wanyu/IteraTeR_v2 huggingface dataset:
Original:  This project, partially inspired by its street greenery counterpart -- Treepedia, is made possible by a multi-step pipeline that combines deep learning and geospatial techniques, demonstrating the feasibility of an automated methodology that generalises successfully across cities with an accuracy of detecting sustainable roofs of up to 100\% in some cities.
Revised:  This project, partly inspired by its street greenery counterpart -- Treepedia, is made possible by a multi-step pipeline that combines deep learning and geospatial techniques, demonstrating the feasibility of an automated methodology that generalises successfully across cities with an accuracy of detecting sustainable roofs of up to 100\% in some cities.
Edit intent: fluency
Original: Sustainable roofs, such as those with greenery and photovoltaic panels, contribute significantly to the roadmap for reducing the carbon footprint of cities.
Revised: Sustainable roofs, such as those with greenery and photovoltaic panels, contribute to the roadmap for reducing the carbon footprint of cities.
Edit intent: clarity
Original:  However, research on sustainable urban roofscapes is rather focused on their potential and  is hindered by the scarcity of data, limiting our understanding of their current content, spatial distribution, and temporal evolution.
Revised:  However, research on sustainable urban roofscapes is rather focused on their potential and it is hindered by the scarcity of data, limiting our understanding of their current content, spatial distribution, and temporal evolution.
Edit intent: coherence
Original:  and (iii) the Roofpedia Index, a derivative from the registry, to benchmark the cities by the extent of sustainable roofscape in term of solar and green roof penetration.
Revised:  and (iii) the Roofpedia Index, a derivative of the registry, to benchmark the cities by the extent of sustainable roofscape in term of solar and green roof penetration.
Edit intent: fluency
Original:  This project, partly inspired by its street greenery counterpart -- Treepedia , is made possible by a multi-step pipeline that combines deep learning and geospatial techniques, demonstrating the feasibility of an automated methodology that generalises successfully across cities with an accuracy of detecting sustainable roofs of up to 100\% in some cities.
Revised:  This project, partly inspired by its street greenery counterpart `Treepedia' , is made possible by a multi-step pipeline that combines deep learning and geospatial techniques, demonstrating the feasibility of an automated methodology that generalises successfully across cities with an accuracy of detecting sustainable roofs of up to 100\% in some cities.
Edit intent: fluency
Original: Because of their highly directional transmissions, radios operating at millimeter wave (mmWave) frequencies need to perform beam management to establish and maintain reliable mmWave links.
Revised: Highly directional millimeter wave (mmWave) frequencies need to perform beam management to establish and maintain reliable mmWave links.
Edit intent: clarity
Original: Because of their highly directional transmissions, radios operating at millimeter wave (mmWave) frequencies need to perform beam management to establish and maintain reliable mmWave links.
Revised: Because of their highly directional transmissions, radios operating at millimeter wave (mmWave) radios need to perform beam management to establish and maintain reliable mmWave links.
Edit intent: clarity
Original:  Existing solutions rely on explicit coordination between the transmitter (TX) and the receiver (RX), which  reduces the airtime available for communication and  complicates the network protocol design.
Revised:  Existing solutions rely on explicit coordination between the transmitter (TX) and the receiver (RX), which reduces the airtime available for communication and further complicates the network protocol design.
Edit intent: clarity
Original:  This paper presents DeepBeam, a framework for beam management in mmWave networks that does not require pilot sequences from the transmitter , nor any beam sweeping or synchronization from the receiver .
Revised:  This paper presents DeepBeam, a framework for beam management that does not require pilot sequences from the transmitter , nor any beam sweeping or synchronization from the receiver .
Edit intent: clarity
Original:  This paper presents DeepBeam, a framework for beam management in mmWave networks that does not require pilot sequences from the transmitter , nor any beam sweeping or synchronization from the receiver .
