wanyu/IteraTeR_v2 huggingface dataset:
Original: Eye gaze analysis is an important research problem in the field of computer vision and Human-Computer Interaction (HCI) . Even with significant progress in the last few years, automatic gaze analysis still remains challenging due to the individuality of eyes , eye-head interplay, occlusion, image quality, and illumination conditions.
Revised: Eye gaze analysis is an important research problem in the field of Computer Vision and Human-Computer Interaction (HCI) . Even with significant progress in the last few years, automatic gaze analysis still remains challenging due to the individuality of eyes , eye-head interplay, occlusion, image quality, and illumination conditions.
Edit intent: fluency
Original: Eye gaze analysis is an important research problem in the field of computer vision and Human-Computer Interaction (HCI) . Even with significant progress in the last few years, automatic gaze analysis still remains challenging due to the individuality of eyes , eye-head interplay, occlusion, image quality, and illumination conditions.
Revised: Eye gaze analysis is an important research problem in the field of computer vision and Human-Computer Interaction . Even with significant progress in the last few years, automatic gaze analysis still remains challenging due to the individuality of eyes , eye-head interplay, occlusion, image quality, and illumination conditions.
Edit intent: clarity
Original: Eye gaze analysis is an important research problem in the field of computer vision and Human-Computer Interaction (HCI) . Even with significant progress in the last few years, automatic gaze analysis still remains challenging due to the individuality of eyes , eye-head interplay, occlusion, image quality, and illumination conditions.
Revised: Eye gaze analysis is an important research problem in the field of computer vision and Human-Computer Interaction (HCI) . Even with notable progress in the last few years, automatic gaze analysis still remains challenging due to the individuality of eyes , eye-head interplay, occlusion, image quality, and illumination conditions.
Edit intent: fluency
Original: Eye gaze analysis is an important research problem in the field of computer vision and Human-Computer Interaction (HCI) . Even with significant progress in the last few years, automatic gaze analysis still remains challenging due to the individuality of eyes , eye-head interplay, occlusion, image quality, and illumination conditions.
Revised: Eye gaze analysis is an important research problem in the field of computer vision and Human-Computer Interaction (HCI) . Even with significant progress in the last few years, automatic gaze analysis still remains challenging due to the uniqueness of eye appearance , eye-head interplay, occlusion, image quality, and illumination conditions.
Edit intent: clarity
Original:  We review the progress across a range of gaze analysis tasks and applications to shed light on these fundamental questions;
Revised:  We review the progress across a range of gaze analysis tasks and applications to elucidate these fundamental questions;
Edit intent: clarity
Original:  We conclude by discussing future research directions for designing a real-world gaze analysis system that can propagate to other domains including computer vision, AR (Augmented Reality ), VR (Virtual Reality ), and HCI ( Human Computer Interaction ).
Revised:  We conclude by discussing future research directions for designing a real-world gaze analysis system that can propagate to other domains including Computer Vision, Augmented Reality (AR), Virtual Reality (VR ), VR (Virtual Reality ), and HCI ( Human Computer Interaction ).
Edit intent: clarity
Original:  We conclude by discussing future research directions for designing a real-world gaze analysis system that can propagate to other domains including computer vision, AR (Augmented Reality ), VR (Virtual Reality ), and HCI ( Human Computer Interaction ).
Revised:  We conclude by discussing future research directions for designing a real-world gaze analysis system that can propagate to other domains including computer vision, AR (Augmented Reality ), and HCI ( Human Computer Interaction ).
Edit intent: coherence
Original:  We conclude by discussing future research directions for designing a real-world gaze analysis system that can propagate to other domains including computer vision, AR (Augmented Reality ), VR (Virtual Reality ), and HCI ( Human Computer Interaction ).
Revised:  We conclude by discussing future research directions for designing a real-world gaze analysis system that can propagate to other domains including computer vision, AR (Augmented Reality ), VR (Virtual Reality ), and Human Computer Interaction ).
