wanyu/IteraTeR_v2 huggingface dataset:
Original:  Our approach associates every subtask with its own modular subpolicy, and jointly optimizes over full task-specific policies by tying parameters across shared subpolicies.
Revised:  Our approach associates every subtask with its own modular subpolicy, and jointly maximizes reward over full task-specific policies by tying parameters across shared subpolicies.
Edit intent: clarity
Original:  This optimization is accomplished via a simple decoupled actor-critic training objective that facilitates learning common behaviors from  dissimilar reward functions.
Revised:  Optimization is accomplished via a simple decoupled actor-critic training objective that facilitates learning common behaviors from dissimilar reward functions.
Edit intent: clarity
Original:  This optimization is accomplished via a simple decoupled actor-critic training objective that facilitates learning common behaviors from  dissimilar reward functions.
Revised:  This optimization is accomplished via a decoupled actor--critic training objective that facilitates learning common behaviors from dissimilar reward functions.
Edit intent: clarity
Original:  This optimization is accomplished via a simple decoupled actor-critic training objective that facilitates learning common behaviors from  dissimilar reward functions.
Revised:  This optimization is accomplished via a simple decoupled actor-critic training objective that facilitates learning common behaviors from multiple dissimilar reward functions.
Edit intent: clarity
Original:  Second, our method naturally induces a library of  primitive behaviors that can be recombined to rapidly acquire policies for new tasks.
Revised:  Second, our method naturally induces a library of primitive behaviors that can be recombined to rapidly adapt to new tasks.
Edit intent: clarity
Original:  Our framework is based upon a substantial generalization of the techniques developed recently in the context of the Koml\'{o discrepancy problem [BDG16].
Revised:  Our framework is based upon a substantial generalization of the techniques developed recently in the context of the Koml\'os discrepancy problem [BDG16].
Edit intent: fluency
Original: When encountering novel object , humans are able to infer a wide range of physical properties such as mass, friction and deformability by interacting with them in a goal driven way.
Revised: When encountering novel objects , humans are able to infer a wide range of physical properties such as mass, friction and deformability by interacting with them in a goal driven way.
Edit intent: fluency
Original:  This process of active interaction is in the same spirit of a scientist performing an experiment to discover hidden facts.
Revised:  This process of active interaction is in the same spirit as a scientist performing an experiment to discover hidden facts.
Edit intent: fluency
Original:  This process of active interaction is in the same spirit of a scientist performing an experiment to discover hidden facts.
Revised:  This process of active interaction is in the same spirit of a scientist performing experiments to discover hidden facts.
Edit intent: fluency
Original:  Recent advances in artificial intelligence have yielded machines that can achieve superhuman performance in Go, Atari, natural language processing, and complex control problems , but it is not clear that these systems can rival the scientific intuition of even a young child.
Revised:  Recent advances in artificial intelligence have yielded machines that can achieve superhuman performance in Go, Atari, natural language processing, and complex control problems ; however, it is not clear that these systems can rival the scientific intuition of even a young child.
Edit intent: coherence
Original:  In this work we introduce a basic set of tasks that require agents to estimate hidden properties such as mass and cohesion of objects in an interactive simulated environment where they can manipulate the objects and observe the consequences.
Revised:  In this work we introduce a basic set of tasks that require agents to estimate properties such as mass and cohesion of objects in an interactive simulated environment where they can manipulate the objects and observe the consequences.
Edit intent: clarity
Original:  From the initial solution, an efficient algorithm based on gradient descent of the final objective function is proposed to learn representations from the input datasets, allowing complete, overcomplete, or undercomplete bases.
Revised:  Starting from the initial solution, an efficient algorithm based on gradient descent of the final objective function is proposed to learn representations from the input datasets, allowing complete, overcomplete, or undercomplete bases.
Edit intent: coherence
Original:  From the initial solution, an efficient algorithm based on gradient descent of the final objective function is proposed to learn representations from the input datasets, allowing complete, overcomplete, or undercomplete bases.
Revised:  From the initial solution, an efficient algorithm based on gradient descent of the final objective function is proposed to learn representations from the input datasets, and the method works for complete, overcomplete, or undercomplete bases.
Edit intent: coherence
Original:  From the initial solution, an efficient algorithm based on gradient descent of the final objective function is proposed to learn representations from the input datasets, allowing complete, overcomplete, or undercomplete bases.
Revised:  From the initial solution, an efficient algorithm based on gradient descent of the final objective function is proposed to learn representations from the input datasets, allowing complete, overcomplete, and undercomplete bases.
Edit intent: fluency
Original:  As confirmed by numerical experiments, our method is robust and highly efficient for extracting salient features from image datasets.
