wanyu/IteraTeR_full_sent huggingface dataset:
Original:  To provide at least 2 Mbps per user, 4G is often the cheapest option , whereas a minimum 10 Mbps per user is cheapest with 5G non-standalone (NSA) . The cost of meeting the UN Broadband Commission target of a minimum 10 Mbps per user is estimated at USD 1.4 trillion using 5G NSA, equating to approximately 0.5 \% of annual GDP for the developing world over the next decade.
Revised:  To provide at least 2 Mbps per user, 4G is often the cheapest option , whereas a minimum 10 Mbps per user is cheapest with 5G non-standalone (NSA) . The cost of meeting the UN Broadband Commission target of a minimum 10 Mbps per user is estimated at USD 1.4 trillion using 5G NSA, equating to approximately 0.6 \% of annual GDP for the developing world over the next decade.
Edit intent: meaning-changed
Original:  However, by creating a favorable regulatory environment, governments can bring down these costs by as much as three quarters to USD 0.5 trillion (approximately 0.2\% of annual GDP) - and avoid the need for public subsidy.
Revised:  However, by creating a favorable regulatory environment, governments can bring down these costs by as much as three quarters , to 0.5 trillion (approximately 0.2\% of annual GDP) - and avoid the need for public subsidy.
Edit intent: clarity
Original:  However, by creating a favorable regulatory environment, governments can bring down these costs by as much as three quarters to USD 0.5 trillion (approximately 0.2\% of annual GDP) - and avoid the need for public subsidy.
Revised:  However, by creating a favorable regulatory environment, governments can bring down these costs by as much as three quarters to USD 0.5 trillion (approximately 0.2\% of annual GDP) , and avoid the need for public subsidy.
Edit intent: fluency
Original:  The cost of meeting the UN Broadband Commission target of a minimum 10 Mbps per user is estimated at  1.7 trillion using 5G NSA, equating to approximately 0.6\% of annual GDP for the developing world over the next decade.
Revised:  The cost of meeting the UN Broadband Commission target of a minimum 10 Mbps per user is estimated at USD 1.7 trillion using 5G NSA, equating to approximately 0.6\% of annual GDP for the developing world over the next decade.
Edit intent: clarity
Original:  However, by creating a favorable regulatory environment, governments can bring down these costs by as much as three quarters, to  0.5 trillion (approximately 0.2\% of annual GDP), and avoid the need for public subsidy.
Revised:  However, by creating a favorable regulatory environment, governments can bring down these costs by as much as three quarters, to USD 0.5 trillion (approximately 0.2\% of annual GDP), and avoid the need for public subsidy.
Edit intent: clarity
Original:  Utilizing remote sensing and geospatial infrastructure simulation , least-cost network designs are developed for eight representative low and middle-income countries (Malawi, Uganda, Kenya, Senegal, Pakistan, Albania, Peru and Mexico), the results from which form the basis for aggregation to the global level.
Revised:  Utilizing remote sensing and demand forecasting , least-cost network designs are developed for eight representative low and middle-income countries (Malawi, Uganda, Kenya, Senegal, Pakistan, Albania, Peru and Mexico), the results from which form the basis for aggregation to the global level.
Edit intent: clarity
Original:  The cost of meeting the UN Broadband Commission target of a minimum 10 Mbps per user is estimated at USD 1.7 trillion using 5G NSA, equating to approximately 0.6\% of annual GDP for the developing world over the next decade.
Revised:  The cost of meeting a minimum 10 Mbps per user is estimated at USD 1.7 trillion using 5G NSA, equating to approximately 0.6\% of annual GDP for the developing world over the next decade.
Edit intent: clarity
Original:  The cost of meeting the UN Broadband Commission target of a minimum 10 Mbps per user is estimated at USD 1.7 trillion using 5G NSA, equating to approximately 0.6\% of annual GDP for the developing world over the next decade.
Revised:  The cost of meeting the UN Broadband Commission target of a minimum 10 Mbps per user is estimated at USD 1.7 trillion using 5G Non-Standalone, approximately 0.6\% of annual GDP for the developing world over the next decade.
