wanyu/IteraTeR_full_sent huggingface dataset:
Original:  Specifically, we first use RNN to model the temporal dependency of each related stock' price movement based on their own information of the past time slices, then we employ GCN to model the influence from involved stock based on three novel graphs which represent the shareholder relationship, industry relationship and concept relationship among stocks based on investment decisions . Experiments on two stock indexes in China market show that our model outperforms other baselines.
Revised:  Specifically, we first use RNN to model the temporal dependency of each related stock' price movement based on their own information of the past time slices, then we employ GCN to model the temporal dependency of stock prices . Experiments on two stock indexes in China market show that our model outperforms other baselines.
Edit intent: clarity
Original:  To take the cross effect into consideration, we propose a deep learning framework, called Multi-GCGRU, which comprises graph convolutional network (GCN) and gated recurrent units (GRU) to predict stock movement.
Revised:  To take the cross effect into consideration, we propose a deep learning framework, called Multi-GCGRU, which comprises graph convolutional network (GCN) and gated recurrent unit (GRU) to predict stock movement.
Edit intent: fluency
Original: We show that a constant factor approximation of the shortest and closest lattice vector problem w.r.t. \ell_{\infty can be computed in time 2^{(0.802 +{\epsilon})\, n}.
Revised: We show that a constant factor approximation of the shortest and closest lattice vector problem w.r.t. any \ell_p-norm can be computed in time 2^{(0.802 +{\epsilon})\, n}.
Edit intent: meaning-changed
Original:  This is breaking thekissing number barrier of 3^n that is inherent in the previous best approaches tackling this problem . We obtain this improvement by incorporating a bound on the number of scaled hypercubes that are necessary to cover the \ell_2-ball of radius \sqrt{n \ell_2.
Revised:  This is breaking thekissing number barrier matches the currently fastest constant factor approximation algorithm for the shortest vector problem w.r.t. \ell_2.
Edit intent: meaning-changed
Original:  In line with this, the health economic impact of dementia is escalating to unsustainable levels, with estimates that by 2050 dementia care will cost an annual 1 \1 trillion in the US alone.
Revised:  In line with this, the health economic impact of dementia is escalating to unsustainable levels, with estimates that by 2050 dementia care will cost an annual \1 trillion in the US alone.
Edit intent: clarity
Original:  This paper will outline a new CT paradigm designed to offset these two limitations . This is achieved by combining the benefits of gamification, virtual reality (VR), and affective adaptation in the development of an engaging, ecologically valid, CT task.
Revised:  This paper will outline a new CT paradigm designed to offset these two limitations by combining the benefits of gamification, virtual reality (VR), and affective adaptation in the development of an engaging, ecologically valid, CT task.
Edit intent: coherence
Original:  Emotion recognition rates of 64.1\% and 76.2\%, for valence and arousal respectively, were achieved by classifying a DWT-Haar approximation of the input signal using kNN.
Revised:  Affect recognition rates of 64.1\% and 76.2\%, for valence and arousal respectively, were achieved by classifying a DWT-Haar approximation of the input signal using kNN.
Edit intent: fluency
Original: As life expectancy rises, age-related diseases causing dementia become more prevalent. In line with this, the health economic impact of dementia is escalating to unsustainable levels, with estimates that by 2050 dementia care will cost an annual%DIFDELCMD < \1 %%% trillion in the US alone.
Revised: %DIFDELCMD < \1 %%% trillion in the US alone.
Edit intent: coherence
Original:  In line with this, the health economic impact of dementia is escalating to unsustainable levels, with estimates that by 2050 dementia care will cost an annual%DIFDELCMD < \1 %%% trillion in the US alone. The development of interventions capable of improving cognition therefore represents an issue of the highest priority for healthcare. There has been considerable focus on cognitive training (CT) in particular, but work to date has been limited by two main factors, namely (i) the lack of transferability of CT gains to real life activities, and (ii) the lack of adherence to CT programmes .
