wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We explore a large, detailed data set of 10^5 armed conflict reports spanning 20 years across nearly 10^4 kilometers. By systematically clustering spatiotemporally proximate events into conflict avalanches , we show that the number of conflict reports, fatalities, duration, and geographic extent satisfy consistent power law scaling relations .
Revised:  We explore a large, detailed data set of 10^5 armed conflict reports spanning 20 years into conflict avalanches , we show that the number of conflict reports, fatalities, duration, and geographic extent satisfy consistent power law scaling relations .
Edit intent: clarity
Original:  By systematically clustering spatiotemporally proximate events into conflict avalanches , we show that the number of conflict reports, fatalities, duration, and geographic extent satisfy consistent power law scaling relations . The temporal evolution of conflicts measured by these scaling variables display emergent symmetry, collapsing onto a universal dynamical profile over a range of scales. The measured exponents and dynamical profiles describe a system distinct from prevailing explanations of conflict growth such as forest fire models. Our findings suggest that armed conflicts are dominated by a low-dimensional process that scales with physical dimensions in a surprisingly unified and predictable way .
Revised:  By systematically clustering spatiotemporally proximate events into conflict avalanches . Conflict profiles collapse over a range of scales. Duration, diameter, extent, fatalities, and report totals satisfy mutually consistent scaling relations captured with a model combining geographic spread and local conflict-site growth. The emergence of such social scaling laws hints at principles guiding conflict evolution .
Edit intent: clarity
Original:   Simulations show that the proposed models have good selection and forecasting performance  , even when the design matrix presents high cross-correlation.
Revised:  We establish good frequentist asymptotic properties of the posterior of the in-sample and out-of-sample prediction error, we recover the optimal posterior contraction rate, and we show optimality of the posterior predictive density. Simulations show that the proposed models have good selection and forecasting performance , even when the design matrix presents high cross-correlation.
Edit intent: meaning-changed
Original:  We find the expressions for average length of binding  (the number of monomers at the chain ends that form bonds) and the critical tube diameter at which such constrained binding occurs  .
Revised:  We find the expressions for average length of binding (the number of monomers at the chain ends that form bonds) and the critical tube diameter at which such constrained binding occurs . We carry out Brownian dynamics simulations of tightly confined chains, demonstrating their binding over the characteristic length m*, changing in tubes of different diameter .
Edit intent: meaning-changed
Original:  We associate nonconvex vector optimization problems to these systemic risk measures and solve them by a recent nonconvex variant of Benson's algorithm which requires solving two types of scalar optimization problems. We provide a detailed analysis of the theoretical features of these problems for the extended Eisenberg-Noe and Rogers-Veraart models.
Revised:  We associate nonconvex vector optimization problems to these systemic risk measures and provide theoretical results related to the weighted-sum and minimum step-length scalarizations of these problems for the extended Eisenberg-Noe and Rogers-Veraart models.
Edit intent: meaning-changed
Original: The visual complexity of a plane graph drawing is defined to be the number of basic geometric objects needed to represent all its edges. In particular, one object may represent multiple edges (e.g., one needs only one line segment to draw a pathwith an arbitrary number of edges).
Revised: The visual complexity of a plane graph drawing is defined to be the number of geometric objects used for the representation of its elements. In this paper, we study planar graph drawings where edges are represented by few segments. In such a drawing, one segment may represent multiple edges (e.g., one needs only one line segment to draw a pathwith an arbitrary number of edges).
Edit intent: meaning-changed
Original:  In particular, one object may represent multiple edges (e.g., one needs only one line segment to draw a pathwith an arbitrary number of edges). A crossing-free straight-line drawing of a graph is called monotone if there is a monotone path between any pair of vertices with respect to some direction. We study drawings of trees, outerplanar graphs, and general planar graphs with few segments on a polynomial size grid.
Revised:  In particular, one object may represent multiple edges forming a path. Drawings of planar graphs with few segments on a polynomial size grid.
Edit intent: clarity
Original:  We study drawings of trees, outerplanar graphs, and general planar graphs with few segments on a polynomial size grid. For trees , the grid size is n\times n. For 3-connected planar graphs and biconnected outerplanar graphs , we compute such drawings that are also monotone .
Revised:  We study drawings of trees, outerplanar graphs, and general planar graphs with few segments were intensively studied in the past years. However, the area requirements were only considered for limited subclasses of planar graphs. In this paper, we show that trees have drawings with 3n/4-1 segments and n^2 area, improving the previous result of O(n^{3.58 3-connected planar graphs and biconnected outerplanar graphs , we compute such drawings that are also monotone .
