wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We introduce a new annotated dataset of 1.3K instances of elaborative simplification  and analyze how entities, ideas, and concepts are elaborated through the lens of contextual specificity.
Revised:  We introduce a new annotated dataset of 1.3K instances of elaborative simplification in the Newsela corpus, and analyze how entities, ideas, and concepts are elaborated through the lens of contextual specificity.
Edit intent: meaning-changed
Original:  However, existing report generation systems, despite achieving high performances on natural language generation metrics such as CIDEr or BLEU, still suffer from incomplete and inconsistent generations , rendering these systems unusable in practice. In this work, we aim to overcome this problem by proposing two new metrics that encourage the factual completeness and consistency of generated radiology reports. The first metric, the Exact Entity Match score, evaluates a generation by its coverage of radiology domain entities against the references.
Revised:  However, existing report generation systems, despite achieving high performances on natural language generation metrics such as CIDEr or BLEU, still suffer from incomplete and inconsistent generations . Here we introduce two new simple rewards to encourage the generation of factually complete and consistent radiology reports: one that encourages the system to generate radiology domain entities against the references.
Edit intent: clarity
Original:  The first metric, the Exact Entity Match score, evaluates a generation by its coverage of radiology domain entities against the references. The second metric, the Entailing Entity Match score, augments the first metric by introducing a natural language inference model into the entity match process to encourage consistent generations that can be entailed from the references.
Revised:  The first metric, the Exact Entity Match score, evaluates a generation by its coverage of radiology domain entities consistent with the reference, and one that uses natural language inference model into the entity match process to encourage consistent generations that can be entailed from the references.
Edit intent: clarity
Original:  The second metric, the Entailing Entity Match score, augments the first metric by introducing a natural language inference model into the entity match process to encourage consistent generations that can be entailed from the references. To achieve this, we also developed an in-domain NLI model via weak supervision to improve its performance on radiology text .
Revised:  The second metric, the Entailing Entity Match score, augments the first metric by introducing a natural language inference to encourage these entities to be described in inferentially consistent ways. We combine these with the novel use of an existing semantic equivalence metric (BERTScore) .
Edit intent: clarity
Original:  On two open radiology report datasets, our system not only achieves the best performance on these two metrics compared to baselines, but also leads to as much as +2.0 improvement on the F1 score of a clinical finding metric. We show via analysis and examples that our system leads to generations that are more  complete and consistent compared to the baselines.
Revised:  On two open radiology report datasets, our system not only achieves the best performance on these two metrics compared to baselines, but also leads to as much as +2.0 improvement on the F1 score of a clinical information extraction performance by +22.1 (Delta +63.9\%). We further show via a human evaluation and a qualitative analysis that our system leads to generations that are more complete and consistent compared to the baselines.
Edit intent: meaning-changed
Original: Recent approaches towards passage retrieval have successfully employed representations from pretrained Language Models(LMs) with large effectiveness gains. However, due to high computational cost those approaches are usually limited to re-ranking scenarios. The candidates in such a scenario are typically retrieved by scalable bag-of-words retrieval models such as BM25.
Revised: Many recent approaches towards neural information retrieval mitigate their computational costs by using a multi-stage ranking pipeline. In the first stage, a number of potentially relevant candidates are retrieved using an efficient retrieval model such as BM25.
Edit intent: clarity
Original:  In this context we propose CoRT, a framework and neural first-stage ranking model that leverages contextual representations from transformer-based language models to complement candidates from term-based ranking functions while causing no significant delay  .
Revised:  In this context we propose CoRT, a simple neural first-stage ranking model that leverages contextual representations from transformer-based language models to complement candidates from term-based ranking functions while causing no significant delay .
Edit intent: meaning-changed
Original:  In this context we propose CoRT, a framework and neural first-stage ranking model that leverages contextual representations from transformer-based language models to complement candidates from term-based ranking functions while causing no significant delay  .
