wanyu/IteraTeR_full_sent huggingface dataset:
Original:  Consequently, minority groups could be perpetually underestimated -- they are never hired, and therefore, data about them is never accumulated. We proved that this problem becomes more serious when the population ratio is imbalanced, as is the case in many extant discrimination problems. We consider two affirmative-action policies for solving this dilemma: One is a subsidy rule that is based on the popular upper confidence bound algorithm, and another is the Rooney Rule , which requires firms to interview at least one minority worker for each hiring opportunity .
Revised:  Consequently, minority groups could be perpetually underestimated -- they are never hired, and therefore, underestimation towards them tends to persist. Even a slight population-ratio imbalance frequently produces perpetual underestimation. We propose two policy solutions: a novel subsidy rule (the hybrid mechanism) and the Rooney Rule , which requires firms to interview at least one minority worker for each hiring opportunity .
Edit intent: clarity
Original:  We consider two affirmative-action policies for solving this dilemma: One is a subsidy rule that is based on the popular upper confidence bound algorithm, and another is the Rooney Rule , which requires firms to interview at least one minority worker for each hiring opportunity .
Revised:  We consider two affirmative-action policies for solving this dilemma: One is a subsidy rule that is based on the popular upper confidence bound algorithm, and another is the Rooney Rule .
Edit intent: coherence
Original:  Second, I combine municipal level price effects on unsorted and recycling waste with their impacts on municipal and pollution costs. I estimate overall welfare benefits after three years of adoption, when waste prices cause significant waste avoidance .
Revised:  Second, I estimate policy impacts on pollution and municipal management costs, and compute the overall social cost savings for each municipality. Social welfare effects become positive for most municipalities after three years of adoption, when waste prices cause significant waste avoidance .
Edit intent: meaning-changed
Original:  We present the open source Medical Concept Annotation Toolkit (MedCAT) that provides: a) a novel self-supervised machine learning algorithm for extracting concepts using any concept vocabulary including UMLS/SNOMED-CT;
Revised:  We present the open-source Medical Concept Annotation Toolkit (MedCAT) that provides: a) a novel self-supervised machine learning algorithm for extracting concepts using any concept vocabulary including UMLS/SNOMED-CT;
Edit intent: fluency
Original:  We show strong transferability (F1 > 0.94) between hospitals, datasets  and concept types indicating cross-domain EHR-agnostic utility for accelerated clinical and research use cases.
Revised:  We show strong transferability (F1 > 0.94) between hospitals, datasets , and concept types indicating cross-domain EHR-agnostic utility for accelerated clinical and research use cases.
Edit intent: fluency
Original: Business analysts create billions of slide decks, reports and documents annually. Most of these documents have well-defined structure comprising of similar content generated from data .
Revised: The financial services industry perpetually processes an overwhelming amount of complex data. Digital reports are often created based on tedious manual analysis as well as visualization of the underlying trends and characteristics of data. Often, the accruing costs of human computation errors in creating these reports are very high .
Edit intent: meaning-changed
Original:  We present 'AI pptX' , a novel AI framework for creating and modifying documents as well as extract insights in the form of natural language sentences from data. AI pptX has three main components: (i) a component that translates users' natural language input into 'skills ' that encapsulate content editing and formatting commands, (ii) a robust continuously learning component that interacts with users, and (iii) a component that automatically generates hierarchical insights in the form of natural language sentences. We illustrate (i) and (ii) with a study of 18 human users tasked to create a presentation deck and observe the learning capability from a decrease in user-input commands by up to 45\%. We demonstrate the robust learning capability of AI pptX with experimental simulations of non-collaborative users. We illustrate (i) and (iii) by automatically generating insights in natural language using a data set from the Electricity Transmission Network of France (RTE); we show that a complex statistical analysis of series can automatically be distilled into easily interpretable explanations called AI Insights .
Revised:  We present 'AI pptX' , a novel AI framework for creating and modifying content in digital documents by modeling natural language interactions as "skills" and using them to transform underlying data. DocuBot has the ability to agglomerate saved skills for reuse, enabling humans to automatically generate recurrent reports. DocuBot also has the capability to continuously learn domain-specific and user-specific vocabulary by interacting with the user. We present evidence that DocuBot adds value to the financial industry and demonstrate its impact with experiments involving real and simulated users tasked with creating PowerPoint presentations .
