wanyu/IteraTeR_full_sent huggingface dataset:
Original:  Essentially, ASTposits that conscious experience in the minds of humans and some other animals is the result of evolution having provided the mind with its own internal model of attention taking place within their own (and others') mind ( the ' attention schema').
Revised:  Essentially, ASTposits that conscious experience in the minds of humans and some other animals is the result of evolution having provided the mind with its own internal model of attention taking place in its own (and others') mind ( the ' attention schema').
Edit intent: clarity
Original:  Essentially, ASTposits that conscious experience in the minds of humans and some other animals is the result of evolution having provided the mind with its own internal model of attention taking place within their own (and others') mind ( the ' attention schema').
Revised:  Essentially, ASTposits that conscious experience in the minds of humans and some other animals is the result of evolution having provided the mind with its own internal model of attention taking place within their own (and others') mind ( `the attention schema').
Edit intent: fluency
Original:  However, the inability of humans to understand how their own subjective awareness arises (related to the so-called ' hard problem' of consciousness) is because the attention schema is inherently incomplete.
Revised:  Moreover, this representation is incomplete for efficiency reasons. This inherent incompleteness of the attention schema results in the inability of humans to understand how their own subjective awareness arises (related to the so-called ' hard problem' of consciousness) is because the attention schema is inherently incomplete.
Edit intent: meaning-changed
Original:  However, the inability of humans to understand how their own subjective awareness arises (related to the so-called ' hard problem' of consciousness) is because the attention schema is inherently incomplete. In this short note, we ask to what extent it is possible, in principle, for a mind (either human or machine-based) to have an attentionschema that is complete in the sense of being able to faithfully represent streams of attention . Using a simple  model and a mathematical argument based on classical topology, we describe some limits of the extent to which an attention schema could be complete .
Revised:  However, the inability of humans to understand how their own subjective awareness arises (related to the so-called ' hard problem' of consciousness) . Given this theory, the present paper asks whether a mind (either human or machine-based) to have an attentionschema that is complete in the sense of being able to faithfully represent streams of attention . Using a simple model and a mathematical argument based on classical topology, we describe some limits of the extent to which an attention schema could be complete .
Edit intent: coherence
Original:  In this short note, we ask to what extent it is possible, in principle, for a mind (either human or machine-based) to have an attentionschema that is complete in the sense of being able to faithfully represent streams of attention . Using a simple  model and a mathematical argument based on classical topology, we describe some limits of the extent to which an attention schema could be complete .
Revised:  In this short note, we ask to what extent it is possible, in principle, for a mind (either human or machine-based) that incorporates attention, and that contains a representation of its own attention, can ever have a complete representation . Using a simple model and a mathematical argument based on classical topology, we describe some limits of the extent to which an attention schema could be complete .
Edit intent: clarity
Original:  In this short note, we ask to what extent it is possible, in principle, for a mind (either human or machine-based) to have an attentionschema that is complete in the sense of being able to faithfully represent streams of attention . Using a simple  model and a mathematical argument based on classical topology, we describe some limits of the extent to which an attention schema could be complete .
Revised:  In this short note, we ask to what extent it is possible, in principle, for a mind (either human or machine-based) to have an attentionschema that is complete in the sense of being able to faithfully represent streams of attention . Using a simple yet general model and a mathematical argument based on classical topology, we describe some limits of the extent to which an attention schema could be complete .
Edit intent: clarity
Original:  In this short note, we ask to what extent it is possible, in principle, for a mind (either human or machine-based) to have an attentionschema that is complete in the sense of being able to faithfully represent streams of attention . Using a simple  model and a mathematical argument based on classical topology, we describe some limits of the extent to which an attention schema could be complete .
Revised:  In this short note, we ask to what extent it is possible, in principle, for a mind (either human or machine-based) to have an attentionschema that is complete in the sense of being able to faithfully represent streams of attention . Using a simple model and a mathematical argument based on classical topology, we show that a complete representation of attention is not possible, since it cannot faithfully represent streams of attention. In this way, the study supports one of the core aspects of AST, that the brain's representation of its own attention is necessarily incomplete .