Revised:  In this context we propose CoRT, a framework and neural first-stage ranking model that leverages contextual representations from pretrained language models such as BERT to complement term-based ranking functions while causing no significant delay .
Edit intent: meaning-changed
Original:  In this context we propose CoRT, a framework and neural first-stage ranking model that leverages contextual representations from transformer-based language models to complement candidates from term-based ranking functions while causing no significant delay  .
Revised:  In this context we propose CoRT, a framework and neural first-stage ranking model that leverages contextual representations from transformer-based language models to complement candidates from term-based ranking functions while causing no significant delay at query time .
Edit intent: clarity
Original:  Consequently, we found subsequent re-rankers achieve superior results while requiring less candidatesto saturate ranking quality. Finally, we demonstrate that with CoRT a representation-focused retrieval at web-scale can be realized with latencies as low as BM25 .
Revised:  Consequently, we found subsequent re-rankers achieve superior results with less candidates. We further demonstrate that passage retrieval using CoRT can be realized with latencies as low as BM25 .
Edit intent: clarity
Original: Due to the compelling improvements brought by BERT, many recent representation models adopted the Transformer architecture as their main building block, consequently inheriting the wordpiece tokenization system even if it is not intrinsically linked to the notion of Transformer .
Revised: Due to the compelling improvements brought by BERT, many recent representation models adopted the Transformer architecture as their main building block, consequently inheriting the wordpiece tokenization system despite it not being intrinsically linked to the notion of Transformer .
Edit intent: coherence
Original: Due to the compelling improvements brought by BERT, many recent representation models adopted the Transformer architecture as their main building block, consequently inheriting the wordpiece tokenization system even if it is not intrinsically linked to the notion of Transformer .
Revised: Due to the compelling improvements brought by BERT, many recent representation models adopted the Transformer architecture as their main building block, consequently inheriting the wordpiece tokenization system even if it is not intrinsically linked to the notion of Transformers .
Edit intent: fluency
Original:  Then, the potential map is regarded as a condition, together with the current dynamics, to generate the trajectory . The trajectory is modeled by a network based continuous function approximator , which naturally reserves the derivatives for high-order supervision without any additional parameters.
Revised:  Then, the potential map is regarded as a condition, together with the current dynamics, to generate a continuous trajectory as output by a continuous function approximator , which naturally reserves the derivatives for high-order supervision without any additional parameters.
Edit intent: clarity
Original:  [STACS '20] provided a 2^{O(\Delta\nu)}\cdot |{\mathcal G}|^{O(1)}-time algorithm to compute the maximum size of  \Delta-temporal matching in a temporal graph \mathcal G, where |\mathcal G| denotes the size of \mathcal G, and \nu is the \Delta-vertex cover number of \mathcal G. The \Delta-vertex cover number is the minimum number of vertices which are needed to hit (or cover ) all edges in any \Delta consecutive layers of the temporal graph  .
Revised:  [STACS '20] provided a 2^{O(\Delta\nu)}\cdot |{\mathcal G}|^{O(1)}-time algorithm to compute the maximum size of a \Delta-temporal matching in a temporal graph \mathcal G, where |\mathcal G| denotes the size of \mathcal G, and \nu is the \Delta-vertex cover number of \mathcal G. The \Delta-vertex cover number is the minimum number of vertices which are needed to hit (or cover ) all edges in any \Delta consecutive layers of the temporal graph .
Edit intent: fluency
Original:  [STACS '20] provided a 2^{O(\Delta\nu)}\cdot |{\mathcal G}|^{O(1)}-time algorithm to compute the maximum size of  \Delta-temporal matching in a temporal graph \mathcal G, where |\mathcal G| denotes the size of \mathcal G, and \nu is the \Delta-vertex cover number of \mathcal G. The \Delta-vertex cover number is the minimum number of vertices which are needed to hit (or cover ) all edges in any \Delta consecutive layers of the temporal graph  .
