wanyu/IteraTeR_full_sent huggingface dataset:
Original:  Conversely, conventional image sensors measure absolute intensity of slowly changing scenes effectively but do poorly on quickly changing scenes with high dynamic range . The proposed approach exploits advantages of hybrid sensors under a unifying uncertainty model for both conventional frames and events.
Revised:  Conversely, conventional image sensors measure absolute intensity of slowly changing scenes effectively but do poorly on quickly changing scenes with high dynamic range or quickly changing scenes. In this paper, we present an event-based video reconstruction pipeline for High Dynamic Range (HDR) scenarios. The proposed algorithm includes a frame augmentation pre-processing step that deblurs and temporally interpolates frame data using events. The augmented frame and event data are then fused using a novel asynchronous Kalman filter under a unifying uncertainty model for both conventional frames and events.
Edit intent: meaning-changed
Original:  The proposed approach exploits advantages of hybrid sensors under a unifying uncertainty model for both conventional frames and events. We present a novel dataset targeting challenging HDR and fast motion scenes captured on two separate sensors: an RGB frame-based camera and an event camera. Our video reconstruction outperforms the state-of-the-art algorithms on existing datasets and our targeted HDR dataset .
Revised:  The proposed approach exploits advantages of hybrid sensors under a unifying uncertainty model for both sensors. Our experimental results are evaluated on both publicly available datasets with challenging lighting conditions and fast motions and our new dataset with HDR reference. The proposed algorithm outperforms state-of-the-art algorithms on existing datasets and our targeted HDR dataset .
Edit intent: meaning-changed
Original:  English GPT-2 models with relearned lexical embeddings can generate realistic sentences in Italian and Dutch , but on average these sentences are still identifiable as artificial by humans . Based on perplexity scores and human judgements, we find that generated sentences become more realistic with some additional full model finetuning, especially for Dutch.
Revised:  English GPT-2 models with relearned lexical embeddings can generate realistic sentences in Italian and Dutch . Though on average these sentences are still identifiable as artificial by humans . Based on perplexity scores and human judgements, we find that generated sentences become more realistic with some additional full model finetuning, especially for Dutch.
Edit intent: coherence
Original:  English GPT-2 models with relearned lexical embeddings can generate realistic sentences in Italian and Dutch , but on average these sentences are still identifiable as artificial by humans . Based on perplexity scores and human judgements, we find that generated sentences become more realistic with some additional full model finetuning, especially for Dutch. For Italian, we see that they are evaluated on par with sentences generated by a GPT-2 model fully trained from scratch .
Revised:  English GPT-2 models with relearned lexical embeddings can generate realistic sentences in Italian and Dutch , but on average these sentences are still identifiable as artificial by humans , they are assessed on par with sentences generated by a GPT-2 model fully trained from scratch .
Edit intent: clarity
Original:  We propose that this memory B cell selection process may be a heuristic solution to two expected risk optimization problems: optimizing for affinity to similar antigens in the future despite mutations or other minor differences, and optimizing to warm-start future plasma B cell training .
Revised:  We propose that this memory B cell selection process may be a heuristic solution to two expected risk optimization problems: optimizing for affinity to similar antigens in the future despite mutations or other minor differences, and optimizing to warm start the generation of plasma B cells in the future .
Edit intent: clarity
Original:  We use simulations to provide evidence for our hypotheses, taking into account data showing that certain B cell mutations are more likely than others  .
Revised:  We use simulations to provide evidence for our hypotheses, taking into account data showing that certain B cell mutations are more likely than others . Our findings are consistent with memory B cells having high-affinity to mutated antigens, but do not provide strong evidence that memory B cells will be more useful than selected naive B cells for seeding the secondary germinal centers .
Edit intent: meaning-changed
Original:  We propose that this memory B cell selection process may be a heuristic solution to two expected risk optimization problems: optimizing for affinity to similar antigens in the future despite mutations or other minor differences, and optimizing to warm start the generation of plasma B cells in the future.
Revised:  We propose that this memory B cell selection process may be an approximate solution to two expected risk optimization problems: optimizing for affinity to similar antigens in the future despite mutations or other minor differences, and optimizing to warm start the generation of plasma B cells in the future.
Edit intent: clarity
Original:  We propose that this memory B cell selection process may be a heuristic solution to two expected risk optimization problems: optimizing for affinity to similar antigens in the future despite mutations or other minor differences, and optimizing to warm start the generation of plasma B cells in the future.
Revised:  We propose that this memory B cell selection process may be a heuristic solution to two optimization problems: optimizing for affinity to similar antigens in the future despite mutations or other minor differences, and optimizing to warm start the generation of plasma B cells in the future.
