wanyu/IteraTeR_full_sent huggingface dataset:
Original:  Exact time-dependent solutions of the CME---which typically consists of infinitely many coupled differential equations---are rare, and are valuable for numerical benchmarking and getting intuition for the behavior of more complicated systems.
Revised:  Exact time-dependent solutions of the CME---which typically consists of infinitely many coupled differential equations -- are rare, and are valuable for numerical benchmarking and getting intuition for the behavior of more complicated systems.
Edit intent: fluency
Original:  To illustrate how the Doi-Peliti approach can go beyond the method of Jahnke and Huisinga, we also find the exact time-dependent solution to a problem involving an autocatalytic reaction that Jahnke and Huisinga identified as not solvable using their method  .
Revised:  To illustrate how the Doi-Peliti approach can go beyond the method of Jahnke and Huisinga, we also find an explicit and exact time-dependent solution to a problem involving an autocatalytic reaction that Jahnke and Huisinga identified as not solvable using their method .
Edit intent: clarity
Original:  To illustrate how the Doi-Peliti approach can go beyond the method of Jahnke and Huisinga, we also find the exact time-dependent solution to a problem involving an autocatalytic reaction that Jahnke and Huisinga identified as not solvable using their method  .
Revised:  To illustrate how the Doi-Peliti approach can go beyond the method of Jahnke and Huisinga, we also find the exact time-dependent solution to a problem involving an autocatalytic reaction that Jahnke and Huisinga identified as not solvable using their method . We also find a formal exact time-dependent solution for any CME whose list of reactions involves only zero and first order reactions, which may be the most general result currently known .
Edit intent: meaning-changed
Original:  We introduce and develop a novel human-machine interaction framework, in which the robo-advisor solves an adaptive mean-variance control problem, with the risk-return tradeoff dynamically updated based on the risk profile communicated by the client.
Revised:  We introduce a novel framework, in which the robo-advisor solves an adaptive mean-variance control problem, with the risk-return tradeoff dynamically updated based on the risk profile communicated by the client.
Edit intent: clarity
Original:  We introduce and develop a novel human-machine interaction framework, in which the robo-advisor solves an adaptive mean-variance control problem, with the risk-return tradeoff dynamically updated based on the risk profile communicated by the client.
Revised:  We introduce and develop a novel human-machine interaction framework, in which a robo-advisor solves an adaptive mean-variance control problem, with the risk-return tradeoff dynamically updated based on the risk profile communicated by the client.
Edit intent: fluency
Original:  We introduce and develop a novel human-machine interaction framework, in which the robo-advisor solves an adaptive mean-variance control problem, with the risk-return tradeoff dynamically updated based on the risk profile communicated by the client.
Revised:  We introduce and develop a novel human-machine interaction framework, in which the robo-advisor interacts with a client to solve an adaptive mean-variance control problem, with the risk-return tradeoff dynamically updated based on the risk profile communicated by the client.
Edit intent: clarity
Original:  We introduce and develop a novel human-machine interaction framework, in which the robo-advisor solves an adaptive mean-variance control problem, with the risk-return tradeoff dynamically updated based on the risk profile communicated by the client.
Revised:  We introduce and develop a novel human-machine interaction framework, in which the robo-advisor solves an adaptive mean-variance portfolio optimization problem. The risk-return tradeoff dynamically updated based on the risk profile communicated by the client.
Edit intent: clarity
Original:  We introduce and develop a novel human-machine interaction framework, in which the robo-advisor solves an adaptive mean-variance control problem, with the risk-return tradeoff dynamically updated based on the risk profile communicated by the client. Our model predicts that clients who value a personalized portfolio are more suitable for robo-advising. Clients who place higher emphasis on delegation and clients with a risk profile that changes frequently benefit less from robo-advising .
