wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We show that, if spike-timing-dependent-plasticity (STDP) is active during sleep, the connections among groups of neurons associated to instances of the same class (digit) are enhanced, and that the internal representation is hierarchical and orthogonalized.
Revised:  If spike-timing-dependent-plasticity (STDP) is active during sleep, the connections among groups of neurons associated to instances of the same class (digit) are enhanced, and that the internal representation is hierarchical and orthogonalized.
Edit intent: coherence
Original:  We show that, if spike-timing-dependent-plasticity (STDP) is active during sleep, the connections among groups of neurons associated to instances of the same class (digit) are enhanced, and that the internal representation is hierarchical and orthogonalized.
Revised:  We show that, if spike-timing-dependent-plasticity (STDP) is active during slow oscillations, a differential homeostatic process is observed. It is characterized by both a specific enhancement of connections among groups of neurons associated to instances of the same class (digit) are enhanced, and that the internal representation is hierarchical and orthogonalized.
Edit intent: meaning-changed
Original:  We show that, if spike-timing-dependent-plasticity (STDP) is active during sleep, the connections among groups of neurons associated to instances of the same class (digit) are enhanced, and that the internal representation is hierarchical and orthogonalized. Such effect might be beneficial to the network to obtain better performances in retrieval and classification tasks and to create hierarchies of categories in integrated representations.
Revised:  We show that, if spike-timing-dependent-plasticity (STDP) is active during sleep, the connections among groups of neurons associated to instances of the same class (digit) and a simultaneous down-regulation of stronger synapses created by the training. This is reflected in a URLanization of post-sleep internal representations. Such effects favour higher performance in retrieval and classification tasks and to create hierarchies of categories in integrated representations.
Edit intent: meaning-changed
Original:  The model leverages on the coincidence of top-down contextual information with bottom-up sensory flow during the training phase and on the integration of top-down predictions and bottom-up  pathways during deep-sleep-like slow oscillations  .
Revised:  The model leverages on the coincidence of top-down contextual information with bottom-up sensory flow during the training phase and on the integration of top-down predictions and bottom-up thalamo-cortical pathways during deep-sleep-like slow oscillations .
Edit intent: meaning-changed
Original:  The model leverages on the coincidence of top-down contextual information with bottom-up sensory flow during the training phase and on the integration of top-down predictions and bottom-up  pathways during deep-sleep-like slow oscillations  .
Revised:  The model leverages on the coincidence of top-down contextual information with bottom-up sensory flow during the training phase and on the integration of top-down predictions and bottom-up pathways during deep-sleep-like slow oscillations . Also, such mechanism hints at possible applications to artificial learning systems .
Edit intent: clarity
Original:  It is characterized by both a specific  enhancement of connections among groups of neurons associated to instances of the same class (digit) and a simultaneous down-regulation of stronger synapses created by the training.
Revised:  It is characterized by both a specific unsupervised enhancement of connections among groups of neurons associated to instances of the same class (digit) and a simultaneous down-regulation of stronger synapses created by the training.
Edit intent: meaning-changed
Original:  The model leverages on the coincidence of top-down contextual information with bottom-up sensory flow during the training phase and on the integration of top-down predictions and bottom-up thalamo-cortical pathways during deep-sleep-like slow oscillations.
Revised:  The model leverages on the interaction between of top-down contextual information with bottom-up sensory flow during the training phase and on the integration of top-down predictions and bottom-up thalamo-cortical pathways during deep-sleep-like slow oscillations.
Edit intent: clarity
Original:  The model leverages on the coincidence of top-down contextual information with bottom-up sensory flow during the training phase and on the integration of top-down predictions and bottom-up thalamo-cortical pathways during deep-sleep-like slow oscillations.
Revised:  The model leverages on the coincidence of top-down cortico-thalamic predictions and bottom-up thalamo-cortical pathways during deep-sleep-like slow oscillations.
Edit intent: clarity
Original:  The model leverages on the coincidence of top-down contextual information with bottom-up sensory flow during the training phase and on the integration of top-down predictions and bottom-up thalamo-cortical pathways during deep-sleep-like slow oscillations.
Revised:  The model leverages on the coincidence of top-down contextual information with bottom-up sensory flow during the training phase and on the integration of top-down predictions and bottom-up thalamo-cortical projections during deep-sleep-like slow oscillations.
Edit intent: clarity
Original:  Such effects favour higher performances in retrieval and classification tasks and create hierarchies of categories in integrated representations. The model leverages on the interaction between of top-down cortico-thalamic predictions and bottom-up thalamo-cortical projections during deep-sleep-like slow oscillations  .
Revised:  Such effects favour higher performances in retrieval and classification tasks . The mechanism is based on the interaction between of top-down cortico-thalamic predictions and bottom-up thalamo-cortical projections during deep-sleep-like slow oscillations .
