wanyu/IteraTeR_v2 huggingface dataset:
Original:  However, because most of these analyses were based on a single behavioral aspect and/or small sample sizes, we lack a quantification of the interplay of these factors.
Revised:  However, because most of these analyses were based on a single behavioral aspect and/or small sample sizes, there is currently no quantification of the interplay of these factors.
Edit intent: clarity
Original:  Here, we infer the academic performance among a cohort of almost 1, 000 freshmen based on data collected through smartphones, which the students used as their primary phone for two years.
Revised:  Here, we study the academic performance among a cohort of almost 1, 000 freshmen based on data collected through smartphones, which the students used as their primary phone for two years.
Edit intent: clarity
Original:  Here, we infer the academic performance among a cohort of almost 1, 000 freshmen based on data collected through smartphones, which the students used as their primary phone for two years.
Revised:  Here, we infer the academic performance among a cohort of almost 1, 000 freshmen based on data collected using smartphones, which the students used as their primary phone for two years.
Edit intent: fluency
Original:  Here, we infer the academic performance among a cohort of almost 1, 000 freshmen based on data collected through smartphones, which the students used as their primary phone for two years.
Revised:  Here, we infer the academic performance among a cohort of almost 1, 000 freshmen based on data collected through smartphones, which the students used as their primary phones for two years.
Edit intent: fluency
Original:  The availability of multi-channel data from a single population allows us to directly compare the predictive power of individual and social characteristics.
Revised:  The availability of multi-channel data from a single population allows us to directly compare the explanatory power of individual and social characteristics.
Edit intent: clarity
Original:  We confirm earlier findings indicating that class attendance is the most important predictor among the individual characteristics.
Revised:  We confirm earlier findings that class attendance is the most important predictor among the individual characteristics.
Edit intent: clarity
Original:  We confirm earlier findings indicating that class attendance is the most important predictor among the individual characteristics.
Revised:  We confirm earlier findings indicating that class attendance is the most important predictor among individual characteristics.
Edit intent: clarity
Original:  Finally, our results indicates potential presence of strong homophily and/or peer effects among university students.
Revised:  Finally, our results suggest the presence of strong homophily and/or peer effects among university students.
Edit intent: clarity
Original:  Evaluation of the proposed model is performed on two datasets of increasing difficulty : pedestrian tracking on the KTH activity recognition dataset and the  KITTI object tracking dataset.
Revised:  Evaluation of the proposed model is performed on two datasets : pedestrian tracking on the KTH activity recognition dataset and the KITTI object tracking dataset.
Edit intent: clarity
Original:  Evaluation of the proposed model is performed on two datasets of increasing difficulty : pedestrian tracking on the KTH activity recognition dataset and the  KITTI object tracking dataset.
Revised:  Evaluation of the proposed model is performed on two datasets of increasing difficulty : pedestrian tracking on the KTH activity recognition dataset and the more difficult KITTI object tracking dataset.
Edit intent: clarity
Original:  An edge set E' \subseteq E is a {\em dominating induced matching} ({\em d.i.m.}) in G if every edge in E is intersected by exactly one edge of E' . In particular, this means that E' is an induced matching, and every edge not in E' shares exactly one vertex with an edge in E' . Clearly, not every graph has a d.i.m.
Revised:  An edge set E' \subseteq E is a {\em dominating induced matching} ({\em d.i.m.}) in G if every edge in E is intersected by exactly one edge of M . In particular, this means that E' is an induced matching, and every edge not in E' shares exactly one vertex with an edge in E' . Clearly, not every graph has a d.i.m.
Edit intent: clarity
Original:  An edge set E' \subseteq E is a {\em dominating induced matching} ({\em d.i.m.}) in G if every edge in E is intersected by exactly one edge of E' . In particular, this means that E' is an induced matching, and every edge not in E' shares exactly one vertex with an edge in E' . Clearly, not every graph has a d.i.m.
Revised:  An edge set E' \subseteq E is a {\em dominating induced matching} ({\em d.i.m.}) in G if every edge in E is intersected by exactly one edge of E' . In particular, this means that M is an induced matching, and every edge not in E' shares exactly one vertex with an edge in E' . Clearly, not every graph has a d.i.m.