Revised:  In line with this, the health economic impact of dementia is escalating to unsustainable levels, with estimates that by 2050 dementia care will cost an annual%DIFDELCMD < \1 %%% Cognitive training has shown promising results for delivering improvements in human cognition related to attention, problem solving, reading comprehension and information retrieval. However, two frequently cited problems in cognitive training literature are a lack of user engagement with the training programme, and a failure of developed skills to generalise to daily life .
Edit intent: coherence
Original:  This paper introduces a new CT paradigm designed to offset these two limitations by combining the benefits of gamification, virtual reality (VR), and affective adaptation in the development of an engaging, ecologically valid, CT task.
Revised:  This paper introduces a new cognitive training (CT) paradigm designed to offset these two limitations by combining the benefits of gamification, virtual reality (VR), and affective adaptation in the development of an engaging, ecologically valid, CT task.
Edit intent: clarity
Original:  This paper introduces a new CT paradigm designed to offset these two limitations by combining the benefits of gamification, virtual reality (VR), and affective adaptation in the development of an engaging, ecologically valid, CT task.
Revised:  This paper introduces a new CT paradigm designed to address these two limitations by combining the benefits of gamification, virtual reality (VR), and affective adaptation in the development of an engaging, ecologically valid, CT task.
Edit intent: clarity
Original:  We further demonstrate that the contrast-adaptive method can also be applied robustly to MRI scans of healthy controls, and replicate previously documented atrophy patterns in deep gray matter structures in MS. The algorithm is publicly available as part of the open-source neuroimaging package FreeSurfer.
Revised:  We further demonstrate that the contrast-adaptive method can also be safely applied to MRI scans of healthy controls, and replicate previously documented atrophy patterns in deep gray matter structures in MS. The algorithm is publicly available as part of the open-source neuroimaging package FreeSurfer.
Edit intent: clarity
Original: We propose a novel categorical thinking model (CTM) where the framing of the decision problem affects how the agent categorizes each product, and the product's category affects her evaluation of the product. We show that a number of prominent models of salience, status quo bias, loss-aversion, inequality aversion, and present bias all fit under the umbrella of CTM.
Revised: We propose a novel categorical thinking model (CTM) where the framing of the decision problem affects how agents categorize alternatives, that in turn affects their evaluation of it. Prominent models of salience, status quo bias, loss-aversion, inequality aversion, and present bias all fit under the umbrella of CTM.
Edit intent: clarity
Original:  ObjTables includes a format for schemas , a markup language for indicating the class and attribute represented by each spreadsheet and column , and software for using schemas to read, write, validate, compare, merge, split, revision, and analyze spreadsheets .
Revised:  ObjTables includes a format for schemas ; markup for indicating the class and attribute represented by each spreadsheet and column , and software for using schemas to read, write, validate, compare, merge, split, revision, and analyze spreadsheets .
Edit intent: clarity
Original:  ObjTables includes a format for schemas , a markup language for indicating the class and attribute represented by each spreadsheet and column , and software for using schemas to read, write, validate, compare, merge, split, revision, and analyze spreadsheets .
Revised:  ObjTables includes a format for schemas , a markup language for indicating the class and attribute represented by each spreadsheet and column ; numerous data types for scientific information; and high-level software for using schemas to read, write, validate, compare, merge, split, revision, and analyze spreadsheets .
Edit intent: meaning-changed
Original:  ObjTables includes a format for schemas , a markup language for indicating the class and attribute represented by each spreadsheet and column , and software for using schemas to read, write, validate, compare, merge, split, revision, and analyze spreadsheets .
Revised:  ObjTables includes a format for schemas , a markup language for indicating the class and attribute represented by each spreadsheet and column , and software for using schemas to read, write, validate, compare, merge, revision, and analyze spreadsheets .