Edit intent: meaning-changed
Original:  Focusing on the empirically relevant case where the risk aversion and the elasticity of intertemporal substitution are both larger than one, we characterize  optimal consumption and investment strategies through backward stochastic differential equations (BSDEs).
Revised:  Focusing on the empirically relevant case where the risk aversion and the elasticity of intertemporal substitution are both larger than one, we characterize the optimal consumption and investment strategies through backward stochastic differential equations (BSDEs).
Edit intent: fluency
Original:  Focusing on the empirically relevant case where the risk aversion and the elasticity of intertemporal substitution are both larger than one, we characterize  optimal consumption and investment strategies through backward stochastic differential equations (BSDEs).
Revised:  Focusing on the empirically relevant case where the risk aversion and the elasticity of intertemporal substitution are both larger than one, we characterize optimal consumption and investment strategies using backward stochastic differential equations (BSDEs).
Edit intent: fluency
Original:  Focusing on the empirically relevant case where the risk aversion and the elasticity of intertemporal substitution are both larger than one, we characterize  optimal consumption and investment strategies through backward stochastic differential equations (BSDEs). Compared with classical results on a fixed horizon, our characterization involves an additional stochastic process to account for the uncertainty of the horizon.
Revised:  Focusing on the empirically relevant case where the risk aversion and the elasticity of intertemporal substitution are both larger than one, we characterize optimal consumption and investment strategies through backward stochastic differential equations with superlinear growth on unbounded random horizons. This characterization, compared with the classical fixed-horizon result, involves an additional stochastic process to account for the uncertainty of the horizon.
Edit intent: meaning-changed
Original:  We discuss the current streams and methodologies of Chinese HCI research . We then propose future HCI research directions such as  including emergent users who have less access to technology  and addressing the cultural dimensions in order to provide better technical solutions and support.
Revised:  We discuss the current streams and methodologies of Chinese HCI research based on two well-known HCI theories: Micro/Marco-HCI and the Three Paradigms of HCI. We evaluate the discussion with a survey of Chinese publications at CHI 2019, which shows HCI research in China has less attention to Macro-HCI topics and the third paradigms of HCI (Phenomenologically situated Interaction). We then propose future HCI research directions such as including emergent users who have less access to technology and addressing the cultural dimensions in order to provide better technical solutions and support.
Edit intent: meaning-changed
Original:  We then propose future HCI research directions such as  including emergent users who have less access to technology  and addressing the cultural dimensions in order to provide better technical solutions and support.
Revised:  We then propose future HCI research directions such as paying more attention to Macro-HCI topics and third paradigm of HCI, combining research methodologies from multiple HCI paradigms, including emergent users who have less access to technology and addressing the cultural dimensions in order to provide better technical solutions and support.
Edit intent: meaning-changed
Original: We study a dynamic game in which information arrives gradually as long as a principal funds research, and an agent takes an action in each period.
Revised: What are the value and form of optimal persuasion when information can be generated only slowly? We study this question in a dynamic model in which a 'sender' provides public information over time subject to a graduality constraint, and a dynamic game in which information arrives gradually as long as a principal funds research, and an agent takes an action in each period.
Edit intent: meaning-changed
Original:  In equilibrium, the principal's patience is the key determinant of her information provision: the lower her discount rate, the more eagerly she funds. When she is sufficiently patient, her information provision and value function are well-approximated by the 'Bayesian persuasion' model. If the conflict of interest is purely belief-based and information is valuable, then she provides full information if she is patient. We also obtain a sharp characterisation of the principal's value function. Our proofs rely on a novel dynamic programming principle rooted in the theory of viscosity solutions of differential equations .
Revised:  Using a novel 'viscosity' dynamic programming principle, we characterise the sender's equilibrium value function and information provision. We show that the graduality constraint inhibits information provision relative to unconstrained persuasion. The gap can be substantial, but closes as the constraint slackens. Contrary to unconstrained persuasion, less-than-full information may be provided even if players have aligned preferences but different prior beliefs .
Edit intent: clarity
Original:  Information about an occupant's preference over room temperatures is available to us through their response to thermal preference queries : "prefer warmer," "prefer cooler" and "satisfied" which we interpret as statements about the derivative of their utility function, i.e. the utility function is "increasing", "decreasing" and "constant" respectively.
Revised:  Information about an occupant's preference over these temperatures is available to us through their response to thermal preference queries : "prefer warmer," "prefer cooler" and "satisfied" which we interpret as statements about the derivative of their utility function, i.e. the utility function is "increasing", "decreasing" and "constant" respectively.
Edit intent: clarity
Original:  We model this hidden utility function using a Gaussian process with a built-in unimodality constraint, i.e., the utility function has a unique maximum, and we train this model using Bayesian inference.
