wanyu/IteraTeR_full_sent huggingface dataset:
Original:  Interestingly our analysis suggests that data corrupted by adding noise to causal features will degrade out-of-domain performance, while noise added to non-causal features may make models more robust out-of-domain . This analysis yields interesting insights that help to explain the efficacy of counterfactually augmented data. Finally, we present a large-scale empirical study that supports this hypothesis .
Revised:  Interestingly our analysis suggests that data corrupted by adding noise to causal features will degrade out-of-domain performance, while noise added to non-causal features may make models more robust out-of-domain performance. This idea inspires a speculative test for determining whether a feature attribution technique has identified the causal spans. If adding noise (e.g., by random word flips) to the highlighted spans degrades both in-domain and out-of-domain performance on a battery of challenge datasets, but adding noise to the complement gives improvements out-of-domain, it suggests we have identified causal spans. We present a large-scale empirical study that supports this hypothesis .
Edit intent: meaning-changed
Original:  Single-cell RNA sequencing can measure the expression of thousands of genes in thousands of neurons. How to interpret the data in the context of neuronal phenotypes? We propose a supervised learning approach that factorizes the gene expression data into components corresponding to individual phenotypic characteristics and their interactions. This new method, which we call factorized linear discriminant analysis (FLDA), seeks a linear transformation of gene expressions that varies highly with only one phenotypic factor and minimally with the others.
Revised:  This representation is often sought from a linear transformation of the original data, for the reasons of model interpretability and computational simplicity. Here we propose a novel method of linear dimensionality reduction to address this problem. This method, which we call factorized linear discriminant analysis (FLDA), seeks a linear transformation of gene expressions that varies highly with only one phenotypic factor and minimally with the others.
Edit intent: coherence
Original:  We applied this approach to a single-cell RNA-Seq dataset of Drosophila T4/T5 neurons , focusing on their dendritic and axonal phenotypes. The analysis confirms results obtained by conventional methods but also points to new genes related to the phenotypes and an intriguing hierarchy in the URLanization of these cells .
Revised:  We applied this approach to a single-cell RNA-Seq dataset of Drosophila T4/T5 neurons . A representation from FLDA captured structures in the data aligned with phenotypic features and revealed critical genes for each phenotype .
Edit intent: meaning-changed
Original:  To investigate whether this is the case, we operationalise the lexical ambiguity of a word as the entropy of meanings it can take, and provide two ways to estimate this---one which requires human annotation (using WordNet), and one which does not (using BERT), making it readily applicable to a large number of languages.
Revised:  To investigate whether this is the case, we operationalise the lexical ambiguity of a word as the entropy of meanings it can take, and provide two ways to estimate this -- one which requires human annotation (using WordNet), and one which does not (using BERT), making it readily applicable to a large number of languages.
Edit intent: fluency
Original:  We then test our main hypothesis---that a word's lexical ambiguity should negatively correlate with its contextual uncertainty---and find significant correlations on all 18 typologically diverse languages we analyse.
Revised:  We then test our main hypothesis -- that a word's lexical ambiguity should negatively correlate with its contextual uncertainty---and find significant correlations on all 18 typologically diverse languages we analyse.
Edit intent: fluency
Original:  We then test our main hypothesis---that a word's lexical ambiguity should negatively correlate with its contextual uncertainty---and find significant correlations on all 18 typologically diverse languages we analyse.
Revised:  We then test our main hypothesis---that a word's lexical ambiguity should negatively correlate with its contextual uncertainty -- and find significant correlations on all 18 typologically diverse languages we analyse.
Edit intent: fluency
Original: Social contagion is a well-studied phenomenon in which people adopt beliefs that they are exposed to by their neighbors, and then pass those beliefs along to others. Research (and daily life) shows that people prefer to adopt beliefs that are consistent with those they already hold. However, scholars do not often account for interactions between beliefs in their models of social contagion .
Revised: Social contagion is a well-studied phenomenon in which people adopt a belief, idea, or practice from a neighbor and pass it along to someone else. For over 100 years, scholars of social contagion .
Edit intent: clarity
Original:  However, scholars do not often account for interactions between beliefs in their models of social contagion . Instead, they assume that beliefs spread independently of one another .