Edit intent: clarity
Original:  The model leverages on the interaction between of top-down cortico-thalamic predictions and bottom-up thalamo-cortical projections during deep-sleep-like slow oscillations  .
Revised:  The model leverages on the interaction between of top-down cortico-thalamic predictions and bottom-up thalamo-cortical projections during deep-sleep-like slow oscillations . Indeed, when learned patterns are replayed during sleep, cortico-thalamo-cortical connections favour the activation of other neurons coding for similar thalamic inputs, promoting their association .
Edit intent: meaning-changed
Original:  In particular, with latent factors, not only do we establish the conditions on factor estimation for a strong oracle property, which are different from those for smooth factor augmented models, but we also identify semi-strong and weak oracle cases and establish a phase transition that describes the effect of first stage factor estimation as the cross-sectional dimension of panel data increases relative to the time-series dimension.
Revised:  In particular, we establish a phase transition that describes the effect of first stage factor estimation as the cross-sectional dimension of panel data increases relative to the time-series dimension.
Edit intent: coherence
Original:  In this paper, we propose an inference procedure that is robust not only to small probability weights entering the IPW estimator, but also to a wide range of trimming threshold choices. Our inference procedure employs resampling with a novel bias correction technique. Specifically, we show that both the IPW and trimmed IPW estimators can have different (Gaussian or non-Gaussian) limiting distributions, depending on how "close to zero" the probability weights are and on  the trimming threshold .
Revised:  In this paper, we first show that the IPW estimator can have different (Gaussian or non-Gaussian) limiting distributions, depending on how "close to zero" the probability weights are and on the trimming threshold .
Edit intent: clarity
Original:  Specifically, we show that both the IPW and trimmed IPW estimators can have different (Gaussian or non-Gaussian) limiting distributions, depending on how "close to zero" the probability weights are and on  the trimming threshold .
Revised:  Specifically, we show that both the IPW and trimmed IPW estimators can have different (Gaussian or non-Gaussian) asymptotic distributions, depending on how "close to zero" the probability weights are and on the trimming threshold .
Edit intent: meaning-changed
Original:  Specifically, we show that both the IPW and trimmed IPW estimators can have different (Gaussian or non-Gaussian) limiting distributions, depending on how "close to zero" the probability weights are and on  the trimming threshold .
Revised:  Specifically, we show that both the IPW and trimmed IPW estimators can have different (Gaussian or non-Gaussian) limiting distributions, depending on how "close to zero" the probability weights are and on how large the trimming threshold .
Edit intent: clarity
Original:  Specifically, we show that both the IPW and trimmed IPW estimators can have different (Gaussian or non-Gaussian) limiting distributions, depending on how "close to zero" the probability weights are and on  the trimming threshold . Our method provides more robust inference for the target estimand by adapting to these different limiting distributions.
Revised:  Specifically, we show that both the IPW and trimmed IPW estimators can have different (Gaussian or non-Gaussian) limiting distributions, depending on how "close to zero" the probability weights are and on the trimming threshold is. As a remedy, we propose an inference procedure that is robust not only to small probability weights entering the IPW estimator but also to a wide range of trimming threshold choices, by adapting to these different limiting distributions.
Edit intent: clarity
Original:  We demonstrate the finite-sample accuracy of our method in a simulation study, and we illustrate its use by revisiting a dataset from the National Supported Work program.
Revised:  We also propose an easy-to-implement method for choosing the trimming threshold by minimizing an empirical analogue of the asymptotic mean squared error. In addition, we show that our inference procedure remains valid with the use of a data-driven trimming threshold. We illustrate our method by revisiting a dataset from the National Supported Work program.
Edit intent: meaning-changed
Original:  Following the seminal work of Downs (1957)  , we assume that voters are rationally inattentive and can process information about candidates' random policies at a cost proportional to entropy reduction as in Sims (1998) and Sims (2003).
Revised:  Following the seminal works of Downs (1957) , we assume that voters are rationally inattentive and can process information about candidates' random policies at a cost proportional to entropy reduction as in Sims (1998) and Sims (2003).
Edit intent: fluency
Original:  Following the seminal work of Downs (1957)  , we assume that voters are rationally inattentive and can process information about candidates' random policies at a cost proportional to entropy reduction as in Sims (1998) and Sims (2003).
Revised:  Following the seminal work of Downs (1957) and Sims (1998) , we assume that voters are rationally inattentive and can process information about candidates' random policies at a cost proportional to entropy reduction as in Sims (1998) and Sims (2003).
