wanyu/IteraTeR_v2 huggingface dataset:
Original:  The TERRA-REF program deployed a suite of high resolution , cutting edge technology sensors on a gantry system with the aim of scanning 1 hectare ( ~ 10^4 m ) at around 1 mm^2 spatial resolution multiple times per week.
Revised:  The TERRA-REF program deployed a suite of high-resolution , cutting edge technology sensors on a gantry system with the aim of scanning 1 hectare ( ~ 10^4 m ) at around 1 mm^2 spatial resolution multiple times per week.
Edit intent: fluency
Original:  The TERRA-REF program deployed a suite of high resolution , cutting edge technology sensors on a gantry system with the aim of scanning 1 hectare ( ~ 10^4 m ) at around 1 mm^2 spatial resolution multiple times per week.
Revised:  The TERRA-REF program deployed a suite of high resolution , cutting edge technology sensors on a gantry system with the aim of scanning 1 hectare ( 10^4 m ) at around 1 mm^2 spatial resolution multiple times per week.
Edit intent: fluency
Original:  The TERRA-REF program deployed a suite of high resolution , cutting edge technology sensors on a gantry system with the aim of scanning 1 hectare ( ~ 10^4 m ) at around 1 mm^2 spatial resolution multiple times per week.
Revised:  The TERRA-REF program deployed a suite of high resolution , cutting edge technology sensors on a gantry system with the aim of scanning 1 hectare ( ~ 10^4 ) at around 1 mm^2 spatial resolution multiple times per week.
Edit intent: clarity
Original:  Associated weather and environmental measurements, information about agronomic management and experimental design, and the genomic sequences of hundreds of plant varieties have been collected and are available alongside the sensor and plant trait (phenotype ) data.
Revised:  Associated weather and environmental measurements, information about agronomic management and experimental design, and the genomic sequences of hundreds of plant varieties have been collected and are available alongside the sensor and plant phenotype data.
Edit intent: clarity
Original:  This focus of this paper is to provide the Computer Vision and Machine Learning communities an overview of the available data and some potential applications of this one of a kind data.
Revised:  The focus of this paper is to provide the Computer Vision and Machine Learning communities an overview of the available data and some potential applications of this one of a kind data.
Edit intent: fluency
Original: Cell division, aging, and stress recovery triggers the spatial reorganization of cellular components in the cytoplasm, but also of membrane bound organelles, with molecular changes in their compositions and structures.
Revised: Cell division, aging, and stress recovery triggers spatial reorganization of cellular components in the cytoplasm, but also of membrane bound organelles, with molecular changes in their compositions and structures.
Edit intent: fluency
Original: Cell division, aging, and stress recovery triggers the spatial reorganization of cellular components in the cytoplasm, but also of membrane bound organelles, with molecular changes in their compositions and structures.
Revised: Cell division, aging, and stress recovery triggers the spatial reorganization of cellular components in the cytoplasm, including membrane bound organelles, with molecular changes in their compositions and structures.
Edit intent: clarity
Original:  We use the budding yeast Saccharomyces cerevisiae as a model eukaryotic unicellular organism to study these questions using recent progress in optical fluorescence microscopy and crowding sensing probe technology.
Revised:  We use the budding yeast Saccharomyces cerevisiae as a model system to study these questions using recent progress in optical fluorescence microscopy and crowding sensing probe technology.
Edit intent: clarity
Original:  We used a F\"orster Resonance Energy Transfer (FRET) based sensor, illuminated by confocal microscopy for high throughput analyses and Slimfield microscopy for single-molecule resolution, to quantify molecular crowding.
Revised:  We used a F\"{o Resonance Energy Transfer (FRET) based sensor, illuminated by confocal microscopy for high throughput analyses and Slimfield microscopy for single-molecule resolution, to quantify molecular crowding.
