wanyu/IteraTeR_full_sent huggingface dataset:
Original: We use data on annuities to study and evaluate an imperfectly competitive market where firms have private information about their (annuitization) costs. Our data is from Chile, where the market is structured as first-price-auction-followed-by-bargaining, and where each retiree chooses a firm and an annuity contract to maximize her expected present discounted utility. We find that retirees with low savings have the highest information processing cost, and they also care about firms' risk-ratings the most.
Revised: We use data on annuities to study and evaluate an imperfectly competitive market where firms have private information about their costs. We model this interaction using multi-stage and multi-attribute auctions where a retiree--auctioneer--maximizes her find that retirees with low savings have the highest information processing cost, and they also care about firms' risk-ratings the most.
Edit intent: clarity
Original:  Furthermore, while almost 50\% of retirees reveal that they do not value leaving bequests, the rest have heterogeneous preference for bequestthat, on average, increases with their savings.
Revised:  The estimates also suggest that almost half the retirees who choose an annuity do not value leaving bequests, the rest have heterogeneous preference for bequestthat, on average, increases with their savings.
Edit intent: meaning-changed
Original:  Furthermore, while almost 50\% of retirees reveal that they do not value leaving bequests, the rest have heterogeneous preference for bequestthat, on average, increases with their savings. On the supply side, we find that firms ' annuitization costs vary across retirees , and the average costs increase with retirees' savings . If these costs were commonly known then the pensions would increase for everyone, but the increment would be substantial only for the high savers.
Revised:  Furthermore, while almost 50\% of retirees reveal that they do not value bequest, and firms are more likely to have low annuitization cost for retirees in the top two savings deciles. Counterfactuals show that under the current mechanism, private information about costs harms only these high savers.
Edit intent: coherence
Original:  Likewise, if we simplify the current pricing mechanism by implementing English auctions and "shutting down" the  risk-ratings , then the pensionswould increase, but again, mostly for the high savers.
Revised:  Likewise, if we simplify the current pricing mechanism by implementing English auctions and "shutting down" theand risk-ratings , then the pensionswould increase, but again, mostly for the high savers.
Edit intent: meaning-changed
Original:  Likewise, if we simplify the current pricing mechanism by implementing English auctions and "shutting down" the  risk-ratings , then the pensionswould increase, but again, mostly for the high savers.
Revised:  Likewise, if we simplify the current pricing mechanism by implementing English auctions and "shutting down" the prohibiting the use of risk-ratings , then the pensionswould increase, but again, mostly for the high savers.
Edit intent: meaning-changed
Original: The performance of a market for annuity contracts depends on the interaction between retirees and strategic life insurance companies with  private information about their costs. We model this interaction using multi-stage and multi-attribute auctions where a retiree--auctioneer--maximizes herexpected present discounted utility .
Revised: The performance of a market for annuity contracts depends on the interaction between retirees and strategic life insurance companies with private information about their expected present discounted utility .
Edit intent: clarity
Original:  We model this interaction using multi-stage and multi-attribute auctions where a retiree--auctioneer--maximizes herexpected present discounted utility . We estimate the model parameters using rich administrative data from Chile and find that retirees with low savings value firms' risk-ratings the most. The estimates also suggest that almost half the retirees who choose an annuity do not value bequest, and firms are more likely to have low annuitization cost for retirees in the top two savings deciles.
Revised:  We model this interaction using multi-stage and multi-attribute auctions where a retiree--auctioneer--maximizes herexpected present discounted utility annuitization costs compete for savings of risk-averse retirees by offering them personalized pensions. We find that (1) retirees' preferences for firms' risk ratings decrease with their savings, (2) almost half of the retirees who choose an annuity do not value bequest, and firms are more likely to have low annuitization cost for retirees in the top two savings deciles.
Edit intent: meaning-changed
Original:  The estimates also suggest that almost half the retirees who choose an annuity do not value bequest, and firms are more likely to have low annuitization cost for retirees in the top two savings deciles.
