wanyu/IteraTeR_v2 huggingface dataset:
Original:  The present study tests a "confidence hypothesis " of advice perception, namely the hypothesis that internal metacognitive processes like decision confidence play an important functional role in the perception and use of social information - such as peers' advice - and can be used, computationally, to estimate advisors' trustworthiness and advice reliability.
Revised:  The present study tests a "confidence hypothesis " of advice perception, namely the hypothesis that internal metacognitive processes like decision confidence play an important functional role in the perception and use of social information , such as peers' advice - and can be used, computationally, to estimate advisors' trustworthiness and advice reliability.
Edit intent: fluency
Original:  The present study tests a "confidence hypothesis " of advice perception, namely the hypothesis that internal metacognitive processes like decision confidence play an important functional role in the perception and use of social information - such as peers' advice - and can be used, computationally, to estimate advisors' trustworthiness and advice reliability.
Revised:  The present study tests a "confidence hypothesis " of advice perception, namely the hypothesis that internal metacognitive processes like decision confidence play an important functional role in the perception and use of social information - such as peers' advice . We propose that confidence can be used, computationally, to estimate advisors' trustworthiness and advice reliability.
Edit intent: coherence
Original:  Here, we use a judge-advisor system paradigm \mbox{ Bonaccio2006 to precisely manipulate participants independent information and advice profile .
Revised:  Here, we use a judge-advisor system paradigm to precisely manipulate participants independent information and advice profile .
Edit intent: coherence
Original:  Here, we use a judge-advisor system paradigm \mbox{ Bonaccio2006 to precisely manipulate participants independent information and advice profile .
Revised:  Here, we use a judge-advisor system paradigm \mbox{ Bonaccio2006 to precisely manipulate the profiles of virtual advisors whose opinions are provided to participants performing a perceptual decision making task .
Edit intent: clarity
Original:  When observers' judgments (and judgments' errors) are correlated - as it is the case in many social contexts - predictable distortions can be observed between feedback and feedback-free scenarios.
Revised:  When observers' judgments (and judgment errors) are correlated - as it is the case in many social contexts - predictable distortions can be observed between feedback and feedback-free scenarios.
Edit intent: fluency
Original:  When observers' judgments (and judgments' errors) are correlated - as it is the case in many social contexts - predictable distortions can be observed between feedback and feedback-free scenarios.
Revised:  When observers' judgments (and judgments' errors) are correlated - as is the case in many social contexts - predictable distortions can be observed between feedback and feedback-free scenarios.
Edit intent: fluency
Original:  A simple model of advice reliability estimation, endowed with metacognitive insight, is able to explain characteristic patterns of results observed in the human data  .
Revised:  A simple model of advice reliability estimation, endowed with metacognitive insight, is able to explain key patterns of results observed in the human data .
Edit intent: clarity
Original: In a recent study, Hemmati et al. (2014) proposed a class of ship routing problems and a benchmark suite based on real shipping segments, considering pickups and deliveries, cargoes selections , ship-dependent starting locations, travel times and costs, time windows,  incompatibility constraints, among other features.
Revised: Recent studies in maritime logistics have introduced a general ship routing problem and a benchmark suite based on real shipping segments, considering pickups and deliveries, cargoes selections , ship-dependent starting locations, travel times and costs, time windows, incompatibility constraints, among other features.
Edit intent: clarity
Original: In a recent study, Hemmati et al. (2014) proposed a class of ship routing problems and a benchmark suite based on real shipping segments, considering pickups and deliveries, cargoes selections , ship-dependent starting locations, travel times and costs, time windows,  incompatibility constraints, among other features.
Revised: In a recent study, Hemmati et al. (2014) proposed a class of ship routing problems and a benchmark suite based on real shipping segments, considering pickups and deliveries, cargo selection , ship-dependent starting locations, travel times and costs, time windows, incompatibility constraints, among other features.
Edit intent: fluency
Original: In a recent study, Hemmati et al. (2014) proposed a class of ship routing problems and a benchmark suite based on real shipping segments, considering pickups and deliveries, cargoes selections , ship-dependent starting locations, travel times and costs, time windows,  incompatibility constraints, among other features.