Edit intent: fluency
Original:  We determine crowding in response to growth and osmotic stress, and its dependence on mother and daughter cells during division, and find unexpectedly the presence of hot spots of crowding across the bud neck in the burgeoning daughter cell , which might be rationalized by the packing of inherited material, like the vacuole, from mother cells.
Revised:  We determine crowding in response to cellular growth of both mother and daughter cells during division, and find unexpectedly the presence of hot spots of crowding across the bud neck in the burgeoning daughter cell , which might be rationalized by the packing of inherited material, like the vacuole, from mother cells.
Edit intent: clarity
Original:  We determine crowding in response to growth and osmotic stress, and its dependence on mother and daughter cells during division, and find unexpectedly the presence of hot spots of crowding across the bud neck in the burgeoning daughter cell , which might be rationalized by the packing of inherited material, like the vacuole, from mother cells.
Revised:  We determine crowding in response to growth and osmotic stress, and its dependence on mother and daughter cells during division, and find unexpectedly the presence of hot spots of crowding across the bud neck in the burgeoning daughter cell . This crowding might be rationalized by the packing of inherited material, like the vacuole, from mother cells.
Edit intent: clarity
Original:  We discuss recent advances in understanding the role of crowding in cellular regulation and key current challenges , and conclude by presenting our recent advances in optimizing FRET-based measurements of crowding whilst simultaneously imaging a third colour , which can be used as an organelle marker and to readout membrane morphology .
Revised:  We discuss recent advances in understanding the role of crowding in cellular regulation and key current challenges and conclude by presenting our recent advances in optimizing FRET-based measurements of crowding whilst simultaneously imaging a third colour , which can be used as an organelle marker and to readout membrane morphology .
Edit intent: fluency
Original:  We discuss recent advances in understanding the role of crowding in cellular regulation and key current challenges , and conclude by presenting our recent advances in optimizing FRET-based measurements of crowding whilst simultaneously imaging a third colour , which can be used as an organelle marker and to readout membrane morphology .
Revised:  We discuss recent advances in understanding the role of crowding in cellular regulation and key current challenges , and conclude by presenting our recent advances in optimizing FRET-based measurements of crowding whilst simultaneously imaging a third color , which can be used as an organelle marker and to readout membrane morphology .
Edit intent: fluency
Original:  We discuss recent advances in understanding the role of crowding in cellular regulation and key current challenges , and conclude by presenting our recent advances in optimizing FRET-based measurements of crowding whilst simultaneously imaging a third colour , which can be used as an organelle marker and to readout membrane morphology .
Revised:  We discuss recent advances in understanding the role of crowding in cellular regulation and key current challenges , and conclude by presenting our recent advances in optimizing FRET-based measurements of crowding whilst simultaneously imaging a third colour , which can be used as a marker that labels organelle membranes .
Edit intent: clarity
Original:  Also, in MTL,  binary-branch architecture more adequately utilizes information from two levels than a uni-branch model.
Revised:  Also, in MTL, a binary-branch architecture more adequately utilizes information from two levels than a uni-branch model.
Edit intent: fluency
Original:  Models can handle both segment-level and utterance-level predictions simultaneously overall under  binary-branch multi-task architecture.
Revised:  Models can handle both segment-level and utterance-level predictions simultaneously overall under a binary-branch multi-task architecture.
Edit intent: fluency
Original:  Monocular 3D detection, as an economical solution compared to conventional settings relying on binocular vision or LiDAR, has drawn increasing attention recently but still yields unsatisfactory results.
Revised:  Monocular 3D detection, as an economical solution compared to conventional settings relying on LiDARs. It has drawn increasing attention recently but still yields unsatisfactory results.
Edit intent: clarity
Original:  This paper first presents a systematic study on this problem and observes that the current monocular 3D detection problem can be simplified as an instance depth estimation problem: The inaccurate instance depth blocks all the other 3D attribute predictions from improving the overall detection performance.