Revised:  The estimates also suggest that almost half the retirees who choose annuities do not value bequest, and firms are more likely to have low annuitization cost for retirees in the top two savings deciles.
Edit intent: fluency
Original:  The estimates also suggest that almost half the retirees who choose an annuity do not value bequest, and firms are more likely to have low annuitization cost for retirees in the top two savings deciles.
Revised:  The estimates also suggest that almost half the retirees who choose an annuity do not value bequests, (3) information processing costs are larger for low savers and for those who receive advise from sales-agent, and (4) firms are more likely to have low annuitization cost for retirees in the top two savings deciles.
Edit intent: meaning-changed
Original:  The estimates also suggest that almost half the retirees who choose an annuity do not value bequest, and firms are more likely to have low annuitization cost for retirees in the top two savings deciles. Counterfactuals show that under the current mechanism, private information about costs harms only these high savers . Implementing English auctionsand prohibiting the use of risk-ratings lead to higher pensions , but only for these high savers .
Revised:  The estimates also suggest that almost half the retirees who choose an annuity do not value bequest, and firms are more likely to have and prohibiting the use of risk-ratings lead to higher pensions , but only for these high savers .
Edit intent: coherence
Original:  Counterfactuals show that under the current mechanism, private information about costs harms only these high savers . Implementing English auctionsand prohibiting the use of risk-ratings lead to higher pensions , but only for these high savers .
Revised:  Counterfactuals show that under the current mechanism, private information about costs harms only these high savers . Implementing English auctions prohibiting the use of risk-ratings lead to higher pensions , but only for these high savers .
Edit intent: fluency
Original:  Counterfactuals show that under the current mechanism, private information about costs harms only these high savers . Implementing English auctionsand prohibiting the use of risk-ratings lead to higher pensions , but only for these high savers .
Revised:  Counterfactuals show that under the current mechanism, private information about costs harms only these high savers . Implementing English auctionsand lower annuitization costs for the top 40\% savers. Counterfactuals suggest that information asymmetry hurts these 40\% savers the most, and replacing the current mechanism with standard English auctions and "shutting-down" risk ratings increase pensions for everyone. But the increase is negligible for most, except for these top 40\% savers, with little effect on welfare .
Edit intent: meaning-changed
Original:  To this end, we develop a model of demand and supply of annuities using discrete choice and multi-attribute auctions where life insurance companies with different risk ratings and private information about their annuitization costscompete for savings of risk-averse retirees by offering them personalized pensions .
Revised:  To this end, we use rich data from Chile, where annuities are sold via a two-stage process: first-price auctions followed by bargaining. Firms have private information about their annuitization costscompete for savings of risk-averse retirees by offering them personalized pensions .
Edit intent: meaning-changed
Original:  To this end, we develop a model of demand and supply of annuities using discrete choice and multi-attribute auctions where life insurance companies with different risk ratings and private information about their annuitization costscompete for savings of risk-averse retirees by offering them personalized pensions .
Revised:  To this end, we develop a model of demand and supply of annuities using discrete choice and multi-attribute auctions where life insurance companies with different risk ratings and private information about their costs, and retirees have heterogeneous preferences for bequest and firms' risk rating .
Edit intent: meaning-changed
Original:  risk ratings decrease with their savings, (2) almost half of the retirees who choose annuities do not value bequests , (3) information processing costs are larger for low savers and for those who receive advise from sales-agent, and (4) firms are more likely to have lower annuitization costs for the top 40\% savers . Counterfactuals suggest that information asymmetry hurts these 40\% savers the most, and replacing the current mechanism with standard English auctions and "shutting-down" risk ratings increase pensions for everyone.
Revised:  risk ratings more than others, and approximately 40\% do not value bequests , (3) information processing costs are larger for low savers and for those who receive advise from sales-agent, and (4) firms are more likely to have lower annuitization costs for the top 40\% savers . Counterfactuals suggest that information asymmetry hurts these 40\% savers the most, and replacing the current mechanism with standard English auctions and "shutting-down" risk ratings increase pensions for everyone.