Edit intent: fluency
Original: Relative localization is a prerequisite for the cooperation of aerial swarms.
Revised: The vision-based relative localization can provide effective feedback for the cooperation of aerial swarms.
Edit intent: clarity
Original:  Inspired by bird flocks in nature , this letter proposes a novel distributed active vision-based relative localization framework for formation control in aerial swarms.
Revised:  Inspired by bird flocks in nature , this letter proposes a novel distributed active vision-based relative localization framework and apply it to formation control in aerial swarms.
Edit intent: coherence
Original:  Aiming at improving observation quality and formation accuracy , we devise graph-based attention planning (GAP) to determine the active observation scheme in the swarm.
Revised:  Aiming at improving observation quality and formation accuracy , we devise graph-based attention planning (GAP) to improve the observation quality of the active vision in the swarm.
Edit intent: clarity
Original:  Then active detection results are fused with onboard measurements from UWB and VIO to obtain real-time relative positions, which further improve the formation control performance . Real-world experiments show that the proposed active vision system enables the swarm agents to achieve agile flocking movements with an acceleration of 4 m/s^2 in circular formation tasks.
Revised:  Then active detection results are fused with onboard measurements from UWB and VIO to obtain real-time relative positions, which further improve the formation control performance of the swarm. Simulations and experiments demonstrate that the proposed active vision system enables the swarm agents to achieve agile flocking movements with an acceleration of 4 m/s^2 in circular formation tasks.
Edit intent: clarity
Original: We  revisit a key idea from the interaction of model theory and combinatorics, the existence of large ``indivisible'' sets, called `` \epsilon-excellent, '' in k-edge stable graphs (equivalently, Littlestone classes)  .
Revised: We revisit a key idea from the interaction of model theory and combinatorics, the existence of large "indivisible" sets, called `` \epsilon-excellent, '' in k-edge stable graphs (equivalently, Littlestone classes) .
Edit intent: fluency
Original: We  revisit a key idea from the interaction of model theory and combinatorics, the existence of large ``indivisible'' sets, called `` \epsilon-excellent, '' in k-edge stable graphs (equivalently, Littlestone classes)  .
Revised: We revisit a key idea from the interaction of model theory and combinatorics, the existence of large ``indivisible'' sets, called " \epsilon-excellent, '' in k-edge stable graphs (equivalently, Littlestone classes) .
Edit intent: fluency
Original: We  revisit a key idea from the interaction of model theory and combinatorics, the existence of large ``indivisible'' sets, called `` \epsilon-excellent, '' in k-edge stable graphs (equivalently, Littlestone classes)  .
Revised: We revisit a key idea from the interaction of model theory and combinatorics, the existence of large ``indivisible'' sets, called `` \epsilon-excellent, " in k-edge stable graphs (equivalently, Littlestone classes) .
Edit intent: fluency
Original:  Recent researches demonstrate that, considering the redundancy between different contrasts or modalities, a target MRI modality under-sampled in the k-space can be better reconstructed with the helps from a fully-sampled sequence (i.e., the reference modality ).
Revised:  Recent researches demonstrate that, considering the redundancy between different contrasts or modalities, a target MRI modality under-sampled in the k-space can be more efficiently reconstructed with a fully-sampled sequence (i.e., the reference modality ).
Edit intent: clarity
Original:  Recent researches demonstrate that, considering the redundancy between different contrasts or modalities, a target MRI modality under-sampled in the k-space can be better reconstructed with the helps from a fully-sampled sequence (i.e., the reference modality ).
Revised:  Recent researches demonstrate that, considering the redundancy between different contrasts or modalities, a target MRI modality under-sampled in the k-space can be better reconstructed with the helps from a fully-sampled MRI contrast as the reference modality ).
Edit intent: clarity
Original:  However, we find that  multi-modal reconstruction can be negatively affected by subtle spatial misalignment between different sequences , which is actually common in clinical practice.