Revised:  We introduce and develop a novel human-machine interaction framework, in which the robo-advisor solves an adaptive mean-variance control problem, with the risk-return tradeoff adapts to the client's risk profile, which depends on idiosyncratic characteristics, market returns, and economic conditions. We show that the optimal investment strategy includes both myopic and intertemporal hedging terms which are impacted by the dynamics of the client's risk profile. We characterize the optimal portfolio personalization via a tradeoff faced by the robo-advisor between receiving client information in a timely manner and mitigating behavioral biases in the risk profile communicated by the client. We argue that the optimal portfolio's Sharpe ratio and return distribution improve if the robo-advisor counters the client's tendency to reduce market exposure during economic contractions when the market risk-return tradeoff is more favorable .
Edit intent: meaning-changed
Original:  One of the major goals of neuroscience is to find interpretable descriptions of what the brain represents and computes by trying to explain complex phenomena in simple terms . Considering this task from the perspective of dimensionality reduction provides an entry point into principled mathematical techniques allowing us to discover these representations directly from experimental data, a key step to developing rich yet comprehensible models for brain function.
Revised:  The objective of this work is to discover directly from the experimental data rich and comprehensible models for brain function that will be concurrently robust to noise . Considering this task from the perspective of dimensionality reduction provides an entry point into principled mathematical techniques allowing us to discover these representations directly from experimental data, a key step to developing rich yet comprehensible models for brain function.
Edit intent: meaning-changed
Original:  One of the major goals of neuroscience is to find interpretable descriptions of what the brain represents and computes by trying to explain complex phenomena in simple terms . Considering this task from the perspective of dimensionality reduction provides an entry point into principled mathematical techniques allowing us to discover these representations directly from experimental data, a key step to developing rich yet comprehensible models for brain function. In this work, we employ two real-world binary datasets describing the spontaneous neuronal activity of two laboratory mice over time, and we aim to their efficient low-dimensional representation.
Revised:  One of the major goals of neuroscience is to find interpretable descriptions of what the brain represents and computes by trying to explain complex phenomena in simple terms . Considering this task from the perspective of dimensionality reduction , we develop an innovative, robust to noise dictionary learning framework based on adversarial training methods for the identification of patterns of synchronous firing activity as well as within a time lag. We employ real-world binary datasets describing the spontaneous neuronal activity of two laboratory mice over time, and we aim to their efficient low-dimensional representation.
Edit intent: meaning-changed
Original:  The results on the classification accuracy for the discrimination between the clean and the adversarial-noisy activation patterns obtained by an SVM classifier highlight the efficacy of the proposed scheme  , and the visualization of the dictionary's distribution demonstrates the multifarious information that we obtain from it.
Revised:  The results on the classification accuracy for the discrimination between the clean and the adversarial-noisy activation patterns obtained by an SVM classifier highlight the efficacy of the proposed scheme compared to other methods , and the visualization of the dictionary's distribution demonstrates the multifarious information that we obtain from it.
Edit intent: meaning-changed
Original: Analogy is the core of cognition , and can be formalized in terms of Bayesian inference . Indeed, thought itself can be thought of as constituting dynamics of cascading belief propagation through the nodes of generative probability models specified by a cortical heterarchy "rooted" in perception-action cycles that ground the mind as an embodied control system for an autonomous agent.
Revised: Analogy is the core of cognition , and can be formalized in terms of Bayesian inference and vice versa, and that both of these positions require a thorough cybernetic grounding in order to fulfill their promise as unifying frameworks for understanding minds. From the Bayesian perspective of the Free Energy Principle and Active Inference framework, thought is constituted by dynamics of cascading belief propagation through the nodes of generative probability models specified by a cortical heterarchy "rooted" in perception-action cycles that ground the mind as an embodied control system for an autonomous agent.
Edit intent: meaning-changed
Original:  Indeed, thought itself can be thought of as constituting dynamics of cascading belief propagation through the nodes of generative probability models specified by a cortical heterarchy "rooted" in perception-action cycles that ground the mind as an embodied control system for an autonomous agent.
Revised:  Indeed, thought itself can be thought of as constituting dynamics of cascading belief propagation through the nodes of probabilistic generative models specified by a cortical heterarchy "rooted" in perception-action cycles that ground the mind as an embodied control system for an autonomous agent.