Edit intent: clarity
Original:  ObjTables includes a format for schemas , a markup language for indicating the class and attribute represented by each spreadsheet and column , and software for using schemas to read, write, validate, compare, merge, split, revision, and analyze spreadsheets . ObjTables supports a wide range of data types .
Revised:  ObjTables includes a format for schemas , a markup language for indicating the class and attribute represented by each spreadsheet and column , and software for using schemas to read, write, validate, compare, merge, split, revision, and analyze spreadsheets .
Edit intent: coherence
Original:   We relate the model to the Beveridge-Nelson decomposition and derive a modified Kalman filter estimator for the fractional components.
Revised:  The model allows for an endogenous estimation of the integration order jointly with the other model parameters and, therefore, no prior specification tests with respect to persistence are required. We relate the model to the Beveridge-Nelson decomposition and derive a modified Kalman filter estimator for the fractional components.
Edit intent: meaning-changed
Original:  For US macroeconomic data we demonstrate that, unlike non-fractional correlated unobserved components models, the new model estimates a smooth trend together with a cycle hitting all NBER recessions  .
Revised:  For US macroeconomic data we demonstrate that, unlike I(1) correlated unobserved components models, the new model estimates a smooth trend together with a cycle hitting all NBER recessions .
Edit intent: meaning-changed
Original:  For US macroeconomic data we demonstrate that, unlike non-fractional correlated unobserved components models, the new model estimates a smooth trend together with a cycle hitting all NBER recessions  .
Revised:  For US macroeconomic data we demonstrate that, unlike non-fractional correlated unobserved components models, the new model estimates a smooth trend together with a cycle hitting all NBER recessions . While I(1) unobserved components models yield an upward-biased signal-to-noise ratio whenever the integration order of the data-generating mechanism is greater than one, the fractionally integrated model attributes less variation to the long-run shocks due to the fractional trend specification and a higher variation to the cycle shocks due to the fractional lag operator, leading to more persistent cycles and smooth trend estimates that reflect macroeconomic common sense .
Edit intent: meaning-changed
Original: We build upon our recently introduced concept of an update structure to show that they are a generalisation of very-well-behaved lenses, that is, there is a bijection between a strict subset of update structures and vwb lenses in cartesian categories.
Revised: We build upon our recently introduced concept of an update structure to show that it is a generalisation of very-well-behaved lenses, that is, there is a bijection between a strict subset of update structures and vwb lenses in cartesian categories.
Edit intent: clarity
Original:  In doing so, we shift the focus from dagger-special commutative Frobenius algebras to interacting (co)magma (co)module pairs, showing that the algebraic properties of the (co)multiplication arise from the module-comodule interaction, rather than direct assumptions about the magma comagma pair.
Revised:  In doing so, we shift the focus from special commutative dagger-Frobenius algebras to interacting (co)magma (co)module pairs, showing that the algebraic properties of the (co)multiplication arise from the module-comodule interaction, rather than direct assumptions about the magma comagma pair.
Edit intent: fluency
Original:  In doing so, we shift the focus from dagger-special commutative Frobenius algebras to interacting (co)magma (co)module pairs, showing that the algebraic properties of the (co)multiplication arise from the module-comodule interaction, rather than direct assumptions about the magma comagma pair. Thus this work is of foundational interest as update structures form a strictly more general class of algebraic objects, the taming of which promises to illuminate novel relationships between separately studied mathematical structures .
Revised:  In doing so, we shift the focus from dagger-special commutative Frobenius algebras to interacting (co)magma (co)module pairs, showing that the algebraic properties of the (co)multiplication arise from the module-comodule interaction, rather than direct assumptions about the magma-comagma pair. We then begin to investigate the zoo of possible update structures, introducing the notions of classical security-flagged databases, and databases of quantum systems. This work is of foundational interest as update structures form a strictly more general class of algebraic objects, the taming of which promises to illuminate novel relationships between separately studied mathematical structures .