Edit intent: coherence
Original:  Combined with existing techniques in vertex separators  , this leads to algorithms with O(n \cdot tw ^4 \log (1/\varepsilon)) and (n \cdot \mathrm{tw ^2 \log (1/\varepsilon) + n^{1.5 . Besides being the first of its kind, our algorithm has run-time nearly matching the fastest run-time for solving the sub-problem Ax=b (under the assumption that no fast matrix multiplication is used).
Revised:  Combined with recent techniques in vertex-capacitated flow , this leads to algorithms with O(n \cdot tw ^4 \log (1/\varepsilon)) and (n \cdot \mathrm{tw ^2 \log (1/\varepsilon) + n^{1.5 . Besides being the first of its kind, our algorithm has run-time nearly matching the fastest run-time for solving the sub-problem Ax=b (under the assumption that no fast matrix multiplication is used).
Edit intent: meaning-changed
Original:  Combined with existing techniques in vertex separators  , this leads to algorithms with O(n \cdot tw ^4 \log (1/\varepsilon)) and (n \cdot \mathrm{tw ^2 \log (1/\varepsilon) + n^{1.5 . Besides being the first of its kind, our algorithm has run-time nearly matching the fastest run-time for solving the sub-problem Ax=b (under the assumption that no fast matrix multiplication is used).
Revised:  Combined with existing techniques in vertex separators BGS21 , this leads to algorithms with O(n \cdot tw ^4 \log (1/\varepsilon)) and (n \cdot \mathrm{tw ^2 \log (1/\varepsilon) + n^{1.5 . Besides being the first of its kind, our algorithm has run-time nearly matching the fastest run-time for solving the sub-problem Ax=b (under the assumption that no fast matrix multiplication is used).
Edit intent: meaning-changed
Original:  Combined with existing techniques in vertex separators  , this leads to algorithms with O(n \cdot tw ^4 \log (1/\varepsilon)) and (n \cdot \mathrm{tw ^2 \log (1/\varepsilon) + n^{1.5 . Besides being the first of its kind, our algorithm has run-time nearly matching the fastest run-time for solving the sub-problem Ax=b (under the assumption that no fast matrix multiplication is used).
Revised:  Combined with existing techniques in vertex separators , this leads to an algorithm with O(n \cdot tw ^4 \log (1/\varepsilon)) and (n \cdot \mathrm{tw ^2 \log (1/\varepsilon) + n^{1.5 . Besides being the first of its kind, our algorithm has run-time nearly matching the fastest run-time for solving the sub-problem Ax=b (under the assumption that no fast matrix multiplication is used).
Edit intent: fluency
Original:  Combined with existing techniques in vertex separators  , this leads to algorithms with O(n \cdot tw ^4 \log (1/\varepsilon)) and (n \cdot \mathrm{tw ^2 \log (1/\varepsilon) + n^{1.5 . Besides being the first of its kind, our algorithm has run-time nearly matching the fastest run-time for solving the sub-problem Ax=b (under the assumption that no fast matrix multiplication is used).
Revised:  Combined with existing techniques in vertex separators , this leads to algorithms with O(n \cdot tw (n \cdot \mathrm{tw ^2 \log (1/\varepsilon) + n^{1.5 . Besides being the first of its kind, our algorithm has run-time nearly matching the fastest run-time for solving the sub-problem Ax=b (under the assumption that no fast matrix multiplication is used).
Edit intent: clarity
Original:  Combined with existing techniques in vertex separators  , this leads to algorithms with O(n \cdot tw ^4 \log (1/\varepsilon)) and (n \cdot \mathrm{tw ^2 \log (1/\varepsilon) + n^{1.5 . Besides being the first of its kind, our algorithm has run-time nearly matching the fastest run-time for solving the sub-problem Ax=b (under the assumption that no fast matrix multiplication is used).