Revised:  This paper first presents a systematic study on this problem . We observe that the current monocular 3D detection problem can be simplified as an instance depth estimation problem: The inaccurate instance depth blocks all the other 3D attribute predictions from improving the overall detection performance.
Edit intent: coherence
Original:  This paper first presents a systematic study on this problem and observes that the current monocular 3D detection problem can be simplified as an instance depth estimation problem: The inaccurate instance depth blocks all the other 3D attribute predictions from improving the overall detection performance.
Revised:  This paper first presents a systematic study on this problem and observes that the current monocular 3D detection can be simplified as an instance depth estimation problem: The inaccurate instance depth blocks all the other 3D attribute predictions from improving the overall detection performance.
Edit intent: fluency
Original:  However, recent methods directly estimate the depth based on isolated instances or pixels while ignoring the geometric relations across different objects , which can be valuable constraints as the key information about depth is not directly manifest in the monocular image.
Revised:  However, recent methods directly estimate the depth based on isolated instances or pixels while ignoring the geometric relations across different objects . These geometric relations can be valuable constraints as the key information about depth is not directly manifest in the monocular image.
Edit intent: clarity
Original:  Despite the simplicity of the basic idea, our method obtains significant improvements on KITTI and nuScenes benchmarks, achieving the 1st place out of all monocular vision-only methods while still maintaining real-time efficiency.
Revised:  Despite the simplicity of the basic idea, our method obtains significant improvements on KITTI and nuScenes benchmarks, achieving 1st place out of all monocular vision-only methods while still maintaining real-time efficiency.
Edit intent: fluency
Original:  Monocular 3D detection, as a representative general setting among image-based approaches, provides a more economical solution than conventional settings relying on LiDARs . It has drawn increasing attention recently but still yields unsatisfactory results.
Revised:  Monocular 3D detection, as a representative general setting among image-based approaches, provides a more economical solution than conventional settings relying on LiDARs but still yields unsatisfactory results.
Edit intent: coherence
Original:  However , recent methods directly estimate the depth based on isolated instances or pixels while ignoring the geometric relations across different objects.
Revised:  Moreover , recent methods directly estimate the depth based on isolated instances or pixels while ignoring the geometric relations across different objects.
Edit intent: coherence
Original: Transferability of adversarial examples is of central importance for attacking an unknown model, which facilitates adversarial attacks in more practical scenarios, e.g., blackbox attacks.
Revised: Transferability of adversarial examples is of central importance for attacking an unknown model, which facilitates adversarial attacks in more practical scenarios, e.g., black-box attacks.
Edit intent: fluency
Original: We introduce a new image segmentation task, termed Entity Segmentation (ES) with the aim to segment all visual entities  in an image without considering semantic category labels.
Revised: We introduce a new image segmentation task, called Entity Segmentation (ES) with the aim to segment all visual entities in an image without considering semantic category labels.
Edit intent: fluency
Original: We introduce a new image segmentation task, termed Entity Segmentation (ES) with the aim to segment all visual entities  in an image without considering semantic category labels.
Revised: We introduce a new image segmentation task, termed Entity Segmentation (ES) , which aims to segment all visual entities in an image without considering semantic category labels.
Edit intent: coherence
Original:  It has many practical applications in image manipulation / editing where the segmentation mask quality is typically crucial but category labels are less important.
Revised:  It has many practical applications such as image manipulation and editing where the segmentation mask quality is typically crucial but category labels are less important.
Edit intent: clarity
Original:  It has many practical applications in image manipulation / editing where the segmentation mask quality is typically crucial but category labels are less important.
Revised:  It has many practical applications in image manipulation / editing where the quality of segmentation masks is crucial but class labels are less important.
Edit intent: clarity
Original:  (2) any model trained on one dataset can generalize exceptionally well to other datasets with unseen domains.
Revised:  (2) any model trained on one dataset can generalize exceptionally well to other test datasets of unseen domains.