Revised: In a recent study, Hemmati et al. (2014) proposed a class of ship routing problems and a benchmark suite based on real shipping segments, considering pickups and deliveries, cargoes selections , ship-dependent starting locations, travel times and costs, time windows, and incompatibility constraints, among other features.
Edit intent: fluency
Original:  We propose an exact branch-and-price (B&P) algorithm and a hybrid metaheuristic.
Revised:  To face this challenge, we propose an exact branch-and-price (B&P) algorithm and a hybrid metaheuristic.
Edit intent: clarity
Original:  As shown in our experimental analyses, the B&P optimally solves 239/240  instances within one hour , with up to 50 ships , 130 cargoes and therefore 260 pickups and deliveries .
Revised:  As shown in our experimental analyses, the B&P optimally solves 239/240 instances within one hour , with up to 50 ships , 130 cargoes and therefore 260 cargoes .
Edit intent: clarity
Original:  These results are noteworthy, since the largest instances of this set are comparable in size with the largest problems routinely solved by shipping companies.
Revised:  These results are noteworthy, since these instances are comparable in size with the largest problems routinely solved by shipping companies.
Edit intent: clarity
Original: This document is designed to be a first-year graduate-level introduction to probabilistic programming.
Revised: This book is a graduate-level introduction to probabilistic programming.
Edit intent: clarity
Original:  We start with a discussion of model-based reasoning and explain why conditioning as a foundational computation is central to the fields of probabilistic machine learning and artificial intelligence.
Revised:  We start with a discussion of model-based reasoning and explain why conditioning is a foundational computation is central to the fields of probabilistic machine learning and artificial intelligence.
Edit intent: fluency
Original:  We start with a discussion of model-based reasoning and explain why conditioning as a foundational computation is central to the fields of probabilistic machine learning and artificial intelligence.
Revised:  We start with a discussion of model-based reasoning and explain why conditioning as a foundational computation central to the fields of probabilistic machine learning and artificial intelligence.
Edit intent: fluency
Original:  We then introduce a simple first-order probabilistic programming language (PPL) whose programs define static-computation-graph, finite-variable-cardinality models .
Revised:  We then introduce a first-order probabilistic programming language (PPL) whose programs define static-computation-graph, finite-variable-cardinality models .
Edit intent: clarity
Original:  We then introduce a simple first-order probabilistic programming language (PPL) whose programs define static-computation-graph, finite-variable-cardinality models .
Revised:  We then introduce a simple first-order probabilistic programming language (PPL) whose programs correspond to graphical models with a known, finite, set of random variables .
Edit intent: clarity
Original:  In the context of this restricted PPL we introduce fundamental inference algorithms and describe how they can be implemented in the context of models denoted by probabilistic programs.
Revised:  In the context of this PPL we introduce fundamental inference algorithms and describe how they can be implemented in the context of models denoted by probabilistic programs.
Edit intent: clarity
Original:  This affords the opportunity to define models with dynamic computation graphs, at the cost of requiring inference methods that generate samples by repeatedly executing the program.
Revised:  This affords the opportunity to define models with dynamic computation graphs, at the cost of requiring inference methods that generate samples by repeatedly evaluating the program.
Edit intent: clarity
Original:  Foundational inference algorithms for this kind of probabilistic programming language are explained in the context of an interface between program executions and an inference controller.
Revised:  Foundational algorithms for this kind of probabilistic programming language are explained in the context of an interface between program executions and an inference controller.
Edit intent: clarity
Original:  Foundational inference algorithms for this kind of probabilistic programming language are explained in the context of an interface between program executions and an inference controller.
Revised:  Foundational inference algorithms for this kind of language are discussed in the context of an interface between program executions and an inference controller.
Edit intent: clarity
Original:  In discrete-time rounds, each node gets black if it has at least r black neighbors and white otherwise , for some 1\leq r\leq d.
Revised:  In discrete-time rounds, each node becomes black if it has at least r black neighbors and white otherwise , for some 1\leq r\leq d.
Edit intent: clarity
Original: In this paper, we explore some basic questions on the complexity of training Neural networks with ReLU activation function.
Revised: In this paper, we explore some basic questions on the complexity of training neural networks with ReLU activation function.
