wanyu/IteraTeR_full_sent huggingface dataset:
Original:  Furthermore, as the lattice parameter decreases, searching our data structure yields a six-approximation of the nearest diagram in \Gamma in O((m %DIFDELCMD < \logn%%%  +m^2)\log\tau) time and a constant factor approximation of the kth nearest diagram in O((m %DIFDELCMD < \logn%%%  +m^2+k)\log\tau) time.
Revised:  Furthermore, as the lattice parameter decreases, searching our data structure yields a six-approximation of the nearest diagram in \Gamma in O((m %DIFDELCMD < \logn%%% \log{n +m^2)\log\tau) time and a constant factor approximation of the kth nearest diagram in O((m %DIFDELCMD < \logn%%% +m^2+k)\log\tau) time.
Edit intent: meaning-changed
Original:  Furthermore, as the lattice parameter decreases, searching our data structure yields a six-approximation of the nearest diagram in \Gamma in O((m %DIFDELCMD < \logn%%%  +m^2)\log\tau) time and a constant factor approximation of the kth nearest diagram in O((m %DIFDELCMD < \logn%%%  +m^2+k)\log\tau) time.
Revised:  Furthermore, as the lattice parameter decreases, searching our data structure yields a six-approximation of the nearest diagram in \Gamma in O((m %DIFDELCMD < \logn%%% +m^2)\log\tau) time and a constant factor approximation of the kth nearest diagram in O((m %DIFDELCMD < \logn%%% \log{n +m^2+k)\log\tau) time.
Edit intent: meaning-changed
Original:  We obtain analogous results in the heterogeneous effects models, where we derive identified sets for marginal distributions of potential outcomes, falsification frontiers, and falsification adaptive sets under continuous relaxations of the instrument exogeneity assumptions  .
Revised:  We obtain analogous results in the heterogeneous effect models, where we derive identified sets for marginal distributions of potential outcomes, falsification frontiers, and falsification adaptive sets under continuous relaxations of the instrument exogeneity assumptions .
Edit intent: fluency
Original:  We obtain analogous results in the heterogeneous effects models, where we derive identified sets for marginal distributions of potential outcomes, falsification frontiers, and falsification adaptive sets under continuous relaxations of the instrument exogeneity assumptions  .
Revised:  We obtain analogous results in the heterogeneous effects models, where we derive identified sets for marginal distributions of potential outcomes, falsification frontiers, and falsification adaptive sets under continuous relaxations of the instrument exogeneity assumptions . We illustrate our results in four different empirical applications .
Edit intent: meaning-changed
Original:  We characterize the structure of the set of selfconfirming equilibria in network games and we relate selfconfirming and Nash equilibria . Thus, we provide conditions on the network under which the Nash equilibrium concept has a learning foundation, despite the fact that agents may have incomplete information. In particular, we show that the choice of being active or inactive in a network is crucial to determine whether agents can make correct inferences about the payoff state and hence play the best reply to the truth in a selfconfirming equilibrium. We also study learning dynamics and show how agents can get stuck in non--Nash selfconfirming equilibria. In such dynamics, the set of inactive agents can only increase in time, because once an agent finds it optimal to be inactive, she gets no feedback about the payoff state, hence she does not change her beliefs and remains inactive .
Revised:  We characterize the structure of the set of selfconfirming equilibria in network games and we relate selfconfirming and Nash equilibria , and we analyze simple conjectural best-reply paths whose limit points are selfconfirming equilibria .
Edit intent: meaning-changed
Original:  Here, we propose a new algorithm for the RNA Design problem, dubbed LEARNA. LEARNA uses deep reinforcement learning to train a policy network to sequentially design an entire RNA sequence given a specified secondary target structure.
Revised:  Here, we propose a new algorithm for the RNA Design problem, dubbed LEARNA. LEARNA uses deep reinforcement learning to train a policy network to sequentially design an entire RNA sequence given a specified target structure.