Edit intent: clarity
Original:  Our code is made publicly available at URL
Revised:  The code has been released at URL
Edit intent: clarity
Original:  Moreover, we fully re-labeled the test set of a popular but noisy real-world scene dataset ScanNetV2 to make it clean, for rigorous experiment and future research.
Revised:  Moreover, we fully re-labeled the validation set of a popular but noisy real-world scene dataset ScanNetV2 to make it clean, for rigorous experiment and future research.
Edit intent: clarity
Original:  Our code and data will be available at URL
Revised:  Our code and data are available at URL
Edit intent: clarity
Original:  In this paper , we propose a learnable compression network with transformer (LCNT) , which projects feature vectors from high dimensional space onto low dimensional space, while preserving neighbor relationship .
Revised:  In this paper , we propose a new network structure called Compression Network with Transformer (CNT) to compress the feature into a low dimensional space, while preserving neighbor relationship .
Edit intent: clarity
Original:  To evaluate the effectiveness of the proposed model, we conduct experimentson two million-scale databases, GIST1M and Deep1M.
Edit intent: coherence
Original:  We equip ManiSkill with  high-quality demonstrations to facilitate learning-from-demonstrations approaches and perform evaluations on common baseline algorithms.
Revised:  We equip ManiSkill with high-quality demonstrations to facilitate learning-from-demonstrations approaches and perform evaluations on baseline algorithms.
Edit intent: clarity
Original:  We believe  ManiSkill can encourage the robot learning community to explore more on learning generalizable object manipulation skills.
Revised:  We believe that ManiSkill can encourage the robot learning community to explore more on learning generalizable object manipulation skills.
Edit intent: fluency
Original: Learning generalizable manipulation skills is central for robots to achieve task automation in environments with endless scene and object variations .
Revised: Object manipulation from 3D visual inputs poses many challenges on building generalizable perception and policy models .
Edit intent: clarity
Original:  However, existing robot learning environments are limited in both scale and diversity of 3D assets (especially of articulated objects), making it difficult to train and evaluate the generalization ability of agents over novel objects.
Revised:  However, 3D assets in existing benchmarks mostly lack the diversity of 3D assets (especially of articulated objects), making it difficult to train and evaluate the generalization ability of agents over novel objects.
Edit intent: clarity
Original:  In this work, we focus on object-level generalization and propose SAPIEN Manipulation Skill Benchmark ( abbreviated as ManiSkill) , a large-scale learning-from-demonstrations benchmark for articulated object manipulation with 3D visual input (point cloud and RGB-D image).
Revised:  In this work, we focus on object-level generalization and propose SAPIEN Manipulation Skill Benchmark ( ManiSkill) to benchmark manipulation skills over diverse objects in a full-physics simulator. 3D visual input (point cloud and RGB-D image).
Edit intent: clarity
Original:  This class encompasses popular methods such as the Euler-Maruyama scheme and the ones based on splitting strategies.
Revised:  This class encompasses popular methods such as the Euler-Maruyama scheme and the schemes based on splitting strategies.
Edit intent: clarity
Original:  This kind of result is a prime interest to obtain estimates on norms of solutions to Poisson equations associated with a given scheme .
Revised:  This kind of result is of prime interest to obtain estimates on norms of solutions to Poisson equations associated with a given scheme .
Edit intent: clarity
Original:  This kind of result is a prime interest to obtain estimates on norms of solutions to Poisson equations associated with a given scheme .
Revised:  This kind of result is a prime interest to obtain estimates on norms of solutions to Poisson equations associated with a given numerical method .
Edit intent: clarity
Original: Deep neural networks represent a powerful option for many real-world applications due to their ability to model even complex data relations.
Revised: Deep neural networks represent a powerful approach for many real-world applications due to their ability to model even complex data relations.
Edit intent: clarity
Original:  Still , if a particular input (called trigger) is fed into a neural network, the network will respond with a wrong result.