Revised:  As confirmed by numerical experiments, our method is robust and highly efficient for extracting salient features from input datasets.
Edit intent: clarity
Original:  Moreover, the method is readily extended to train deep structure networks by unsupervised or supervised learning .
Revised:  Furthermore, the proposed method is easily extended to the supervised or unsupervised model for training deep structure networks by unsupervised or supervised learning .
Edit intent: clarity
Original:  Moreover, the method is readily extended to train deep structure networks by unsupervised or supervised learning .
Revised:  Moreover, the method is readily extended to train deep structure networks .
Edit intent: coherence
Original:  These metrics and statistics include both those common in urban design and transportation studies, as well as metrics that measure the structure and topology of the network.
Revised:  These metrics and statistics include both those common in urban design and transportation studies, and other measures of the structure and topology of the network.
Edit intent: clarity
Original:  To address these challenges, this study presents a new tool to make the collection of data and creation and analysis of street networks simple, consistent, and automatable . OSMnx is a new Python package that downloads administrative boundary shapes and street networks from OpenStreetMap . OSMnx contributes five significant new capabilities for researchers and city planners : first, the automatic downloading of administrative place boundaries and shapefiles;
Revised:  To address these challenges, this paper presents OSMnx, a new tool to make the collection of data and creation and analysis of street networks simple, consistent, and automatable . OSMnx is a new Python package that downloads administrative boundary shapes and street networks from OpenStreetMap . OSMnx contributes five significant new capabilities for researchers and city planners : first, the automatic downloading of administrative place boundaries and shapefiles;
Edit intent: clarity
Original:  To address these challenges, this study presents a new tool to make the collection of data and creation and analysis of street networks simple, consistent, and automatable . OSMnx is a new Python package that downloads administrative boundary shapes and street networks from OpenStreetMap . OSMnx contributes five significant new capabilities for researchers and city planners : first, the automatic downloading of administrative place boundaries and shapefiles;
Revised:  To address these challenges, this study presents a new tool to make the collection of data and creation and analysis of street networks simple, consistent, and automatable . OSMnx is a new Python package that downloads administrative boundary shapes and street networks from OpenStreetMap . OSMnx contributes five new capabilities for researchers and city planners : first, the automatic downloading of administrative place boundaries and shapefiles;
Edit intent: clarity
Original:  To address these challenges, this study presents a new tool to make the collection of data and creation and analysis of street networks simple, consistent, and automatable . OSMnx is a new Python package that downloads administrative boundary shapes and street networks from OpenStreetMap . OSMnx contributes five significant new capabilities for researchers and city planners : first, the automatic downloading of administrative place boundaries and shapefiles;
Revised:  To address these challenges, this study presents a new tool to make the collection of data and creation and analysis of street networks simple, consistent, and automatable . OSMnx is a new Python package that downloads administrative boundary shapes and street networks from OpenStreetMap . OSMnx contributes five significant new capabilities for urban researchers and practitioners : first, the automatic downloading of administrative place boundaries and shapefiles;
Edit intent: clarity
Original:  To address these challenges, this study presents a new tool to make the collection of data and creation and analysis of street networks simple, consistent, and automatable . OSMnx is a new Python package that downloads administrative boundary shapes and street networks from OpenStreetMap . OSMnx contributes five significant new capabilities for researchers and city planners : first, the automatic downloading of administrative place boundaries and shapefiles;
Revised:  To address these challenges, this study presents a new tool to make the collection of data and creation and analysis of street networks simple, consistent, and automatable . OSMnx is a new Python package that downloads administrative boundary shapes and street networks from OpenStreetMap . OSMnx contributes five significant new capabilities for researchers and city planners : first, the automated downloading of administrative place boundaries and shapefiles;
Edit intent: fluency
Original:  second, the tailored and automated downloading and constructing of street networks from OpenStreetMap (including driving, walking, biking, etc.) ;
Revised:  second, the tailored and automated downloading and constructing of street networks from OpenStreetMap ;
Edit intent: coherence
Original:  third, the automated correction and simplification of network topology;
Revised:  third, the algorithmic correction and simplification of network topology;
Edit intent: clarity
Original:  and fifth, the ability to analyze street networks, calculate routes, project and visualize the networks, and calculate network metrics and statistics.
Revised:  and fifth, the ability to analyze street networks, calculate routes, project and visualize networks, and calculate network metrics and statistics.
Edit intent: clarity
Original:  These metrics and statistics include both those common in urban design and transportation studies, and other measures of the structure and topology of the network  .
Revised:  These metrics and statistics include both those common in urban design and transportation studies, as well as advanced measures of the structure and topology of the network .