Revised:  Combined with existing techniques in vertex separators , this leads to algorithms with O(n \cdot tw ^4 \log (1/\varepsilon)) and ^2 \log (1/\varepsilon) + n^{1.5 . Besides being the first of its kind, our algorithm has run-time nearly matching the fastest run-time for solving the sub-problem Ax=b (under the assumption that no fast matrix multiplication is used).
Edit intent: meaning-changed
Original:  Combined with existing techniques in vertex separators  , this leads to algorithms with O(n \cdot tw ^4 \log (1/\varepsilon)) and (n \cdot \mathrm{tw ^2 \log (1/\varepsilon) + n^{1.5 . Besides being the first of its kind, our algorithm has run-time nearly matching the fastest run-time for solving the sub-problem Ax=b (under the assumption that no fast matrix multiplication is used).
Revised:  Combined with existing techniques in vertex separators , this leads to algorithms with O(n \cdot tw ^4 \log (1/\varepsilon)) and (n \cdot \mathrm{tw ^2 \log (1/\varepsilon) ) run-time . Besides being the first of its kind, our algorithm has run-time nearly matching the fastest run-time for solving the sub-problem Ax=b (under the assumption that no fast matrix multiplication is used).
Edit intent: meaning-changed
Original:  We obtain these results by combining recent techniques in interior-point methods (IPMs), sketching, and a novel representation of the solution under a multiscale basis similar to the wavelet basis . This representation further yields the first IPM with o(%DIFDELCMD < \operatorname{rank}%%% (A)) time per iteration when the treewidth is small .
Revised:  We obtain these results by combining recent techniques in interior-point methods (IPMs), sketching, and a novel representation of the solution under a multiscale basis similar to the wavelet basis %DIFDELCMD < \operatorname{rank}%%% (A)) time per iteration when the treewidth is small .
Edit intent: meaning-changed
Original: By fitting a compartment ODE model for Covid-19 propagation to cumulative case and death data for US states and European countries, we find that the case mortality rate seems to have decreased by at least 80 percent in most of the US  and at least 90 percent in most of Europe.
Revised: Our compartment model shows that the COVID-19 case mortality rate seems to have decreased by at least 80 percent in most of the US and at least 90 percent in most of Europe.
Edit intent: clarity
Original: By fitting a compartment ODE model for Covid-19 propagation to cumulative case and death data for US states and European countries, we find that the case mortality rate seems to have decreased by at least 80 percent in most of the US  and at least 90 percent in most of Europe.
Revised: By fitting a compartment ODE model for Covid-19 propagation to cumulative case and death data for US states and European countries, we find that the case mortality rate decreased by at least 80 percent in most of the US and at least 90 percent in most of Europe.
Edit intent: clarity
Original: By fitting a compartment ODE model for Covid-19 propagation to cumulative case and death data for US states and European countries, we find that the case mortality rate seems to have decreased by at least 80 percent in most of the US  and at least 90 percent in most of Europe.
Revised: By fitting a compartment ODE model for Covid-19 propagation to cumulative case and death data for US states and European countries, we find that the case mortality rate seems to have decreased by at least 80 percent in most of the US states and at least 90 percent in most of Europe.
Edit intent: fluency
Original: By fitting a compartment ODE model for Covid-19 propagation to cumulative case and death data for US states and European countries, we find that the case mortality rate seems to have decreased by at least 80 percent in most of the US  and at least 90 percent in most of Europe. These are much larger and faster changes than reported in empirical studies, such as the 18 percent decrease in morality found for the New York City hospital system from March to August 2020 1%DIFDELCMD < ]%%% . Our reported decreases surprisingly do not have strong correlations to other model parameters (such as contact rate) or other standard state/national metrics such as  population density, GDP, and median age.
Revised: By fitting a compartment ODE model for Covid-19 propagation to cumulative case and death data for US states and European countries, we find that the case mortality rate seems to have decreased by at least 80 percent in most of the US and at least 90 percent in most European countries. These drops are much larger and faster changes than reported in empirical studies, such as the 18 percent decrease in morality found for the New York City hospital system from March to August 2020 1%DIFDELCMD < ]%%% . Our reported decreases surprisingly do not have strong correlations to other model parameters (such as contact rate) or other standard state/national metrics such as population density, GDP, and median age.