Edit intent: clarity
Original:  By meta-learning across 8000 different RNA target structures for one hour on 20  cores, our extension Meta-LEARNA constructs an RNA Design policy that can be applied out of the box to solve novel RNA target structures .
Revised:  By meta-learning across 65000 different RNA Design tasks for one hour on 20 cores, our extension Meta-LEARNA constructs an RNA Design policy that can be applied out of the box to solve novel RNA target structures .
Edit intent: meaning-changed
Original:  By meta-learning across 8000 different RNA target structures for one hour on 20  cores, our extension Meta-LEARNA constructs an RNA Design policy that can be applied out of the box to solve novel RNA target structures .
Revised:  By meta-learning across 8000 different RNA target structures for one hour on 20 CPU cores, our extension Meta-LEARNA constructs an RNA Design policy that can be applied out of the box to solve novel RNA target structures .
Edit intent: meaning-changed
Original:  By meta-learning across 8000 different RNA target structures for one hour on 20  cores, our extension Meta-LEARNA constructs an RNA Design policy that can be applied out of the box to solve novel RNA target structures .
Revised:  By meta-learning across 8000 different RNA target structures for one hour on 20 cores, our extension Meta-LEARNA constructs an RNA Design policy that can be applied out of the box to solve novel RNA Design tasks .
Edit intent: clarity
Original:  Methodologically, for what we believe to be the first time, we jointly optimize over a rich space of neural architectures for the policy network, the hyperparameters of the training procedure and the formulation of the decision process.
Revised:  Methodologically, for what we believe to be the first time, we jointly optimize over a rich space of architectures for the policy network, the hyperparameters of the training procedure and the formulation of the decision process.
Edit intent: clarity
Original:  Comprehensive empirical results on two widely-used RNA secondary structure design benchmarks, as well as a third one that we introduce, show that our approach achieves new state-of-the-art performance on all benchmarks while also being orders of magnitudes faster in reaching the previous state-of-the-art performance.
Revised:  Comprehensive empirical results on two widely-used RNA Design benchmarks, as well as a third one that we introduce, show that our approach achieves new state-of-the-art performance on all benchmarks while also being orders of magnitudes faster in reaching the previous state-of-the-art performance.
Edit intent: clarity
Original:  Comprehensive empirical results on two widely-used RNA secondary structure design benchmarks, as well as a third one that we introduce, show that our approach achieves new state-of-the-art performance on all benchmarks while also being orders of magnitudes faster in reaching the previous state-of-the-art performance.
Revised:  Comprehensive empirical results on two widely-used RNA secondary structure design benchmarks, as well as a third one that we introduce, show that our approach achieves new state-of-the-art performance on the former while also being orders of magnitudes faster in reaching the previous state-of-the-art performance.
Edit intent: meaning-changed
Original: In this review we present a concept that, despite mounting evidence , received little attention so far: susceptibility to adult neurodegenerative diseases may be programmed in utero and early postnatal preventive measures may reduce the risk.
Revised: We review evidence supporting the role of early life programming in the susceptibility for adult neurodegenerative diseases may be programmed in utero and early postnatal preventive measures may reduce the risk.
Edit intent: clarity
Original: In this review we present a concept that, despite mounting evidence , received little attention so far: susceptibility to adult neurodegenerative diseases may be programmed in utero and early postnatal preventive measures may reduce the risk. We delineate the key mechanisms and players mediating this phenomenon laying a foundation for preventive strategies. First, we discuss what is likely the most common insult taking place during fetal development and imprinting upon fetal brain: chronic pregnancy stress. We propose that such imprinting is mediated via the microglial (and perhaps astrocytic) memory and that such memory may increase susceptibility to neurodegenerative diseases in adult life. We discuss microglial plasticity and mechanisms by which in utero insults influence the dynamic process of microglial-neuronal interactions in the developing brain. Microglial role in adult neurodegenerative disorders is reviewed and this concept is brought back to the perinatal origins of adult susceptibility to neurodegeneration.