Revised:  [STACS '20] provided a 2^{O(\Delta\nu)}\cdot |{\mathcal G}|^{O(1)}-time algorithm to compute the maximum size of \Delta-temporal matching in a temporal graph \mathcal G, where |\mathcal G| denotes the size of \mathcal G, and \nu is the \Delta-vertex cover number of \mathcal G. The \Delta-vertex cover number is the minimum number \nu such that the classical vertex cover number of the union of any \Delta consecutive layers of the temporal graph .
Edit intent: meaning-changed
Original:  [STACS '20] provided a 2^{O(\Delta\nu)}\cdot |{\mathcal G}|^{O(1)}-time algorithm to compute the maximum size of  \Delta-temporal matching in a temporal graph \mathcal G, where |\mathcal G| denotes the size of \mathcal G, and \nu is the \Delta-vertex cover number of \mathcal G. The \Delta-vertex cover number is the minimum number of vertices which are needed to hit (or cover ) all edges in any \Delta consecutive layers of the temporal graph  .
Revised:  [STACS '20] provided a 2^{O(\Delta\nu)}\cdot |{\mathcal G}|^{O(1)}-time algorithm to compute the maximum size of \Delta-temporal matching in a temporal graph \mathcal G, where |\mathcal G| denotes the size of \mathcal G, and \nu is the \Delta-vertex cover number of \mathcal G. The \Delta-vertex cover number is the minimum number of vertices which are needed to hit (or cover ) all edges in any \Delta consecutive layers of the temporal graph is upper-bounded by \nu .
Edit intent: meaning-changed
Original:  Here we consider for the first time open QA over both tabular and textual data and present a new large-scale dataset Open Table-Text Question Answering (OTT-QA) to evaluate performance on this task.
Revised:  Here we consider for the first time open QA over both tabular and textual data and present a new large-scale dataset Open Table-and-Text Question Answering (OTT-QA) to evaluate performance on this task.
Edit intent: clarity
Original:  Most questions in OTT-QA require multi-hop inference across tabular data and unstructured text, and the evidence required to answer a question can be distributed in different ways over these two types of input, making evidence retrieval challenging---our baseline model using an iterative retriever and BERT-based reader achieves an exact match score less than 10\%.
Revised:  Most questions in OTT-QA require multi-hop inference across tabular data and unstructured text, and the evidence required to answer a question can be distributed in different ways over these two types of input, making evidence retrieval challenging -- our baseline model using an iterative retriever and BERT-based reader achieves an exact match score less than 10\%.
Edit intent: fluency
Original:  For uncorrelated estimators of bounds --notably if bounds are estimated from distinct subsamples-- and conventional coverage levels, this step can be skipped. The proposed 95\\%DIF < confidence interval then simplifies to the union of a simple 90\\% (!) confidence interval for the partially identified parameter and an equally simple 95\\% confidence interval for a point-identified pseudotrue parameter.
Revised:  However, except for large positive correlation of bound estimators, the practical result will be simple: To achieve 95\\%DIF < confidence interval then simplifies to the union of a simple 90\\% (!) confidence interval for the partially identified parameter and an equally simple 95\\% confidence interval for a point-identified pseudotrue parameter.
Edit intent: clarity
Original:  However, except for large positive correlation of bound estimators, the practical result will be simple: To achieve 95 %DIFDELCMD < \\%%% %DIF < coverage, compute both a simple 90\\% (!) confidence interval for the identified set and a standard 95\\% confidence interval for the pseudotrue parameter and report the union of these intervals.
Revised:  In most cases, the practical result will be simple: To achieve 95 %DIFDELCMD < \\%%% %DIF < coverage, compute both a simple 90\\% (!) confidence interval for the identified set and a standard 95\\% confidence interval for the pseudotrue parameter and report the union of these intervals.
