wanyu/IteraTeR_v2 huggingface dataset:
Original: Reconfigurable intelligent surfaces (RISs) have attracted attention in the last year as nearly-passive, planar structures that can dynamically change their reflection or refraction characteristics , and therefore realize anomalous reflection, focalization, or other radiowave or signal transformations, to engineer and optimize complex propagation environments.
Revised: Reconfigurable intelligent surfaces (RISs) have attracted attention in the last year as nearly-passive, thin structures that can dynamically change their reflection or refraction characteristics , and therefore realize anomalous reflection, focalization, or other radiowave or signal transformations, to engineer and optimize complex propagation environments.
Edit intent: clarity
Original: Reconfigurable intelligent surfaces (RISs) have attracted attention in the last year as nearly-passive, planar structures that can dynamically change their reflection or refraction characteristics , and therefore realize anomalous reflection, focalization, or other radiowave or signal transformations, to engineer and optimize complex propagation environments.
Revised: Reconfigurable intelligent surfaces (RISs) have attracted attention in the last year as nearly-passive, planar structures that can dynamically change their reflection or refraction behaviour , and therefore realize anomalous reflection, focalization, or other radiowave or signal transformations, to engineer and optimize complex propagation environments.
Edit intent: clarity
Original: Reconfigurable intelligent surfaces (RISs) have attracted attention in the last year as nearly-passive, planar structures that can dynamically change their reflection or refraction characteristics , and therefore realize anomalous reflection, focalization, or other radiowave or signal transformations, to engineer and optimize complex propagation environments.
Revised: Reconfigurable intelligent surfaces (RISs) have attracted attention in the last year as nearly-passive, planar structures that can dynamically change their reflection or refraction characteristics , and therefore realize anomalous reflection, focalization, or other wave transformations, to engineer and optimize complex propagation environments.
Edit intent: clarity
Original: Reconfigurable intelligent surfaces (RISs) have attracted attention in the last year as nearly-passive, planar structures that can dynamically change their reflection or refraction characteristics , and therefore realize anomalous reflection, focalization, or other radiowave or signal transformations, to engineer and optimize complex propagation environments.
Revised: Reconfigurable intelligent surfaces (RISs) have attracted attention in the last year as nearly-passive, planar structures that can dynamically change their reflection or refraction characteristics , and therefore realize anomalous reflection, focalization, or other radiowave or signal transformations, to engineer complex radio propagation environments.
Edit intent: clarity
Original:  Evaluating the performance and optimizing the deployment of RISs in wireless networks need physically sound frameworks that account for the actual electromagnetic and physical characteristics of engineered metasurfaces.
Revised:  Evaluating the performance and optimizing the deployment of RISs in wireless networks need physically sound frameworks that account for the actual characteristics of engineered metasurfaces.
Edit intent: clarity
Original:  In this paper, we introduce a general macroscopic model for the realistic evaluation of RIS scattering, based on its decomposition into multiple scattering mechanisms  . Since state-of-the-art ray models can already efficiently simulate specular interactions (reflection, diffraction) and diffuse scattering, but not anomalous reradiation, we complement them with a Huygens principle approach implemented using either an integral formulation, or a simpler antenna-array-like formulation .
Revised:  In this paper, we introduce a general macroscopic model for the realistic evaluation of RIS scattering, based on its decomposition into multiple scattering mechanisms . Since state-of-the-art ray models can already efficiently simulate specular interactions (reflection, diffraction) and diffuse scattering, but not anomalous reradiation, we complement them with a Huygens principle approach and two possible implementations of it .
Edit intent: clarity
Original:  The different scattering mechanisms are combined through a generalization of the Effective Roughness model using a suitable power conservation equation.
Revised:  The different scattering mechanisms are combined through a suitable power conservation equation.
Edit intent: clarity
Original:  In addition, we validate the overall model  accuracy by benchmarking it against several case studies available in the literature, either based on analytical models, full-wave simulations, or experimental measurements.