Revised:  This paper presents DeepBeam, a framework for beam management in mmWave networks that does not require pilot sequences from the transmitter , nor any beam sweeping or synchronization from the RX .
Edit intent: fluency
Original:   This is possible because different beam patterns introduce different "impairments " to the waveform, which can be subsequently learned by a convolutional neural network (CNN).
Revised:  This is possible because different beam patterns introduce different impairments to the waveform, which can be subsequently learned by a convolutional neural network (CNN).
Edit intent: fluency
Original:  To demonstrate DeepBeam's generality, we conduct an extensive experimental  campaign where we collect more than 4 TB of mmWave waveforms with (i) 4 phased array antennas at 60.48 GHz, (ii) 2 codebooks containing 24 one-dimensional beams and 12 two-dimensional beams;
Revised:  We conduct an extensive experimental campaign where we collect more than 4 TB of mmWave waveforms with (i) 4 phased array antennas at 60.48 GHz, (ii) 2 codebooks containing 24 one-dimensional beams and 12 two-dimensional beams;
Edit intent: coherence
Original:  To demonstrate DeepBeam's generality, we conduct an extensive experimental  campaign where we collect more than 4 TB of mmWave waveforms with (i) 4 phased array antennas at 60.48 GHz, (ii) 2 codebooks containing 24 one-dimensional beams and 12 two-dimensional beams;
Revised:  To demonstrate DeepBeam's generality, we conduct an extensive experimental data collection campaign where we collect more than 4 TB of mmWave waveforms with (i) 4 phased array antennas at 60.48 GHz, (ii) 2 codebooks containing 24 one-dimensional beams and 12 two-dimensional beams;
Edit intent: clarity
Original:  We also collect waveform data with two custom-designed mmWave software-defined radios with fully-digital beamforming architectures at 58 GHz , and implement our learning models in FPGA to evaluate latency performance.
Revised:  Moreover, we collect waveform data with two custom-designed mmWave software-defined radios with fully-digital beamforming architectures at 58 GHz , and implement our learning models in FPGA to evaluate latency performance.
Edit intent: coherence
Original:  We also collect waveform data with two custom-designed mmWave software-defined radios with fully-digital beamforming architectures at 58 GHz , and implement our learning models in FPGA to evaluate latency performance.
Revised:  We also collect waveform data with two custom-designed mmWave software-defined radios with fully-digital beamforming architectures at 58 GHz . Results show that
Edit intent: coherence
Original:  and (ii) reduces latency by up to 7x with respect to the 5G NR initial beam sweep in a default configuration and with a 12-beam codebook.
Revised:  (ii) reduces latency by up to 7x with respect to the 5G NR initial beam sweep in a default configuration and with a 12-beam codebook.
Edit intent: fluency
Original:  Additionally, we pledge to share our waveform dataset and the full DeepBeam code repo with the community .
Revised:  The waveform dataset and the full DeepBeam code repo with the community .
Edit intent: clarity
Original: We show that the entailment problem \varphi \models \psi in Separation Logic is decidable for separated conjunctions of atoms \varphi and \psi, that contain predicate symbols whose interpretation is given inductively by a set\iseq \not\iseq  of recursive rules.
Revised: The entailment problem \varphi \models \psi in Separation Logic is decidable for separated conjunctions of atoms \varphi and \psi, that contain predicate symbols whose interpretation is given inductively by a set\iseq \not\iseq of recursive rules.
Edit intent: coherence
Original:  The proof is based on a reduction to a class of entailment problems  0pt and }  shown to be decidable in \mbox{ IosifRogalewiczSimacek130pt .
Revised:  The proof is based on a reduction to a class of entailment problems establishment 0pt and } shown to be decidable in \mbox{ IosifRogalewiczSimacek130pt .
Edit intent: fluency
Original:  The proof is based on a reduction to a class of entailment problems  0pt and }  shown to be decidable in \mbox{ IosifRogalewiczSimacek130pt .