Edit intent: clarity
Original:  These are much larger and faster changes than reported in empirical studies, such as the 18 percent decrease in morality found for the New York City hospital system from March to August 2020 1%DIFDELCMD < ]%%% . Our reported decreases surprisingly do not have strong correlations to other model parameters (such as contact rate) or other standard state/national metrics such as  population density, GDP, and median age.
Revised:  These are much larger and faster 1%DIFDELCMD < ]%%% . Our reported decreases surprisingly do not have strong correlations to other model parameters (such as contact rate) or other standard state/national metrics such as population density, GDP, and median age.
Edit intent: clarity
Original:  These are much larger and faster changes than reported in empirical studies, such as the 18 percent decrease in morality found for the New York City hospital system from March to August 2020 1%DIFDELCMD < ]%%% . Our reported decreases surprisingly do not have strong correlations to other model parameters (such as contact rate) or other standard state/national metrics such as  population density, GDP, and median age.
Revised:  These are much larger and faster changes than reported in empirical studies, such as the 18 percent decrease in morality found for the New York City hospital system from March to August 2020 %DIFDELCMD < ]%%% . Our reported decreases surprisingly do not have strong correlations to other model parameters (such as contact rate) or other standard state/national metrics such as population density, GDP, and median age.
Edit intent: clarity
Original:  These are much larger and faster changes than reported in empirical studies, such as the 18 percent decrease in morality found for the New York City hospital system from March to August 2020 1%DIFDELCMD < ]%%% . Our reported decreases surprisingly do not have strong correlations to other model parameters (such as contact rate) or other standard state/national metrics such as  population density, GDP, and median age.
Revised:  These are much larger and faster changes than reported in empirical studies, such as the 18 percent decrease in morality found for the New York City hospital system from March to August 2020 1%DIFDELCMD < ]%%% than those previously reported and surprisingly do not have strong correlations to other model parameters (such as contact rate) or other standard state/national metrics such as population density, GDP, and median age.
Edit intent: clarity
Original:  These are much larger and faster changes than reported in empirical studies, such as the 18 percent decrease in morality found for the New York City hospital system from March to August 2020 1%DIFDELCMD < ]%%% . Our reported decreases surprisingly do not have strong correlations to other model parameters (such as contact rate) or other standard state/national metrics such as  population density, GDP, and median age.
Revised:  These are much larger and faster changes than reported in empirical studies, such as the 18 percent decrease in morality found for the New York City hospital system from March to August 2020 1%DIFDELCMD < ]%%% . Our reported decreases surprisingly do not correlate well with our model parameters (such as contact rate) or other standard state/national metrics such as population density, GDP, and median age.
Edit intent: clarity
Original:  These are much larger and faster changes than reported in empirical studies, such as the 18 percent decrease in morality found for the New York City hospital system from March to August 2020 1%DIFDELCMD < ]%%% . Our reported decreases surprisingly do not have strong correlations to other model parameters (such as contact rate) or other standard state/national metrics such as  population density, GDP, and median age.
Revised:  These are much larger and faster changes than reported in empirical studies, such as the 18 percent decrease in morality found for the New York City hospital system from March to August 2020 1%DIFDELCMD < ]%%% . Our reported decreases surprisingly do not have strong correlations to other model parameters (such as the contact rate or testing rate) or state/national metrics such as population density, GDP, and median age.
Edit intent: clarity
Original:  These are much larger and faster changes than reported in empirical studies, such as the 18 percent decrease in morality found for the New York City hospital system from March to August 2020 1%DIFDELCMD < ]%%% . Our reported decreases surprisingly do not have strong correlations to other model parameters (such as contact rate) or other standard state/national metrics such as  population density, GDP, and median age.
Revised:  These are much larger and faster changes than reported in empirical studies, such as the 18 percent decrease in morality found for the New York City hospital system from March to August 2020 1%DIFDELCMD < ]%%% . Our reported decreases surprisingly do not have strong correlations to other model parameters (such as contact rate) or other standard state/national metrics such as the population density, GDP, and median age.