Edit intent: meaning-changed
Original: Virtual reality has the potential to change the way we create and consume content in our everyday life. Entertainment, training, design and manufacturing, communication, or advertising are all applications that already benefit from this new medium reaching consumer level. VR is inherently different from traditional media: it offers a more immersive experience, and has the ability to elicit a sense of presence through the place and plausibility illusions. It also gives the user unprecedented capabilities to explore their environment, in contrast with traditional media.
Revised: Virtual reality has the potential to change the way we create and consume content .
Edit intent: coherence
Original:  Therefore, the sensory cues that are available in a virtual environment can be leveraged to enhance the final experience. This may include increasing realism, or the sense of presence; predicting or guiding the attention of the user through the experience; or increasing their performance if the experience involves the completion of certain tasks. In this state-of-the-art report, we survey the body of work addressing multimodality in virtual reality, its role and benefits in the final user experience.
Revised:  In this survey, we review the body of work addressing multimodality in virtual reality, its role and benefits in the final user experience.
Edit intent: clarity
Original:  In this state-of-the-art report, we survey the body of work addressing multimodality in virtual reality, its role and benefits in the final user experience. The works here reviewed thus encompass several fields of research, including computer graphics, human computer interaction, or psychology and perception.
Revised:  In this state-of-the-art report, we survey the body of work addressing multimodality in virtual reality, its role and benefits in user experience, together with different applications that leverage multimodality in many disciplines. These works thus encompass several fields of research, including computer graphics, human computer interaction, or psychology and perception.
Edit intent: meaning-changed
Original:  The works here reviewed thus encompass several fields of research, including computer graphics, human computer interaction, or psychology and perception. Additionally, we give an overview of different applications that leverage multimodal input in areas such as medicine, training and education, or entertainment; we include works in which the integration of multiple sensory information yields significant improvements, demonstrating how multimodality can play a fundamental role in the way VRsystems are designed, and VR experiences created and consumed .
Revised:  The works here reviewed thus encompass several fields of research, and demonstrate that multimodality plays a fundamental role in the way VRsystems are designed, and VR experiences created and consumed .
Edit intent: coherence
Original:  we include works in which the integration of multiple sensory information yields significant improvements, demonstrating how multimodality can play a fundamental role in the way VRsystems are designed, and VR experiences created and consumed .
Revised:  we include works in which the integration of multiple sensory information yields significant improvements, demonstrating how multimodality can play a fundamental role in VR; enhancing the experience, improving overall performance, and yielding unprecedented abilities in skill and knowledge transfer .
Edit intent: meaning-changed
Original:  For this purpose, we use stated preferences of over 1000 Indian consumers and present the first estimates of the additional purchase price that Indian consumers are willing to pay to improve the electric vehicle attributes(e.g., driving range) .
Revised:  This study contributes to the EV demand literature in the Indian context by (a) analysing the EV attributes and attitudinal factors of Indian car buyers that determine consumers' preferences for EVs, (b) estimating Indian consumers' willingness to pay (WTP) to buy EVs with improved attributes, and c) quantifying how the reference dependence affects the WTP estimates .
Edit intent: meaning-changed
Original:  We adopt a hybrid choice modelling framework to simultaneously model the willingness to pay and the effect of consumers' latent attitudes (e. g., hedonic and symbolic values) on their likelihood to adopt electric vehicles. We also account for reference dependence by considering a conventional vehicle as the reference alternative and illustrate that the resulting willingness to pay estimates are more realistic . Based on our results , Indian consumers are willing to pay  additional USD 10-34 in  purchase price to reduce the fast charging time by 1 minute, USD 7-40 to add a kilometre to the driving range of electric vehicle at 200 kilometres, and USD 104-692 to save USD 1 per 100 kilometres in operating cost.
Revised:  We adopt a hybrid choice modelling approach for the above analysis. The results indicate that accounting for reference dependence by considering a conventional vehicle as the reference alternative and illustrate that the resulting willingness to pay estimates are more realistic . Based on our results , Indian consumers are willing to pay additional USD 10-34 in purchase price to reduce the fast charging time by 1 minute, USD 7-40 to add a kilometre to the driving range of electric vehicle at 200 kilometres, and USD 104-692 to save USD 1 per 100 kilometres in operating cost.
