies safety certification and convergence guarantee of complex software systems for decision-making during design-time , the uncertainty in run-time conditions and the unknown future deployment environments of autonomous systems as well as the complexity of learning-based perception systems make the generalisation of the verification results from design-time  to run-time problematic.
Revised:  Although there is an established field that studies safety certification and convergence guarantee of complex software systems for decision-making during design-time , the uncertainty in run-time conditions and the unknown future deployment environments of an autonomous system and the complexity of learning-based perception systems make the generalisation of the verification results from design-time to run-time problematic.
Edit intent: coherence
Original:  Although there is an established field that studies safety certification and convergence guarantee of complex software systems for decision-making during design-time , the uncertainty in run-time conditions and the unknown future deployment environments of autonomous systems as well as the complexity of learning-based perception systems make the generalisation of the verification results from design-time  to run-time problematic.
Revised:  Although there is an established field that studies safety certification and convergence guarantee of complex software systems for decision-making during design-time , the uncertainty in run-time conditions and the unknown future deployment environments of autonomous systems as well as the complexity of learning-based perception make the generalization of design-time to run-time problematic.
Edit intent: coherence