Revised: In this review we present a concept that, despite mounting evidence , received little attention so far: susceptibility to adult neurodegenerative diseases while highlighting questions and proposing avenues for future research to advance our understanding of this fundamental process. The key elements of this phenomenon are chronic stress, neuroinflammation triggering microglial polarization, microglial memory and their connection to neurodegeneration.
Edit intent: clarity
Original: We employ CPS data to analyze the sources of hourly real wage changes in the United States for 1976 to 2016 at various quantiles of the wage distribution.
Revised: We employ CPS data to analyze the sources of hourly real wage changes in the distribution of hourly wages in the United States using CPS data for the survey years 1976 to 2016 at various quantiles of the wage distribution.
Edit intent: meaning-changed
Original:  We account for the selection bias from the  annual hours of work decision by developing and implementing an estimator for nonseparable selection models with censored selection rules. We then decompose wage changes into composition, structural and selection effects.
Revised:  We account for the selection bias from the annual hours of work and estimating a nonseparable model of wages which uses a control function to account for selection. This allows the inclusion of all individuals working positive hours and thus provides a fuller description of the wage distribution. We decompose changes in the distribution of wages into composition, structural and selection effects.
Edit intent: meaning-changed
Original: Seashells are an ideal model system for understanding the morpho-elastic basis of exoskeleton evolution in invertebrates . During the formation of the shell, the mantle tissue secretes proteins and minerals that calcify to form a new incremental layer of the exoskeleton.
Revised: Mollusk shells are an ideal model system for understanding the morpho-elastic basis of exoskeleton evolution in invertebrates . During the formation of the shell, the mantle tissue secretes proteins and minerals that calcify to form a new incremental layer of the exoskeleton.
Edit intent: clarity
Original: Seashells are an ideal model system for understanding the morpho-elastic basis of exoskeleton evolution in invertebrates . During the formation of the shell, the mantle tissue secretes proteins and minerals that calcify to form a new incremental layer of the exoskeleton.
Revised: Seashells are an ideal model system for understanding the morpho-elastic basis of morphological evolution of invertebrates' exoskeletons . During the formation of the shell, the mantle tissue secretes proteins and minerals that calcify to form a new incremental layer of the exoskeleton.
Edit intent: clarity
Original:  We demonstrate the potential of this formulation by applying it to explain the stepwise morphologenesis of seashells during growth: New material surfaces are laid down by accretive growth on the mantle whose form is determined by its morpho-elastic growth.
Revised:  We exercise this framework by applying it to explain the stepwise morphologenesis of seashells during growth: New material surfaces are laid down by accretive growth on the mantle whose form is determined by its morpho-elastic growth.
Edit intent: clarity
Original:  We demonstrate the potential of this formulation by applying it to explain the stepwise morphologenesis of seashells during growth: New material surfaces are laid down by accretive growth on the mantle whose form is determined by its morpho-elastic growth.
Revised:  We demonstrate the potential of this formulation by applying it to explain the stepwise morphogenesis of seashells during growth: New material surfaces are laid down by accretive growth on the mantle whose form is determined by its morpho-elastic growth.
Edit intent: clarity
Original:  We demonstrate the potential of this formulation by applying it to explain the stepwise morphologenesis of seashells during growth: New material surfaces are laid down by accretive growth on the mantle whose form is determined by its morpho-elastic growth.
Revised:  We demonstrate the potential of this formulation by applying it to explain the stepwise morphologenesis of seashells during growth: new material surfaces are laid down by accretive growth on the mantle whose form is determined by its morpho-elastic growth.
Edit intent: fluency
Original: Burgeoning interest in the area of bacteria powered bio-hybrid micro-robotic systems motivates a fundamental question on how one achieves optimal cargo-carrying capacity in such systems. Here we demonstrate a process to attach oil-droplet cargos to cell bodies of flagellated single bacteria which allowed us to probe cargo-carrying capacity of single bacteria over cargo sizes as large as 200 times a single cell volume. The most remarkable finding from our studies is that , for a given cargo size, the swim-speed is maximized when the rotational drag coefficient of the flagella is tuned to the torque-speed  characteristics of the bacterial flagellar motor .