Revised:  In addition, we validate the overall model 's accuracy by benchmarking it against several case studies available in the literature, either based on analytical models, full-wave simulations, or experimental measurements.
Edit intent: fluency
Original:  Extensive experiments against other state-of-the-art deep learning based methods for L3 localization prove the superiority of our technique which performs well even with  limited amount of data and annotations.
Revised:  Extensive experiments against other state-of-the-art deep learning based methods for L3 localization prove the superiority of our technique which performs well even with a limited amount of data and annotations.
Edit intent: fluency
Original: Executive Order (EO) 14028, "Improving the Nation's Cybersecurity , "  12 May 2021, directs the National Institute of Standards and Technology (NIST) to recommend minimum standards for software testing within 60 days.
Revised: Executive Order (EO) 14028, "Improving the Nation's Cybersecurity " 12 May 2021, directs the National Institute of Standards and Technology (NIST) to recommend minimum standards for software testing within 60 days.
Edit intent: fluency
Original: Executive Order (EO) 14028, "Improving the Nation's Cybersecurity , "  12 May 2021, directs the National Institute of Standards and Technology (NIST) to recommend minimum standards for software testing within 60 days.
Revised: Executive Order (EO) 14028, "Improving the Nation's Cybersecurity , " , 12 May 2021, directs the National Institute of Standards and Technology (NIST) to recommend minimum standards for software testing within 60 days.
Edit intent: fluency
Original:  test cases Code-based structural test cases Historical test cases Fuzzing Web app scanners, if applicable Address included code (libraries, packages, services) The document does not address the totality of software verification, but instead  recommends techniques that are broadly applicable and form the minimum standards.
Revised:  test cases Code-based structural test cases Historical test cases Fuzzing Web app scanners, if applicable Address included code (libraries, packages, services) The document does not address the totality of software verification, but instead , recommends techniques that are broadly applicable and form the minimum standards.
Edit intent: fluency
Original:  The document was developed by NIST in consultation with the National Security Agency  .
Revised:  The document was developed by NIST in consultation with the National Security Agency (NSA) .
Edit intent: clarity
Original:  Additionally, we received input from numerous outside organizations through papers submitted to a NIST workshop on the Executive Order held in early June , 2021 and discussion at the workshop  as well as follow up with several of the submitters.
Revised:  Additionally, we received input from numerous outside organizations through papers submitted to a NIST workshop on the Executive Order held in early June 2021 and discussion at the workshop as well as follow up with several of the submitters.
Edit intent: fluency
Original:  Additionally, we received input from numerous outside organizations through papers submitted to a NIST workshop on the Executive Order held in early June , 2021 and discussion at the workshop  as well as follow up with several of the submitters.
Revised:  Additionally, we received input from numerous outside organizations through papers submitted to a NIST workshop on the Executive Order held in early June , 2021 , discussion at the workshop as well as follow up with several of the submitters.
Edit intent: fluency
Original:  Additionally, we received input from numerous outside organizations through papers submitted to a NIST workshop on the Executive Order held in early June , 2021 and discussion at the workshop  as well as follow up with several of the submitters.
Revised:  Additionally, we received input from numerous outside organizations through papers submitted to a NIST workshop on the Executive Order held in early June , 2021 and discussion at the workshop , as well as follow up with several of the submitters.
Edit intent: fluency
Original:  This paper examines the design space trade-offs of such accelerators aiming to achieve competitive performance and efficiency metrics for all four combinations of dense or sparse activation/weight tensors.
Revised:  This paper examines the design space trade-offs of DNNs accelerators aiming to achieve competitive performance and efficiency metrics for all four combinations of dense or sparse activation/weight tensors.
Edit intent: clarity
Original:  To do so, we systematically examine  overheads of supporting sparsity on top of an optimized dense core.
Revised:  To do so, we systematically examine the overheads of supporting sparsity on top of an optimized dense core.
