wanyu/IteraTeR_full_sent huggingface dataset:
Original:  The recent image leaks from popular OSN services and the abuse of personal photos using advanced algorithms (e.g. DeepFake) have prompted the public to rethink individual privacy needs when sharingimages on OSNs . However, OSN image sharing itself is relatively complicated, and systems currently in place to manage privacy in practice are labor-intensive yet fail to provide personalized, accurate and flexible privacy protection.
Revised:  The recent image leaks from popular OSN services and the abuse of personal photos using advanced algorithms (e.g. DeepFake) have prompted the public to rethink individual privacy needs in OSN image sharing . However, OSN image sharing itself is relatively complicated, and systems currently in place to manage privacy in practice are labor-intensive yet fail to provide personalized, accurate and flexible privacy protection.
Edit intent: clarity
Original:  The recent image leaks from popular OSN services and the abuse of personal photos using advanced algorithms (e.g. DeepFake) have prompted the public to rethink individual privacy needs when sharingimages on OSNs . However, OSN image sharing itself is relatively complicated, and systems currently in place to manage privacy in practice are labor-intensive yet fail to provide personalized, accurate and flexible privacy protection.
Revised:  The recent image leaks from popular OSN services and the abuse of personal photos using advanced algorithms (e.g. DeepFake) have prompted the public to rethink individual privacy needs when sharingimages on OSNs . However, OSN image privacy itself is quite complicated, and systems currently in place to manage privacy in practice are labor-intensive yet fail to provide personalized, accurate and flexible privacy protection.
Edit intent: clarity
Original:  The recent image leaks from popular OSN services and the abuse of personal photos using advanced algorithms (e.g. DeepFake) have prompted the public to rethink individual privacy needs when sharingimages on OSNs . However, OSN image sharing itself is relatively complicated, and systems currently in place to manage privacy in practice are labor-intensive yet fail to provide personalized, accurate and flexible privacy protection.
Revised:  The recent image leaks from popular OSN services and the abuse of personal photos using advanced algorithms (e.g. DeepFake) have prompted the public to rethink individual privacy needs when sharingimages on OSNs . However, OSN image sharing itself is relatively complicated, and solutions currently in place to manage privacy in practice are labor-intensive yet fail to provide personalized, accurate and flexible privacy protection.
Edit intent: clarity
Original:  The recent image leaks from popular OSN services and the abuse of personal photos using advanced algorithms (e.g. DeepFake) have prompted the public to rethink individual privacy needs when sharingimages on OSNs . However, OSN image sharing itself is relatively complicated, and systems currently in place to manage privacy in practice are labor-intensive yet fail to provide personalized, accurate and flexible privacy protection.
Revised:  The recent image leaks from popular OSN services and the abuse of personal photos using advanced algorithms (e.g. DeepFake) have prompted the public to rethink individual privacy needs when sharingimages on OSNs . However, OSN image sharing itself is relatively complicated, and systems currently in place for privacy management in reality are insufficient to provide personalized, accurate and flexible privacy protection.
Edit intent: clarity
Original:  To fill the gap, we contribute a systematic survey of 'privacy intelligence' solutions that target modern privacy issues related to OSN image sharing  . Specifically, we present a  high-level  analysis framework based on the entire lifecycle of OSN image sharing to address the various privacy issues and solutions facing this interdisciplinary field .
Revised:  To fill the gap, we contribute a survey of "privacy intelligence" that targets modern privacy issues related to OSN image sharing . Specifically, we present a high-level analysis framework based on the entire lifecycle of OSN image sharing to address the various privacy issues and solutions facing this interdisciplinary field .
Edit intent: clarity
Original:  To fill the gap, we contribute a systematic survey of 'privacy intelligence' solutions that target modern privacy issues related to OSN image sharing  . Specifically, we present a  high-level  analysis framework based on the entire lifecycle of OSN image sharing to address the various privacy issues and solutions facing this interdisciplinary field .