Edit intent: fluency
Original:  We show that it is NP-hard to train a two- hidden layer feedforward ReLU neural network.
Revised:  We show that it is NP-hard to train a two-hidden layer feedforward ReLU neural network.
Edit intent: fluency
Original:  We also show that if sufficient over-parameterization is provided in the first hidden layer of ReLU neural network  then there is a polynomial time algorithm which finds weights such that output of the over-parameterized ReLU neural network matches with the output of the given data 
Revised:  We also show that if sufficient over-parameterization is provided in the first hidden layer of ReLU neural network , then there is a polynomial time algorithm which finds weights such that output of the over-parameterized ReLU neural network matches with the output of the given data 
Edit intent: fluency
Original:  We also show that if sufficient over-parameterization is provided in the first hidden layer of ReLU neural network  then there is a polynomial time algorithm which finds weights such that output of the over-parameterized ReLU neural network matches with the output of the given data 
Revised:  We also show that if sufficient over-parameterization is provided in the first hidden layer of ReLU neural network then there is a polynomial time algorithm which finds weights such that output of the over-parameterized ReLU neural network matches with the output of the given data .
Edit intent: fluency
Original:  The aim of this work is the analysis of the SVD in Sobolev spaces.
Revised:  Our goal is the analysis of the SVD in Sobolev spaces.
Edit intent: clarity
Original: Let {\cal G}=(G,\lambda) be a labeled graph on n vertices with \lambda:E_G\to N a locally injective mapping that assigns to every edge a unique integer label.
Revised: Let {\cal G}=(G,\lambda) be a labeled graph on n vertices with \lambda:E_G\to N a locally injective mapping that assigns to every edge a single integer label.
Edit intent: clarity
Original:  We investigate a question by Kempe, Kleinberg, and Kumar (JCSS 2002) , asking whether {\em sparse} subsets of edges can always be found that preserve temporal connectivity if the rest is removed .
Revised:  In a seminal paper, Kempe, Kleinberg, and Kumar (JCSS 2002) , asking whether {\em sparse} subsets of edges can always be found that preserve temporal connectivity if the rest is removed .
Edit intent: clarity
Original:  We investigate a question by Kempe, Kleinberg, and Kumar (JCSS 2002) , asking whether {\em sparse} subsets of edges can always be found that preserve temporal connectivity if the rest is removed .
Revised:  We investigate a question by Kempe, Kleinberg, and Kumar (JCSS 2002) , asking whether {\em sparse} subset of edges can always be found that preserve temporal connectivity if the rest is removed .
Edit intent: fluency
Original:  We investigate a question by Kempe, Kleinberg, and Kumar (JCSS 2002) , asking whether {\em sparse} subsets of edges can always be found that preserve temporal connectivity if the rest is removed .
Revised:  We investigate a question by Kempe, Kleinberg, and Kumar (JCSS 2002) , asking whether {\em sparse} subsets of edges can always be found that preserves temporal connectivity if the rest is removed .
Edit intent: fluency
Original:  We call such subsets {\em temporal spanners} of%DIFDELCMD < {\cal %%% G . Despite the simplicity of the model, no significative progress has been made so far on this question;
Revised:  We call such subsets {\em temporal spanners} %DIFDELCMD < {\cal %%% G . Despite the simplicity of the model, no significative progress has been made so far on this question;
Edit intent: fluency
Original:  We call such subsets {\em temporal spanners} of%DIFDELCMD < {\cal %%% G . Despite the simplicity of the model, no significative progress has been made so far on this question;
Revised:  We call such subsets {\em temporal spanners} of%DIFDELCMD < {\cal %%% . Despite the simplicity of the model, no significative progress has been made so far on this question;
Edit intent: coherence
Original:  In this paper , we settle the question (affirmatively) {\em  for complete graphs, showing that %DIFDELCMD < {\em %%% all edges but a sub-quadratic amount of them (namely O(n \log n) ) can always be removed, making the first significant progress towards the original question.
Revised:  In this article , we settle the question (affirmatively) {\em for complete graphs, showing that %DIFDELCMD < {\em %%% all edges but a sub-quadratic amount of them (namely O(n \log n) ) can always be removed, making the first significant progress towards the original question.