Revised:  The proof is based on a reduction to a class of entailment problems 0pt and } shown to be 0pt .
Edit intent: clarity
Original:  it is only assumed that the rules are progressing, i.e.} \twoexptime \ that they allocate exactly one memory location }\hspace{0pt} and \mbox{ \cite{EIP21a}}\hspace{0pt} , respectively, and a many-one reduction of established to restricted entailment problems has been given \mbox{ \cite{EIP21a}}\hspace{0pt} .
Revised:  it is only assumed that the rules are progressing, i.e.} in\twoexptime \ that they allocate exactly one memory location }\hspace{0pt} and \mbox{ \cite{EIP21a}}\hspace{0pt} , respectively, and a many-one reduction of established to restricted entailment problems has been given \mbox{ \cite{EIP21a}}\hspace{0pt} .
Edit intent: clarity
Original:  We provide a many-one reduction of this generalized class, called }\emph{ \twoexptime .
Revised:  We provide a many-one reduction of this generalized class, called }\emph{safe \twoexptime .
Edit intent: fluency
Original:  Our algorithm is  practical: it improves upon the performance of  prior methods when training deep neural networks, it is relatively lightweight, and  is the first method to withstand two recently-proposed Byzantine attacks.
Revised:  Our algorithm is practical: it improves upon the performance of all prior methods when training deep neural networks, it is relatively lightweight, and is the first method to withstand two recently-proposed Byzantine attacks.
Edit intent: clarity
Original:  Our algorithm is  practical: it improves upon the performance of  prior methods when training deep neural networks, it is relatively lightweight, and  is the first method to withstand two recently-proposed Byzantine attacks.
Revised:  Our algorithm is practical: it improves upon the performance of prior methods when training deep neural networks, it is relatively lightweight, and it is the first method to withstand two recently-proposed Byzantine attacks.
Edit intent: fluency
Original:  In this work we investigate the expressivity of versions of G\"odel's system T where programs are circularly typed, rather than including an explicit recursion combinator.
Revised:  In this work we investigate the expressivity of a variant CT of G\"odel's system T where programs are circularly typed, rather than including an explicit recursion combinator.
Edit intent: clarity
Original:  In fact we give a logical correspondence between the two settings, interpreting the quantifier-free type 1 theory of level n+1 T into that of level n circular derivations and vice-versa \T  .
Revised:  In fact we give a logical correspondence between the two settings, interpreting the quantifier-free type 1 theory of level n+1 T into that of level n C and vice-versa \T .
Edit intent: clarity
Original:  In this work , we present YASO -- a new crowd-sourced TSA evaluation dataset , collected using a new annotation scheme for labeling targets and their sentiments.
Revised:  In this work , we present YASO - a new TSA evaluation dataset , collected using a new annotation scheme for labeling targets and their sentiments.
Edit intent: clarity
Original:  The dataset contains 2,215 English sentences from movie, business and product reviews, and 7,415 terms and their corresponding sentiments annotated within these sentences .
Revised:  The dataset contains 2,215 English sentences from movie, business and product reviews, and 7,415 terms and their sentiment .
Edit intent: clarity
Original:  Our analysis verifies the reliability of our annotations, and explores the characteristics of the collected data.
Revised:  Our analysis verifies the reliability of these annotations, and explores the characteristics of the collected data.
Edit intent: clarity
Original:  Lastly, benchmark results using five contemporary TSA systems lay the foundation for future work, and show there is ample room for improvement on this challenging new dataset. 
Revised:  Benchmark results using five contemporary TSA systems lay the foundation for future work, and show there is ample room for improvement on this challenging new dataset. 
Edit intent: coherence
Original:  Lastly, benchmark results using five contemporary TSA systems lay the foundation for future work, and show there is ample room for improvement on this challenging new dataset. 
Revised:  Lastly, benchmark results using five contemporary TSA systems show there is ample room for improvement on this challenging new dataset. 