Revised:  However, scholars do not often account for interactions between beliefs in their models of social contagion have almost exclusively made the same implicit assumption: that only one belief, idea, or practice spreads through the population at a time. It is a default assumption that we don't bother to state, let alone justify. The assumption is so ingrained that our literature doesn't even have a word for "whatever is to be diffused", because we have never needed to discuss more than one of them. But this assumption is obviously false. Millions of beliefs, ideas, and practices (let's call them "diffusants") spread through social media every day. To assume that diffusants spread one at a time (or more generously, that they spread independently of one another .
Edit intent: meaning-changed
Original:  Instead, they assume that beliefs spread independently of one another . Is this a harmless simplification? Or does omitting interdependence between beliefs suppress important dynamics, and change the outcome of social contagion? This paper performs a head-to-head comparison between independent and interdependent diffusion.
Revised:  Instead, they assume that beliefs spread independently of one another ) is to assume that interactions between diffusants have no influence on adoption patterns. This could be true, or it could be wildly off the mark. We've never stopped to find out. This paper makes a direct comparison between the spread of independent and interdependent diffusion.
Edit intent: meaning-changed
Original:  This paper performs a head-to-head comparison between independent and interdependent diffusion. Simulations identify two social processes that emerge when diffusants interact, and predict that as a result of interdependent diffusion, worldviews will emerge that are unconstrained by external truth, and polarization will develop in homogenous populations. A controlled laboratory experimentconfirms these predictions with 2400 participants in 120 artificial social networks. I conclude that the assumption of independence between diffusants is not as universally appropriate as its ubiquity would suggest.
Revised:  This paper performs a head-to-head comparison between independent and interdependent beliefs using simulations, observational data analysis, and a 2400-subject laboratory experiment. I find that in assuming independence between diffusants is not as universally appropriate as its ubiquity would suggest.
Edit intent: clarity
Original:  I conclude that the assumption of independence between diffusants is not as universally appropriate as its ubiquity would suggest. Instead, interdependence between diffusants is likely to be both common and consequential .
Revised:  I conclude that the assumption of independence between diffusants , scholars have overlooked social processes that fundamentally change the outcomes of social contagion. Interdependence between beliefs generates polarization, irrespective of social network structure, homophily, demographics, politics, or any other commonly cited cause. It also leads to the emergence of popular worldviews that are unconstrained by ground truth .
Edit intent: meaning-changed
Original:  For a data set of size n, our data structure supports a batch of insertions or deletions of size m in O(m\log ( 1+ (n+m)/m)) expected work and O(\log (n+m)\log^*(n+m)) depth with high probability, and takes linear space.
Revised:  For a data set of size n, our data structure supports a batch of insertions or deletions of size m in O(m\log ( (n+m)/m)) expected work and O(\log (n+m)\log^*(n+m)) depth with high probability, and takes linear space.
Edit intent: clarity
Original:  On 48 cores with hyper-threading, the  algorithms achieve up to 51.45x (29.42x on average) speedup, and Rabin's algorithm performs the best on average.
Revised:  On 48 cores with hyper-threading, the static algorithms achieve up to 51.45x (29.42x on average) speedup, and Rabin's algorithm performs the best on average.
Edit intent: meaning-changed
Original:  Comparing our dynamic algorithm to the fastest static algorithm, we find that it is advantageous to use the dynamic algorithm for batch sizes of up to 70 \\%DIF < of the data set.
Revised:  Comparing our dynamic algorithm to the fastest static algorithm, we find that it is advantageous to use the dynamic algorithm for batch sizes of up to 20 \\%DIF < of the data set.
Edit intent: meaning-changed
Original: Preconditions provide a form of logical connection between events that explains why some events occur together and information that is complementary to the more widely studied relations such as causation, temporal ordering, entailment, and discourse relations.
Revised: Preconditions provide a form of logical connection between events that explains why some events occur together and information that is complementary to the more widely studied relations such as causation, temporal ordering, entailment, and discourse relations.
Edit intent: fluency
Original: In the paper "Fast Fibonacci heaps with worst case extensions"  we have described heaps with both Meld, DecreaseKey and DecreaseKey interfaces, allowing operations with guaranted worst case assymptotically optimal times.