Revised:  However, we find that multi-modal reconstruction can be negatively affected by subtle spatial misalignment between different contrasts , which is actually common in clinical practice.
Edit intent: clarity
Original:  In this paper,  we integrate the spatial alignment network with reconstruction, to improve the quality of the reconstructed target modality.
Revised:  In this paper, we integrate the spatial alignment network with multi-modal reconstruction towards better reconstruction quality of the reconstructed target modality.
Edit intent: clarity
Original:  In this paper,  we integrate the spatial alignment network with reconstruction, to improve the quality of the reconstructed target modality.
Revised:  In this paper, we integrate the spatial alignment network with reconstruction, to improve the quality of the target modality.
Edit intent: fluency
Original:  Specifically , the spatial alignment network estimates the spatial misalignment between the fully-sampled reference and the under-sampled target images, and warps the reference image accordingly.
Revised:  First , the spatial alignment network estimates the spatial misalignment between the fully-sampled reference and the under-sampled target images, and warps the reference image accordingly.
Edit intent: coherence
Original:  Then, the aligned fully-sampled reference image joins the  under-sampled target image in the reconstruction network, to produce the high-quality target image.
Revised:  Then, the aligned fully-sampled reference image joins the under-sampled target image.
Edit intent: clarity
Original:  Considering the contrast difference between the target and the reference  , we particularly design the cross-modality-synthesis-based registration loss, in combination with the reconstruction loss, to jointly train the spatial alignment network and the reconstruction network.
Revised:  Also, considering the contrast difference between the target and the reference , we particularly design the cross-modality-synthesis-based registration loss, in combination with the reconstruction loss, to jointly train the spatial alignment network and the reconstruction network.
Edit intent: coherence
Original:  Considering the contrast difference between the target and the reference  , we particularly design the cross-modality-synthesis-based registration loss, in combination with the reconstruction loss, to jointly train the spatial alignment network and the reconstruction network.
Revised:  Considering the contrast difference between the target and the reference images , we particularly design the cross-modality-synthesis-based registration loss, in combination with the reconstruction loss, to jointly train the spatial alignment network and the reconstruction network.
Edit intent: clarity
Original:  Our experiments on both clinical MRI and multi-coil k-space raw data demonstrate the superiority and robustness of  our spatial alignment network.
Revised:  Experiments on both clinical MRI and multi-coil k-space raw data demonstrate the superiority and robustness of our spatial alignment network.
Edit intent: clarity
Original:  Code is publicly available at URL
Revised:  Our code is publicly available at URL
Edit intent: clarity
Original:  These information "filter bubbles" and the growing challenge of information overload limit awareness across the literature , making it difficult to keep track of even narrow areas of interest, let alone discover new ones . Algorithmic curation and recommendation, which often prioritize relevance, can further reinforce these bubbles.
Revised:  These information "filter bubbles" and the growing challenge of information overload limit awareness across the literature , making it difficult to keep track of even narrow areas of interest, let alone discover new ones . Algorithmic curation and recommendation, which often prioritize relevance, can further reinforce these informational "filter bubbles."
Edit intent: clarity
Original:  In response, we describe Bridger, a system for facilitating discovery of scholars and their work, to explore design tradeoffs among relevant and novel recommendations.
Revised:  In response, we describe Bridger, a system for facilitating discovery of scholars and their work, to explore design tradeoffs between relevant and novel recommendations.
Edit intent: fluency
Original:  We construct a faceted representation of authors using information extracted from their papers and inferred personas.
Revised:  We construct a faceted representation of authors with information gleaned from their papers and inferred personas.
Edit intent: clarity
Original:  We develop an approach that locates commonalities  and contrasts between scientists---retrieving partially similar authors , rather than aiming for strict similarity.
Revised:  We develop an approach that locates commonalities and contrasts between scientists -- retrieving partially similar authors , rather than aiming for strict similarity.
Edit intent: fluency
Original:  We develop an approach that locates commonalities  and contrasts between scientists---retrieving partially similar authors , rather than aiming for strict similarity.