Revised:  Then , if a particular input (called trigger) is fed into a neural network, the network will respond with a wrong result.
Edit intent: fluency
Original:  In this work, we explore the option of backdoor attacks to automatic speech recognition systems where we inject inaudible triggers.
Revised:  In this work, we explore backdoor attacks for automatic speech recognition systems where we inject inaudible triggers.
Edit intent: clarity
Original:  We conduct experiments on two versions of datasets and three neural networks and explore the performance of our attack concerning the duration, position, and type of the trigger.
Revised:  We conduct experiments on two versions of a dataset and three neural networks and explore the performance of our attack concerning the duration, position, and type of the trigger.
Edit intent: fluency
Original:  What is more, while the trigger is inaudible, making it without limitations with respect to the duration of the signal,  we observed that even short, non-continuous triggers result in highly successful attacks  .
Revised:  Since the trigger is inaudible, making it without limitations with respect to the duration of the signal, we observed that even short, non-continuous triggers result in highly successful attacks .
Edit intent: coherence
Original:  What is more, while the trigger is inaudible, making it without limitations with respect to the duration of the signal,  we observed that even short, non-continuous triggers result in highly successful attacks  .
Revised:  What is more, while the trigger is inaudible, it makes it without limitations with respect to the duration of the signal, we observed that even short, non-continuous triggers result in highly successful attacks .
Edit intent: clarity
Original:  What is more, while the trigger is inaudible, making it without limitations with respect to the duration of the signal,  we observed that even short, non-continuous triggers result in highly successful attacks  .
Revised:  What is more, while the trigger is inaudible, making it without limitations with respect to the duration of the signal, and we observed that even short, non-continuous triggers result in highly successful attacks .
Edit intent: coherence
Original:  Recently, the key features of quantum supermaps were captured through a general categorical framework, which when iterated yields the framework of higher order process theories (HOPT).
Revised:  Recently, key features of quantum supermaps were captured through a general categorical framework, which when iterated yields the framework of higher order process theories (HOPT).
Edit intent: fluency
Original:  Recently, the key features of quantum supermaps were captured through a general categorical framework, which when iterated yields the framework of higher order process theories (HOPT).
Revised:  Recently, the key features of quantum supermaps were captured through a general categorical framework, which led to a framework of higher order process theories (HOPT).
Edit intent: clarity
Original:  The HOPT framework combines lower and higher order transformations in a single unified theory, with its mathematical structure shown to coincide with the notion of a closed  monoidal category.
Revised:  The HOPT framework models lower and higher order transformations in a single unified theory, with its mathematical structure shown to coincide with the notion of a closed monoidal category.
Edit intent: clarity
Original:  We then use the HOPT framework to establish connections between foundational features such as causality, determinism , and signalling, and to explore their interaction with the mathematical structure of *-autonomy.
Revised:  We then use the HOPT framework to establish connections between foundational features such as causality, determinism and signalling, and to explore their interaction with the mathematical structure of *-autonomy.
Edit intent: fluency
Original:  We then use the HOPT framework to establish connections between foundational features such as causality, determinism , and signalling, and to explore their interaction with the mathematical structure of *-autonomy.
Revised:  We then use the HOPT framework to establish connections between foundational features such as causality, determinism , and signalling, alongside exploring their interaction with the mathematical structure of *-autonomy.
Edit intent: coherence
Original:  However, the extent of disagreement in science, its evolution over time, and the fields in which it happens, remains largely unknown . Leveraging a massive collection of  scientific texts, we develop a cue-phrase based approach to identify instances of disagreement citations across more than four million scientific articles.
Revised:  However, the extent of disagreement in science, its evolution over time, and the fields in which it happens, remains poorly understood . Leveraging a massive collection of scientific texts, we develop a cue-phrase based approach to identify instances of disagreement citations across more than four million scientific articles.
Edit intent: clarity