Edit intent: meaning-changed
Original:  A single octopus arm is modeled as a Hamiltonian control system, where the continuum mechanics of the arm is captured by the Cosserat rod theory, and internal, distributed muscle forces and couples are considered as controls.
Revised:  A single octopus arm is modeled as a Hamiltonian control system, where the continuum mechanics of the arm is modeled after the Cosserat rod theory, and internal, distributed muscle forces and couples are considered as controls.
Edit intent: clarity
Original:  We show that by treating the secant condition using a penalty method approach  , one can smoothly interpolate between updating the inverse Hessian approximation with the original BFGS update formula and not updating the inverse Hessian approximation.
Revised:  We show that by treating the secant condition with a penalty method approach , one can smoothly interpolate between updating the inverse Hessian approximation with the original BFGS update formula and not updating the inverse Hessian approximation.
Edit intent: fluency
Original:  We show that by treating the secant condition using a penalty method approach  , one can smoothly interpolate between updating the inverse Hessian approximation with the original BFGS update formula and not updating the inverse Hessian approximation.
Revised:  We show that by treating the secant condition using a penalty method approach motivated by regularized least squares estimation , one can smoothly interpolate between updating the inverse Hessian approximation with the original BFGS update formula and not updating the inverse Hessian approximation.
Edit intent: meaning-changed
Original:  These developments allow us to develop an algorithm we refer to as secant penalized BFGS (SP-BFGS) that allows one to relax the secant condition based on the amount of noise in the gradient measurements.
Revised:  These developments allow us to develop a method we refer to as secant penalized BFGS (SP-BFGS) that allows one to relax the secant condition based on the amount of noise in the gradient measurements.
Edit intent: clarity
Original:  Mathematically, SP-BFGS provides a means of incrementally updating the new inverse Hessian approximation with a controlled amount of bias towards the previous inverse Hessian approximation . Practically speaking, this can be used to help replace the overwriting nature of the  BFGS update with an averaging nature that resists the destructive effects of noise .
Revised:  SP-BFGS provides a means of incrementally updating the new inverse Hessian approximation with a controlled amount of bias towards the previous inverse Hessian approximation . Practically speaking, this can be used to help replace the overwriting nature of the BFGS update with an averaging nature that resists the destructive effects of noise .
Edit intent: coherence
Original:  Mathematically, SP-BFGS provides a means of incrementally updating the new inverse Hessian approximation with a controlled amount of bias towards the previous inverse Hessian approximation . Practically speaking, this can be used to help replace the overwriting nature of the  BFGS update with an averaging nature that resists the destructive effects of noise .
Revised:  Mathematically, SP-BFGS provides a means of incrementally updating the new inverse Hessian approximation with a controlled amount of bias towards the previous inverse Hessian approximation , which allows one to replace the overwriting nature of the BFGS update with an averaging nature that resists the destructive effects of noise .
Edit intent: clarity
Original:  Mathematically, SP-BFGS provides a means of incrementally updating the new inverse Hessian approximation with a controlled amount of bias towards the previous inverse Hessian approximation . Practically speaking, this can be used to help replace the overwriting nature of the  BFGS update with an averaging nature that resists the destructive effects of noise .
Revised:  Mathematically, SP-BFGS provides a means of incrementally updating the new inverse Hessian approximation with a controlled amount of bias towards the previous inverse Hessian approximation . Practically speaking, this can be used to help replace the overwriting nature of the original BFGS update with an averaging nature that resists the destructive effects of noise .
Edit intent: meaning-changed
Original:  Mathematically, SP-BFGS provides a means of incrementally updating the new inverse Hessian approximation with a controlled amount of bias towards the previous inverse Hessian approximation . Practically speaking, this can be used to help replace the overwriting nature of the  BFGS update with an averaging nature that resists the destructive effects of noise . We provide a convergence analysis of SP-BFGS, and present numerical results illustrating the performance of SP-BFGS  in the presence of noisy gradients .