Edit intent: fluency
Original:  Several plausible causes for this drop are examined , such as improvements in treatment , face mask wearing, a new virus strain, and potentially changing demographics of infected patients, but none are overwhelmingly convincing given the currently available evidence .
Revised:  Plausible causes for this drop are examined , such as improvements in treatment , face mask wearing, a new virus strain, and potentially changing demographics of infected patients, but none are overwhelmingly convincing given the currently available evidence .
Edit intent: fluency
Original:  Several plausible causes for this drop are examined , such as improvements in treatment , face mask wearing, a new virus strain, and potentially changing demographics of infected patients, but none are overwhelmingly convincing given the currently available evidence .
Revised:  Several plausible causes for this drop are discussed , such as improvements in treatment , face mask wearing, a new virus strain, and potentially changing demographics of infected patients, but none are overwhelmingly convincing given the currently available evidence .
Edit intent: clarity
Original:  Several plausible causes for this drop are examined , such as improvements in treatment , face mask wearing, a new virus strain, and potentially changing demographics of infected patients, but none are overwhelmingly convincing given the currently available evidence .
Revised:  Several plausible causes for this drop are examined , such as improvements in treatments , face mask wearing, a new virus strain, and potentially changing demographics of infected patients, but none are overwhelmingly convincing given the currently available evidence .
Edit intent: fluency
Original:  Several plausible causes for this drop are examined , such as improvements in treatment , face mask wearing, a new virus strain, and potentially changing demographics of infected patients, but none are overwhelmingly convincing given the currently available evidence .
Revised:  Several plausible causes for this drop are examined , such as improvements in treatment , face mask wearing, a new virus strain, and age demographics of infected patients, but none are overwhelmingly convincing given the currently available evidence .
Edit intent: clarity
Original:  Several plausible causes for this drop are examined , such as improvements in treatment , face mask wearing, a new virus strain, and potentially changing demographics of infected patients, but none are overwhelmingly convincing given the currently available evidence .
Revised:  Several plausible causes for this drop are examined , such as improvements in treatment , face mask wearing, a new virus strain, and potentially changing demographics of infected patients, but none alone support such large decreases .
Edit intent: meaning-changed
Original: Our compartment model shows that the COVID-19 case mortality rate  decreased by at least 80 percent in most of the US states and at least 90 percent in most European countries.
Revised: By fitting a compartment ODE model for Covid-19 propagation to cumulative case and death data for US states and European countries, we find that the case mortality rate decreased by at least 80 percent in most of the US states and at least 90 percent in most European countries.
Edit intent: meaning-changed
Original: Our compartment model shows that the COVID-19 case mortality rate  decreased by at least 80 percent in most of the US states and at least 90 percent in most European countries. These drops are much larger and faster than those previously reported and surprisingly do not correlate well with our model parameters (such as the contact rateor testing rate) or state/national metrics such as the population density, GDP, and median age.
Revised: Our compartment model shows that the COVID-19 case mortality rate decreased by at least 80 percent in most of the US states and at least 90 \% in most of Europe. These are much larger and faster than those previously reported and surprisingly do not correlate well with our model parameters (such as the contact rateor testing rate) or state/national metrics such as the population density, GDP, and median age.
Edit intent: clarity
Original:  These drops are much larger and faster than those previously reported and surprisingly do not correlate well with our model parameters (such as the contact rateor testing rate) or state/national metrics such as the population density, GDP, and median age.
Revised:  These drops are much larger and faster changes than reported in empirical studies, such as the 18\% decrease in mortality found for the New York City hospital system from March to August 2020 (Horwitz et al, Trends in Covid-19 risk-adjusted mortality rates, J. Hosp. Med. 2020). Our reported decreases surprisingly do not correlate well with our model parameters (such as the contact rateor testing rate) or state/national metrics such as the population density, GDP, and median age.
Edit intent: meaning-changed