Revised:  We model this hidden utility function using a Gaussian process prior with built-in unimodality constraint, i.e., the utility function has a unique maximum, and we train this model using Bayesian inference.
Edit intent: clarity
Original: The goal of this paper is to establish a benchmark for transaction cost analysis in bond trading for retail investors.
Revised: With the rise of the electronic trading, corporate bond traders have access to data information of past trades. As a first step to automation, they have to start monitoring their own trades, and using past data to build a benchmark for the expected transaction costs with given bond characteristics and market conditions. Given the limited liquidity of corporate bonds which are traded few times daily, a statistical model is the only way to benchmark effective costs. It brings focused attention of the dealing desk of an institutional investor on the most costly trades, and enables identifying and improving business practices such as the market timing for selection counterparties. Unlike existing literature which focuses on general measurements using OLS, this paper takes the viewpoint of a given investor, and provides an analytical approach to establish a benchmark for transaction cost analysis in bond trading for retail investors.
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Original:  The first step is  to identify abnormal trades by approximating the market liquidity using different statistical regression methods: OLS, two-step LASSO and Elastic Net  .
Revised:  The first step is to identify abnormal trades by approximating the market liquidity using different statistical regression methods: OLS, two-step LASSO and Elastic Net , are adopted to identify key features for the bid-ask spread of corporate bonds .
Edit intent: meaning-changed
Original: With the rise of the electronic trading, corporate bond traders have access to data information of past trades. As a first step to automation, they have to start monitoring their own trades, and using past data to build a benchmark for the expected transaction costs with given bond characteristics and market conditions.
Revised: Electronic platform has been increasingly popular for the execution of large orders among asset managers dealing desks. Properly monitoring each individual trade by the appropriate Transaction Cost Analysis (TCA) is the first key step towards this electronic automation. One of the challenges in TCA is to build a benchmark for the expected transaction costs with given bond characteristics and market conditions.
Edit intent: meaning-changed
Original:  As a first step to automation, they have to start monitoring their own trades, and using past data to build a benchmark for the expected transaction costs with given bond characteristics and market conditions.
Revised:  As a first step to automation, they have to start monitoring their own trades, and using past data to build a benchmark for the expected transaction cost and to characterize the price impact of each individual trade, with given bond characteristics and market conditions.
Edit intent: meaning-changed
Original:  Given the limited liquidity of corporate bonds which are traded few times daily, a statistical model is the only way to benchmark effective costs. It brings focused attention of the dealing desk of an institutional investor on the most costly trades, and enables identifying and improving business practices such as the market timing for selection counterparties. Unlike existing literature which focuses on general measurements using OLS, this paper takes the viewpoint of a given investor, and provides an analytical approach to establish a benchmark for transaction cost analysis in corporate bond tradings. Regularized methods are used to improve the selection of explanatory variables, as fewer variables provide easier analytics from a business perspective. This benchmark is constructed in two steps .
Revised:  Given the limited liquidity of corporate bonds which are traded few times daily, a statistical model as a benchmark for effective cost and a non-parametric model for the price impact kernel. Our TCA analysis is conducted based on the TRACE Enhanced dataset and consists of four steps in two different time scales .
Edit intent: meaning-changed
Original:  The first step is the regression analysis with cross validation to identify abnormal trades. Three regression approaches, OLS, two-step Lasso and Elastic Net, are adopted to identify key features for the bid-ask spread of corporate bonds.
Revised:  The first step is to identify the initiator of a transaction and the riskless-principle-trades (RPTs). With the estimated initiator of each trade, the second step is to estimate the bid-ask spread of corporate bonds.
Edit intent: meaning-changed
Original:  Three regression approaches, OLS, two-step Lasso and Elastic Net, are adopted to identify key features for the bid-ask spread of corporate bonds. The second step is to use the non-parametric approach to estimate the amplitude and decay pattern of price impact .
Revised:  Three regression approaches, OLS, two-step Lasso and Elastic Net, are adopted to identify key features for the bid-ask spread and the mid-price movements. The third step is to use the non-parametric approach to estimate the amplitude and decay pattern of price impact .
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Original:  The second step is to use the non-parametric approach to estimate the amplitude and decay pattern of price impact .
Revised:  The second step is to estimate the expected average cost on a weekly basis via regularized regression analysis. The final step is to investigate each trade for the amplitude of its price impact and the price decay after the transaction for liquid corporate bonds. Here we apply a transient impact model (TIM) to estimate the price impact kernel via a non-parametric approach to estimate the amplitude and decay pattern of price impact .