Edit intent: fluency
Original:  In this paper , we settle the question (affirmatively) {\em  for complete graphs, showing that %DIFDELCMD < {\em %%% all edges but a sub-quadratic amount of them (namely O(n \log n) ) can always be removed, making the first significant progress towards the original question.
Revised:  In this paper , we settle the question {\em for complete graphs, showing that %DIFDELCMD < {\em %%% all edges but a sub-quadratic amount of them (namely O(n \log n) ) can always be removed, making the first significant progress towards the original question.
Edit intent: coherence
Original:  In this paper , we settle the question (affirmatively) {\em  for complete graphs, showing that %DIFDELCMD < {\em %%% all edges but a sub-quadratic amount of them (namely O(n \log n) ) can always be removed, making the first significant progress towards the original question.
Revised:  In this paper , we settle the question (affirmatively) {\em for complete graphs, showing that %DIFDELCMD < {\em %%% edges but a sub-quadratic amount of them (namely O(n \log n) ) can always be removed, making the first significant progress towards the original question.
Edit intent: clarity
Original:  First, we observe that the existing argument for removing \Theta(n) edges can be generalized to removing \Theta (n^2) edges ( namely, a sixth of the edges).
Revised:  First, we observe that the existing argument for removing \Theta(n) edges can be generalized to removing \Theta (n^2) edges ( a sixth of the edges).
Edit intent: clarity
Original:  Then, building on top of a gradual set of techniques, we establish that a quarter of the edges can always be removed, then half of the edges, and eventually {\em all} but O(n \log n) edges.
Revised:  Then, using a completely different approach, we establish a gradual set of techniques, we establish that a quarter of the edges can always be removed, then half of the edges, and eventually {\em all} but O(n \log n) edges.
Edit intent: clarity
Original:  Then, building on top of a gradual set of techniques, we establish that a quarter of the edges can always be removed, then half of the edges, and eventually {\em all} but O(n \log n) edges.
Revised:  Then, building on top of a gradual set of results, showing that a quarter of the edges can always be removed, then half of the edges, and eventually {\em all} but O(n \log n) edges.
Edit intent: clarity
Original:  Then, building on top of a gradual set of techniques, we establish that a quarter of the edges can always be removed, then half of the edges, and eventually {\em all} but O(n \log n) edges.
Revised:  Then, building on top of a gradual set of techniques, we establish that a quarter of the edges can be removed, then half of the edges, and eventually {\em all} but O(n \log n) edges.
Edit intent: clarity
Original:  These results are robust in the sense that they extend, with reasonable assumptions, to general graph models where the labels may not be locally unique and every edge may have several labels.
Revised:  This result is robust in the sense that they extend, with reasonable assumptions, to general graph models where the labels may not be locally unique and every edge may have several labels.
Edit intent: fluency
Original:  These results are robust in the sense that they extend, with reasonable assumptions, to general graph models where the labels may not be locally unique and every edge may have several labels.
Revised:  These results are robust in the sense that they extend, with reasonable assumptions, to general graph models where the labels may not be locally unique and a same edge may have several labels.
Edit intent: clarity
Original:  We conjecture that sparse spanners always exist in the general case (G not being complete) and we hope that some of our techniques might be used in this perspective .
Revised:  The main open question is now to understand where the separation occurs between graphs that admit sparse spanners and graphs that do not .
Edit intent: clarity
Original: Let %DIFDELCMD < {\cal %%% G =( G,\lambda) be a labeled graph on n vertices with \lambda:E _G \to \mathbb{N mapping that assigns to every edge a single integer label.
Revised: Let %DIFDELCMD < {\cal %%% G =( G,\lambda) be a labeled graph on n vertices with \lambda:E _G \to \mathbb{N mapping that assigns to every edge a single integer label.
Edit intent: fluency
Original: Let %DIFDELCMD < {\cal %%% G =( G,\lambda) be a labeled graph on n vertices with \lambda:E _G \to \mathbb{N mapping that assigns to every edge a single integer label.