Revised:  Mathematically, SP-BFGS provides a means of incrementally updating the new inverse Hessian approximation with a controlled amount of bias towards the previous inverse Hessian approximation . Practically speaking, this can be used to help replace the overwriting nature of the BFGS update with an averaging nature that resists the destructive effects of noise and can cope with negative curvature measurements. We discuss the theoretical properties of SP-BFGS, and present numerical results illustrating the performance of SP-BFGS in the presence of noisy gradients .
Edit intent: meaning-changed
Original:  We provide a convergence analysis of SP-BFGS, and present numerical results illustrating the performance of SP-BFGS  in the presence of noisy gradients .
Revised:  We provide a convergence analysis of SP-BFGS, including convergence when minimizing strongly convex functions in the presence of uniformly bounded noise. Finally, we present extensive numerical experiments using over 30 problems from the CUTEst test problem set that demonstrate the superior performance of SP-BFGS in the presence of noisy gradients .
Edit intent: meaning-changed
Original:  Finally, in order to study numerical convergence and thus illustrate the improved performances with the proposed methods, we provide numerical results for several 100-dimensional nonlinear BSDEs including a nonlinear pricing problem in finance.
Revised:  Finally, in order to study numerical convergence and thus illustrate the improved performances with the proposed methods, we provide numerical results for several 100-dimensional nonlinear BSDEs including nonlinear pricing problems in finance.
Edit intent: fluency
Original: Multi-Agent Path Finding (MAPF), i.e., finding collision-free paths for multiple robots, is important for many applications where small runtimes are important , including the kind of automated warehouses operated by Amazon.
Revised: Multi-Agent Path Finding (MAPF), i.e., finding collision-free paths for multiple robots, is important for many applications where small runtimes are necessary , including the kind of automated warehouses operated by Amazon.
Edit intent: clarity
Original:  ECBS is a bounded-suboptimal variant of CBS that uses focal search to speed up CBS by sacrificing optimality and instead guaranteeing that the costs of its solution are within a given factor of optimal.
Revised:  ECBS is a bounded-suboptimal variant of CBS that uses focal search to speed up CBS by sacrificing optimality and instead guaranteeing that the costs of its solutions are within a given factor of optimal.
Edit intent: fluency
Original:  Motivated by Explicit Estimation Search (EES), we propose Explicit Estimation CBS (EECBS), a new bounded-suboptimal variant of CBS, that uses online learning to inadmissibly estimate the cost of the solution under each high-level node and uses EES to choose which high-level node to expand next.
Revised:  Motivated by Explicit Estimation Search (EES), we propose Explicit Estimation CBS (EECBS), a new bounded-suboptimal variant of CBS, that uses online learning to obtain inadmissible estimates of the cost of the solution under each high-level node and uses EES to choose which high-level node to expand next.
Edit intent: clarity
Original:  Motivated by Explicit Estimation Search (EES), we propose Explicit Estimation CBS (EECBS), a new bounded-suboptimal variant of CBS, that uses online learning to inadmissibly estimate the cost of the solution under each high-level node and uses EES to choose which high-level node to expand next.
Revised:  Motivated by Explicit Estimation Search (EES), we propose Explicit Estimation CBS (EECBS), a new bounded-suboptimal variant of CBS, that uses online learning to inadmissibly estimate the cost of the solution of each high-level node and uses EES to choose which high-level node to expand next.
Edit intent: clarity
Original:  We find that EECBS with the improvements runs significantly faster than the  MAPF algorithms ECBS, BCP-7, and eMDD-SAT on a variety of MAPF instances.
Revised:  We find that EECBS with the improvements runs significantly faster than the state-of-the-art bounded-suboptimal MAPF algorithms ECBS, BCP-7, and eMDD-SAT on a variety of MAPF instances.
Edit intent: meaning-changed
Original:  To fill the gaps, we propose a new method SumGNN: ~%DIFDELCMD < {\it %%% knowledge summarization graph neural network , which is enabled by a subgraph extraction module that can efficiently anchor on relevant subgraphs from a KG, a self-attention based subgraph summarization scheme to generate  reasoning path within the subgraph, and a multi-channel knowledge and data integration module that utilizes massive external biomedical knowledge for significantly improved multi-typed DDI predictions.