Edit intent: clarity
Original:  An edge set E' \subseteq E is a {\em dominating induced matching} ({\em d.i.m.}) in G if every edge in E is intersected by exactly one edge of E' . In particular, this means that E' is an induced matching, and every edge not in E' shares exactly one vertex with an edge in E' . Clearly, not every graph has a d.i.m.
Revised:  An edge set E' \subseteq E is a {\em dominating induced matching} ({\em d.i.m.}) in G if every edge in E is intersected by exactly one edge of E' . In particular, this means that E' is an induced matching, and every edge not in E' shares exactly one vertex with an edge in M . Clearly, not every graph has a d.i.m.
Edit intent: clarity
Original:  However, DIM is solvable in polynomial time for claw-free  graphs, for S_{1,2,3}-free graphs as well as for S_{2,2,2}-free graphs and more generally, for S_{2,2,3 in linear time for P_7-free graphs, and in polynomial time for P_8-free graphs  .
Revised:  However, DIM is solvable in polynomial time for claw-free graphs, for S_{1,2,3}-free graphs as well as for S_{2,2,2}-free graphs , in linear time for P_7-free graphs, and in polynomial time for P_8-free graphs .
Edit intent: coherence
Original: Anti-Kekul\'{e} problem is a concept of chemical graph theory precluding the Kekul\'{e} structure of molecules .
Revised: Anti-Kekul\'{e} problem is a concept of chemical graph theory precluding the Kekul\'{e} structure .
Edit intent: clarity
Original:  In this paper, we mainly prove that anti-Kekul\'{e} problem on bipartite graphs is NP-complete .
Revised:  In this paper, we mainly prove that anti-Kekul\'{e} problem are NP-complete .
Edit intent: clarity
Original:  As an extension to (conditional) matching preclusion problem , we propose the concept of s-restricted matching preclusion problem , and prove that such problem on bipartite graphs is also NP-complete.
Revised:  As an extension to (conditional) matching preclusion problem to s-restricted matching preclusion problem , and prove that such problem on bipartite graphs is also NP-complete.
Edit intent: coherence
Original:  Finally, we determine that s-restricted matching preclusion number of Q_n (n%DIFDELCMD < \geq3%%% ) is 2n-2 .
Revised:  Finally, we determine that s-restricted matching preclusion %DIFDELCMD < \geq3%%% ) is 2n-2 .
Edit intent: clarity
Original: Given a graph G and k\in{\mathbb N, the Dominating Set problem asks for a subset D of k vertices such that every vertex in G is either in D or has a neighbor in D.
Revised: , the Dominating Set problem asks for a subset D of k vertices such that every vertex in G is either in D or has a neighbor in D.
Edit intent: clarity
Original:  It is well known that Dominating Set is }%DIFDELCMD < {\sf %DIFDELCMD < %%% W 2%DIFDELCMD < ]%%% -hard when parameterized by k.
Revised:  It is well known that Dominating Set is }%DIFDELCMD < {\sf %DIFDELCMD < %%% 2%DIFDELCMD < ]%%% -hard when parameterized by k.
Edit intent: fluency
Original:  But it admits a linear kernel on graphs of bounded expansion and a polynomial kernel on K_{d,d D%DIFDELCMD < ] %%% is required to be connected) is known not to admit such kernels unlessNP \subseteqcoNP/poly .
Revised:  But it admits a linear kernel on graphs of bounded expansion and a polynomial kernel on K_{d,d %DIFDELCMD < ] %%% is required to be connected) is known not to admit such kernels unlessNP \subseteqcoNP/poly .
Edit intent: fluency
Original:  But it admits a linear kernel on graphs of bounded expansion and a polynomial kernel on K_{d,d D%DIFDELCMD < ] %%% is required to be connected) is known not to admit such kernels unlessNP \subseteqcoNP/poly .
Revised:  But it admits a linear kernel on graphs of bounded expansion and a polynomial kernel on K_{d,d D%DIFDELCMD < ] %%% NP \subseteqcoNP/poly .
Edit intent: coherence
Original:  But it admits a linear kernel on graphs of bounded expansion and a polynomial kernel on K_{d,d D%DIFDELCMD < ] %%% is required to be connected) is known not to admit such kernels unlessNP \subseteqcoNP/poly .