Edit intent: clarity
Original:  almost half of the retirees who choose annuities do not value bequests , (3) information processing costs are larger for low savers and for those who receive advise from sales-agent, and (4) firms are more likely to have lower annuitization costs for the top 40\% savers . Counterfactuals suggest that information asymmetry hurts these 40\% savers the most, and replacing the current mechanism with standard English auctions and "shutting-down" risk ratings increase pensions for everyone.
Revised:  almost half of the retirees who choose annuities do not value bequests . Counterfactuals suggest that information asymmetry hurts these 40\% savers the most, and replacing the current mechanism with standard English auctions and "shutting-down" risk ratings increase pensions for everyone.
Edit intent: coherence
Original:  almost half of the retirees who choose annuities do not value bequests , (3) information processing costs are larger for low savers and for those who receive advise from sales-agent, and (4) firms are more likely to have lower annuitization costs for the top 40\% savers . Counterfactuals suggest that information asymmetry hurts these 40\% savers the most, and replacing the current mechanism with standard English auctions and "shutting-down" risk ratings increase pensions for everyone. But the increase is negligible for most, except for these top 40\% savers, with little effect on welfare .
Revised:  almost half of the retirees who choose annuities do not value bequests , (3) information processing costs are larger for low savers and for those who receive advise from sales-agent, and (4) firms are more likely to have lower annuitization costs for the top 40\% savers . Counterfactuals suggest that using simpler English auctions increases pensions but mainly for those in the top four savings deciles .
Edit intent: clarity
Original:  We find that retirees with low savings value firms ' risk ratings more than others, and approximately 40\% do not value bequests. Counterfactuals suggest that using simpler English auctions increases pensionsbut mainly for those in the top four savings deciles .
Revised:  We find substantial costs and preference heterogeneity and that having many firms is crucial for good market outcomes. Counterfactuals show that simplifying the current mechanism with English auctions and "shutting down" risk ratings increase pensions, but only for high-savers .
Edit intent: meaning-changed
Original:  We find substantial costs and preference heterogeneity and that having many firmsis crucial for good market outcomes . Counterfactuals show that simplifying the current mechanism with English auctions and "shutting down" risk ratings increase pensions, but only for high-savers.
Revised:  We find substantial costs and preference heterogeneity , and because there are many firms, the market performs well . Counterfactuals show that simplifying the current mechanism with English auctions and "shutting down" risk ratings increase pensions, but only for high-savers.
Edit intent: coherence
Original:  As  sensitive attributes like our identity, gender, indicators of mental health status, alongside moods, emotions and their temporal patterns, are easily inferred using deep acoustic models, we encounter a new generation of privacy risks by using these services.
Revised:  As our emotional patterns and sensitive attributes like our identity, gender, indicators of mental health status, alongside moods, emotions and their temporal patterns, are easily inferred using deep acoustic models, we encounter a new generation of privacy risks by using these services.
Edit intent: meaning-changed
Original:  One approach to mitigate the risk of paralinguistic-based privacy breaches is to exploit a combination of cloud-based processing with privacy-preserving  on-device paralinguistic information filtering prior to transmitting voice data.
Revised:  One approach to mitigate the risk of paralinguistic-based privacy breaches is to exploit a combination of cloud-based processing with privacy-preserving , on-device paralinguistic information filtering prior to transmitting voice data.
Edit intent: fluency
Original:  One approach to mitigate the risk of paralinguistic-based privacy breaches is to exploit a combination of cloud-based processing with privacy-preserving  on-device paralinguistic information filtering prior to transmitting voice data.
Revised:  One approach to mitigate the risk of paralinguistic-based privacy breaches is to exploit a combination of cloud-based processing with privacy-preserving on-device paralinguistic information learning and filtering before transmitting voice data.