Revised: In the paper "Fast Fibonacci heaps with worst case extensions" , we have described heaps with both Meld, DecreaseKey and DecreaseKey interfaces, allowing operations with guaranted worst case assymptotically optimal times.
Edit intent: fluency
Original: In the paper "Fast Fibonacci heaps with worst case extensions"  we have described heaps with both Meld, DecreaseKey and DecreaseKey interfaces, allowing operations with guaranted worst case assymptotically optimal times.
Revised: In the paper "Fast Fibonacci heaps with worst case extensions" we have described heaps with both Meld-DecreaseKey and DecreaseKey interfaces, allowing operations with guaranted worst case assymptotically optimal times.
Edit intent: fluency
Original: In the paper "Fast Fibonacci heaps with worst case extensions"  we have described heaps with both Meld, DecreaseKey and DecreaseKey interfaces, allowing operations with guaranted worst case assymptotically optimal times.
Revised: In the paper "Fast Fibonacci heaps with worst case extensions" we have described heaps with both Meld, DecreaseKey and DecreaseKey interfaces, allowing operations with guaranteed worst-case asymptotically optimal times.
Edit intent: fluency
Original:  The paper was intended to concentrate on  DecreaseKey interface, but it could be hard to separate the two described data structures without carefull reading. Current paper's goal is not to invent a novel data structure, but to describe the rather easy DecreaseKey version in  hopefully readable form.
Revised:  The paper was intended to concentrate on DecreaseKey interface, but it could be hard to separate the two described data structures without careful reading. The current paper's goal is not to invent a novel data structure, but to describe the rather easy DecreaseKey version in hopefully readable form.
Edit intent: fluency
Original:  We will prove that for euclidean Traveling Salesman Problems with n cities the approximation ratio of the 2-Opt heuristic is \Theta(\log n/ \log \log n).  ] 
Revised:  We will prove that for Euclidean Traveling Salesman Problems with n cities the approximation ratio of the 2-Opt heuristic is \Theta(\log n/ \log \log n). ] 
Edit intent: fluency
Original:  We will prove that for euclidean Traveling Salesman Problems with n cities the approximation ratio of the 2-Opt heuristic is \Theta(\log n/ \log \log n).  ] 
Revised:  We will prove that for euclidean Traveling Salesman Problems with n cities the approximation ratio of the 2-Opt heuristic is \Theta(\log n/ \log \log n). This improves the upper bound of O(\log n) given by Chandra, Karloff, and Tovey ] 
Edit intent: meaning-changed
Original:  We will prove that for euclidean Traveling Salesman Problems with n cities the approximation ratio of the 2-Opt heuristic is \Theta(\log n/ \log \log n).  ] 
Revised:  We will prove that for euclidean Traveling Salesman Problems with n cities the approximation ratio of the 2-Opt heuristic is \Theta(\log n/ \log \log n). 3] 
Edit intent: meaning-changed
Original:  We will prove that for euclidean Traveling Salesman Problems with n cities the approximation ratio of the 2-Opt heuristic is \Theta(\log n/ \log \log n).  ] 
Revised:  We will prove that for euclidean Traveling Salesman Problems with n cities the approximation ratio of the 2-Opt heuristic is \Theta(\log n/ \log \log n). ] in 1999.
Edit intent: meaning-changed
Original:  We show that these conjectures are false in dimension three or higher by giving an O(\log^2 n) query algorithm for the three-dimensional Tarski problem , which generalises to give an O(\log^{ k-1\lceil \rceil } n) query algorithm for the k-dimensional problem when k%DIFDELCMD < \ge %%% 3.
Revised:  We show that these conjectures are false in dimension three or higher by giving an O(\log^2 n) query algorithm for the three-dimensional Tarski problem . We also give a new decomposition theorem for k-dimensional Tarski problems which, in combination with our new algorithm for three dimensions, gives an O(\log^{ k-1\lceil \rceil } n) query algorithm for the k-dimensional problem when k%DIFDELCMD < \ge %%% 3.
Edit intent: meaning-changed
Original:  We show that these conjectures are false in dimension three or higher by giving an O(\log^2 n) query algorithm for the three-dimensional Tarski problem , which generalises to give an O(\log^{ k-1\lceil \rceil } n) query algorithm for the k-dimensional problem when k%DIFDELCMD < \ge %%% 3.