Edit intent: clarity
Original:  Indeed, thought itself can be thought of as constituting dynamics of cascading belief propagation through the nodes of generative probability models specified by a cortical heterarchy "rooted" in perception-action cycles that ground the mind as an embodied control system for an autonomous agent.
Revised:  Indeed, thought itself can be thought of as constituting dynamics of cascading belief propagation through the nodes of generative probability models specified by a cortical heterarchy "rooted" in action-perception cycles that ground the mind as an embodied control system for an autonomous agent.
Edit intent: fluency
Original:  From this perspective, a translating principle between cognitive science and machine learning can be obtained that should result in productive cross-fertilization between these disciplines: simply, cortical columns represent nodes in a particular kind of directed graphical model, where the symbolic level emerges from the sub-symbolic level through hierarchical pattern abstraction.
Revised:  From the analogical structure mapping perspective, thought is constituted by the alignment and comparison of heterogeneous structural representations. Here I will propose that this core cognitive process for analogical reasoning is naturally implemented by predictive coding mechanisms. However, both Bayesian cognitive science and models of cognitive development via analogical reasoning require rich base domains and priors (or reliably learnable posteriors) from which they can commence the process of bootstrapping minds. Here in the sub-symbolic level through hierarchical pattern abstraction.
Edit intent: meaning-changed
Original:  From this perspective, a translating principle between cognitive science and machine learning can be obtained that should result in productive cross-fertilization between these disciplines: simply, cortical columns represent nodes in a particular kind of directed graphical model, where the symbolic level emerges from the sub-symbolic level through hierarchical pattern abstraction. In terms of development, embodiment provides useful inductive biases that act as a toehold in allowing the learner to bootstrap its way to the full flourishing of cognition. More specifically, I argue that URLanisms are such effective learners because they begin with a sense of their own embodiment as a kind of prototypical object from which they can partially generalize, and they pay attention to this object because it is directly connected to the mechanisms of reinforcement. This account of cognitive development can explain the knowledge that infants possess, as well as how they use this acquired core knowledgeto partially generalize to other classes of phenomena, even sometimes incorrectly.
Revised:  From this perspective, a translating principle between cognitive science and machine learning can be obtained that should result in productive cross-fertilization between these disciplines: simply, cortical columns represent nodes in a particular kind of directed graphical model, where the symbolic level emerges from the spirit of the work of URLe Lakoff and Mark Johnson, I propose that embodiment provides many of the inductive biases that are usually described in terms of innate core knowledge. (Please note: this manuscript was written and finalized in 2012.)
Edit intent: meaning-changed
Original:  Some evidence for RAR includes physiological similarities between hyperventilation and laughter and the fact that smiles often indicate negative affect in non-human primates (e.g. fear grimaces where teeth are exposed as a kind of inhibited threat display , as suggested by Michael Graziano). If humor reliably indicates conditions of a) anxiety induction, b) anxiety reduction, and c) the time-course relating these things--so productively constraining inference spaces regarding latent mental states--then we know a great deal about the values and capacities of the persons experiencing humor.
Revised:  Some evidence for RAR includes physiological similarities between hyperventilation and laughter and the fact that smiles often indicate negative affect in non-human primates (e.g. fear grimaces where teeth are exposed as a kind of inhibited threat display ). In accordance with Benign Violation Theory, if humor reliably indicates conditions of a) anxiety induction, b) anxiety reduction, and c) the time-course relating these things--so productively constraining inference spaces regarding latent mental states--then we know a great deal about the values and capacities of the persons experiencing humor.
Edit intent: meaning-changed
Original:  If humor reliably indicates conditions of a) anxiety induction, b) anxiety reduction, and c) the time-course relating these things--so productively constraining inference spaces regarding latent mental states--then we know a great deal about the values and capacities of the persons experiencing humor.