Edit intent: fluency
Original:  Our findings suggest that even a best design targeting dual sparsity yields  20\%-30\% drop in power efficiency when performing on single sparse models, i.e., those with only sparse weight or sparse activation tensors.
Revised:  Our findings suggest that even the best design targeting dual sparsity yields 20\%-30\% drop in power efficiency when performing on single sparse models, i.e., those with only sparse weight or sparse activation tensors.
Edit intent: fluency
Original:  Our findings suggest that even a best design targeting dual sparsity yields  20\%-30\% drop in power efficiency when performing on single sparse models, i.e., those with only sparse weight or sparse activation tensors.
Revised:  Our findings suggest that even a best design targeting dual sparsity yields a 20\%-30\% drop in power efficiency when performing on single sparse models, i.e., those with only sparse weight or sparse activation tensors.
Edit intent: fluency
Original:  We introduce novel techniques to reuse resources of the same core to maintain high performance and efficiency when running single sparsity or dense models.
Revised:  We found that one can reuse resources of the same core to maintain high performance and efficiency when running single sparsity or dense models.
Edit intent: clarity
Original:  Griffin is 1.2, 3.0, 3.1, and 1.4X more power efficient than state-of-the-art sparse architectures, for dense, weight-only sparse, activation-only sparse, and dual sparse models, respectively.
Revised:  Griffin is 1.2, 3.0, 3.1, and 1.4X more power-efficient than state-of-the-art sparse architectures, for dense, weight-only sparse, activation-only sparse, and dual sparse models, respectively.
Edit intent: fluency
Original:  Unfortunately, resetting the environment to its initial state after each trial requires substantial amount of human supervision and extensive instrumentation of the environment which defeats the purpose of autonomous reinforcement learning .
Revised:  Unfortunately, resetting the environment to its initial state after each trial requires substantial amount of human supervision and extensive instrumentation of the environment which defeats the goal of autonomous acquisition of complex behaviors .
Edit intent: clarity
Original:  The efficacy of our proposed method is validated by experimental results on the THUMOS14 (54.3\\% at IoU @0.5) and ActivityNet v1.3 ( 51.24 \\%DIF < at IoU@0.5) datasets, which outperforms %DIF > at tIoU@0.5) datasets, which  recent states of the art. 
Revised:  The efficacy of our proposed method is validated by experimental results on the THUMOS14 (54.3\\% at tIoU @0.5) and ActivityNet v1.3 ( 51.24 \\%DIF < at IoU@0.5) datasets, which outperforms %DIF > at tIoU@0.5) datasets, which recent states of the art. 
Edit intent: fluency
Original:  The efficacy of our proposed method is validated by experimental results on the THUMOS14 (54.3\\% at IoU @0.5) and ActivityNet v1.3 ( 51.24 \\%DIF < at IoU@0.5) datasets, which outperforms %DIF > at tIoU@0.5) datasets, which  recent states of the art. 
Revised:  The efficacy of our proposed method is validated by experimental results on the THUMOS14 (54.3\\% at IoU @0.5) and ActivityNet v1.3 ( 51.24 \\%DIF < at IoU@0.5) datasets, which outperforms %DIF > at tIoU@0.5) datasets, which outperforms recent states of the art. 
Edit intent: fluency
Original:  In this contribution, we utilise a dataset which includes continuous emotion and physiological signals - Heartbeats per Minute (BPM), Electrodermal Activity (EDA), and Respiration-rate - captured during a stress induced scenario (Trier Social Stress Test).
Revised:  In this contribution, we utilise a dataset which includes continuous emotion and physiological signals - Heartbeats per Minute (BPM), Electrodermal Activity (EDA), and Respiration-rate - captured during a stress inducing scenario (Trier Social Stress Test).
Edit intent: fluency
Original:  A similar concern was previously noted several years ago for image based zero-shot recognition , but has not been considered by the zero-shot action recognition community.
Revised:  A similar concern was previously noted several years ago for image based zero-shot recognition but has not been considered by the zero-shot action recognition community.