Revised:  We show that these conjectures are false in dimension three or higher by giving an O(\log^2 n) query algorithm for the three-dimensional Tarski problem , which generalises to give an O(\log^{ 2\lceil \rceil } n) query algorithm for the k-dimensional problem when k%DIFDELCMD < \ge %%% 3.
Edit intent: meaning-changed
Original:  We show that these conjectures are false in dimension three or higher by giving an O(\log^2 n) query algorithm for the three-dimensional Tarski problem , which generalises to give an O(\log^{ k-1\lceil \rceil } n) query algorithm for the k-dimensional problem when k%DIFDELCMD < \ge %%% 3.
Revised:  We show that these conjectures are false in dimension three or higher by giving an O(\log^2 n) query algorithm for the three-dimensional Tarski problem , which generalises to give an O(\log^{ k-1\lceil k/3\rceil } n) query algorithm for the k-dimensional problem when k%DIFDELCMD < \ge %%% 3.
Edit intent: meaning-changed
Original:  We show that these conjectures are false in dimension three or higher by giving an O(\log^2 n) query algorithm for the three-dimensional Tarski problem , which generalises to give an O(\log^{ k-1\lceil \rceil } n) query algorithm for the k-dimensional problem when k%DIFDELCMD < \ge %%% 3.
Revised:  We show that these conjectures are false in dimension three or higher by giving an O(\log^2 n) query algorithm for the three-dimensional Tarski problem , which generalises to give an O(\log^{ k-1\lceil \rceil } n) query algorithm for the k-dimensional problem %DIFDELCMD < \ge %%% 3.
Edit intent: coherence
Original:  We show that these conjectures are false in dimension three or higher by giving an O(\log^2 n) query algorithm for the three-dimensional Tarski problem , which generalises to give an O(\log^{ k-1\lceil \rceil } n) query algorithm for the k-dimensional problem when k%DIFDELCMD < \ge %%% 3.
Revised:  We show that these conjectures are false in dimension three or higher by giving an O(\log^2 n) query algorithm for the three-dimensional Tarski problem , which generalises to give an O(\log^{ k-1\lceil \rceil } n) query algorithm for the k-dimensional problem when k%DIFDELCMD < \ge %%% .
Edit intent: meaning-changed
Original: We review studies on tissue transplantation experiments for various species: one piece of the donor tissue is excised , and transplanted into a slit in the host tissue, then observe the behavior of this grafted tissue.
Revised: We review studies on tissue transplantation experiments for various species: one piece of the donor tissue is excised and transplanted into a slit in the host tissue, then observe the behavior of this grafted tissue.
Edit intent: fluency
Original: We present a forced sentence alignment procedure for Swiss German speech and Standard German text. It is able to create a speech-to-text corpus in a fully automatic fashion, given an audio recording and the corresponding unaligned transcript. Compared to a manual alignment, it achieves a mean IoU of 0.8401 with a sentence recall of 0.9491. When applying our IoU estimate filter, the mean IoU can be further improved to 0.9271 at the cost of a lower sentence recall of 0.4881. Using this procedure, we created the Swiss Parliaments Corpus  , an automatically aligned Swiss German speech to Standard German text corpus.
Revised: We present the Swiss Parliaments Corpus , an automatically aligned Swiss German speech to Standard German text corpus.
Edit intent: coherence
Original:  65 \% of the raw data could be transformed to sentence-level audio-text-pairs, resulting in 293 hours of training data. We have made the corpus freely available for download.
Revised:  65 \% of the raw data could be transformed to sentence-level audio-text-pairs, resulting in 293 hours of data. It was created using a novel forced sentence alignment procedure and an alignment quality estimator, which can be used to trade off corpus size and quality. We trained Automatic Speech Recognition (ASR) models as baselines on different subsets of the data and achieved a Word Error Rate (WER) of 0.278 and a BLEU score of 0.586 on the SPC test set. The corpus is freely available for download.
