wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We evaluate the performance of pre-processing and post-processing debiasers for improving fairness in random forest classifierstrained on a suite of data sets. Specifically, we study how these debiasers generalize with respect to both out-of-sample test error for computing fairness -- performance and fairness -- fairness trade-offs, and on the change in other fairness metrics that were not explicitly optimised.
Revised:  We evaluate the performance of pre-processing and can in fact make fairness worse rather than better. A rigorous evaluation of the debiasing treatment effect requires extensive cross-validation beyond what is usually done. We demonstrate that this phenomenon can be explained as a consequence of bias-variance trade-off, with an increase in variance necessitated by imposing a fairness constraint. Follow-up experiments validate the theoretical prediction that the estimation variance depends strongly on the base rates of the protected class. Considering fairness--performance trade-offs justifies the counterintuitive notion that partial debiasing can actually yield better results in practice on out-of-sample test error for computing fairness -- performance and fairness -- fairness trade-offs, and on the change in other fairness metrics that were not explicitly optimised.
Edit intent: meaning-changed
Original:  Specifically, we study how these debiasers generalize with respect to both out-of-sample test error for computing fairness -- performance and fairness -- fairness trade-offs, and on the change in other fairness metrics that were not explicitly optimised. Our results demonstrate that out-of-sample performance on fairness and performance can vary substantially and unexpectedly. Moreover, the variance in estimation arises from class imbalances with respect to both the outcome and the protected classes. Our results highlight the importance of evaluating out-of-sample performance in practical usage .
Revised:  Specifically, we study how these debiasers generalize with respect to both out-of-sample data .
Edit intent: coherence
Original:  Such timer mechanisms are difficult to implement at the level of single cells , however, due to saturation in molecular components and stochasticity in the limited intracellular space.
Revised:  At the single-cell level, timer mechanisms can be implemented with genetic circuits: sets of genes connected to achieve specific tasks. However, such systems are difficult to implement at the level of single cells , however, due to saturation in molecular components and stochasticity in the limited intracellular space.
Edit intent: meaning-changed
Original:  Experiments on machine translation and abstract text summarization demonstrate the effectiveness of our proposed approach -- we obtain an average F1 of around 0.6 across all the benchmark datasets  and achieve significant improvements in sentence-level hallucination scoring compared to baseline methods.
Revised:  Experiments on machine translation and abstract text summarization demonstrate the effectiveness of our proposed approach -- we obtain an average F1 of around 60 across all the benchmark datasets and achieve significant improvements in sentence-level hallucination scoring compared to baseline methods.
Edit intent: meaning-changed
Original:  Experiments on machine translation and abstract text summarization demonstrate the effectiveness of our proposed approach -- we obtain an average F1 of around 0.6 across all the benchmark datasets  and achieve significant improvements in sentence-level hallucination scoring compared to baseline methods.
Revised:  Experiments on machine translation and abstract text summarization demonstrate the effectiveness of our proposed approach -- we obtain an average F1 of around 0.6 across all the benchmark datasets . Furthermore, we demonstrate how to use the token-level hallucination labels to define a fine-grained loss over the target sequence in the low-resource machine translation and achieve significant improvements in sentence-level hallucination scoring compared to baseline methods.
Edit intent: meaning-changed
Original:  Experiments on machine translation and abstract text summarization demonstrate the effectiveness of our proposed approach -- we obtain an average F1 of around 0.6 across all the benchmark datasets  and achieve significant improvements in sentence-level hallucination scoring compared to baseline methods.
Revised:  Experiments on machine translation and abstract text summarization demonstrate the effectiveness of our proposed approach -- we obtain an average F1 of around 0.6 across all the benchmark datasets and achieve significant improvements over strong baseline methods.
Edit intent: clarity
Original: Neural sequence models can generate highly fluent sentences  but recent studies have also shown that they are also prone to hallucinate additional content not supported by the input , which can cause a lack of trust in the model. To better assess the faithfulness of the machine outputs , we propose a new task to predict whether each token in the output sequence is hallucinated conditioned on the source input, and collect new manually annotated evaluation sets for this task.
Revised: Neural sequence models can generate highly fluent sentences but recent studies have also shown that they are also prone to hallucinate additional content not supported by the input . These variety of fluent but wrong outputs are particularly problematic, as it will not be possible for users to tell they are being presented incorrect content. To detect these errors, we propose a new task to predict whether each token in the output sequence is hallucinated conditioned on the source input, and collect new manually annotated evaluation sets for this task.
Edit intent: coherence
Original:  To better assess the faithfulness of the machine outputs , we propose a new task to predict whether each token in the output sequence is hallucinated conditioned on the source input, and collect new manually annotated evaluation sets for this task.