Revised:  To fill the gaps, we propose a new method SumGNN: %DIFDELCMD < {\it %%% knowledge summarization graph neural network , which is enabled by a subgraph extraction module that can efficiently anchor on relevant subgraphs from a KG, a self-attention based subgraph summarization scheme to generate reasoning path within the subgraph, and a multi-channel knowledge and data integration module that utilizes massive external biomedical knowledge for significantly improved multi-typed DDI predictions.
Edit intent: fluency
Original:  To fill the gaps, we propose a new method SumGNN: ~%DIFDELCMD < {\it %%% knowledge summarization graph neural network , which is enabled by a subgraph extraction module that can efficiently anchor on relevant subgraphs from a KG, a self-attention based subgraph summarization scheme to generate  reasoning path within the subgraph, and a multi-channel knowledge and data integration module that utilizes massive external biomedical knowledge for significantly improved multi-typed DDI predictions.
Revised:  To fill the gaps, we propose a new method SumGNN: ~%DIFDELCMD < {\it %%% knowledge summarization graph neural network , which is enabled by a subgraph extraction module that can efficiently anchor on relevant subgraphs from a KG, a self-attention based subgraph summarization scheme to generate a reasoning path within the subgraph, and a multi-channel knowledge and data integration module that utilizes massive external biomedical knowledge for significantly improved multi-typed DDI predictions.
Edit intent: fluency
Original: This paper proposes a procedure to execute external source codes from a %DIFDELCMD < \LaTeX\space %%%  document and include the calculation outputs in the resulting Portable Document Format (pdf) file automatically.
Revised: This paper proposes a procedure to execute external source codes from a %DIFDELCMD < \LaTeX\space %%% LaTeX document and include the calculation outputs in the resulting Portable Document Format (pdf) file automatically.
Edit intent: meaning-changed
Original:  In our proposed approach to a %DIFDELCMD < \LaTeX%%% -based scientific notebook the user can easily invoke any programming language or a command-line program when compiling the %DIFDELCMD < \LaTeX\space %%%  document, while using their favorite %DIFDELCMD < \LaTeX\space %%%  editor in the writing process.
Revised:  In our proposed approach to a %DIFDELCMD < \LaTeX%%% LaTeX-based scientific notebook the user can easily invoke any programming language or a command-line program when compiling the %DIFDELCMD < \LaTeX\space %%% document, while using their favorite %DIFDELCMD < \LaTeX\space %%% editor in the writing process.
Edit intent: meaning-changed
Original:  In our proposed approach to a %DIFDELCMD < \LaTeX%%% -based scientific notebook the user can easily invoke any programming language or a command-line program when compiling the %DIFDELCMD < \LaTeX\space %%%  document, while using their favorite %DIFDELCMD < \LaTeX\space %%%  editor in the writing process.
Revised:  In our proposed approach to a %DIFDELCMD < \LaTeX%%% -based scientific notebook the user can easily invoke any programming language or a command-line program when compiling the %DIFDELCMD < \LaTeX\space %%% LaTeX document, while using their favorite %DIFDELCMD < \LaTeX\space %%% editor in the writing process.
Edit intent: meaning-changed
Original:  In our proposed approach to a %DIFDELCMD < \LaTeX%%% -based scientific notebook the user can easily invoke any programming language or a command-line program when compiling the %DIFDELCMD < \LaTeX\space %%%  document, while using their favorite %DIFDELCMD < \LaTeX\space %%%  editor in the writing process.
Revised:  In our proposed approach to a %DIFDELCMD < \LaTeX%%% -based scientific notebook the user can easily invoke any programming language or a command-line program when compiling the %DIFDELCMD < \LaTeX\space %%% document, while using their favorite %DIFDELCMD < \LaTeX\space %%% LaTeX editor in the writing process.