Revised:  But it admits a linear kernel on graphs of bounded expansion and a polynomial kernel on K_{d,d D%DIFDELCMD < ] %%% is required to be connected) is known not to admit such kernels unless \subseteqcoNP/poly .
Edit intent: fluency
Original:  In this framework, for \alpha > 1, an \alpha-approximate bikernel (kernel) is a polynomial-time algorithm that takes as input an instance (I, k)  and outputs an instance (I',k')  of a problem (the same problem) such that, for every c > 1, a c-approximate solution for the new instance can be turned into a c\alpha -approximate solution of the original instance in polynomial time.
Revised:  In this framework, for \alpha > 1, an \alpha-approximate (bi-)kernel is a polynomial-time algorithm that takes as input an instance (I, k) and outputs an instance (I',k') of a problem (the same problem) such that, for every c > 1, a c-approximate solution for the new instance can be turned into a c\alpha -approximate solution of the original instance in polynomial time.
Edit intent: fluency
Original:  In this framework, for \alpha > 1, an \alpha-approximate bikernel (kernel) is a polynomial-time algorithm that takes as input an instance (I, k)  and outputs an instance (I',k')  of a problem (the same problem) such that, for every c > 1, a c-approximate solution for the new instance can be turned into a c\alpha -approximate solution of the original instance in polynomial time.
Revised:  In this framework, for \alpha > 1, an \alpha-approximate bikernel (kernel) is a polynomial-time algorithm that takes as input an instance (I, k) and outputs an instance (I',k') ( of a problem (the same problem) such that, for every c > 1, a c-approximate solution for the new instance can be turned into a c\alpha -approximate solution of the original instance in polynomial time.
Edit intent: fluency
Original:  We show that Connected Dominating Set admits an \alpha-approximate bikernel on graphs of bounded expansion and an \alpha-approximate kernel on K_{d,d-free graphs , for every \alpha} \textsf{ \textsf{  is somewhere dense and closed under taking subgraphs, then for some value of r\in\mathbb{N} there cannot exist an \alpha-approximate bi-kernel for the (Connected)
Revised:  We show that Connected Dominating Set admits an \alpha-approximate -free graphs , for every \alpha} \textsf{ \textsf{ is somewhere dense and closed under taking subgraphs, then for some value of r\in\mathbb{N} there cannot exist an \alpha-approximate bi-kernel for the (Connected)
Edit intent: clarity
Original:  We show that , for input theories whose semi-incidence graph has bounded treewidth, our algorithm decides whether a theory has a stable extension in linear time and enumerates all characteristic generating defaults with linear delay .
Revised:  We show that our algorithm decides whether a theory has a stable extension in linear time and enumerates all characteristic generating defaults with linear delay .
Edit intent: clarity
Original:  We show that , for input theories whose semi-incidence graph has bounded treewidth, our algorithm decides whether a theory has a stable extension in linear time and enumerates all characteristic generating defaults with linear delay .
Revised:  We show that , for input theories whose semi-incidence graph has bounded treewidth, our algorithm decides Ext in linear time and enumerates all characteristic generating defaults with linear delay .
Edit intent: clarity
Original:  In particular, we recover and extend the results that Bernstein et al. (2000) , developed in the context of manifold learning, and those of Karaman and Frazzoli (2011), developed in the context of robotics .
Revised:  In particular, we recover and extend the results that Bernstein et al. (2000) .
Edit intent: coherence
Original:  We further explore the impact on growthrate of generational correlations between cell cycle durations  .
Revised:  We further explore the impact of generational correlations between cell cycle durations .
Edit intent: clarity
Original:  Finally, we explore the growthrate gain - the phenomenon that noise in the cell cycle duration leads to an improved bulk growthrate - in this context.
Revised:  Finally, we explore the "growth rate gain" - the phenomenon that noise in the cell cycle duration leads to an improved bulk growthrate - in this context.
Edit intent: fluency
Original:  Finally, we explore the growthrate gain - the phenomenon that noise in the cell cycle duration leads to an improved bulk growthrate - in this context.