Edit intent: clarity
Original:  We also account for reference dependence by considering a conventional vehicle as the reference alternative and illustrate that the resulting willingness to pay estimates are more realistic . Based on our results , Indian consumers are willing to pay  additional USD 10-34 in  purchase price to reduce the fast charging time by 1 minute, USD 7-40 to add a kilometre to the driving range of electric vehicle at 200 kilometres, and USD 104-692 to save USD 1 per 100 kilometres in operating cost.
Revised:  We also account for reference dependence provides more realistic WTP estimates than the standard utility estimation approach. Our results suggest that Indian consumers are willing to pay additional USD 10-34 in purchase price to reduce the fast charging time by 1 minute, USD 7-40 to add a kilometre to the driving range of electric vehicle at 200 kilometres, and USD 104-692 to save USD 1 per 100 kilometres in operating cost.
Edit intent: clarity
Original:  We also account for reference dependence by considering a conventional vehicle as the reference alternative and illustrate that the resulting willingness to pay estimates are more realistic . Based on our results , Indian consumers are willing to pay  additional USD 10-34 in  purchase price to reduce the fast charging time by 1 minute, USD 7-40 to add a kilometre to the driving range of electric vehicle at 200 kilometres, and USD 104-692 to save USD 1 per 100 kilometres in operating cost.
Revised:  We also account for reference dependence by considering a conventional vehicle as the reference alternative and illustrate that the resulting willingness to pay estimates are more realistic . Based on our results , Indian consumers are willing to pay an additional USD 10-34 in purchase price to reduce the fast charging time by 1 minute, USD 7-40 to add a kilometre to the driving range of electric vehicle at 200 kilometres, and USD 104-692 to save USD 1 per 100 kilometres in operating cost.
Edit intent: fluency
Original:  We also account for reference dependence by considering a conventional vehicle as the reference alternative and illustrate that the resulting willingness to pay estimates are more realistic . Based on our results , Indian consumers are willing to pay  additional USD 10-34 in  purchase price to reduce the fast charging time by 1 minute, USD 7-40 to add a kilometre to the driving range of electric vehicle at 200 kilometres, and USD 104-692 to save USD 1 per 100 kilometres in operating cost.
Revised:  We also account for reference dependence by considering a conventional vehicle as the reference alternative and illustrate that the resulting willingness to pay estimates are more realistic . Based on our results , Indian consumers are willing to pay additional USD 10-34 in the purchase price to reduce the fast charging time by 1 minute, USD 7-40 to add a kilometre to the driving range of electric vehicle at 200 kilometres, and USD 104-692 to save USD 1 per 100 kilometres in operating cost.
Edit intent: fluency
Original:  We also account for reference dependence by considering a conventional vehicle as the reference alternative and illustrate that the resulting willingness to pay estimates are more realistic . Based on our results , Indian consumers are willing to pay  additional USD 10-34 in  purchase price to reduce the fast charging time by 1 minute, USD 7-40 to add a kilometre to the driving range of electric vehicle at 200 kilometres, and USD 104-692 to save USD 1 per 100 kilometres in operating cost.
Revised:  We also account for reference dependence by considering a conventional vehicle as the reference alternative and illustrate that the resulting willingness to pay estimates are more realistic . Based on our results , Indian consumers are willing to pay additional USD 10-34 in purchase price to reduce the fast charging time by 1 minute, USD 7-40 to add a kilometre to the driving range of EVs at 200 kilometres, and USD 104-692 to save USD 1 per 100 kilometres in operating cost.
Edit intent: fluency
Original:  These estimates and the effect of attitudes on the likelihood to adopt electric vehicles provide insights about electric vehicle design, marketing strategies, and pro-electric-vehicle policies (e.g., specialised lanes and reserved parking for electric vehicles ) to expedite the adoption of electric vehicles in India.