Revised:  If humor reliably indicates both a) anxiety induction, b) anxiety reduction, and c) the time-course relating these things--so productively constraining inference spaces regarding latent mental states--then we know a great deal about the values and capacities of the persons experiencing humor.
Edit intent: clarity
Original:  If humor reliably indicates conditions of a) anxiety induction, b) anxiety reduction, and c) the time-course relating these things--so productively constraining inference spaces regarding latent mental states--then we know a great deal about the values and capacities of the persons experiencing humor.
Revised:  If humor reliably indicates conditions of a) anxiety induction, b) anxiety reduction, and c) the time-course over which anxiety is reduced, then the intersection of these conditions productively constrains inference spaces over latent mental states with respect to the values and capacities of the persons experiencing humor.
Edit intent: clarity
Original:  Finally, if humor is such an essential aspect of the human experience, and if humor can be expressed in such a simple formula which has remained undiscovered for this long, then this is an extremely surprising state of affairs worthy of further investigation.
Revised:  Finally, if humor is such an essential aspect of the human experience, and if humor can be expressed in such a simple formula with clear ties to phenomenology, and yet this discovery regarding such an essential part of the human experience has remained undiscovered for this long, then this is an extremely surprising state of affairs worthy of further investigation.
Edit intent: meaning-changed
Original:  Toward this end, I propose an analogy can be found with consciousness studies, where in addition to the "Hard problem" of trying to explain humor, we would do well to consider a "Meta-Problem" of why humor seems so difficult to explain, and why relatively simple explanations may have eluded us for this long. 
Revised:  Towards this end, I propose an analogy can be found with consciousness studies, where in addition to the "Hard problem" of trying to explain humor, we would do well to consider a "Meta-Problem" of why humor seems so difficult to explain, and why relatively simple explanations may have eluded us for this long. 
Edit intent: fluency
Original:  Toward this end, I propose an analogy can be found with consciousness studies, where in addition to the "Hard problem" of trying to explain humor, we would do well to consider a "Meta-Problem" of why humor seems so difficult to explain, and why relatively simple explanations may have eluded us for this long. 
Revised:  Toward this end, I propose an analogy can be found with consciousness studies, where in addition to the "Hard problem" of trying to explain humor, we would do well to consider a "Meta-Problem" of why humor seems so difficult to explain, and why relatively simple explanations may have eluded us for this long. (Please note: RAR was conceived in 2008, and last majorly updated in 2012.)
Edit intent: meaning-changed
Original:  The <i>k-level<i> of {\cal A } consists of all intersection points v of lines in%DIFDELCMD < {\cal %%% A which have exactly k lines of {\cal A } passing below v. The complexity  of the k-level in a line arrangement has been widely studied.
Revised:  The k-level of {\cal A } consists of all intersection points v of lines in%DIFDELCMD < {\cal %%% A which have exactly k lines of {\cal A } passing below v. The complexity of the k-level in a line arrangement has been widely studied.
Edit intent: clarity
Original:  The <i>k-level<i> of {\cal A } consists of all intersection points v of lines in%DIFDELCMD < {\cal %%% A which have exactly k lines of {\cal A } passing below v. The complexity  of the k-level in a line arrangement has been widely studied.
Revised:  The <i>k-level<i> of {\cal L } consists of all intersection points v of lines in%DIFDELCMD < {\cal %%% A which have exactly k lines of {\cal A } passing below v. The complexity of the k-level in a line arrangement has been widely studied.
Edit intent: meaning-changed
Original:  The <i>k-level<i> of {\cal A } consists of all intersection points v of lines in%DIFDELCMD < {\cal %%% A which have exactly k lines of {\cal A } passing below v. The complexity  of the k-level in a line arrangement has been widely studied.
Revised:  The <i>k-level<i> of {\cal A } consists of all %DIFDELCMD < {\cal %%% A which have exactly k lines of {\cal A } passing below v. The complexity of the k-level in a line arrangement has been widely studied.