Edit intent: clarity
Original:  More generally, simulations suggest that the novel confidence interval has excellent length and size control.abstract 
Revised:  More generally, simulations suggest that the novel confidence interval has excellent length and size control.abstract \% coverage, report the union of a simple 90\% (!) confidence interval for the identified set and a standard 95\% confidence interval for the pseudotrue parameter. For uncorrelated estimators -- notably if bounds are estimated from distinct subsamples -- and conventional coverage levels, validity of this simple procedure can be shown analytically. The case obtains in the motivating empirical application (de Quidt, Haushofer, and Roth, 2018), in which improvement over existing inference methods is demonstrated. More generally, simulations suggest that the novel confidence interval has excellent length and size control. This is partly because, in anticipation of never being empty, the interval can be made shorter than conventional ones in relevant regions of sample space.
Edit intent: meaning-changed
Original:  Phoneme inputs are usually preferred over graphemes in order to limit the amount of pronunciation errors. In this work we show that , in the case of a well-curated French dataset, graphemes can be used as input without increasing the amount of pronunciation errors.
Revised:  Indeed, they can be trained using either graphemes or phonemes as input directly. However , in the case of a well-curated French dataset, graphemes can be used as input without increasing the amount of pronunciation errors.
Edit intent: meaning-changed
Original:  In this work we show that , in the case of a well-curated French dataset, graphemes can be used as input without increasing the amount of pronunciation errors. Furthermore, we perform an analysis of the representation learned by the Tacotron model and show that the contextual grapheme embeddings encode phoneme information , and that they can be used for grapheme-to-phoneme conversion and phoneme control of synthetic speech.
Revised:  In this work we show that , in the case of grapheme inputs, little is known concerning the relation between the underlying representations learned by the Tacotron model and show that the contextual grapheme embeddings encode phoneme information , and that they can be used for grapheme-to-phoneme conversion and phoneme control of synthetic speech.
Edit intent: clarity
Original:  Furthermore, we perform an analysis of the representation learned by the Tacotron model and show that the contextual grapheme embeddings encode phoneme information , and that they can be used for grapheme-to-phoneme conversion and phoneme control of synthetic speech.
Revised:  Furthermore, we perform an analysis of the representation learned by the model and word pronunciations. This work investigates this relation in the case of a Tacotron model trained on French graphemes. Our analysis shows that grapheme embeddings are related to phoneme information despite no such information being present during training. Thanks to this property, we show that grapheme embeddings learned by Tacotron models can be useful for tasks such as grapheme-to-phoneme conversion and phoneme control of synthetic speech.
Edit intent: meaning-changed
Original:  Furthermore, we perform an analysis of the representation learned by the Tacotron model and show that the contextual grapheme embeddings encode phoneme information , and that they can be used for grapheme-to-phoneme conversion and phoneme control of synthetic speech.
Revised:  Furthermore, we perform an analysis of the representation learned by the Tacotron model and show that the contextual grapheme embeddings encode phoneme information , and that they can be used for grapheme-to-phoneme conversion and control of the pronunciation in synthetic speech.
Edit intent: clarity
Original:  This step can cure a problem I have identified with modern monetary theory, which is that breaking the monetary circuit of taxation in the minds of politicians will free them from centuries of restraint, optimizing their opportunities for implementing tyranny.
Revised:  Taking these steps can cure a problem I have identified with modern monetary theory, which is that breaking the monetary circuit of taxation in the minds of politicians will free them from centuries of restraint, optimizing their opportunities for implementing tyranny.
Edit intent: clarity
Original:  Second, that non-cancellation of loan principal upon payment cures an old problem of maintenance of positive equity in the private sector. And third , that crediting this money to local government, or to at-risk ventures that create new utility value  creates an additional virtuous monetary circuit that ties finances of government directly to commercial activity.
Revised:  Second, that non-cancellation of loan principal upon payment cures an old problem of maintenance of positive equity in the non-governmental sector. Third , that crediting this money to local government, or to at-risk ventures that create new utility value creates an additional virtuous monetary circuit that ties finances of government directly to commercial activity.