Edit intent: meaning-changed
Original:  In this paper we introduce EDGY, a new lightweight disentangled representation learning model that transforms and filters high-dimensional voice data to remove sensitive attributes at the edge prior to offloading to the cloud.
Revised:  In this paper we introduce EDGY, a configurable, lightweight, disentangled representation learning model that transforms and filters high-dimensional voice data to remove sensitive attributes at the edge prior to offloading to the cloud.
Edit intent: clarity
Original:  In this paper we introduce EDGY, a new lightweight disentangled representation learning model that transforms and filters high-dimensional voice data to remove sensitive attributes at the edge prior to offloading to the cloud.
Revised:  In this paper we introduce EDGY, a new lightweight disentangled representation learning framework that transforms and filters high-dimensional voice data to remove sensitive attributes at the edge prior to offloading to the cloud.
Edit intent: clarity
Original:  In this paper we introduce EDGY, a new lightweight disentangled representation learning model that transforms and filters high-dimensional voice data to remove sensitive attributes at the edge prior to offloading to the cloud.
Revised:  In this paper we introduce EDGY, a new lightweight disentangled representation learning model that transforms and filters high-dimensional voice data to identify and contain sensitive attributes at the edge prior to offloading to the cloud.
Edit intent: meaning-changed
Original:  Our experimental results show that EDGY runs in tens of milliseconds with  minimal performance penalties or accuracy losses in speech recognition using only a CPU and a single core ARM device without specialized hardware.
Revised:  Our experimental results show that EDGY runs in tens of milliseconds with 0.2\% relative improvement in ABX score or minimal performance penalties or accuracy losses in speech recognition using only a CPU and a single core ARM device without specialized hardware.
Edit intent: meaning-changed
Original: We propose a novel medical term embedding method named CODER, which stands for mediCal knOwledge embeDded tErm Representation . CODER is designed for medical term normalization by providing close vector representations for  terms that represent the same or similar concepts with multi-language support.
Revised: This paper proposes CODER: contrastive learning on knowledge graphs for cross-lingual medical term representation . CODER is designed for medical term normalization by providing close vector representations for terms that represent the same or similar concepts with multi-language support.
Edit intent: meaning-changed
Original: We propose a novel medical term embedding method named CODER, which stands for mediCal knOwledge embeDded tErm Representation . CODER is designed for medical term normalization by providing close vector representations for  terms that represent the same or similar concepts with multi-language support.
Revised: We propose a novel medical term embedding method named CODER, which stands for mediCal knOwledge embeDded tErm Representation . CODER is designed for medical term normalization by providing close vector representations for different terms that represent the same or similar concepts with multi-language support.
Edit intent: meaning-changed
Original: We propose a novel medical term embedding method named CODER, which stands for mediCal knOwledge embeDded tErm Representation . CODER is designed for medical term normalization by providing close vector representations for  terms that represent the same or similar concepts with multi-language support. CODER is trained on top of BERT (Devlin et al., 2018) with the innovation that token vector aggregation is trained using relations from the UMLS Metathesaurus (Bodenreider, 2004), which is a comprehensive medical knowledge graph with multi-language support .
Revised: We propose a novel medical term embedding method named CODER, which stands for mediCal knOwledge embeDded tErm Representation . CODER is designed for medical term normalization by providing close vector representations for terms that represent the same or similar medical concepts with cross-lingual support. We train CODER via contrastive learning on a medical knowledge graph with multi-language support .
Edit intent: meaning-changed
Original:  CODER is trained on top of BERT (Devlin et al., 2018) with the innovation that token vector aggregation is trained using relations from the UMLS Metathesaurus (Bodenreider, 2004), which is a comprehensive medical knowledge graph with multi-language support .
Revised:  CODER is trained on top of BERT (Devlin et al., 2018) with the innovation that token vector aggregation is trained using relations from the UMLS Metathesaurus (Bodenreider, 2004), which is a comprehensive medical knowledge graph (KG) named the Unified Medical Language System, where similarities are calculated utilizing both terms and relation triplets from KG .