Edit intent: clarity
Original:  The <i>k-level<i> of {\cal A } consists of all intersection points v of lines in%DIFDELCMD < {\cal %%% A which have exactly k lines of {\cal A } passing below v. The complexity  of the k-level in a line arrangement has been widely studied.
Revised:  The <i>k-level<i> of {\cal A } consists of all intersection points v of lines in%DIFDELCMD < {\cal %%% vertices v of the arrangement which have exactly k lines of {\cal A } passing below v. The complexity of the k-level in a line arrangement has been widely studied.
Edit intent: meaning-changed
Original:  The <i>k-level<i> of {\cal A } consists of all intersection points v of lines in%DIFDELCMD < {\cal %%% A which have exactly k lines of {\cal A } passing below v. The complexity  of the k-level in a line arrangement has been widely studied.
Revised:  The <i>k-level<i> of {\cal A } consists of all intersection points v of lines in%DIFDELCMD < {\cal %%% A which have exactly k lines of {\cal L } passing below v. The complexity of the k-level in a line arrangement has been widely studied.
Edit intent: meaning-changed
Original:  The <i>k-level<i> of {\cal A } consists of all intersection points v of lines in%DIFDELCMD < {\cal %%% A which have exactly k lines of {\cal A } passing below v. The complexity  of the k-level in a line arrangement has been widely studied.
Revised:  The <i>k-level<i> of {\cal A } consists of all intersection points v of lines in%DIFDELCMD < {\cal %%% A which have exactly k lines of {\cal A } passing below v. The complexity (the maximum size) of the k-level in a line arrangement has been widely studied.
Edit intent: meaning-changed
Original:  We investigate the complexity of k-levels in random line and hyperplane arrangements. When the arrangement is obtained from any fixed projective line arrangement of n lines by choosing a random cellto contain the south-pole, we prove an upper bound of O((k+1)^2) on the expected complexity of the k-level .
Revised:  Due to the correspondence between lines in the plane and great-circles on the sphere, the asymptotic bounds carry over to arrangements of great-circles on the sphere, where the k-level denotes the vertices at distance at most k to a marked cell, the prove an upper bound of O((k+1)^2) on the expected complexity of the k-level .
Edit intent: meaning-changed
Original:  When the arrangement is obtained from any fixed projective line arrangement of n lines by choosing a random cellto contain the south-pole, we prove an upper bound of O((k+1)^2) on the expected complexity of the k-level .
Revised:  When the arrangement is obtained from any fixed projective line arrangement of n lines by choosing a random cellto contain the south-pole, wesouth pole prove an upper bound of O((k+1)^2) on the expected complexity of the k-level .
Edit intent: meaning-changed
Original:  When the arrangement is obtained from any fixed projective line arrangement of n lines by choosing a random cellto contain the south-pole, we prove an upper bound of O((k+1)^2) on the expected complexity of the k-level .
Revised:  When the arrangement is obtained from any fixed projective line arrangement of n lines by choosing a random cellto contain the south-pole, we. We prove an upper bound of O((k+1)^2) on the expected complexity of the k-level .
Edit intent: fluency
Original:  When the arrangement is obtained from any fixed projective line arrangement of n lines by choosing a random cellto contain the south-pole, we prove an upper bound of O((k+1)^2) on the expected complexity of the k-level . As a byproduct we show that the complexity of any (\leq j)-zone in a d-dimensional simple arrangement of n hyperplanes is of order \Theta((j+1)n^{d-1 We also consider arrangements of great (d-1)-spheres on the sphere \mathbb{S}^d which are orthogonal to a set of random points on \mathbb{S}^d.
Revised:  When the arrangement is obtained from any fixed projective line arrangement of n lines by choosing a random cellto contain the south-pole, we prove an upper bound of O((k+1)^2) on the expected complexity of the k-level in great-circle arrangements if the south pole is chosen uniformly at random among all cells. We also consider arrangements of great (d-1)-spheres on the sphere \mathbb{S}^d which are orthogonal to a set of random points on \mathbb{S}^d.
Edit intent: meaning-changed