Edit intent: meaning-changed
Original:  Following the seminal work of Downs (1957)  , we assume that voters are rationally inattentive and can process information about candidates' random policies at a cost proportional to entropy reduction as in Sims (1998) and Sims (2003).
Revised:  Following the seminal work of Downs (1957) , we assume that voters are rationally inattentive and can process information about the policies at a cost proportional to entropy reduction as in Sims (1998) and Sims (2003).
Edit intent: clarity
Original:  Following the seminal work of Downs (1957)  , we assume that voters are rationally inattentive and can process information about candidates' random policies at a cost proportional to entropy reduction as in Sims (1998) and Sims (2003). Two salient patterns emerge in equilibrium as we increase the attention cost or garble the news technology : first, arousing and attracting voter' s attention becomes harder;
Revised:  Following the seminal work of Downs (1957) , we assume that voters are rationally inattentive and can process information about candidates' random policies at a cost proportional to entropy reduction . The main finding is an equilibrium phenomenon called attention- and media-driven extremism, namely as we increase the attention cost or garble the news technology : first, arousing and attracting voter' s attention becomes harder;
Edit intent: meaning-changed
Original:  Two salient patterns emerge in equilibrium as we increase the attention cost or garble the news technology : first, arousing and attracting voter' s attention becomes harder; second, doing so leads the varying types of the candidates to adopt extreme and exaggerated policy and issue positions .
Revised:  Two salient patterns emerge in equilibrium as we increase the attention cost or garble the news technology , a truncated set of the equilibria captures voters' attention through enlarging the policy differentials between the varying types of the candidates to adopt extreme and exaggerated policy and issue positions .
Edit intent: meaning-changed
Original:  Through analysis of the trade-off between giving incentives to agents and saving the cost of data processing and analysis , we obtain characterizations of optimal monitoring technologies such as information aggregation, strict MLRP, likelihood ratio-convex performance classification, group evaluation in response to high monitoring costs, and assessing the various task performances according to agents' endogenous tendencies to shirk.
Revised:  Through analysis of the trade-off between giving incentives to agents and saving the monitoring cost , we obtain characterizations of optimal monitoring technologies such as information aggregation, strict MLRP, likelihood ratio-convex performance classification, group evaluation in response to high monitoring costs, and assessing the various task performances according to agents' endogenous tendencies to shirk.
Edit intent: clarity
Original:  Through analysis of the trade-off between giving incentives to agents and saving the cost of data processing and analysis , we obtain characterizations of optimal monitoring technologies such as information aggregation, strict MLRP, likelihood ratio-convex performance classification, group evaluation in response to high monitoring costs, and assessing the various task performances according to agents' endogenous tendencies to shirk.
Revised:  Through analysis of the trade-off between giving incentives to agents and saving the cost of data processing and analysis , we obtain characterizations of optimal monitoring technologies such as information aggregation, strict MLRP, likelihood ratio-convex performance classification, group evaluation in response to rising monitoring costs, and assessing the various task performances according to agents' endogenous tendencies to shirk.
Edit intent: clarity
Original:  Through analysis of the trade-off between giving incentives to agents and saving the cost of data processing and analysis , we obtain characterizations of optimal monitoring technologies such as information aggregation, strict MLRP, likelihood ratio-convex performance classification, group evaluation in response to high monitoring costs, and assessing the various task performances according to agents' endogenous tendencies to shirk.
Revised:  Through analysis of the trade-off between giving incentives to agents and saving the cost of data processing and analysis , we obtain characterizations of optimal monitoring technologies such as information aggregation, strict MLRP, likelihood ratio-convex performance classification, group evaluation in response to high monitoring costs, and assessing multiple task performances according to agents' endogenous tendencies to shirk.
Edit intent: clarity
Original: Many real-world problems such as salesand healthcare regulation involve a principal, multiple intermediaries, and agents with hidden characteristics. In these problems, intermediaries compete through offering menus of multifaceted consumption bundles to agents, whereas the principal is limited to regulating sub-aspects of the sold bundles by legal , informational and administrative barriers.
Revised: We examine problems of "intermediated implementation." An example is sales, whereby retailers compete through offering menus of multifaceted consumption bundles to agents, whereas the principal is limited to regulating sub-aspects of the sold bundles by legal , informational and administrative barriers.
Edit intent: clarity
Original:  In these problems, intermediaries compete through offering menus of multifaceted consumption bundles to agents, whereas the principal is limited to regulating sub-aspects of the sold bundles by legal , informational and administrative barriers.
Revised:  In these problems, intermediaries compete through offering menus of multifaceted consumption bundles to consumers with hidden tastes, whereas a manufacturer with a potentially different goal than retailers' can regulate only the sold goods but not the charged prices by legal barriers.