Revised:  To better assess the faithfulness of the machine outputs , we propose a task to predict whether each token in the output sequence is hallucinated conditioned on the source input, and collect new manually annotated evaluation sets for this task.
Edit intent: coherence
Original:  To better assess the faithfulness of the machine outputs , we propose a new task to predict whether each token in the output sequence is hallucinated conditioned on the source input, and collect new manually annotated evaluation sets for this task.
Revised:  To better assess the faithfulness of the machine outputs , we propose a new task to predict whether each token in the output sequence is hallucinated (not contained in the input) and collect new manually annotated evaluation sets for this task.
Edit intent: meaning-changed
Original:  We also introduce a novel method for learning to model hallucination detection, based on pretrained language models fine tuned on synthetic data that includes automatically inserted hallucinations . Experiments on machine translation and abstract text summarization demonstrate the effectiveness of our proposed approach -- we obtain an average F1 of around 60 across all the benchmark datasets.
Revised:  We also introduce a method for learning to model hallucination detection, based on pretrained language models fine tuned on synthetic data that includes automatically inserted hallucinations . Experiments on machine translation and abstract text summarization demonstrate the effectiveness of our proposed approach -- we obtain an average F1 of around 60 across all the benchmark datasets.
Edit intent: clarity
Original:  We also introduce a novel method for learning to model hallucination detection, based on pretrained language models fine tuned on synthetic data that includes automatically inserted hallucinations . Experiments on machine translation and abstract text summarization demonstrate the effectiveness of our proposed approach -- we obtain an average F1 of around 60 across all the benchmark datasets.
Revised:  We also introduce a novel method for learning to detect hallucinations using pretrained language models fine tuned on synthetic data that includes automatically inserted hallucinations . Experiments on machine translation and abstract text summarization demonstrate the effectiveness of our proposed approach -- we obtain an average F1 of around 60 across all the benchmark datasets.
Edit intent: clarity
Original:  We also introduce a novel method for learning to model hallucination detection, based on pretrained language models fine tuned on synthetic data that includes automatically inserted hallucinations . Experiments on machine translation and abstract text summarization demonstrate the effectiveness of our proposed approach -- we obtain an average F1 of around 60 across all the benchmark datasets.
Revised:  We also introduce a novel method for learning to model hallucination detection, based on pretrained language models fine tuned on synthetic data that includes automatically inserted hallucinations Experiments on machine translation and abstract text summarization demonstrate the effectiveness of our proposed approach -- we obtain an average F1 of around 60 across all the benchmark datasets.
Edit intent: fluency
Original:  We also introduce a novel method for learning to model hallucination detection, based on pretrained language models fine tuned on synthetic data that includes automatically inserted hallucinations . Experiments on machine translation and abstract text summarization demonstrate the effectiveness of our proposed approach -- we obtain an average F1 of around 60 across all the benchmark datasets.
Revised:  We also introduce a novel method for learning to model hallucination detection, based on pretrained language models fine tuned on synthetic data that includes automatically inserted hallucinations . Experiments on machine translation (MT) and abstractive summarization demonstrate that our proposed approach -- we obtain an average F1 of around 60 across all the benchmark datasets.
Edit intent: clarity
Original:  We also introduce a novel method for learning to model hallucination detection, based on pretrained language models fine tuned on synthetic data that includes automatically inserted hallucinations . Experiments on machine translation and abstract text summarization demonstrate the effectiveness of our proposed approach -- we obtain an average F1 of around 60 across all the benchmark datasets.
Revised:  We also introduce a novel method for learning to model hallucination detection, based on pretrained language models fine tuned on synthetic data that includes automatically inserted hallucinations . Experiments on machine translation and abstract text summarization demonstrate the effectiveness of our proposed approach consistently outperforms strong baselines on all benchmark datasets.
Edit intent: meaning-changed
Original:  Traditional SBP FD operators that approximate first-order spatial derivatives with central-difference stencils often have spurious unresolved  wave-modes in their numerical solutions. On marginally resolved computational grids  , these spurious wave-modes have the potential to destroy the accuracy of numerical solutions for a first-order hyperbolic partial differential equation, such as the elastic wave equation.
Revised:  Traditional SBP FD operators that approximate first-order spatial derivatives with central-difference stencils often have spurious unresolved wave-modes in their computed solutions. Recently derived high order accurate upwind SBP operators based upwind FD stencils have the potential to suppress these poisonous spurious wave-modes on marginally resolved computational grids , these spurious wave-modes have the potential to destroy the accuracy of numerical solutions for a first-order hyperbolic partial differential equation, such as the elastic wave equation.