Edit intent: meaning-changed
Original:  We parameterize a dialog system using a Transformer-based auto-regressive language model, which subsumes different dialog mod-ules (e.g., state tracker, dialog policy, responsegenerator ) into a single neural model.
Revised:  We parameterize a dialog system using a Transformer-based auto-regressive language model, which subsumes different dialog modules (e.g., state tracker, dialog policy, responsegenerator ) into a single neural model.
Edit intent: fluency
Original:  We parameterize a dialog system using a Transformer-based auto-regressive language model, which subsumes different dialog mod-ules (e.g., state tracker, dialog policy, responsegenerator ) into a single neural model.
Revised:  We parameterize a dialog system using a Transformer-based auto-regressive language model, which subsumes different dialog mod-ules (e.g., state tracker, dialog policy, response generator ) into a single neural model.
Edit intent: fluency
Original:  Our experiments demonstrate that (i) SOLOIST creates new state-of-the-art results on two well-known benchmarks, CamRest and MultiWOZ, (ii) in the few-shot learning setting, the dialog systems developed by SOLOIST significantly outperform those  by existing methods, and (iii) the use of machine teaching substantially reduces the labeling cost.
Revised:  Our experiments demonstrate that (i) SOLOIST creates new state-of-the-art results on two well-known benchmarks, CamRest and MultiWOZ, (ii) in the few-shot learning setting, the dialog systems developed by SOLOIST significantly outperform those developed by existing methods, and (iii) the use of machine teaching substantially reduces the labeling cost.
Edit intent: clarity
Original:  The main results of this work are providing sufficient conditions for existence and uniqueness of the clearing solutions (i.e., liquidations, borrowing, fire sale prices, and haircut levels)  .
Revised:  The main results of this work are providing sufficient conditions for existence and uniqueness of the clearing solutions (i.e., liquidations, borrowing, fire sale prices, and haircut levels) as well as sufficient conditions for uniqueness of the clearing solutions .
Edit intent: meaning-changed
Original:  Specifically, we take the pretrained models of Transformer, GPT, and BERT-GPT on dialog datasets and other large-scale texts, then finetune them on our CovidDialog datasets. Experiments demonstrate that these approaches are promising in generating meaningful medical dialogues about COVID-19.
Revised:  Specifically, we take the pretrained models of Transformer, GPT, and BERT-GPT on dialog datasets and other large-scale texts, then finetune them on our CovidDialog tasks. We perform both automatic and human evaluation of responses generated by these models. The results show that the generated responses are promising in generating meaningful medical dialogues about COVID-19.
Edit intent: clarity
Original:  Our approach allows for the incorporation of intergroup bias such that messages from trusted in-group sources enjoy greater leeway than out-group ones  .
Revised:  Our approach allows for the incorporation of intergroup bias such that messages from trusted in-group sources enjoy greater leeway than out-group ones . We are able to extrapolate these nonlinear microscopic dynamics to macroscopic population distributions by using probabilistic functions representing biased environments .
Edit intent: meaning-changed
Original:  An analysis of lead-lag relationships between the time series of extracted emotions from official bulletins and social media using Granger's causality showed that state bulletins were leading the social media for some emotions such as fear .
Revised:  An analysis of lead-lag relationships between the time series of extracted emotions from official bulletins and social media using Granger's causality showed that state bulletins were leading the social media for some emotions such as Medical Emergency .
Edit intent: meaning-changed
Original:  The tools we develop will be useful for classifications of other classes of signed graphs, and we mention some follow-up research of this kind; the classifications are surprisingly complex .
Revised:  The tools we develop will be useful for classifications of other classes of signed graphs, and we illustrate this by classifying the complexity of irreflexive signed graphs in which the unicoloured edges form some simple structures, namely paths or cycles. The structure of the signed graphs in the polynomial cases is interesting, suggesting they may constitute a nice class of signed graphs analogous to the so-called bi-arc graphs (which characterized the polynomial cases of list homomorphisms to unsigned graphs) .