Edit intent: clarity
Original: We introduce a novel iterative eigenvalue algorithm for near-diagonal matrices termed iterative perturbative theory (IPT).
Revised: We introduce a novel iterative eigenvalue algorithm for near-diagonal matrices termed iterative perturbative theory (IPT).
Edit intent: fluency
Original: We introduce a novel iterative eigenvalue algorithm for near-diagonal matrices termed iterative perturbative theory (IPT).
Revised: We introduce a novel eigenvalue algorithm for near-diagonal matrices termed iterative perturbative theory (IPT).
Edit intent: fluency
Original:  Built upon a "perturbative" partitioning of the matrix into diagonal and off-diagonal parts, IPT computes one or all eigenpairs with a complexity per iteration of one matrix-vector or one matrix-matrix multiplication respectively .
Revised:  Built upon a "perturbative" partitioning of the matrix into diagonal and off-diagonal parts, IPT can be used to compute one or all eigenpairs with a complexity per iteration of one matrix-vector or one matrix-matrix multiplication respectively .
Edit intent: clarity
Original:  Built upon a "perturbative" partitioning of the matrix into diagonal and off-diagonal parts, IPT computes one or all eigenpairs with a complexity per iteration of one matrix-vector or one matrix-matrix multiplication respectively .
Revised:  Built upon a "perturbative" partitioning of the matrix into diagonal and off-diagonal parts, IPT computes one or all eigenpairs with the same basic iterative algorithm .
Edit intent: clarity
Original: Cardinality estimation is one of the fundamental problems in database management systems and it is an essential component in query optimizers .
Revised: Cardinality estimation (CardEst) is an essential component in query optimizers .
Edit intent: clarity
Original:  Our experimental results on several single-relation and multi-relation databases indicate that BayesCardwith a reasonable estimation time has a better estimation accuracythan deep learning models, and has from one to two orders of magnitude less training cost nevertheless .
Revised:  Our experimental results on several single-table and multi-table benchmarks indicate BayesCard's superiority over existing state-of-the-art CardEst methods: BayesCard achieves comparable or better accuracy, 1-2 orders of magnitude less training cost nevertheless .
Edit intent: clarity
Original:  In a classical approach, audio features are usually extracted from fixed regions of speech such as  syllable nucleus.
Revised:  In a classical approach, audio features are usually extracted from fixed regions of speech such as the syllable nucleus.
Edit intent: fluency
Original:  Moreover, in order to improve its computational efficiency and robustness, the new method uses the switching preconditioning technique between the L-BFGS method and the inverse of the Hessian matrix .
Revised:  Moreover, in order to improve its computational efficiency and robustness, the new method uses the switching preconditioning technique .
Edit intent: coherence
Original: We consider the problem of knowledge-based strategy synthesis for a team of agents with imperfect information due to partial observability, playing against Nature towards achieving a common objective with no communication during the play of the game.
Revised: We study teams of agents that play against Nature towards achieving a common objective. The agents are assumed to have imperfect information due to partial observability, playing against Nature towards achieving a common objective with no communication during the play of the game.
Edit intent: clarity
Original: We consider the problem of knowledge-based strategy synthesis for a team of agents with imperfect information due to partial observability, playing against Nature towards achieving a common objective with no communication during the play of the game.
Revised: We consider the problem of knowledge-based strategy synthesis for a team of agents with imperfect information due to partial observability, and have no communication during the play of the game.
Edit intent: coherence
Original:  We  introduce a multi-agent extension, MKBSC, of the well-known knowledge-based subset construction applied to such games.
Revised:  We introduce a multi-agent extension, MKBSC, of the well-known Knowledge-Based Subset Construction applied to such games.
Edit intent: fluency
Original:  We also relate and compare the intensional view on knowledge-based strategies based on explicit knowledge representation and update, with the extensional view on finite memory strategies based on finite transducers and show that, in a certain sense, these are equivalent.