Revised: In a classic paper, Edward Purcell analysed the dynamics of flagellated bacterial swimmers and derived a geometrical relationship which optimizes the propulsion efficiency. Experimental measurements for wild-type bacterial species E. coli have revealed that they closely satisfy this geometric optimality. However, the dependence of the flagellar motor speed on the load and more generally the role of the torque-speed characteristics of the bacterial flagellar motor .
Edit intent: coherence
Original:  The most remarkable finding from our studies is that , for a given cargo size, the swim-speed is maximized when the rotational drag coefficient of the flagella is tuned to the torque-speed  characteristics of the bacterial flagellar motor .
Revised:  The most remarkable finding from our studies is that , for a given cargo size, the swim-speed is maximized when the rotational drag coefficient of the flagella is tuned to the torque-speed characteristics of the flagellar motor is not considered in Purcell's original analysis. Here we derive a tuned condition representing a match between the flagella geometry and the torque-speed characteristics of the bacterial flagellar motor .
Edit intent: meaning-changed
Original:  The most remarkable finding from our studies is that , for a given cargo size, the swim-speed is maximized when the rotational drag coefficient of the flagella is tuned to the torque-speed  characteristics of the bacterial flagellar motor . This tuning criterion discovered in our analysis is not satisfied by wild-type bacteria such as E. coli .
Revised:  The most remarkable finding from our studies is that , for a given cargo size, the swim-speed is maximized when the rotational drag coefficient of the flagella is tuned to the torque-speed characteristics of the flagellar motor to maximize the bacterial swimming speed for a given load. This condition is independent of the geometric optimality condition derived by Purcell and interestingly this condition is not satisfied by wild-type bacteria such as E. coli .
Edit intent: meaning-changed
Original:  This tuning criterion discovered in our analysis is not satisfied by wild-type bacteria such as E. coli . Operating in the tuned regime leads to swim-speed enhancements in excess of 4 times relative to wild-type condition. This result provides a simple design rule to achieve optimal cargo transport for future bio-hybrid or synthetic flagellated micro-swimmers. Additionally, our study also reveals the existence of an anomalous propulsion regime where swim-speed increases with increasing load  .
Revised:  This tuning criterion discovered in our analysis is not satisfied by wild-type bacteria such as E. coli which swim 2-3 times slower than the maximum possible speed given the amount of available motor torque. Our analysis also reveals the existence of an anomalous propulsion regime where swim-speed increases with increasing load .
Edit intent: meaning-changed
Original:  Unfortunately, if the researcher allows for an arbitrarily small failure of instrumental validity then the failure of such a smoothness condition is generally not testable and in fact one cannot identify any upper bound on the magnitude of the failure. To address these problems we propose an alternative method in which the structural function is treated as partially identified .
Revised:  However, we show that in general the smoothness assumptions cannot be confirmed empirically. In response, we treat the structural function is treated as partially identified .
Edit intent: coherence
Original:  To address these problems we propose an alternative method in which the structural function is treated as partially identified . Under our procedure the researcher achieves robust confidence sets using a priori bounds on the deviation from instrumental validity and approximation error.
Revised:  To address these problems we propose an alternative method in which the structural function is treated as partially identified and construct a consistent estimator of the identified set under bounds on the deviation from instrumental validity and approximation error.
Edit intent: clarity
Original:  Under our procedure the researcher achieves robust confidence sets using a priori bounds on the deviation from instrumental validity and approximation error. Our procedure is based on the sieve-minimum distance method and has an added advantage in that it reduces the need to choose the size of the sieve space either directly or algorithmically. We also present a related method that allows the researcher to assess the sensitivity of their NPIV estimates to misspecification.