Edit intent: clarity
Original:  In this work, we investigate whether we can apply analysis-by-synthesis with NeRF for 6DoF pose estimation - given an image, find the translation and rotation of a camera relative to a 3D model.
Revised:  In this work, we investigate whether we can apply analysis-by-synthesis via NeRF for mesh-free, RGB-only 6DoF pose estimation - given an image, find the translation and rotation of a camera relative to a 3D model.
Edit intent: meaning-changed
Original:  In this work, we investigate whether we can apply analysis-by-synthesis with NeRF for 6DoF pose estimation - given an image, find the translation and rotation of a camera relative to a 3D model.
Revised:  In this work, we investigate whether we can apply analysis-by-synthesis with NeRF for 6DoF pose estimation - given an image, find the translation and rotation of a camera relative to a 3D object or scene. Our method assumes that no object mesh models are available during either training or test time.
Edit intent: meaning-changed
Original:  A few modes in the semi-infinite subdomain are found to suffice to deal with outgoing single wave and wave train signals  , thus providing an appealing model for fluid flow simulations in unbounded regions.
Revised:  A few modes in the semi-infinite subdomain are found to suffice to deal with outgoing single wave and wave train signals more accurately than standard approaches at a given computational cost , thus providing an appealing model for fluid flow simulations in unbounded regions.
Edit intent: meaning-changed
Original:  The new method combines functional tensor train (FTT) series expansions, operator splitting time integration, and a new rank-adaptive algorithm based on a thresholding criterion that limits the component of the PDE velocity vector normal to the FTT tensor manifold.
Revised:  The method combines functional tensor train (FTT) series expansions, operator splitting time integration, and a new rank-adaptive algorithm based on a thresholding criterion that limits the component of the PDE velocity vector normal to the FTT tensor manifold.
Edit intent: coherence
Original:  However, some five-year outcomes, such as glycosylated hemoglobin (A1C) , are over 40%DIFDELCMD < \\%%% %DIF < missing data.
Revised:  However, as usual in longitudinal medical studies, there is a significant amount of missing data in the outcome variables. For example, 40 percent of glycosylated hemoglobin (A1C) , are over 40%DIFDELCMD < \\%%% %DIF < missing data.
Edit intent: clarity
Original:  and iii) to improve and optimize clinical interventions based on expected glucose changes according to patients' baseline characteristics.abstract 
Revised:  and iii) to improve and optimize clinical interventions based on expected glucose changes according to patients' baseline characteristics.abstract biomarker data are missing five years ahead. With the purpose to reduce the impact of this issue, this article proposes a new data analysis framework based on learning in reproducing kernel Hilbert spaces (RKHS) with missing responses that allows to capture non-linear relations between variable studies in different supervised modeling tasks. First, we extend the Hilbert-Schmidt dependence measure to test statistical independence in this context introducing a new bootstrap procedure, for which we prove consistency. Next, we adapt or use existing models of variable selection, regression, and conformal inference to obtain new clinical findings about glucose changes five years ahead with the AEGIS data. The most relevant findings are summarized below: i) We identify new factors associated with long-term glucose evolution; ii) We show the clinical sensibility of CGM data to detect changes in glucose metabolism; iii) We can improve clinical interventions based on our algorithms' expected glucose changes according to patients' baseline characteristics.
Edit intent: meaning-changed
Original:  By not being tied to any real data, random graph models are inadequate in many practical contexts , including areas of research, such as computational epidemiology, which are recently high on the agenda.
Revised:  By not being tied to any real data, random graph models cannot capture all the subtleties of real networks and are inadequate for many practical contexts , including areas of research, such as computational epidemiology, which are recently high on the agenda.
Edit intent: meaning-changed
Original:  The factors governing the structure of the obtained network, such as the dependency of friendship upon distance and age composition , are thoroughly studied through extensive simulations focused on three Italian cities of different size.
Revised:  While household links are entirely data-driven, we propose a parametric probabilistic model for friendship, based on the assumption that distances and age differences play a role, and that not all individuals are equally sociable. The demographic and geographic factors governing the structure of the obtained network, such as the dependency of friendship upon distance and age composition , are thoroughly studied through extensive simulations focused on three Italian cities of different size.
Edit intent: meaning-changed
Original:  As the main benefit of this new approach  , stochastic gradient descent type algorithms can be applied in the training of the committor function without the need of computing any  second-order derivatives  . Numerical results are provided to demonstrate the performance of the proposed method.
Revised:  There are two major benefits of this new approach , stochastic gradient descent type algorithms can be applied in the training of the committor function without the need of computing any second-order derivatives . Numerical results are provided to demonstrate the performance of the proposed method.