Edit intent: meaning-changed
Original:  The IFGF strategy, which leads to an extremely simple algorithm, capitalizes on slow variations inherent in a certain Green-function "analytic factor"{\em  , which is analytic up to and including infinity, and which therefore allows for accelerated evaluation of fields produced by groups of sources on the basis of a recursive application of classical interpolation methods.
Revised:  The IFGF strategy, which leads to an extremely simple algorithm, capitalizes on slow variations inherent in a certain Green function{\em , which is analytic up to and including infinity, and which therefore allows for accelerated evaluation of fields produced by groups of sources on the basis of a recursive application of classical interpolation methods.
Edit intent: clarity
Original:  The IFGF strategy, which leads to an extremely simple algorithm, capitalizes on slow variations inherent in a certain Green-function "analytic factor"{\em  , which is analytic up to and including infinity, and which therefore allows for accelerated evaluation of fields produced by groups of sources on the basis of a recursive application of classical interpolation methods.
Revised:  The IFGF strategy, which leads to an extremely simple algorithm, capitalizes on slow variations inherent in a certain Green-function "analytic factor"{\em analytic factor , which is analytic up to and including infinity, and which therefore allows for accelerated evaluation of fields produced by groups of sources on the basis of a recursive application of classical interpolation methods.
Edit intent: meaning-changed
Original:  Unlike other approaches, the IFGF method does not utilize the Fast Fourier Transforms (FFT), and is thus better suited than other methods for efficient parallelization in distributed-memory computer systems.
Revised:  Unlike other approaches, the IFGF method does not utilize the Fast Fourier Transform (FFT), and is thus better suited than other methods for efficient parallelization in distributed-memory computer systems.
Edit intent: fluency
Original:  Only a serial implementation of the algorithm is considered in this paper, however, whose efficiency in terms of memory and speed is illustrated by means of a variety of numerical results, for a problem of acoustic size of 512\lambda} .
Revised:  Only a serial implementation of the algorithm is considered in this paper, however, whose efficiency in terms of memory and speed is illustrated by means of a variety of numerical experiments -- including a 43 min., single-core operator evaluation (on 10 GB of peak memory), with a relative error of 1.5\times 10^{-2, for a problem of acoustic size of 512\lambda} .
Edit intent: meaning-changed
Original: In order to overcome the expressive limitations of graph neural networks (GNNs) , we propose the first method that exploits vector flows over graphs to develop globally consistent directional and asymmetric aggregation functions.
Revised: The lack of anisotropic kernels in graph neural networks (GNNs) , we propose the first method that exploits vector flows over graphs to develop globally consistent directional and asymmetric aggregation functions.
Edit intent: meaning-changed
Original: In order to overcome the expressive limitations of graph neural networks (GNNs) , we propose the first method that exploits vector flows over graphs to develop globally consistent directional and asymmetric aggregation functions.
Revised: In order to overcome the expressive limitations of graph neural networks (GNNs) strongly limits their expressiveness, contributing to well-known issues such as over-smoothing. To overcome this limitation, we propose the first method that exploits vector flows over graphs to develop globally consistent directional and asymmetric aggregation functions.
Edit intent: meaning-changed
Original: In order to overcome the expressive limitations of graph neural networks (GNNs) , we propose the first method that exploits vector flows over graphs to develop globally consistent directional and asymmetric aggregation functions. We show that our directional graph networks (DGNs) generalize convolutional neural networks (CNNs) when applied on a grid. Whereas recent theoretical works focus on understanding local neighbourhoods, local structures and local isomorphism with no global information flow, our novel theoretical framework allows directional convolutional kernels in any graph.
Revised: In order to overcome the expressive limitations of graph neural networks (GNNs) , we propose the first globally consistent anisotropic kernels for GNNs, allowing for graph convolutions that are defined according to topologicaly-derived directional flows.
Edit intent: clarity
Original:  Then  we propose the use of the Laplacian eigenvectors as such vector field , and we show that the method generalizes CNNs on an n-dimensional grid , and is provably more discriminative than standard GNNs regarding the Weisfeiler-Lehman 1-WL test.
Revised:  Then , we propose the use of the Laplacian eigenvectors as such vector field , and we show that the method generalizes CNNs on an n-dimensional grid , and is provably more discriminative than standard GNNs regarding the Weisfeiler-Lehman 1-WL test.
Edit intent: fluency