Revised:  To fill the gap, we contribute a systematic survey of 'privacy intelligence' solutions that target modern privacy issues in dynamic OSN image sharing . Specifically, we present a high-level analysis framework based on the entire lifecycle of OSN image sharing to address the various privacy issues and solutions facing this interdisciplinary field .
Edit intent: meaning-changed
Original:  To fill the gap, we contribute a systematic survey of 'privacy intelligence' solutions that target modern privacy issues related to OSN image sharing  . Specifically, we present a  high-level  analysis framework based on the entire lifecycle of OSN image sharing to address the various privacy issues and solutions facing this interdisciplinary field .
Revised:  To fill the gap, we contribute a systematic survey of 'privacy intelligence' solutions that target modern privacy issues related to OSN image sharing from a user-centric perspective . Specifically, we present a high-level analysis framework based on the entire lifecycle of OSN image sharing to address the various privacy issues and solutions facing this interdisciplinary field .
Edit intent: meaning-changed
Original:  To fill the gap, we contribute a systematic survey of 'privacy intelligence' solutions that target modern privacy issues related to OSN image sharing  . Specifically, we present a  high-level  analysis framework based on the entire lifecycle of OSN image sharing to address the various privacy issues and solutions facing this interdisciplinary field .
Revised:  To fill the gap, we contribute a systematic survey of 'privacy intelligence' solutions that target modern privacy issues related to OSN image sharing . Specifically, we present a definition and a taxonomy of OSN image privacy, and a high-level analysis framework based on the entire lifecycle of OSN image sharing to address the various privacy issues and solutions facing this interdisciplinary field .
Edit intent: meaning-changed
Original:  To fill the gap, we contribute a systematic survey of 'privacy intelligence' solutions that target modern privacy issues related to OSN image sharing  . Specifically, we present a  high-level  analysis framework based on the entire lifecycle of OSN image sharing to address the various privacy issues and solutions facing this interdisciplinary field .
Revised:  To fill the gap, we contribute a systematic survey of 'privacy intelligence' solutions that target modern privacy issues related to OSN image sharing . Specifically, we present a high-level privacy analysis framework based on the entire lifecycle of OSN image sharing to address the various privacy issues and solutions facing this interdisciplinary field .
Edit intent: fluency
Original:  To fill the gap, we contribute a systematic survey of 'privacy intelligence' solutions that target modern privacy issues related to OSN image sharing  . Specifically, we present a  high-level  analysis framework based on the entire lifecycle of OSN image sharing to address the various privacy issues and solutions facing this interdisciplinary field .
Revised:  To fill the gap, we contribute a systematic survey of 'privacy intelligence' solutions that target modern privacy issues related to OSN image sharing . Specifically, we present a high-level analysis framework based on the lifecycle of OSN image sharing to address the various privacy issues and solutions facing this interdisciplinary field .
Edit intent: clarity
Original:  To fill the gap, we contribute a systematic survey of 'privacy intelligence' solutions that target modern privacy issues related to OSN image sharing  . Specifically, we present a  high-level  analysis framework based on the entire lifecycle of OSN image sharing to address the various privacy issues and solutions facing this interdisciplinary field .
Revised:  To fill the gap, we contribute a systematic survey of 'privacy intelligence' solutions that target modern privacy issues related to OSN image sharing . Specifically, we present a high-level analysis framework based on the entire lifecycle of OSN image sharing .
Edit intent: coherence
Original:  We argue that  solution of RATs can be interpreted as a first passage search problem on a free association network and study a variety of different search algorithms. We demonstate that in easy RATs (those solved by more than 64 \% subjects in 15 seconds) there are strong links directly connecting stimuli and response, and thus an efficient strategy consist in activating these direct links.
Revised:  We argue that solution of RATs can be interpreted as a first passage search problem on a network whose vertices are words and links are associations between words. We propose different heuristic search algorithms and demonstrate that in "easily-solving" RATs (those solved by more than 64 \% subjects in 15 seconds) there are strong links directly connecting stimuli and response, and thus an efficient strategy consist in activating these direct links.