Edit intent: meaning-changed
Original:  As the main benefit of this new approach  , stochastic gradient descent type algorithms can be applied in the training of the committor function without the need of computing any  second-order derivatives  . Numerical results are provided to demonstrate the performance of the proposed method.
Revised:  As the main benefit of this new approach . First , stochastic gradient descent type algorithms can be applied in the training of the committor function without the need of computing any second-order derivatives . Numerical results are provided to demonstrate the performance of the proposed method.
Edit intent: coherence
Original:  As the main benefit of this new approach  , stochastic gradient descent type algorithms can be applied in the training of the committor function without the need of computing any  second-order derivatives  . Numerical results are provided to demonstrate the performance of the proposed method.
Revised:  As the main benefit of this new approach , stochastic gradient descent type algorithms can be applied in the training of the committor function without the need of computing any mixed second-order derivatives . Numerical results are provided to demonstrate the performance of the proposed method.
Edit intent: meaning-changed
Original:  As the main benefit of this new approach  , stochastic gradient descent type algorithms can be applied in the training of the committor function without the need of computing any  second-order derivatives  . Numerical results are provided to demonstrate the performance of the proposed method.
Revised:  As the main benefit of this new approach , stochastic gradient descent type algorithms can be applied in the training of the committor function without the need of computing any second-order derivatives . Moreover, unlike the previous methods that enforce the boundary conditions through penalty terms, the new method takes into account the boundary conditions automatically . Numerical results are provided to demonstrate the performance of the proposed method.
Edit intent: meaning-changed
Original: Noninvasive brain-computer interface (BCI) decodes brain signals to understand user intention . Especially, decoding of sensation imagery based on brain signals could provide various industries such as developing advanced touch displays  and more immersive virtual reality and augmented reality.
Revised: Noninvasive brain-computer interface (BCI) is widely used to recognize users' intentions . Especially, decoding of sensation imagery based on brain signals could provide various industries such as developing advanced touch displays and more immersive virtual reality and augmented reality.
Edit intent: meaning-changed
Original: Noninvasive brain-computer interface (BCI) decodes brain signals to understand user intention . Especially, decoding of sensation imagery based on brain signals could provide various industries such as developing advanced touch displays  and more immersive virtual reality and augmented reality.
Revised: Noninvasive brain-computer interface (BCI) decodes brain signals to understand user intention . Especially, BCI related to tactile and sensation decoding could provide various industries such as developing advanced touch displays and more immersive virtual reality and augmented reality.
Edit intent: clarity
Original: Noninvasive brain-computer interface (BCI) decodes brain signals to understand user intention . Especially, decoding of sensation imagery based on brain signals could provide various industries such as developing advanced touch displays  and more immersive virtual reality and augmented reality.
Revised: Noninvasive brain-computer interface (BCI) decodes brain signals to understand user intention . Especially, decoding of sensation imagery based on brain signals could provide various effects on many industrial fields such as manufacturing advanced touch displays and more immersive virtual reality and augmented reality.
Edit intent: clarity
Original: Noninvasive brain-computer interface (BCI) decodes brain signals to understand user intention . Especially, decoding of sensation imagery based on brain signals could provide various industries such as developing advanced touch displays  and more immersive virtual reality and augmented reality.
Revised: Noninvasive brain-computer interface (BCI) decodes brain signals to understand user intention . Especially, decoding of sensation imagery based on brain signals could provide various industries such as developing advanced touch displays , controlling robotic devices, and more immersive virtual reality and augmented reality.
Edit intent: clarity
Original: Noninvasive brain-computer interface (BCI) decodes brain signals to understand user intention . Especially, decoding of sensation imagery based on brain signals could provide various industries such as developing advanced touch displays  and more immersive virtual reality and augmented reality.
Revised: Noninvasive brain-computer interface (BCI) decodes brain signals to understand user intention . Especially, decoding of sensation imagery based on brain signals could provide various industries such as developing advanced touch displays and more immersive virtual reality or augmented reality.
Edit intent: fluency
Original:  This paperintroduces a preliminary study to develop a neurohaptic-based BCI system for a variety of scenarios using actual touch and touch imagery paradigms.
Revised:  In this paper, we introduce haptic and sensory perception-based BCI systems called neurohaptics. It is a preliminary study to develop a neurohaptic-based BCI system for a variety of scenarios using actual touch and touch imagery paradigms.
Edit intent: meaning-changed
Original:  This work is strongly motivated by emerging applications in flow level performance of wireless networks that give rise in queueing models with scalable service capacity, such as the discrete-time processor sharing queue with limited state dependency, as well as in queue-based random access protocols, where the network's parameters are functions of the queue lengths.
Revised:  This work is strongly motivated by emerging applications in flow level performance of wireless networks that give rise in queueing models with scalable service capacity, as well as in queue-based random access protocols, where the network's parameters are functions of the queue lengths.