Edit intent: clarity
Original:  And third , that crediting this money to local government, or to at-risk ventures that create new utility value  creates an additional virtuous monetary circuit that ties finances of government directly to commercial activity.
Revised:  And third , that crediting this money to local /state government, and fourth crediting to at-risk ventures that create new utility value creates an additional virtuous monetary circuit that ties finances of government directly to commercial activity.
Edit intent: meaning-changed
Original: Outer polyhedral representations of a given polynomial curve are extensively exploited in computer graphics rendering, computer gaming, path planning for robots, and finite element simulations. B\'ezier curves (which use the Bernstein basis) or B-Splines are a very common choice for these polyhedral representations because their non-negativity and partition-of-unity properties guarantee that each interval of the curve is contained inside the convex hull of its control points. However, the convex hull provided by these bases is not the one with smallest volume, producing therefore undesirable levels of conservatism in all of the applicationsmentioned above.
Revised: This paper studies the problem of finding the smallest n-simplex enclosing a given n^{\text{th by these bases is not the one with smallest volume, producing therefore undesirable levels of conservatism in all of the applicationsmentioned above.
Edit intent: clarity
Original:  However, the convex hull provided by these bases is not the one with smallest volume, producing therefore undesirable levels of conservatism in all of the applicationsmentioned above. This paper presents the MINVO basis, a polynomial basis that generates the smallest n-simplex that encloses any given n^\text{th .   }-degree polynomial curve given.
Revised:  However, the convex hull provided by these bases are not the smallest n-simplex that encloses any given n^\text{th . }-degree polynomial curve given.
Edit intent: coherence
Original:  This paper presents the MINVO basis, a polynomial basis that generates the smallest n-simplex that encloses any given n^\text{th .   }-degree polynomial curve given.
Revised:  This paper presents the MINVO basis, a polynomial basis that generates the smallest n-simplex that encloses any given n^\text{th . We first prove that the polynomial basis that solves this problem (MINVO basis) also solves for the n^\text{th }-degree polynomial curve given.
Edit intent: meaning-changed
Original:  This paper presents the MINVO basis, a polynomial basis that generates the smallest n-simplex that encloses any given n^\text{th .   }-degree polynomial curve given.
Revised:  This paper presents the MINVO basis, a polynomial basis that generates the smallest n-simplex that encloses any given n^\text{th . of the n-simplex or n^{\text{th}-degree polynomial curve given.
Edit intent: meaning-changed
Original:  By using Sum-Of-Squares (SOS) programming, branch and bound, and moment relaxations, we obtain high-quality feasible solutions for any n\inN and prove numerical global optimality for n=1,2,3. } The results obtained for n=3 show that, for any given 3^{rd} -order polynomial curve, the MINVO basis is able to obtain an enclosing simplex whose volume is 2.36 and 254.9 times smaller than the ones obtained by the Bernstein and B-Spline bases, respectively.
Revised:  By using Sum-Of-Squares (SOS) programming, branch and bound, and moment relaxations, we obtain high-quality feasible solutions for any n\inN and prove numerical global optimality for n=1,2,3. } The results obtained for n=3 show that, for any given 3^{rd} -degree polynomial curve, the MINVO basis is able to obtain an enclosing simplex whose volume is 2.36 and 254.9 times smaller than the ones obtained by the Bernstein and B-Spline bases, respectively.
Edit intent: clarity
Original: This work presents a novel  approach to simultaneously track a robot with respect to multiple rigid entities, including the environment and additional dynamic objects in a scene . Previous approaches treat dynamic parts of a scene as outliers and are thus limited to  small amount of dynamics , or rely on prior information for all objects in the scene to enable robust camera tracking.
Revised: This work presents a novel RGB-D SLAM approach to simultaneously track a robot with respect to multiple rigid entities, including the environment and additional dynamic objects in a scene . Previous approaches treat dynamic parts of a scene as outliers and are thus limited to small amount of dynamics , or rely on prior information for all objects in the scene to enable robust camera tracking.
Edit intent: meaning-changed