Revised: Let %DIFDELCMD < {\cal %%% G =( G,\lambda) be a labeled graph on n vertices and \lambda:E _G \to \mathbb{N mapping that assigns to every edge a single integer label.
Edit intent: coherence
Original:  In a seminal paper, Kempe, Kleinberg, and Kumar ( JCSS 2002 ) asked whether, given such a labeled graph, a %DIFDELCMD < {\em %%% sparse subset of edges can always be found that preserves temporal connectivity if the other edges are removed -- we call such subsets%DIFDELCMD < {\em %%% temporal spanners . Recently, Axiotis and Fotakis (ICALP 2016) answered negatively , exhibiting a family of minimally connected temporal graphs with \Omega (n^2) edges .
Revised:  In a seminal paper, Kempe, Kleinberg, and Kumar ( JCSS 2002 ) asked whether, given such a temporal graph, a %DIFDELCMD < {\em %%% sparse subset of edges can always be found that preserves temporal connectivity if the other edges are removed -- we call such subsets%DIFDELCMD < {\em %%% temporal spanners . Recently, Axiotis and Fotakis (ICALP 2016) answered negatively , exhibiting a family of minimally connected temporal graphs with \Omega (n^2) edges .
Edit intent: fluency
Original:  In a seminal paper, Kempe, Kleinberg, and Kumar ( JCSS 2002 ) asked whether, given such a labeled graph, a %DIFDELCMD < {\em %%% sparse subset of edges can always be found that preserves temporal connectivity if the other edges are removed -- we call such subsets%DIFDELCMD < {\em %%% temporal spanners . Recently, Axiotis and Fotakis (ICALP 2016) answered negatively , exhibiting a family of minimally connected temporal graphs with \Omega (n^2) edges .
Revised:  In a seminal paper, Kempe, Kleinberg, and Kumar ( JCSS 2002 ) asked whether, given such a labeled graph, a %DIFDELCMD < {\em %%% sparse subset of edges can always be found that preserves temporal connectivity if the other edges are removed -- we call such subsets%DIFDELCMD < {\em %%% temporal spanners . Recently, Axiotis and Fotakis (ICALP 2016) answered negatively , exhibiting a family of minimally connected temporal graphs with \Omega (n^2) edges .
Edit intent: fluency
Original:  In a seminal paper, Kempe, Kleinberg, and Kumar ( JCSS 2002 ) asked whether, given such a labeled graph, a %DIFDELCMD < {\em %%% sparse subset of edges can always be found that preserves temporal connectivity if the other edges are removed -- we call such subsets%DIFDELCMD < {\em %%% temporal spanners . Recently, Axiotis and Fotakis (ICALP 2016) answered negatively , exhibiting a family of minimally connected temporal graphs with \Omega (n^2) edges .
Revised:  In a seminal paper, Kempe, Kleinberg, and Kumar ( JCSS 2002 ) asked whether, given such a labeled graph, a %DIFDELCMD < {\em %%% sparse subset of edges can always be found %DIFDELCMD < {\em %%% temporal spanners . Recently, Axiotis and Fotakis (ICALP 2016) answered negatively , exhibiting a family of minimally connected temporal graphs with \Omega (n^2) edges .
Edit intent: coherence
Original:  In a seminal paper, Kempe, Kleinberg, and Kumar ( JCSS 2002 ) asked whether, given such a labeled graph, a %DIFDELCMD < {\em %%% sparse subset of edges can always be found that preserves temporal connectivity if the other edges are removed -- we call such subsets%DIFDELCMD < {\em %%% temporal spanners . Recently, Axiotis and Fotakis (ICALP 2016) answered negatively , exhibiting a family of minimally connected temporal graphs with \Omega (n^2) edges .
Revised:  In a seminal paper, Kempe, Kleinberg, and Kumar ( JCSS 2002 ) asked whether, given such a labeled graph, a %DIFDELCMD < {\em %%% sparse subset of edges can always be found that preserves temporal connectivity if the other edges are removed -- we call such subsets%DIFDELCMD < {\em %%% . Recently, Axiotis and Fotakis (ICALP 2016) answered negatively , exhibiting a family of minimally connected temporal graphs with \Omega (n^2) edges .
Edit intent: clarity