Edit intent: meaning-changed
Original:  We demonstate that in easy RATs (those solved by more than 64 \% subjects in 15 seconds) there are strong links directly connecting stimuli and response, and thus an efficient strategy consist in activating these direct links.
Revised:  We demonstate that in easy RATs (those that are solved in 15 seconds by more than 64 \% subjects in 15 seconds) there are strong links directly connecting stimuli and response, and thus an efficient strategy consist in activating these direct links.
Edit intent: clarity
Original:  We demonstate that in easy RATs (those solved by more than 64 \% subjects in 15 seconds) there are strong links directly connecting stimuli and response, and thus an efficient strategy consist in activating these direct links. In turn, the most efficient mechanism of solving medium and hard RATs consists of preferentially following what we call "moderately weak" associations.
Revised:  We demonstate that in easy RATs (those solved by more than 64 
Edit intent: clarity
Original:  By analysing millions of anonymous mobile phone users' visit trajectories to various places  , the daily and weekly dynamic origin-to-destination (O-D) population flows are computed, aggregated, and inferred at three geographic scales: census tract, county, and state.
Revised:  By analyzing millions of anonymous mobile phone users' visit trajectories to various places , the daily and weekly dynamic origin-to-destination (O-D) population flows are computed, aggregated, and inferred at three geographic scales: census tract, county, and state.
Edit intent: clarity
Original:  By analysing millions of anonymous mobile phone users' visit trajectories to various places  , the daily and weekly dynamic origin-to-destination (O-D) population flows are computed, aggregated, and inferred at three geographic scales: census tract, county, and state.
Revised:  By analysing millions of anonymous mobile phone users' visits to various places , the daily and weekly dynamic origin-to-destination (O-D) population flows are computed, aggregated, and inferred at three geographic scales: census tract, county, and state.
Edit intent: clarity
Original:  By analysing millions of anonymous mobile phone users' visit trajectories to various places  , the daily and weekly dynamic origin-to-destination (O-D) population flows are computed, aggregated, and inferred at three geographic scales: census tract, county, and state.
Revised:  By analysing millions of anonymous mobile phone users' visit trajectories to various places provided by SafeGraph , the daily and weekly dynamic origin-to-destination (O-D) population flows are computed, aggregated, and inferred at three geographic scales: census tract, county, and state.
Edit intent: meaning-changed
Original:  We propose a scalable approach to adapt confusion sets by exploiting hierarchical character embeddings to (1) obviate the need to handcraft confusion sets, and (2) resolve sparsity issues related to seldom-occurring errors.
Revised:  We propose a scalable adaptable filter that exploits hierarchical character embeddings to (1) obviate the need to handcraft confusion sets, and (2) resolve sparsity issues related to seldom-occurring errors.
Edit intent: clarity
Original:  We propose a scalable approach to adapt confusion sets by exploiting hierarchical character embeddings to (1) obviate the need to handcraft confusion sets, and (2) resolve sparsity issues related to seldom-occurring errors.
Revised:  We propose a scalable approach to adapt confusion sets by exploiting hierarchical character embeddings to (1) obviate the need to handcraft confusion sets, and (2) resolve sparsity problems related to infrequent errors.
Edit intent: clarity
Original:  Using Data Science and Machine Learning techniques, we analyse two distinct data sets: job advertisements (ads) data comprising 3,698 journalist job ads from a corpus of over 6.7 million Australian job ads;
Revised:  Using Data Science and Machine Learning techniques, we analyse two distinct data sets: job advertisements (ads) data comprising 3,698 journalist job ads from a corpus of over 8 million Australian job ads;
Edit intent: meaning-changed
Original:  We can also tease out more granular findings, including: that there are now more women than men journalists in Australia, but that gender inequity is worsening, with women journalists getting younger and worse-paid just as men journalists are, on average, getting older and better-paid;
Revised:  We then tease out more granular findings, including: that there are now more women than men journalists in Australia, but that gender inequity is worsening, with women journalists getting younger and worse-paid just as men journalists are, on average, getting older and better-paid;
Edit intent: clarity
Original: Recently, the predicate detection problem was shown to be in the parallel complexity class NC . In this paper, we give the first work-optimal parallel algorithm to solve the predicate detection problem on a distributed computation with n processes and at most m states per process.