Revised:  Finally, we explore the growthrate gain - the phenomenon that variations in the cell cycle duration leads to an improved bulk growthrate - in this context.
Edit intent: clarity
Original:  Finally, we explore the growthrate gain - the phenomenon that noise in the cell cycle duration leads to an improved bulk growthrate - in this context.
Revised:  Finally, we explore the growthrate gain - the phenomenon that noise in the cell cycle duration lead to an improved bulk growthrate - in this context.
Edit intent: fluency
Original: The consumption of a wide and heterogeneous mass of information sources on social media may affect the mechanisms behind the formation of public opinion.
Revised: Social media are pervaded by unsubstantiated or untruthful rumors, that contribute to the alarming phenomenon of misinformation. The widespread presence of a heterogeneous mass of information sources on social media may affect the mechanisms behind the formation of public opinion.
Edit intent: coherence
Original: The consumption of a wide and heterogeneous mass of information sources on social media may affect the mechanisms behind the formation of public opinion.
Revised: The consumption of a wide and heterogeneous mass of information sources may affect the mechanisms behind the formation of public opinion.
Edit intent: clarity
Original:  In this essay  we focus on a collection of works aiming at providing quantitative evidence about the cognitive determinants behind misinformation and rumor spreading.
Revised:  In this essay , we focus on a collection of works aiming at providing quantitative evidence about the cognitive determinants behind misinformation and rumor spreading.
Edit intent: fluency
Original:  In particular, we analyze Facebook data on a time span of five years in both the Italian and the US context, and measure users  response to i) information consistent with one's narrative, ii) troll contents, and iii) dissenting information e.g., debunking attempts.
Revised:  In particular, we analyze Facebook data on a time span of five years in both the Italian and the US context, and measure users ' response to i) information consistent with one's narrative, ii) troll contents, and iii) dissenting information e.g., debunking attempts.
Edit intent: fluency
Original:  Our findings suggest that users  join polarized communities sharing a common narrative (echo chamber)and tend to a) to acquire information confirming their beliefs (confirmation bias) even if containing false claims b ) ignore dissenting information.
Revised:  Our findings suggest that users tend to a) join polarized communities sharing a common narrative (echo chamber)and tend to a) to acquire information confirming their beliefs (confirmation bias) even if containing false claims b ) ignore dissenting information.
Edit intent: fluency
Original:  Our findings suggest that users  join polarized communities sharing a common narrative (echo chamber)and tend to a) to acquire information confirming their beliefs (confirmation bias) even if containing false claims b ) ignore dissenting information.
Revised:  Our findings suggest that users join polarized communities sharing a common narrative (echo chambers), b) acquire information confirming their beliefs (confirmation bias) even if containing false claims b ) ignore dissenting information.
Edit intent: clarity
Original:  The question arises ' How to extract information from this large chunk of data?
Revised:  The question arises " How to extract information from this large chunk of data?
Edit intent: fluency
Original:  The question arises ' How to extract information from this large chunk of data?
Revised:  The question arises ' How to extract information from large chunk of data?
Edit intent: clarity
Original:  ' The concept of ' rich data and poor information ' is being challenged by big data analytics  .
Revised:  " The concept of ' rich data and poor information ' is being challenged by big data analytics .
Edit intent: fluency
Original:  ' The concept of ' rich data and poor information ' is being challenged by big data analytics  .
Revised:  ' The concept of " rich data and poor information ' is being challenged by big data analytics .
Edit intent: fluency
Original:  ' The concept of ' rich data and poor information ' is being challenged by big data analytics  .
Revised:  ' The concept of ' rich data and poor information " is being challenged by big data analytics .
Edit intent: fluency
Original:  Along with technological advancements like Internet of Things  , big data analytics will play an important role for electric utilities.
Revised:  Along with technological advancements like Internet of Things (IoT) , big data analytics will play an important role for electric utilities.
Edit intent: clarity
Original:  The aim will be to make the current asset management more smarter than it was, and this work describes some pathways .
Revised:  The aim will be to make the current asset management practices smarter for the future .
Edit intent: clarity
Original:  In contrast, the process matrix formalism allows one to model indefinite causal structures in a linear way, getting rid of these effects, and raising the possibility that its computational power is rather tame.