Edit intent: meaning-changed
Original:  The required %DIFDELCMD < \LaTeX\space %%%  setup, a new  package, and the defined preamble are discussed in detail, and working examples using , , and to reproduce existing research are provided to illustrate the proposed procedure.
Revised:  The required %DIFDELCMD < \LaTeX\space %%% LaTeX setup, a new package, and the defined preamble are discussed in detail, and working examples using , , and to reproduce existing research are provided to illustrate the proposed procedure.
Edit intent: meaning-changed
Original:  The required %DIFDELCMD < \LaTeX\space %%%  setup, a new  package, and the defined preamble are discussed in detail, and working examples using , , and to reproduce existing research are provided to illustrate the proposed procedure.
Revised:  The required %DIFDELCMD < \LaTeX\space %%% setup, a new Python package, and the defined preamble are discussed in detail, and working examples using , , and to reproduce existing research are provided to illustrate the proposed procedure.
Edit intent: meaning-changed
Original:  The required %DIFDELCMD < \LaTeX\space %%%  setup, a new  package, and the defined preamble are discussed in detail, and working examples using , , and to reproduce existing research are provided to illustrate the proposed procedure.
Revised:  The required %DIFDELCMD < \LaTeX\space %%% setup, a new package, and the defined preamble are discussed in detail, and working examples using , and to reproduce existing research are provided to illustrate the proposed procedure.
Edit intent: fluency
Original:  The required %DIFDELCMD < \LaTeX\space %%%  setup, a new  package, and the defined preamble are discussed in detail, and working examples using , , and to reproduce existing research are provided to illustrate the proposed procedure.
Revised:  The required %DIFDELCMD < \LaTeX\space %%% setup, a new package, and the defined preamble are discussed in detail, and working examples using , R, Julia, and MatLab to reproduce existing research are provided to illustrate the proposed procedure.
Edit intent: meaning-changed
Original: We propose a framework for holistic static and animated 3D scene generation from diverse text descriptions. Prior works of scene generation rely on static rule-based entity extraction from natural language description .
Revised: Generating coherent and useful image/video scenes from a free-form textual description is technically a very difficult problem to handle. Textual description of the same scene can vary greatly from person to person, or sometimes even for the same person from time to time. As the choice of words and syntax vary while preparing a textual description, it is challenging for the system to reliably produce a consistently desirable output from different forms of language input. The prior works of scene generation rely on static rule-based entity extraction from natural language description .
Edit intent: coherence
Original:  Prior works of scene generation rely on static rule-based entity extraction from natural language description .
Revised:  Prior works of scene generation have been mostly confined to rigorous sentence structures of text input which restrict the freedom of users to write description. In our work, we study a new pipeline that aims to generate static as well as animated 3D scenes from different types of free-form textual scene description without any major restriction. In particular, to keep our study practical and tractable, we focus on a small subspace of all possible 3D scenes, containing various combinations of cube, cylinder and sphere. We design a two-stage pipeline. In the first stage, we encode the free-form text using an encoder-decoder neural architecture .
Edit intent: meaning-changed
Original:  However, this limits the usability of a practical solution. To overcome this limitation, we use one of state-of-the-art architecture- TransformerXL. Instead of rule-based extraction, our framework leverages the rich contextual encoding which allows us to process a larger range (diverse) of possible natural language descriptions.
Revised:  In the second stage, we generate a 3D scene based on the generated encoding. Our neural architecture exploits state-of-the-art language model as encoder to leverage rich contextual encoding which allows us to process a larger range (diverse) of possible natural language descriptions.
Edit intent: meaning-changed
Original:  Instead of rule-based extraction, our framework leverages the rich contextual encoding which allows us to process a larger range (diverse) of possible natural language descriptions. We empirically show how our proposed mechanism generalizes even on novel combinations of object-features during inference. We also show how our framework can jointly generate static and animated 3D scene efficiently.
Revised:  Instead of rule-based extraction, our framework leverages the rich contextual encoding and a new multi-head decoder to predict multiple features of an object in the scene simultaneously. For our experiments, we generate a large synthetic data-set which contains 13,00,000 and 14,00,000 samples of unique static and animated 3D scene efficiently.
Edit intent: meaning-changed