Edit intent: clarity
Original:  OSMnx contributes five new capabilities for urban researchers and practitioners: first, the automated downloading of administrative place boundaries and shapefiles ;
Revised:  OSMnx contributes five significant capabilities for researchers and practitioners: first, the automated downloading of administrative place boundaries and shapefiles ;
Edit intent: clarity
Original:  OSMnx contributes five new capabilities for urban researchers and practitioners: first, the automated downloading of administrative place boundaries and shapefiles ;
Revised:  OSMnx contributes five new capabilities for urban researchers and practitioners: first, the automated downloading of administrative place boundaries and building footprints ;
Edit intent: clarity
Original:  second, the tailored and automated downloading and constructing of street networks from OpenStreetMap;
Revised:  second, the tailored and automated downloading and constructing of street network data from OpenStreetMap;
Edit intent: clarity
Original:  third, the algorithmic correction and simplification of network topology;
Revised:  third, the algorithmic correction of network topology;
Edit intent: clarity
Original:  and fifth, the ability to analyze street networks, calculate routes, project and visualize networks, and calculate metric and topological measures.
Revised:  and fifth, the ability to analyze street networks, including calculating routes, projecting and visualizing networks, and calculate metric and topological measures.
Edit intent: clarity
Original:  and fifth, the ability to analyze street networks, calculate routes, project and visualize networks, and calculate metric and topological measures.
Revised:  and fifth, the ability to analyze street networks, calculate routes, project and visualize networks, and calculating metric and topological measures.
Edit intent: fluency
Original:  Finally it presents a simple case study using OSMnx to construct and analyze street networks in Portland, Oregon.
Revised:  Finally , this paper presents a simple case study using OSMnx to construct and analyze street networks in Portland, Oregon.
Edit intent: clarity
Original:  To address these challenges, this paper presents OSMnx, a new tool to make the collection of data and creation and analysis of street networks simple, consistent, automatable and sound from the perspectives of graph theory, transportation, and urban design.
Revised:  To address these challenges, this article presents OSMnx, a new tool to make the collection of data and creation and analysis of street networks simple, consistent, automatable and sound from the perspectives of graph theory, transportation, and urban design.
Edit intent: fluency
Original:  Finally, this paper presents a simple case study using OSMnx to construct and analyze street networks in Portland, Oregon.
Revised:  Finally, this article presents a simple case study using OSMnx to construct and analyze street networks in Portland, Oregon.
Edit intent: fluency
Original:  We show this by using percentile shares to analyze  factors influencing citation impact  (FICs;
Revised:  We show this by using percentile shares to analyze so-called " factors influencing citation impact (FICs;
Edit intent: clarity
Original:  We show this by using percentile shares to analyze  factors influencing citation impact  (FICs;
Revised:  We show this by using percentile shares to analyze factors influencing citation impact " (FICs;
Edit intent: fluency
Original:  The comparison of the effects of the different FICs (the number of cited references, number of authors, number of pages, and JIF) on citation impact shows that JIF has indeed the strongest effect on the citation scores.
Revised:  The comparison of the effects of the different FICs (the number of cited references, number of authors, number of pages, and JIF) on citation impact shows that JIF has indeed the strongest correlations with the citation scores.
Edit intent: clarity
Original:  However, the effect of the FICs on citation impact is reduced , if citations are normalized instead of using raw citation counts.
Revised:  However, the correlation between FICs and citation impact is reduced , if citations are normalized instead of using raw citation counts.
Edit intent: clarity
Original:  However, the effect of the FICs on citation impact is reduced , if citations are normalized instead of using raw citation counts.
Revised:  However, the effect of the FICs on citation impact is lower , if citations are normalized instead of using raw citation counts.
Edit intent: coherence
Original: This document briefly describes our freely distributed Maple library spectra {\sc  , for Semidefinite Programming solved Exactly with Computational Tools of Real Algebra.
Revised: This document describes our freely distributed Maple library spectra {\sc , for Semidefinite Programming solved Exactly with Computational Tools of Real Algebra.
Edit intent: clarity
Original:  In particular, we show that the models regularized with OrthoReg have higher accuracy bounds even when batch normalization and dropout  present.
Revised:  In particular, we show that the models regularized with OrthoReg have higher accuracy bounds even when batch normalization and dropout are present.
Edit intent: clarity
Original: We discuss a range of modeling choices that arise when constructing an end-to-end differentiable programming language suitable for learning programs from input-output examples.
Revised: We discuss a range of modeling choices that arise when constructing a differentiable programming language suitable for learning programs from input-output examples.
Edit intent: clarity
Original:  In this paper, we propose to adapt a classical operator from quantum mechanics to the field of shape analysis where we suggest to integrate a scalar function through a unified elliptical Hamiltonian operator.