Edit intent: meaning-changed
Original:  On marginally resolved computational grids  , these spurious wave-modes have the potential to destroy the accuracy of numerical solutions for a first-order hyperbolic partial differential equation, such as the elastic wave equation.
Revised:  On marginally resolved computational grids . In this paper, we demonstrate that not all high order upwind SBP FD operators are applicable. Numerical dispersion relation analysis shows that odd-order upwind SBP FD operators also support spurious unresolved high-frequencies on marginally resolved meshes. Meanwhile, even-order upwind SBP FD operators (of order 2, 4 , these spurious wave-modes have the potential to destroy the accuracy of numerical solutions for a first-order hyperbolic partial differential equation, such as the elastic wave equation.
Edit intent: meaning-changed
Original:  On marginally resolved computational grids  , these spurious wave-modes have the potential to destroy the accuracy of numerical solutions for a first-order hyperbolic partial differential equation, such as the elastic wave equation. To ensure the accuracy of numerical solutions of the three space dimensional (3D) elastic wave equation in complex geometries, we discretise the 3D elastic wave equation with a pair of non-central (upwind) finite-difference stencils, on boundary-conforming curvilinear meshes.
Revised:  On marginally resolved computational grids , 6) do not support spurious unresolved high frequency wave modes and also have better numerical dispersion properties. We discretise the three space dimensional (3D) elastic wave equation in complex geometries, we discretise the 3D elastic wave equation with a pair of non-central (upwind) finite-difference stencils, on boundary-conforming curvilinear meshes.
Edit intent: meaning-changed
Original:  To ensure the accuracy of numerical solutions of the three space dimensional (3D) elastic wave equation in complex geometries, we discretise the 3D elastic wave equation with a pair of non-central (upwind) finite-difference stencils, on boundary-conforming curvilinear meshes.
Revised:  To ensure the accuracy of numerical solutions of the three space dimensional (3D) elastic wave equation on boundary-conforming curvilinear meshes.
Edit intent: clarity
Original:  Using the energy method we prove that the numerical method is numerically stable , and energy conserving. Furthermore, computational results show the robustness of the scheme. We present numerical simulations of the 3D elastic wave equation in heterogeneous media with complex non-planar free surface topography  , including numerical simulations of community developed seismological benchmark problems.
Revised:  Using the energy method we prove that the semi-discrete approximation is stable and energy-conserving. We derive a priori error estimate and prove the convergence of the numerical error. Numerical experiments for the 3D elastic wave equation in complex geometries corroborate the theoretical analysis. Numerical simulations of the 3D elastic wave equation in heterogeneous media with complex non-planar free surface topography , including numerical simulations of community developed seismological benchmark problems.
Edit intent: meaning-changed
Original:  We present numerical simulations of the 3D elastic wave equation in heterogeneous media with complex non-planar free surface topography  , including numerical simulations of community developed seismological benchmark problems.
Revised:  We present numerical simulations of the 3D elastic wave equation in heterogeneous media with complex non-planar free surface topography are given , including numerical simulations of community developed seismological benchmark problems.
Edit intent: meaning-changed
Original:  Our results show that the upwind SBP operators are more  robust and less prone to numerical dispersion errors on marginally resolved meshes when compared to traditional SBP operators, thereby increasing efficiency .
Revised:  Our results show that even-order upwind SBP FD operators are more robust and less prone to numerical dispersion errors on marginally resolved meshes when compared to traditional SBP operators, thereby increasing efficiency .
Edit intent: meaning-changed
Original:  Our results show that the upwind SBP operators are more  robust and less prone to numerical dispersion errors on marginally resolved meshes when compared to traditional SBP operators, thereby increasing efficiency .
Revised:  Our results show that the upwind SBP operators are more robust and less prone to numerical dispersion errors on marginally resolved meshes when compared to the odd-order upwind and traditional SBP FD operators .
Edit intent: meaning-changed
Original:  If we assume Bitcoin's market capitalization grows in line with the one of gold, we find that the annual electricity consumption of Bitcoin may increase from 50 to 400 TWh between 2020 and 2100.
Revised:  If we assume Bitcoin's market capitalization grows in line with the one of gold, we find that the annual electricity consumption of Bitcoin may increase from 60 to 400 TWh between 2020 and 2100.
Edit intent: meaning-changed
Original:  However, in the business-as-usual scenario, emissions sum up to 2 gigatons until 2100, an amount comparable to 6 \% of global emissions in 2018.
Revised:  However, in the business-as-usual scenario, emissions sum up to 2 gigatons until 2100, an amount comparable to 7 \% of global emissions in 2018.
Edit intent: meaning-changed
Original:  However, in the business-as-usual scenario, emissions sum up to 2 gigatons until 2100, an amount comparable to 6 \% of global emissions in 2018.