Edit intent: coherence
Original: We perform time-dependent extended Tsallis statistics analysis on stock market indices  . Specifically, we evaluate the q-triplet for particular time periods of the market with the purpose of demonstrating the temporal dependence of the extended characteristics of the underlying market dynamics.
Revised: We perform non-linear analysis on stock market indices . Specifically, we evaluate the q-triplet for particular time periods of the market with the purpose of demonstrating the temporal dependence of the extended characteristics of the underlying market dynamics.
Edit intent: clarity
Original: We perform time-dependent extended Tsallis statistics analysis on stock market indices  . Specifically, we evaluate the q-triplet for particular time periods of the market with the purpose of demonstrating the temporal dependence of the extended characteristics of the underlying market dynamics.
Revised: We perform time-dependent extended Tsallis statistics analysis on stock market indices using time-dependent extended Tsallis statistics . Specifically, we evaluate the q-triplet for particular time periods of the market with the purpose of demonstrating the temporal dependence of the extended characteristics of the underlying market dynamics.
Edit intent: meaning-changed
Original: We perform time-dependent extended Tsallis statistics analysis on stock market indices  . Specifically, we evaluate the q-triplet for particular time periods of the market with the purpose of demonstrating the temporal dependence of the extended characteristics of the underlying market dynamics.
Revised: We perform time-dependent extended Tsallis statistics analysis on stock market indices . Specifically, we evaluate the q-triplet for particular time periods with the purpose of demonstrating the temporal dependence of the extended characteristics of the underlying market dynamics.
Edit intent: clarity
Original:  For comparison, we  compute time-dependent Generalized Hurst Exponents (GHE) Hq using the GHE method, thus estimating the temporal evolution of the multiscaling characteristics of the index dynamics.
Revised:  For comparison, we also compute time-dependent Generalized Hurst Exponents (GHE) Hq using the GHE method, thus estimating the temporal evolution of the multiscaling characteristics of the index dynamics.
Edit intent: coherence
Original:  and find that the  q-triplet values significantly differ among these periods indicating that in the rising period before a bubble break, the underlying extended statistics of the market dynamics strongly deviates from purely stochastic behavior, whereas, after the breakdown, it gradually converges to the Gaussian-like behavior which is a characteristic of an efficient market.
Revised:  and find that the temporal trends of q-triplet values significantly differ among these periods indicating that in the rising period before a bubble break, the underlying extended statistics of the market dynamics strongly deviates from purely stochastic behavior, whereas, after the breakdown, it gradually converges to the Gaussian-like behavior which is a characteristic of an efficient market.
Edit intent: clarity
Original:   Differences between endogenous and exogenous stock market crises are also captured by the temporal changes in the Tsallis q-triplet.
Revised:  We also conclude that relative temporal variation patterns of the Tsallis q-triplet can be connected to different aspects of market dynamics and reveals useful information about market conditions especially those underlying the development of a stock market bubble. We found specific temporal patterns and trends in the relative variation of the indices in the q-triplet that distinguish periods just before and just after a stock-market bubble break. Differences between endogenous and exogenous stock market crises are also captured by the temporal changes in the Tsallis q-triplet.
Edit intent: meaning-changed
Original:  We also introduce two new time-dependent empirical metrics (Q-metrics) that are functions of the Tsallis q-triplet . We apply them to the above stock market index price timeseries and discuss the significance of their temporal dependence on market dynamics and the possibility of using them, together with the temporal changes in the q-triplet, as signaling tools for future market events such as the development of a market bubble .
Revised:  We also introduce two new time-dependent empirical metrics (Q-metrics) that are functions of the Tsallis q-triplet .
Edit intent: coherence
Original:  However, as cells are added, removed, reordered, and rerun, this hidden intermediate state accumulates in a way that is not necessarily correlated with the code visible in the notebook's cells , making execution behavior difficult to reason about, and leading to errors and lack of reproducibility.
Revised:  However, as cells are added, removed, reordered, and rerun, this hidden intermediate state accumulates in a way that is not necessarily correlated with the notebook's cells , making execution behavior difficult to reason about, and leading to errors and lack of reproducibility.
Edit intent: clarity
Original:  However, as cells are added, removed, reordered, and rerun, this hidden intermediate state accumulates in a way that is not necessarily correlated with the code visible in the notebook's cells , making execution behavior difficult to reason about, and leading to errors and lack of reproducibility.
Revised:  However, as cells are added, removed, reordered, and rerun, this hidden intermediate state accumulates in a way that is not necessarily correlated with the code visible in the notebook's visible code , making execution behavior difficult to reason about, and leading to errors and lack of reproducibility.
Edit intent: clarity