Revised:  In contrast, the process matrix formalism allows one to model indefinite causal structures in a linear way, getting rid of these effects, and raising the possibility that its computational power is rather tame.
Edit intent: fluency
Original: The application of semantic technologies to content on the web is, in many regards, as important as urgent.
Revised: The application of semantic technologies to content on the web is, in many regards, important and urgent.
Edit intent: clarity
Original:  Yet  the process of creating this kind of data is still complicated and the necessity of it is widely unknown.
Revised:  Yet , the process of creating this kind of data is still complicated and the necessity of it is widely unknown.
Edit intent: fluency
Original:  Yet  the process of creating this kind of data is still complicated and the necessity of it is widely unknown.
Revised:  Yet the process of creating this kind of data is still complicated and widely unknown.
Edit intent: clarity
Original:  It demonstrates , that the creation process of semantically annotated data must not be hard, shows use cases and pilot users of the created software and presents where the development of this platform or alike projects could go to in the future.
Revised:  It demonstrates that the creation process of semantically annotated data must not be hard, shows use cases and pilot users of the created software and presents where the development of this platform or alike projects could go to in the future.
Edit intent: fluency
Original:  It demonstrates , that the creation process of semantically annotated data must not be hard, shows use cases and pilot users of the created software and presents where the development of this platform or alike projects could go to in the future.
Revised:  It demonstrates , that the creation process of semantically annotated data does not have to be hard, shows use cases and pilot users of the created software and presents where the development of this platform or alike projects could go to in the future.
Edit intent: clarity
Original:  It demonstrates , that the creation process of semantically annotated data must not be hard, shows use cases and pilot users of the created software and presents where the development of this platform or alike projects could go to in the future.
Revised:  It demonstrates , that the creation process of semantically annotated data must not be hard, shows use cases and pilot users of the created software and presents where the development of this platform or alike projects lead to in the future.
Edit intent: clarity
Original:  To assign a sequence of fossil samples in the phylogenetic tree to the same species, i.e., to specify a stratigraphic range, we need to specify the concept of speciation.
Revised:  To assign a sequence of fossil samples in the phylogenetic tree to the same species, i.e., to specify a stratigraphic range, we need to define the mode of speciation.
Edit intent: clarity
Original:  We provide expressions to account for three common speciation concepts : budding (or asymmetric) speciation, cladogenetic (or symmetric) speciation, and anagenetic speciation.
Revised:  We provide expressions to account for three common speciation modes : budding (or asymmetric) speciation, cladogenetic (or symmetric) speciation, and anagenetic speciation.
Edit intent: clarity
Original:  Thus, we present a model that allows for incorporation of multiple sequences through time from a single patient.
Revised:  Thus, we present a model that allows for incorporation of multiple observations through time from a single patient.
Edit intent: clarity
Original:  The current fastest algorithm that yields the optimal m = O(\varepsilon^{-2}\lg N) dimensions has an embedding time of O(n \lg N + \varepsilon^{-2} \lg^3 N).
Revised:  The current fastest algorithm that yields the optimal m = O(\varepsilon^{-2}\lg N) dimensions has an embedding time of O(n \lg n + \varepsilon^{-2} \lg^3 N).
Edit intent: fluency
Original:  We perform numerical analysis of the HMMs applied to bisulfite sequencing measurements and accurately predict wild type data.
Revised:  We perform numerical analysis of the HMMs applied to bisulfite sequencing measurements and accurately predict wild-type data.
Edit intent: fluency
Original:   We prove, using a decision procedure based on nested-word automata, that every natural number is the sum of at most 4 natural numbers whose base-2 representation is a palindrome.
Revised:  We prove, using a decision procedure based on automata, that every natural number is the sum of at most 4 natural numbers whose base-2 representation is a palindrome.
Edit intent: clarity
Original:  In this paper we discuss the use of a convolutional auto-encoder devoted to learning an end-to-end map from an input image of a fixed size to its selectional output, in which activations indicate whether the pixel must be classified as foreground or background.
Revised:  In this paper we discuss the use of convolutional auto-encoders devoted to learning an end-to-end map from an input image of a fixed size to its selectional output, in which activations indicate whether the pixel must be classified as foreground or background.
Edit intent: fluency