Revised:  However, in the business-as-usual scenario, emissions sum up to 2 gigatons until 2100, an amount comparable to 6 \% of global emissions in 2019. The Bitcoin price spike at the end of 2020 shows, however, that progressive development of market capitalization could yield an electricity consumption of more than 100 TWh already in 2021, and lead to cumulative emissions of over 5 gigatons by 2100.
Edit intent: meaning-changed
Original:  Many of the previous researches focus on GPR image-based feature detection only, and none can process sparse GPR measurements to successfully reconstruct a very fine and detailed 3D model of underground objects for better visualization.
Revised:  Many previous researches focus on GPR image-based feature detection only, and none can process sparse GPR measurements to successfully reconstruct a very fine and detailed 3D model of underground objects for better visualization.
Edit intent: coherence
Original:  The experiments show that our method can generate a dense and complete point cloud model of pipe-shaped utilities based on a sparse input, i.e., GPR raw data , with various levels of incompleteness and noise.
Revised:  In this paper, both the quantitative and qualitative experiment results verify our method that can generate a dense and complete point cloud model of pipe-shaped utilities based on a sparse input, i.e., GPR raw data , with various levels of incompleteness and noise.
Edit intent: coherence
Original:  Of particular interest in this work is the development of high order finite volume (FV) weighted essentially non-oscillatory (WENO) methods, which utilize RBF approximations to obtain required data at the cell interfaces.
Revised:  Of particular interest in this work is the development of high order finite volume (FV) weighted essentially non-oscillatory (WENO) methods, which utilize RBF approximations to obtain required data at cell interfaces.
Edit intent: fluency
Original:  To highlight the effectiveness of the non-polynomial basis,  the proposed methods are applied to one-dimensional hyperbolic and weakly hyperbolic systems of conservation laws  .
Revised:  To highlight the effectiveness of the non-polynomial basis, the proposed methods are applied to one-dimensional hyperbolic and weakly hyperbolic systems of conservation laws and compared with several well-known FV WENO schemes in the literature .
Edit intent: meaning-changed
Original:  The system is based on the EDA architecture of Horiguchi et al., but utilizes the incremental Transformer encoder, attending only to its left contexts and using block-level recurrence in the hidden states to carry information from block to block, making the algorithm complexity linear in time.
Revised:  The system is based on the Encoder-Decoder-Attractor (EDA) architecture of Horiguchi et al., but utilizes the incremental Transformer encoder, attending only to its left contexts and using block-level recurrence in the hidden states to carry information from block to block, making the algorithm complexity linear in time.
Edit intent: meaning-changed
Original:  With more than two speakers, the accuracy gap between online and offline grows, but it still outperforms a baseline offline clustering diarization system for one to four speakers with unlimited context size, and shows comparable accuracy with context size of 10 seconds.
Revised:  With more than two speakers, the accuracy gap between online and offline grows, but the algorithm still outperforms a baseline offline clustering diarization system for one to four speakers with unlimited context size, and shows comparable accuracy with context size of 10 seconds.
Edit intent: clarity
Original: We here study the Battle of the Sexes game on small networks, extending the response strategy analysis to asymmetric gamesand three players. We model the different steady states, that are obtained in numerical simulations from the various update strategies, as different response strategy equilibria.
Revised: We here study the Battle of the Sexes game , a textbook case of asymmetric games, on small networks. Due to the conflicting preferences of the players, analytical approaches are scarce and most often update strategies are employed in numerical simulations from the various update strategies, as different response strategy equilibria.
Edit intent: meaning-changed
Original:  We model the different steady states, that are obtained in numerical simulations from the various update strategies, as different response strategy equilibria. These are then mapped to a generalized Ising model , describing the correlations between the players ' outcomes in a way that is agnostic to the existence of a link, but that coincides with the correlation device if there is one.
Revised:  We model the different steady states, that are obtained in numerical simulations of repeated games on networks until convergence is reached. As a result, correlations between the choices of the players emerge. Our approach is to study these correlations with a generalized Ising model , describing the correlations between the players ' outcomes in a way that is agnostic to the existence of a link, but that coincides with the correlation device if there is one.
Edit intent: meaning-changed
Original:  These are then mapped to a generalized Ising model , describing the correlations between the players ' outcomes in a way that is agnostic to the existence of a link, but that coincides with the correlation device if there is one.
Revised:  These are then mapped to a generalized Ising model . Using the response strategy framework, we describe how the actions of the players can bring the network into a steady configuration, starting from an out-of-equilibrium one. We obtain these configurations using game-theoretical tools, and describe the results using Ising parameters. We exhaust the two-player case, giving a detailed account of all the equilibrium possibilities.
Edit intent: meaning-changed