Revised:  These estimates and the effect of attitudes on the likelihood to adopt EVs provide insights about electric vehicle design, marketing strategies, and pro-electric-vehicle policies (e.g., specialised lanes and reserved parking for electric vehicles ) to expedite the adoption of electric vehicles in India.
Edit intent: clarity
Original:  These estimates and the effect of attitudes on the likelihood to adopt electric vehicles provide insights about electric vehicle design, marketing strategies, and pro-electric-vehicle policies (e.g., specialised lanes and reserved parking for electric vehicles ) to expedite the adoption of electric vehicles in India.
Revised:  These estimates and the effect of attitudes on the likelihood to adopt electric vehicles provide insights about EV design, marketing strategies, and pro-electric-vehicle policies (e.g., specialised lanes and reserved parking for electric vehicles ) to expedite the adoption of electric vehicles in India.
Edit intent: clarity
Original:  These estimates and the effect of attitudes on the likelihood to adopt electric vehicles provide insights about electric vehicle design, marketing strategies, and pro-electric-vehicle policies (e.g., specialised lanes and reserved parking for electric vehicles ) to expedite the adoption of electric vehicles in India.
Revised:  These estimates and the effect of attitudes on the likelihood to adopt electric vehicles provide insights about electric vehicle design, marketing strategies, and pro-EV policies (e.g., specialised lanes and reserved parking for electric vehicles ) to expedite the adoption of electric vehicles in India.
Edit intent: clarity
Original:  These estimates and the effect of attitudes on the likelihood to adopt electric vehicles provide insights about electric vehicle design, marketing strategies, and pro-electric-vehicle policies (e.g., specialised lanes and reserved parking for electric vehicles ) to expedite the adoption of electric vehicles in India.
Revised:  These estimates and the effect of attitudes on the likelihood to adopt electric vehicles provide insights about electric vehicle design, marketing strategies, and pro-electric-vehicle policies (e.g., specialised lanes and reserved parking for EVs ) to expedite the adoption of electric vehicles in India.
Edit intent: clarity
Original:  These estimates and the effect of attitudes on the likelihood to adopt electric vehicles provide insights about electric vehicle design, marketing strategies, and pro-electric-vehicle policies (e.g., specialised lanes and reserved parking for electric vehicles ) to expedite the adoption of electric vehicles in India.
Revised:  These estimates and the effect of attitudes on the likelihood to adopt electric vehicles provide insights about electric vehicle design, marketing strategies, and pro-electric-vehicle policies (e.g., specialised lanes and reserved parking for electric vehicles ) to expedite the adoption of EVs in India.
Edit intent: style
Original:  We are the first to thoroughly investigate this powerful combination in sequence tagging . We find that taggers based on deep pre-trained models can benefit from Bayesian query strategies with the help of the Monte Carlo (MC) dropout.
Revised:  We are the first to thoroughly investigate this powerful combination for the sequence tagging task. We conduct an extensive empirical study of various Bayesian uncertainty estimation methods and Monte Carlo dropout options for deep pre-trained models can benefit from Bayesian query strategies with the help of the Monte Carlo (MC) dropout.
Edit intent: meaning-changed
Original:  We find that taggers based on deep pre-trained models can benefit from Bayesian query strategies with the help of the Monte Carlo (MC) dropout. Results of experiments with various uncertainty estimates and MC dropout variants show that the Bayesian active learning by disagreement query strategy coupled with the MC dropout applied only in the classification layer of a Transformer-based tagger is the best option in terms of quality. This option also has very little computational overhead. We also demonstrate that it is possible to reduce the computational overhead of AL by using a smaller distilled versionof a Transformer model for acquiring instances during AL .
Revised:  We find that taggers based on deep pre-trained models in the active learning framework and find the best combinations for different types of models. Besides, we also demonstrate that to acquire instances during active learning, a full-size Transformer can be substituted with a distilled version, which yields better computational performance and reduces obstacles for applying deep active learning in practice .
Edit intent: coherence
Original:  To make this data immediately useful for a wide area of researchers , we further enhance the data with cluster labels computed from the retweet graph, user suspension status, and  perceptual hashes of tweeted images.