Edit intent: fluency
Original:  In our extensive analysis  we find that our TruZe splits are significantly harder than comparable random splits as nothing is leaking from pre-training, i.e. unseen performance is consistently lower,up to 9.4 \% for zero-shot action recognition.
Revised:  In our extensive analysis , we find that our TruZe splits are significantly harder than comparable random splits as nothing is leaking from pre-training, i.e. unseen performance is consistently lower,up to 9.4 \% for zero-shot action recognition.
Edit intent: fluency
Original:  We have achieved a TDC with higher raw linearity , reduced empty bins , and a simpler structure compared with the previous FPGA-based TDC .
Revised:  We have achieved a TDC with higher raw linearity , reduced empty bins , and a simpler structure compared with the previous FPGA-based TDCs .
Edit intent: clarity
Original:  Concurrently operating closed loops aiming for individual optimization targets may cause conflicts which, left unresolved, would lead to significant degradation in network Key Performance Indicators (KPIs), thereby resulting in sub-optimal network performance.
Revised:  Concurrently operating closed loops aiming for individual optimization cause conflicts which, left unresolved, would lead to significant degradation in network Key Performance Indicators (KPIs), thereby resulting in sub-optimal network performance.
Edit intent: clarity
Original:  Concurrently operating closed loops aiming for individual optimization targets may cause conflicts which, left unresolved, would lead to significant degradation in network Key Performance Indicators (KPIs), thereby resulting in sub-optimal network performance.
Revised:  Concurrently operating closed loops aiming for individual optimization targets may cause conflicts which, left unresolved, leads to significant degradation in network Key Performance Indicators (KPIs), thereby resulting in sub-optimal network performance.
Edit intent: coherence
Original:  Concurrently operating closed loops aiming for individual optimization targets may cause conflicts which, left unresolved, would lead to significant degradation in network Key Performance Indicators (KPIs), thereby resulting in sub-optimal network performance.
Revised:  Concurrently operating closed loops aiming for individual optimization targets may cause conflicts which, left unresolved, would lead to significant degradation in performance indicators, resulting in sub-optimal network performance.
Edit intent: clarity
Original:  Centralized coordination, albeit optimal, is impractical in large scale networks and for time-critical applications.
Revised:  Centralized optimization avoids conflicts, but impractical in large-scale networks for time-critical applications.
Edit intent: clarity
Original:  Decentralized approaches are therefore envisaged in the evolution to B5G and subsequently, 6G networks.
Revised:  Distributed, pervasive intelligence is therefore envisaged in the evolution to B5G and subsequently, 6G networks.
Edit intent: clarity
Original: The paper studies the multi-user precoding problem as a non-convex optimization problem for wireless MIMO systems.
Revised: The paper studies the multi-user precoding problem as a non-convex optimization problem for wireless multiple input and multiple output (MIMO) systems.
Edit intent: clarity
Original:  In this paper, we propose new explainability approaches for point cloud deep neural networks based on local surrogate model-based methods to show which components make the main contribution to the classification.
Revised:  In this paper, we propose a point cloud-applicable explainability approach based on local surrogate model-based methods to show which components make the main contribution to the classification.
Edit intent: clarity
Original:  In this paper, we propose new explainability approaches for point cloud deep neural networks based on local surrogate model-based methods to show which components make the main contribution to the classification.
Revised:  In this paper, we propose new explainability approaches for point cloud deep neural networks based on local surrogate model-based method to show which components make the main contribution to the classification.
Edit intent: fluency
Original:  In this paper, we propose new explainability approaches for point cloud deep neural networks based on local surrogate model-based methods to show which components make the main contribution to the classification.
Revised:  In this paper, we propose new explainability approaches for point cloud deep neural networks based on local surrogate model-based methods to show which components contribute to the classification.
Edit intent: clarity
Original:  Moreover, we propose a quantitative validation method for explainability methods of point clouds which enhances the persuasive power of explainability by dropping the most positive or negative contributing features and monitoring how the classification scores of specific categories change.