Edit intent: meaning-changed
Original:  We propose new methods to anonymize, publish, and explore data on identified victims of trafficking , implemented as a single pipeline producing three data artifacts: (1) synthetic microdata modelled on sensitive case records and released in their place, mitigating the privacy risk that traffickers might link distinctive combinations of attributes in published records to known victims ;
Revised:  We present new methods to anonymize, publish, and explore data on identified victims of trafficking , implemented as a single pipeline producing three data artifacts: (1) synthetic microdata modelled on sensitive case records and released in their place, mitigating the privacy risk that traffickers might link distinctive combinations of attributes in published records to known victims ;
Edit intent: clarity
Original:  We propose new methods to anonymize, publish, and explore data on identified victims of trafficking , implemented as a single pipeline producing three data artifacts: (1) synthetic microdata modelled on sensitive case records and released in their place, mitigating the privacy risk that traffickers might link distinctive combinations of attributes in published records to known victims ;
Revised:  We propose new methods to anonymize, publish, and explore such data , implemented as a single pipeline producing three data artifacts: (1) synthetic microdata modelled on sensitive case records and released in their place, mitigating the privacy risk that traffickers might link distinctive combinations of attributes in published records to known victims ;
Edit intent: clarity
Original:  We propose new methods to anonymize, publish, and explore data on identified victims of trafficking , implemented as a single pipeline producing three data artifacts: (1) synthetic microdata modelled on sensitive case records and released in their place, mitigating the privacy risk that traffickers might link distinctive combinations of attributes in published records to known victims ;
Revised:  We propose new methods to anonymize, publish, and explore data on identified victims of trafficking , implemented as a pipeline generating three artifacts: (1) synthetic microdata modelled on sensitive case records and released in their place, mitigating the privacy risk that traffickers might link distinctive combinations of attributes in published records to known victims ;
Edit intent: clarity
Original:  We propose new methods to anonymize, publish, and explore data on identified victims of trafficking , implemented as a single pipeline producing three data artifacts: (1) synthetic microdata modelled on sensitive case records and released in their place, mitigating the privacy risk that traffickers might link distinctive combinations of attributes in published records to known victims ;
Revised:  We propose new methods to anonymize, publish, and explore data on identified victims of trafficking , implemented as a single pipeline producing three data artifacts: (1) synthetic data mitigating the privacy risk that traffickers might link distinctive combinations of attributes in published records to known victims ;
Edit intent: coherence
Original:  We propose new methods to anonymize, publish, and explore data on identified victims of trafficking , implemented as a single pipeline producing three data artifacts: (1) synthetic microdata modelled on sensitive case records and released in their place, mitigating the privacy risk that traffickers might link distinctive combinations of attributes in published records to known victims ;
Revised:  We propose new methods to anonymize, publish, and explore data on identified victims of trafficking , implemented as a single pipeline producing three data artifacts: (1) synthetic microdata modelled on sensitive case records and released in their place, mitigating the privacy risk that published attribute combinations might be linked to known individuals or groups ;
Edit intent: clarity
Original:  and (3) visual analytics interfaces for parallel exploration and evaluation of synthetic data representations and sensitive data aggregates, mitigating the accessibility risk that privacy mechanisms or analysis tools might not be understandable or usable by all stakeholders.
Revised:  and (3) visual analytics interfaces for parallel exploration and evaluation of synthetic data representations and sensitive data aggregates, mitigating the accessibility risk that privacy mechanisms or analysis tools might not be understandable and usable by all stakeholders.
Edit intent: fluency
Original:  We present our work as a design study motivated by the goal of creating a new privacy-preserving data platform for the Counter-Trafficking Data Collaborative (CTDC), transforming how the world's largest database of identified victims is made available for global collaboration against human trafficking.
Revised:  We present our work as a design study motivated by the goal of transforming how the world's largest database of identified victims is made available for global collaboration against human trafficking.
Edit intent: clarity