Revised: Recently, the predicate detection problem was shown to be in the parallel complexity class NC . In this paper, we give the first work-optimal parallel algorithm to solve the predicate detection problem on a distributed computation with n processes and at most m states per process.
Edit intent: fluency
Original:  Furthermore, our algorithms improve upon the space complexity of ParallelCut . Both of our algorithms have space complexity O(mn^2) whereas ParallelCut has space complexity O(m^2n^2).
Revised:  Furthermore, our algorithms improve upon the space complexity of ParallelCut . Both of our algorithms have space complexity O(mn^2) whereas ParallelCut has space complexity O(m^2n^2).
Edit intent: fluency
Original:  We argue that regression tree models are ideally suited for macroeconomic nowcasting in the face of the extreme observations produced by the pandemic due to their flexibility and ability to model outliers.
Revised:  We argue that regression tree models are ideally suited for macroeconomic nowcasting in the face of the extreme observations produced by the COVID-19 pandemic of 2020. This is due to their flexibility and ability to model outliers.
Edit intent: meaning-changed
Original:  In a nowcasting application involving four major countries in the European Union , we find substantial improvements in nowcasting performance relative to a linear mixed frequency VAR . A detailed examination of the predictive densities in the first six months of 2020 shows where these improvements are achieved .
Revised:  In an application involving four major countries in the European Union , we find substantial improvements in nowcasting performance relative to a linear mixed frequency VAR . A detailed examination of the predictive densities in the first six months of 2020 shows where these improvements are achieved .
Edit intent: clarity
Original:  In a nowcasting application involving four major countries in the European Union , we find substantial improvements in nowcasting performance relative to a linear mixed frequency VAR . A detailed examination of the predictive densities in the first six months of 2020 shows where these improvements are achieved .
Revised:  In a nowcasting application involving four major euro area countries , we find substantial improvements in nowcasting performance relative to a linear mixed frequency VAR . A detailed examination of the predictive densities in the first six months of 2020 shows where these improvements are achieved .
Edit intent: clarity
Original:  In a nowcasting application involving four major countries in the European Union , we find substantial improvements in nowcasting performance relative to a linear mixed frequency VAR . A detailed examination of the predictive densities in the first six months of 2020 shows where these improvements are achieved .
Revised:  In a nowcasting application involving four major countries in the European Union , we find substantial improvements in nowcasting performance relative to a linear mixed frequency VAR .
Edit intent: coherence
Original: Model-based reinforcement learning approaches add explicit domain knowledge to agents in hopes of improving the sample-efficiency in comparison to model-free agents . However, in practice model-based methods are unable to achieve the same asymptotic performance on challenging continuous control tasks due to the complexity of learning and controlling an explicit world model .
Revised: Model-based reinforcement learning approaches add explicit domain knowledge to agents in hopes of improving the sample-efficiency in comparison to model-free agents in terms of final reward, especially in non-trivial environments. In response, researchers have proposed model-based methods are unable to achieve the same asymptotic performance on challenging continuous control tasks due to the complexity of learning and controlling an explicit world model .
Edit intent: meaning-changed
Original:  However, in practice model-based methods are unable to achieve the same asymptotic performance on challenging continuous control tasks due to the complexity of learning and controlling an explicit world model . In this paper we investigate the stochastic value gradient (SVG), which is a well-known family of methods for controlling continuous systems which includes model-based approaches that distill a model-based value expansion into a model-free policy.
Revised:  However, in practice model-based agents with increasingly complex components, from ensembles of probabilistic dynamics models, to heuristics for mitigating model error. In a reversal of this trend, we show that simple model-based approaches that distill a model-based value expansion into a model-free policy.