Edit intent: meaning-changed
Original:  In addition, mutation, in combination with heterogeneous updating rules, also diminishes co-operators, a phenomenon that is prominent when a large proportion of the population consists of imitators rather than adopters of aspiration-based updating.
Revised:  In addition, mutation, in combination with heterogeneous updating rules, also diminishes cooperators. This phenomenon is prominent when a large proportion of the population consists of imitators rather than adopters of aspiration-based updating.
Edit intent: coherence
Original:  Notwithstanding this , a high mutation rate, in combination with a low aspiration level, has positive nonlinear effects, and a heterogeneous system achieves a higher level of co-operation relative to a homogeneous system .
Revised:  Nevertheless , a high mutation rate, in combination with a low aspiration level, has positive nonlinear effects, and a heterogeneous system achieves a higher level of co-operation relative to a homogeneous system .
Edit intent: coherence
Original:  Notwithstanding this , a high mutation rate, in combination with a low aspiration level, has positive nonlinear effects, and a heterogeneous system achieves a higher level of co-operation relative to a homogeneous system .
Revised:  Notwithstanding this , a high mutation rate, in combination with a low aspiration level, has positive nonlinear effects, and a heterogeneous population achieves a higher level of co-operation relative to a homogeneous system .
Edit intent: clarity
Original:  Notwithstanding this , a high mutation rate, in combination with a low aspiration level, has positive nonlinear effects, and a heterogeneous system achieves a higher level of co-operation relative to a homogeneous system .
Revised:  Notwithstanding this , a high mutation rate, in combination with a low aspiration level, has positive nonlinear effects, and a heterogeneous system achieves a higher level of cooperation than the weighted average of homogeneous populations .
Edit intent: meaning-changed
Original:  We find that the most inner core (i.e., the most connected kernel) of the conscious-state functional network (the visual cortex and the left middle frontal gyrus) corresponds to the areas which remain functionally active when the brain transitions from the conscious-state to the subliminal-state.
Revised:  We find that the most inner core (i.e., the most connected kernel) of the conscious-state functional network corresponds to areas which remain functionally active when the brain transitions from the conscious-state to the subliminal-state.
Edit intent: coherence
Original:  Rather than specify or fit a parametric network formation model, I introduce a new method based on matching pairs of agents with similar columns of the squared adjacency matrix, the ijth entry of which contains the number of other agents linked to both agents i and j.
Revised:  Rather than specify and fit a parametric network formation model, I introduce a new method based on matching pairs of agents with similar columns of the squared adjacency matrix, the ijth entry of which contains the number of other agents linked to both agents i and j.
Edit intent: fluency
Original: Model robustness has been an important issue, since adding small adversarial perturbations to images is sufficient to drive the model accuracy down to nearly zero .
Revised: Adversarial robustness has emerged as an important topic in deep learning as carefully crafted attack samples can significantly disturb the performance of a model. Many recent methods have proposed to improve adversarial robustness by utilizing adversarial training or model distillation, which adds additional procedures to model training .
Edit intent: clarity
Original:  In this paper, we propose a new training objective " Guided Complement Entropy " (GCE) that has dual desirable effects: (a) neutralizing the predicted probabilities of incorrect classes,and (b) maximizing the predicted probability of the ground-truth class , particularly when (a) is achieved.
Revised:  In this paper, we propose a new training paradigm called Guided Complement Entropy " (GCE) that has dual desirable effects: (a) neutralizing the predicted probabilities of incorrect classes,and (b) maximizing the predicted probability of the ground-truth class , particularly when (a) is achieved.
Edit intent: clarity
Original:  In this paper, we propose a new training objective " Guided Complement Entropy " (GCE) that has dual desirable effects: (a) neutralizing the predicted probabilities of incorrect classes,and (b) maximizing the predicted probability of the ground-truth class , particularly when (a) is achieved.
Revised:  In this paper, we propose a new training objective " Guided Complement Entropy (GCE) that has dual desirable effects: (a) neutralizing the predicted probabilities of incorrect classes,and (b) maximizing the predicted probability of the ground-truth class , particularly when (a) is achieved.
Edit intent: fluency
Original:  In this paper, we propose a new training objective " Guided Complement Entropy " (GCE) that has dual desirable effects: (a) neutralizing the predicted probabilities of incorrect classes,and (b) maximizing the predicted probability of the ground-truth class , particularly when (a) is achieved.
Revised:  In this paper, we propose a new training objective " Guided Complement Entropy " (GCE) that is capable of achieving "adversarial defense for free," which involves no additional procedures in the process of improving adversarial robustness. In addition to maximizing model probabilities on the ground-truth class , particularly when (a) is achieved.
Edit intent: meaning-changed