Edit intent: meaning-changed
Original:  We evaluated CODER in term normalization, semantic similarity, and relation classification benchmarks, which showed that CODER outperformed various state-of-the-art biomedical word embeddings , concept embeddings, and contextual embeddings. 
Revised:  We evaluate CODER in zero-shot term normalization, semantic similarity, and relation classification benchmarks, which showed that CODER outperformed various state-of-the-art biomedical word embeddings , concept embeddings, and contextual embeddings. 
Edit intent: meaning-changed
Original:  We evaluated CODER in term normalization, semantic similarity, and relation classification benchmarks, which showed that CODER outperformed various state-of-the-art biomedical word embeddings , concept embeddings, and contextual embeddings. 
Revised:  We evaluated CODER in term normalization, semantic similarity, and relation classification benchmarks, which show that CODERoutperforms various state-of-the-art biomedical word embeddings , concept embeddings, and contextual embeddings. 
Edit intent: fluency
Original:  We evaluated CODER in term normalization, semantic similarity, and relation classification benchmarks, which showed that CODER outperformed various state-of-the-art biomedical word embeddings , concept embeddings, and contextual embeddings. 
Revised:  We evaluated CODER in term normalization, semantic similarity, and relation classification benchmarks, which showed that CODER outperformed various state-of-the-art biomedical word embedding , concept embeddings, and contextual embeddings. 
Edit intent: fluency
Original:  We evaluated CODER in term normalization, semantic similarity, and relation classification benchmarks, which showed that CODER outperformed various state-of-the-art biomedical word embeddings , concept embeddings, and contextual embeddings. 
Revised:  We evaluated CODER in term normalization, semantic similarity, and relation classification benchmarks, which showed that CODER outperformed various state-of-the-art biomedical word embeddings , concept embeddings, and contextual embeddings. Our codes and models are available at URL
Edit intent: meaning-changed
Original: Let \alpha=\{a_1,a_2,a_3,...,a_n\} be a set of elements, \delta < n be a positive integer, and \Gamma: \alpha \to \{0, 1, 2, ..., n\} be a total mapping.
Revised: Let \alpha=\{a_1,a_2,a_3,...,a_n\} be a set of elements, \delta < n be a non-negative integer, and \Gamma: \alpha \to \{0, 1, 2, ..., n\} be a total mapping.
Edit intent: meaning-changed
Original:  The so-far open issue that we close in this paper is regarding whether the \delta-partitions of \alpha can be computed without computing the partitions of \alpha in advance. As we show in this paper, this issue is not as trivial as it might seem at first sight, especially if any naive generate-and-test procedure has to be avoided.
Revised:  The so-far open issue that we close in this paper is regarding whether the \delta-partitions of \alpha in \Omega(n) time. On the opposite, a naive generate-and-test procedure has to be avoided.
Edit intent: meaning-changed
Original:  As we show in this paper, this issue is not as trivial as it might seem at first sight, especially if any naive generate-and-test procedure has to be avoided. To resolve this issue, we give a formal proof of the correctness of a smart backtracking algorithm that computes the \delta-partitions of \alpha efficiently without a prior construction of the partitions of~\alpha.
Revised:  As we show in this paper, this issue is not as trivial as it might seem at first sight, especially if any naive generate-and-test algorithm would compute all \delta-partitions of \alpha efficiently without a prior construction of the partitions of~\alpha.
Edit intent: clarity
Original:  To resolve this issue, we give a formal proof of the correctness of a smart backtracking algorithm that computes the \delta-partitions of \alpha efficiently without a prior construction of the partitions of~\alpha. The algorithm does so by checking (ahead) two properties identifying parts of the search space that are devoid of any \delta-partition of~\alpha .
Revised:  To resolve this issue, we give a formal proof of the correctness of a smart backtracking algorithm that computes the \delta-partitions of \alpha in \Omega(nB_n) time where B_n is the Bell number .
Edit intent: meaning-changed