Revised:  In this paper, we propose to adapt the classical Hamiltonian operator from quantum mechanics to the field of shape analysis where we suggest to integrate a scalar function through a unified elliptical Hamiltonian operator.
Edit intent: fluency
Original:  The suggested operator is shown to produce better functional spaces to operate with, as demonstrated by the proposed framework that outperforms existing spectral methods, for example, when applied to shape matching benchmarks .
Revised:  The suggested operator is shown to produce better functional spaces to operate with, as demonstrated on different shape analysis tasks .
Edit intent: clarity
Original: A piecewise Chebyshevian spline space is good for design when it possesses a B-spline basis and this property is preserved under arbitrary knot insertion.
Revised: A piecewise Chebyshevian spline space is good for design when it possesses a B-spline basis and this property is preserved under knot insertion.
Edit intent: clarity
Original:  The interest in piecewise Chebyshevian spline spaces that are good for design is justified by the fact that, similarly as for polynomial splines, the related parametric curves exhibit the desired properties of convex hull inclusion, variation diminution and intuitive relation between the curve shape and the location of the control points.
Revised:  The interest in such kind of spaces is justified by the fact that, similarly as for polynomial splines, the related parametric curves exhibit the desired properties of convex hull inclusion, variation diminution and intuitive relation between the curve shape and the location of the control points.
Edit intent: clarity
Original:  For all good-for-design spaces , in this paper we construct a set of functions, called transition functions, which allow for efficient computation of the B-spline basis, even in the case of nonuniform and multiple knots.
Revised:  For a good-for-design spaces , in this paper we construct a set of functions, called transition functions, which allow for efficient computation of the B-spline basis, even in the case of nonuniform and multiple knots.
Edit intent: clarity
Original:  For all good-for-design spaces , in this paper we construct a set of functions, called transition functions, which allow for efficient computation of the B-spline basis, even in the case of nonuniform and multiple knots.
Revised:  For all good-for-design space , in this paper we construct a set of functions, called transition functions, which allow for efficient computation of the B-spline basis, even in the case of nonuniform and multiple knots.
Edit intent: fluency
Original: We report first observations of an integrated analog photonic network, in which connections are configured by microring weight banks , as well as the first use of electro-optic modulators as photonic neurons . A mathematical isomorphism between the silicon photonic circuit and a continuous neural  model is demonstrated through dynamical bifurcation analysis.
Revised: We report first observations of an integrated analog photonic network, in which connections are configured by microring weight banks . A mathematical isomorphism between the silicon photonic circuit and a continuous neural model is demonstrated through dynamical bifurcation analysis.
Edit intent: coherence
Original: We report first observations of an integrated analog photonic network, in which connections are configured by microring weight banks , as well as the first use of electro-optic modulators as photonic neurons . A mathematical isomorphism between the silicon photonic circuit and a continuous neural  model is demonstrated through dynamical bifurcation analysis.
Revised: We report first observations of an integrated analog photonic network, in which connections are configured by microring weight banks , as well as the first use of electro-optic modulators as photonic neurons . A mathematical isomorphism between the silicon photonic circuit and a continuous neural network model is demonstrated through dynamical bifurcation analysis.
Edit intent: fluency
Original:  A 49-node silicon photonic neural network programmed using a "neural compiler" is simulated and predicted to outperform a conventional approach 1,960-fold in a toy differential system emulation task.
Revised:  A 49-node silicon photonic neural network programmed using an existing "neural compiler" is simulated and predicted to outperform a conventional approach 1,960-fold in a toy differential system emulation task.
Edit intent: clarity
Original:  A 49-node silicon photonic neural network programmed using a "neural compiler" is simulated and predicted to outperform a conventional approach 1,960-fold in a toy differential system emulation task.
Revised:  A 49-node silicon photonic neural network programmed using a "neural compiler" to solve a differential system emulation task.
Edit intent: clarity
Original:  Exploiting this isomorphism, a simulated 24-node silicon photonic neural network programmed using an existing "neural compiler" to solve a differential system emulation task.
Revised:  Exploiting this isomorphism, a simulated 24-node silicon photonic neural network is programmed using "neural compiler" to solve a differential system emulation task.
Edit intent: clarity
Original:  In this work we propose two novel frameworks in which to study estimation, learning, and optimization in the presence of significant fractions of arbitrary data.
Revised:  In this work we consider two frameworks in which to study estimation, learning, and optimization in the presence of significant fractions of arbitrary data.
Edit intent: clarity
Original:  The first framework, which we term list-decodable learning, asks whether it is possible to return a list of answers, with the guarantee that at least one of them is accurate.
Revised:  The first framework, list-decodable learning, asks whether it is possible to return a list of answers, with the guarantee that at least one of them is accurate.
Edit intent: clarity