Revised:  Under our procedure the researcher achieves robust confidence sets using a priori bounds on the degree of misspecification. Our proposed technique is a practical alternative to standard NPIV estimation and allows the researcher to assess the sensitivity of their NPIV estimates to misspecification.
Edit intent: clarity
Original:  We also present a related method that allows the researcher to assess the sensitivity of their NPIV estimates to misspecification. This sensitivity analysis can inform the choice of sieve space in point estimation .
Revised:  We also present a related method that allows the researcher to make meaningful inferences about the structural function when misspecification cannot ruled out. The method is easy to implement and computationally light. The first stage resembles that of sieve minimum-distance estimation, and the second stage requires numerical solution of a linear programming problem. In contrast to existing methods our second stage does not require that the researcher choose any penalty function, penalty parameter nor a particular dimension of a sieve space. To compare our method to existing approaches we present an empirical application based on Horowitz (2011) .
Edit intent: meaning-changed
Original:   Our proposed technique is a practical alternative to standard NPIV estimation and allows the researcher to make meaningful inferences about the structural function when  misspecification cannot ruled out.
Revised:  The set estimator can interpreted as error bounds on a point estimator and used to perform sensitivity analysis. Our proposed technique is a practical alternative to standard NPIV estimation and allows the researcher to make meaningful inferences about the structural function when misspecification cannot ruled out.
Edit intent: meaning-changed
Original:  The first stage resembles that of sieve minimum-distance estimation, and the second stage requires numerical solution of a linear programming problem. In contrast to existing methods our second stage does not require that the researcher choose any penalty function, penalty parameter nor a particular dimension of a sieve space. To compare our method to existing approaches we present an empirical application based on Horowitz (2011)  .
Revised:  The first stage resembles that of sieve minimum-distance estimation, and the second stage is formulated as a linear program. We apply our methods to the empirical setting of Blundell et al. (2007) and Horowitz (2011) .
Edit intent: clarity
Original:  An arbitrarily small deviation from instrumental validity can lead to large asymptotic bias for many NPIV estimators. Imposing strong smoothness conditions on the structural function may reduce the severity of the problem .
Revised:  An arbitrarily small deviation from instrumental validity can lead to large asymptotic bias for a broad class of estimators. The problem is mitigated if strong restrictions on the structural function may reduce the severity of the problem .
Edit intent: clarity
Original:  In response, we treat the structural function as partially identified and construct a consistent estimator of the identified set and robust confidence bands under bounds on the degree of misspecification. The set estimator can interpreted as error bounds on a point estimator and used to perform sensitivity analysis. Our proposed technique is a practical alternative to standard methods and allows the researcher to make meaningful inferences about the structural function when some misspecification cannot ruled out.
Revised:  Therefore, there is a trade-off between the sensitivity to invalid instruments and bias from imposing excessive restrictions. We propose a partial identification approach that allows a researcher to explicitly and transparently examine this trade-off and make inferences about the structural function when some misspecification cannot ruled out.
Edit intent: meaning-changed
Original:  Our proposed technique is a practical alternative to standard methods and allows the researcher to make meaningful inferences about the structural function when some misspecification cannot ruled out. Our procedure is easy to implement and computationally light. The first stage resembles that of sieve minimum-distance estimation, and the second stage is formulated as a linear program .
Revised:  Our proposed technique is a practical alternative to standard methods and allows the researcher to make meaningful inferences about the structural function that are valid under a small failure of instrumental validity. We construct a simple, consistent estimator of the identified set .
Edit intent: meaning-changed
Original: We show that nonparametric instrumental variables  estimators are highly sensitive to misspecification: an arbitrarily small deviation from instrumental validity can lead to large asymptotic bias for a broad class of estimators.
Revised: We show that nonparametric instrumental variables (NPIV) estimators are highly sensitive to misspecification: an arbitrarily small deviation from instrumental validity can lead to large asymptotic bias for a broad class of estimators.
Edit intent: meaning-changed