Revised:  To make this data immediately useful for a diverse set of research projects , we further enhance the data with cluster labels computed from the retweet graph, user suspension status, and perceptual hashes of tweeted images.
Edit intent: clarity
Original:  To make this data immediately useful for a wide area of researchers , we further enhance the data with cluster labels computed from the retweet graph, user suspension status, and  perceptual hashes of tweeted images.
Revised:  To make this data immediately useful for a wide area of researchers , we further enhance the data with cluster labels computed from the retweet graph, each user's suspension status, and perceptual hashes of tweeted images.
Edit intent: clarity
Original:  To make this data immediately useful for a wide area of researchers , we further enhance the data with cluster labels computed from the retweet graph, user suspension status, and  perceptual hashes of tweeted images.
Revised:  To make this data immediately useful for a wide area of researchers , we further enhance the data with cluster labels computed from the retweet graph, user suspension status, and the perceptual hashes of tweeted images.
Edit intent: fluency
Original:  We find that policies learned in this way allow for interpretable table-to-text and headline generation that is competitive with or better than state-of-the-art autoregressive token-level policies in terms of automatic metrics, and moreover allows for fasterdecoding .
Revised:  We find that policies learned in this way allow for interpretable table-to-text or headline generation that is competitive with or better than state-of-the-art autoregressive token-level policies in terms of automatic metrics, and moreover allows for fasterdecoding .
Edit intent: fluency
Original:  We find that policies learned in this way allow for interpretable table-to-text and headline generation that is competitive with or better than state-of-the-art autoregressive token-level policies in terms of automatic metrics, and moreover allows for fasterdecoding .
Revised:  We find that policies learned in this way allow for interpretable table-to-text and headline generation that is competitive with neighbor-based token-level policies in terms of automatic metrics, and moreover allows for fasterdecoding .
Edit intent: clarity
Original:  We find that policies learned in this way allow for interpretable table-to-text and headline generation that is competitive with or better than state-of-the-art autoregressive token-level policies in terms of automatic metrics, and moreover allows for fasterdecoding .
Revised:  We find that policies learned in this way allow for interpretable table-to-text and headline generation that is competitive with or better than state-of-the-art autoregressive token-level policies on automatic metrics, and moreover allows for fasterdecoding .
Edit intent: clarity
Original:  We find that policies learned in this way allow for interpretable table-to-text and headline generation that is competitive with or better than state-of-the-art autoregressive token-level policies in terms of automatic metrics, and moreover allows for fasterdecoding .
Revised:  We find that policies learned in this way allow for interpretable table-to-text and headline generation that is competitive with or better than state-of-the-art autoregressive token-level policies in terms of automatic metrics, though on all but one dataset neighbor-based policies underperform a strong neighborless baseline. In all cases, however, generating by splicing is faster .
Edit intent: meaning-changed
Original:  We show the following paradox . There are basic well-conditioned problems in scientific computing where one can prove the existence of NNs with great approximation qualities, however, there does not exist any algorithm, even randomised, that can train (or compute) such a NN. Indeed, for any positive integers K > 2 and L, there are cases where simultaneously:
Revised:  We address this paradox by demonstrating basic well-conditioned problems in scientific computing where one can prove the existence of NNs with great approximation qualities, however, there does not exist any algorithm, even randomised, that can train (or compute) such a NN. Indeed, for any positive integers K > 2 and L, there are cases where simultaneously:
Edit intent: clarity
Original:  There are basic well-conditioned problems in scientific computing where one can prove the existence of NNs with great approximation qualities, however, there does not exist any algorithm, even randomised, that can train (or compute) such a NN. Indeed, for any positive integers K > 2 and L, there are cases where simultaneously:
Revised:  There are basic well-conditioned problems in scientific computing where one can prove the existence of NNs with great approximation qualities, however, there does not exist any algorithm, even randomised, that can train (or compute) such a NN. For any positive integers K > 2 and L, there are cases where simultaneously:
Edit intent: coherence