Edit intent: meaning-changed
Original:  When intermediaries have private values, intermediated implementation can be achieved by a per-unit fee schedule that allows intermediaries to break even under the target social choice rule . When intermediaries have interdependent values, per-unit fee schedules cannot generally be used to achieve implementation, whereas regulating the distribution over sub-aspects can under general conditions about the target allocation .
Revised:  When intermediaries have private values, intermediated implementation can be achieved by a per-unit fee schedule that allows intermediaries to break even under the target social choice rule for consumers. We demonstrate the effectiveness of per-unit fee schedules cannot generally be used to achieve implementation, whereas regulating the distribution over sub-aspects can under general conditions about the target allocation .
Edit intent: meaning-changed
Original:  When intermediaries have interdependent values, per-unit fee schedules cannot generally be used to achieve implementation, whereas regulating the distribution over sub-aspects can under general conditions about the target allocation .
Revised:  When intermediaries have interdependent values, per-unit fee schedules and distribution regulations, which hinges on whether retailers have private or interdependent values. We formulate problems of this kind and give applications to taxation and healthcare .
Edit intent: meaning-changed
Original: We examine problems of "intermediated implementation . "  An example is sales, whereby retailers compete through offering consumption bundles to consumers with hidden tastes, whereas a manufacturer with a potentially different goal than retailers' can regulate only the sold goods but not the charged prices by legal barriers.
Revised: We examine problems of "intermediated implementation , " An example is sales, whereby retailers compete through offering consumption bundles to consumers with hidden tastes, whereas a manufacturer with a potentially different goal than retailers' can regulate only the sold goods but not the charged prices by legal barriers.
Edit intent: fluency
Original: We examine problems of "intermediated implementation . "  An example is sales, whereby retailers compete through offering consumption bundles to consumers with hidden tastes, whereas a manufacturer with a potentially different goal than retailers' can regulate only the sold goods but not the charged prices by legal barriers.
Revised: We examine problems of "intermediated implementation . " in which a single principal can only regulate limited aspects of the consumption bundles traded between intermediaries and agents with hidden characteristics. An example is sales, whereby retailers compete through offering consumption bundles to consumers with hidden tastes, whereas a manufacturer with a potentially different goal than retailers' can regulate only the sold goods but not the charged prices by legal barriers.
Edit intent: meaning-changed
Original: We examine problems of "intermediated implementation . "  An example is sales, whereby retailers compete through offering consumption bundles to consumers with hidden tastes, whereas a manufacturer with a potentially different goal than retailers' can regulate only the sold goods but not the charged prices by legal barriers.
Revised: We examine problems of "intermediated implementation . " An example is sales, whereby retailers compete through offering consumption bundles to customers with hidden tastes, whereas a manufacturer with a potentially different goal than retailers' can regulate only the sold goods but not the charged prices by legal barriers.
Edit intent: clarity
Original: We examine problems of "intermediated implementation . "  An example is sales, whereby retailers compete through offering consumption bundles to consumers with hidden tastes, whereas a manufacturer with a potentially different goal than retailers' can regulate only the sold goods but not the charged prices by legal barriers.
Revised: We examine problems of "intermediated implementation . " An example is sales, whereby retailers compete through offering consumption bundles to consumers with hidden tastes, whereas a manufacturer with a potentially different goal than retailers' is limited to regulating the sold goods but not the charged prices by legal barriers.
Edit intent: clarity
Original:  An example is sales, whereby retailers compete through offering consumption bundles to customers with hidden tastes, whereas a manufacturer with a potentially different goal than retailers' is limited to regulating the sold goods but not the charged prices by legal barriers.
Revised:  An example is sales, in which retailers offer menus of consumption bundles to customers with hidden tastes, whereas a manufacturer with a potentially different goal than retailers' is limited to regulating the sold goods but not the charged prices by legal barriers.
Edit intent: clarity
Original:  An example is sales, whereby retailers compete through offering consumption bundles to customers with hidden tastes, whereas a manufacturer with a potentially different goal than retailers' is limited to regulating the sold goods but not the charged prices by legal barriers.
Revised:  An example is sales, whereby retailers compete through offering consumption bundles to customers with hidden tastes, whereas a manufacturer with a potentially different goal from retailers' is limited to regulating the sold goods but not the charged prices by legal barriers.
Edit intent: fluency
Original:  An example is sales, whereby retailers compete through offering consumption bundles to customers with hidden tastes, whereas a manufacturer with a potentially different goal than retailers' is limited to regulating the sold goods but not the charged prices by legal barriers.
Revised:  An example is sales, whereby retailers compete through offering consumption bundles to customers with hidden tastes, whereas a manufacturer with a potentially different goal than retailers' is limited to regulating sold consumption goods but not the charged prices by legal barriers.
Edit intent: fluency