Revised:  Moreover, we propose quantitative fidelity validations for generated explanations that enhance the persuasive power of explainability by dropping the most positive or negative contributing features and monitoring how the classification scores of specific categories change.
Edit intent: clarity
Original: There has been a growing interest in unsupervised domain adaptation (UDA)  to alleviate the data scalability issue, while the existing works usually focus on classifying independently discrete labels.
Revised: The unsupervised domain adaptation (UDA) to alleviate the data scalability issue, while the existing works usually focus on classifying independently discrete labels.
Edit intent: clarity
Original:  Instead of the typically i.i.d. Gaussian latent prior, in this work, a recursively conditional Gaussian (RCG) set is proposed for ordered constraint modeling, which admits a tractable joint distribution prior.
Revised:  Instead of the typically i.i.d. Gaussian latent prior, in this work, a recursively conditional Gaussian (RCG) set is adapted for ordered constraint modeling, which admits a tractable joint distribution prior.
Edit intent: clarity
Original:  Furthermore, we are able to control the density of content vectors that violate the poset constraint by a simple "three-sigma rule".
Revised:  Furthermore, we are able to control the density of content vector that violates the poset constraints by a simple "three-sigma rule".
Edit intent: fluency
Original: In this paper, we study how robots can autonomously learn skills that require a combination of navigation and grasping.
Revised: We study how robots can autonomously learn skills that require a combination of navigation and grasping.
Edit intent: clarity
Original:  Learning robotic skills in the real world remains challenging without large-scale data collection and supervision.
Revised:  Learning robotic skills in the real world is challenging and often requires extensive instrumentation and supervision.
Edit intent: clarity
Original:  Our aim is to devise a robotic reinforcement learning system for learning navigation and manipulation together, in an autonomous way without human intervention, enabling continual learning under realistic assumptions.
Revised:  Our aim is to devise a robotic reinforcement learning system for learning navigation and manipulation together, in an autonomous way without human intervention, enabling continual learning under realistic assumptions.
Edit intent: fluency
Original:  Specifically, our system, ReLMM, can learn continuously on a real-world platform without any environment instrumentation, without human intervention, and without access to privileged information, such as maps, objects positions, or a global view of the environment.
Revised:  Our proposed system, ReLMM, can learn continuously on a real-world platform without any environment instrumentation, without human intervention, and without access to privileged information, such as maps, objects positions, or a global view of the environment.
Edit intent: clarity
Original:  Our method employs a modularized policy with components for manipulation and navigation, where uncertainty over the manipulation success drives exploration for the navigation controller, and the manipulation module provides rewards for navigation.
Revised:  Our method employs a modularized policy with components for manipulation and navigation, where manipulation policy uncertainty drives exploration for the navigation controller, and the manipulation module provides rewards for navigation.
Edit intent: clarity
Original:  We evaluate our method on a room cleanup task, where the robot must navigate to and pick up items of scattered on the floor.
Revised:  We evaluate our method on a room cleanup task, where the robot must navigate to and pick up items scattered on the floor.
Edit intent: fluency
Original: The default paradigm for the forecasting of human behavior in social conversations is characterized by top-down approaches.
Revised: The default paradigm in the forecasting of human behavior in social conversations is characterized by top-down approaches.
Edit intent: clarity
Original:  We formulate the task of Social Cue Forecasting to leverage the larger amount of unlabeled low-level behavior cues  , and characterize the  modeling challenges involved.
Revised:  We formulate the task of Social Cue Forecasting to leverage the larger amount of low-level behavior cues , and characterize the modeling challenges involved.
Edit intent: clarity
Original:  Evaluation on synthesized and real-world behavior data shows that our SP models achieve higher log-likelihood than the NP baselines, and also highlights important considerations for applying such techniques within the domain of social human interactions .
Revised:  Evaluation on synthesized and real-world behavior data validates our meta-learning approach. Moreover, ablations and comparison against meta-learning models with similar assumptions validate our specific modeling choices for this task .
Edit intent: clarity