Revised:  We develop an approach that locates commonalities and contrasts between scientists---retrieving partially similar authors rather than aiming for strict similarity.
Edit intent: fluency
Original:  We find this approach helps users discover authors  useful for generating novel research ideas of relevance to their work, at a higher rate than a state-of-art neural model.
Revised:  We find this approach helps users discover authors useful for generating novel research directions, outperforming a state-of-art neural model.
Edit intent: clarity
Original: While automatic performance metrics are crucial for machine learn-ing of artificial human-like behaviour, the gold standard for eval-uation remains human judgement.
Revised: While automatic performance metrics are crucial for machine learning of artificial human-like behaviour, the gold standard for eval-uation remains human judgement.
Edit intent: fluency
Original: While automatic performance metrics are crucial for machine learn-ing of artificial human-like behaviour, the gold standard for eval-uation remains human judgement.
Revised: While automatic performance metrics are crucial for machine learn-ing of artificial human-like behaviour, the gold standard for evaluation remains human judgement.
Edit intent: fluency
Original:  The subjective evaluation ofartificial human-like behaviour in embodied conversational agentsis however expensive and little is known about the quality of thedata it returns.
Revised:  The subjective evaluation of artificial human-like behaviour in embodied conversational agentsis however expensive and little is known about the quality of thedata it returns.
Edit intent: fluency
Original:  The subjective evaluation ofartificial human-like behaviour in embodied conversational agentsis however expensive and little is known about the quality of thedata it returns.
Revised:  The subjective evaluation ofartificial human-like behaviour in embodied conversational agents is however expensive and little is known about the quality of thedata it returns.
Edit intent: fluency
Original:  The subjective evaluation ofartificial human-like behaviour in embodied conversational agentsis however expensive and little is known about the quality of thedata it returns.
Revised:  The subjective evaluation ofartificial human-like behaviour in embodied conversational agentsis however expensive and little is known about the quality of the data it returns.
Edit intent: fluency
Original:  Two approaches to subjective evaluation can belargely distinguished, one relying on ratings, the other on pairwisecomparisons .
Revised:  Two approaches to subjective evaluation can be largely distinguished, one relying on ratings, the other on pairwisecomparisons .
Edit intent: fluency
Original:  Two approaches to subjective evaluation can belargely distinguished, one relying on ratings, the other on pairwisecomparisons .
Revised:  Two approaches to subjective evaluation can belargely distinguished, one relying on ratings, the other on pairwise comparisons .
Edit intent: fluency
Original:  In this study we use co-speech gestures to comparethe two against each other and answer questions about their appro-priateness for evaluation of artificial behaviour.
Revised:  In this study we use co-speech gestures to compare the two against each other and answer questions about their appro-priateness for evaluation of artificial behaviour.
Edit intent: fluency
Original:  In this study we use co-speech gestures to comparethe two against each other and answer questions about their appro-priateness for evaluation of artificial behaviour.
Revised:  In this study we use co-speech gestures to comparethe two against each other and answer questions about their appropriateness for evaluation of artificial behaviour.
Edit intent: fluency
Original:  We consider theirability to rate quality, but also aspects pertaining to the effort of useand the time required to collect subjective data.
Revised:  We consider their ability to rate quality, but also aspects pertaining to the effort of useand the time required to collect subjective data.
Edit intent: fluency
Original:  We consider theirability to rate quality, but also aspects pertaining to the effort of useand the time required to collect subjective data.
Revised:  We consider theirability to rate quality, but also aspects pertaining to the effort of use and the time required to collect subjective data.
Edit intent: fluency
Original:  We use crowd sourc-ing to rate the quality of co-speech gestures in avatars, assessingwhich method picks up more detail in subjective assessments.
Revised:  We use crowd sourcing to rate the quality of co-speech gestures in avatars, assessingwhich method picks up more detail in subjective assessments.