Edit intent: meaning-changed
Original:  In this paper we investigate the stochastic value gradient (SVG), which is a well-known family of methods for controlling continuous systems which includes model-based approaches that distill a model-based value expansion into a model-free policy.
Revised:  In this paper we investigate the stochastic value gradient (SVG), which is a well-known family of methods for controlling continuous systems which includes model-based agents can be derived from existing ideas that not only match, but outperform state-of-the-art model-free policy.
Edit intent: meaning-changed
Original:  In this paper we investigate the stochastic value gradient (SVG), which is a well-known family of methods for controlling continuous systems which includes model-based approaches that distill a model-based value expansion into a model-free policy. We consider a variant of the model-based SVG that scales to larger systems and uses 1) an entropy regularization to help with exploration, 2) a learned deterministic world model to improve the short-horizon value estimate, and 3) a learned model-free value estimate after the model's rollout.
Revised:  In this paper we investigate the stochastic value gradient (SVG), which is a well-known family of methods for controlling continuous systems which includes model-based approaches that distill a model-based value expansion into a model-free agents in terms of both sample-efficiency and final reward. We find that a model-free value estimate after the model's rollout.
Edit intent: meaning-changed
Original:  We consider a variant of the model-based SVG that scales to larger systems and uses 1) an entropy regularization to help with exploration, 2) a learned deterministic world model to improve the short-horizon value estimate, and 3) a learned model-free value estimate after the model's rollout. This SVG variation captures the model-free soft actor-critic method as an instance when the model rollout horizon is zero, and otherwise uses short-horizon model rollouts to improve the value estimate for the policy update.
Revised:  We consider a variant of the model-based SVG that scales to larger systems and uses 1) an entropy regularization to help with exploration, 2) a learned deterministic world model to improve the short-horizon value estimate, and 3) a learned model-free soft value estimate for the policy update.
Edit intent: meaning-changed
Original:  This SVG variation captures the model-free soft actor-critic method as an instance when the model rollout horizon is zero, and otherwise uses short-horizon model rollouts to improve the value estimate for the policy update. We surpass the asymptotic performance of other model-based methods on the proprioceptive MuJoCo locomotion tasks from the OpenAI gym, including a humanoid.
Revised:  This SVG variation captures the model-free soft actor-critic method as an instance when the model rollout horizon is zero, and otherwise uses short-horizon model rollouts to improve the value estimate for policy evaluation and a model-based methods on the proprioceptive MuJoCo locomotion tasks from the OpenAI gym, including a humanoid.
Edit intent: clarity
Original:  We surpass the asymptotic performance of other model-based methods on the proprioceptive MuJoCo locomotion tasks from the OpenAI gym, including a humanoid. We notably achieve these results with a simple deterministic world model without requiring an ensemble .
Revised:  We surpass the asymptotic performance of other model-based stochastic value gradient for policy improvement is an effective combination, achieving state-of-the-art results on a high-dimensional humanoid control task, which most model-based agents are unable to solve. Our findings suggest that model-based policy evaluation deserves closer attention .
Edit intent: meaning-changed
Original:  The S1 coronavirus subunit of S-proteins contains the receptor-binding domain (RBD) that is able to recognize different host receptors, highlighting its remarkable capacity to adapt to their hosts along the viral evolution.
Revised:  The S1 subunit of S-proteins contains the receptor-binding domain (RBD) that is able to recognize different host receptors, highlighting its remarkable capacity to adapt to their hosts along the viral evolution.
Edit intent: clarity
Original:  While RBD in spike proteins is determinant for the virus-receptor interaction, the active residues lie at the receptor-binding motif (RBM), which is part of RBD and plays a fundamental role binding the outer surface of their receptors.
Revised:  While RBD in spike proteins is determinant for the virus-receptor interaction, the active residues lie at the receptor-binding motif (RBM), a region located in RBD that plays a fundamental role binding the outer surface of their receptors.
Edit intent: clarity