Edit intent: fluency
Original:  We use crowd sourc-ing to rate the quality of co-speech gestures in avatars, assessingwhich method picks up more detail in subjective assessments.
Revised:  We use crowd sourc-ing to rate the quality of co-speech gestures in avatars, assessing which method picks up more detail in subjective assessments.
Edit intent: fluency
Original:  Wecompared gestures generated by three different machine learningmodels with various level of behavioural quality.
Revised:  We compared gestures generated by three different machine learningmodels with various level of behavioural quality.
Edit intent: fluency
Original:  Wecompared gestures generated by three different machine learningmodels with various level of behavioural quality.
Revised:  Wecompared gestures generated by three different machine learning models with various level of behavioural quality.
Edit intent: fluency
Original:  We found thatboth approaches were able to rank the videos according to qualityand that the ranking significantly correlated, showing that in termsof quality there is no preference of one method over the other.
Revised:  We found that both approaches were able to rank the videos according to qualityand that the ranking significantly correlated, showing that in termsof quality there is no preference of one method over the other.
Edit intent: fluency
Original:  We found thatboth approaches were able to rank the videos according to qualityand that the ranking significantly correlated, showing that in termsof quality there is no preference of one method over the other.
Revised:  We found thatboth approaches were able to rank the videos according to quality and that the ranking significantly correlated, showing that in termsof quality there is no preference of one method over the other.
Edit intent: fluency
Original:  We found thatboth approaches were able to rank the videos according to qualityand that the ranking significantly correlated, showing that in termsof quality there is no preference of one method over the other.
Revised:  We found thatboth approaches were able to rank the videos according to qualityand that the ranking significantly correlated, showing that in terms of quality there is no preference of one method over the other.
Edit intent: fluency
Original:  Wealso found that pairwise comparisons were slightly faster and camewith improved inter-rater reliability, suggesting that for small-scalestudies pairwise comparisons are to be favoured over ratings.
Revised:  We also found that pairwise comparisons were slightly faster and camewith improved inter-rater reliability, suggesting that for small-scalestudies pairwise comparisons are to be favoured over ratings.
Edit intent: fluency
Original:  Wealso found that pairwise comparisons were slightly faster and camewith improved inter-rater reliability, suggesting that for small-scalestudies pairwise comparisons are to be favoured over ratings.
Revised:  Wealso found that pairwise comparisons were slightly faster and came with improved inter-rater reliability, suggesting that for small-scalestudies pairwise comparisons are to be favoured over ratings.
Edit intent: fluency
Original:  Wealso found that pairwise comparisons were slightly faster and camewith improved inter-rater reliability, suggesting that for small-scalestudies pairwise comparisons are to be favoured over ratings.
Revised:  Wealso found that pairwise comparisons were slightly faster and camewith improved inter-rater reliability, suggesting that for small-scale studies pairwise comparisons are to be favoured over ratings.
Edit intent: fluency
Original:  In extensive experiments, we show that gesture properties related to gesture meaning (semantics and category) are predictable from text features (time-aligned BERT embeddings) alone, but not from prosodic audio features, while rhythm-related gesture properties (phase) on the other hand can be predicted from either audio , text(with word-level timing information), or both .
Revised:  In extensive experiments, we show that gesture properties related to gesture meaning (semantics and category) are predictable from text features (time-aligned BERT embeddings) alone, but not from prosodic audio features, while rhythm-related gesture properties (phase) on the other hand can be predicted from audio features better than from text .
Edit intent: clarity
Original:  Moreover, we assume that the individual risk assessments are  consistent with the respective second-order stochastic dominance relations.
Revised:  Moreover, individual risk assessments are consistent with the respective second-order stochastic dominance relations.
Edit intent: coherence
Original:  Moreover, we assume that the individual risk assessments are  consistent with the respective second-order stochastic dominance relations.
Revised:  Moreover, we assume that the individual risk assessments are assumed to be consistent with the respective second-order stochastic dominance relations.
Edit intent: fluency