Revised:  We also relate and compare the "intensional" view on knowledge-based strategies based on explicit knowledge representation and update, with the extensional view on finite memory strategies based on finite transducers and show that, in a certain sense, these are equivalent.
Edit intent: fluency
Original:  We also relate and compare the intensional view on knowledge-based strategies based on explicit knowledge representation and update, with the extensional view on finite memory strategies based on finite transducers and show that, in a certain sense, these are equivalent.
Revised:  We also relate and compare the intensional view on knowledge-based strategies based on explicit knowledge representation and update, with the "extensional" view on finite memory strategies based on finite transducers and show that, in a certain sense, these are equivalent.
Edit intent: coherence
Original:  Neural Information Retrieval (Neu-IR) models have shown their effectiveness and thrive from end-to-end training with massive high-quality relevance labels.
Revised: The effectiveness of Neural Information Retrieval (Neu-IR) models have shown their effectiveness and thrive from end-to-end training with massive high-quality relevance labels.
Edit intent: clarity
Original: Many concepts have been proposed for meta learning with neural networks (NNs), e.g., NNs that learn to control fast weights, hyper networks, learned learning rules, and meta recurrent neural networks (Meta RNNs) .
Revised: Many concepts have been proposed for meta learning with neural networks (NNs), e.g., NNs that learn to control fast weights, hyper networks, learned learning rules, and meta recurrent NNs .
Edit intent: clarity
Original:  A simple implementation of VS-ML called Variable Shared Meta RNN allows for implementing the backpropagation learning algorithm solely by running an RNN in forward-mode.
Revised:  A simple implementation of VS-ML called Variable Shared Meta RNN allows for implementing the backpropagation LA solely by running an RNN in forward-mode.
Edit intent: clarity
Original:  It can even meta-learn new learning algorithms that improve upon backpropagation , generalizing to different datasets without explicit gradient calculation  .
Revised:  It can even meta-learn new LAs that improve upon backpropagation , generalizing to different datasets without explicit gradient calculation .
Edit intent: clarity
Original: Many concepts have been proposed for meta learning with neural networks (NNs), e.g., NNs that learn to control fast weights, hyper networks , learned learning rules, and meta recurrent NNs.
Revised: Many concepts have been proposed for meta learning with neural networks (NNs), e.g., NNs that learn to reprogram fast weights, hyper networks , learned learning rules, and meta recurrent NNs.
Edit intent: clarity
Original:  Our Variable Shared Meta Learning ( VS-ML ) unifies the above and demonstrates that simple weight-sharing and sparsity in an NN is sufficient to express powerful learning algorithms (LAs) in a reusable fashion.
Revised:  Our Variable Shared Meta Learning ( VSML ) unifies the above and demonstrates that simple weight-sharing and sparsity in an NN is sufficient to express powerful learning algorithms (LAs) in a reusable fashion.
Edit intent: clarity
Original:  A simple implementation of VS-ML called VS-ML RNN allows for implementing the backpropagation LA solely by running an RNN in forward-mode.
Revised:  A simple implementation of VS-ML called VS-ML RNN allows for implementing the backpropagation LA solely by running in forward-mode.
Edit intent: clarity
Original:  It can even meta-learn new LAs that improve upon backpropagation and generalize to datasets outside of the meta training distribution without explicit gradient calculation.
Revised:  It can even meta learn new LAs that improve upon backpropagation and generalize to datasets outside of the meta training distribution without explicit gradient calculation.
Edit intent: fluency
Original:  Introspection reveals that our meta-learned LAs learn qualitatively different from gradient descent through fast association .
Revised:  Introspection reveals that our meta learned LAs learn through fast association in a way that is qualitatively different from gradient descent through fast association .
Edit intent: clarity
Original:  Introspection reveals that our meta-learned LAs learn qualitatively different from gradient descent through fast association .
Revised:  Introspection reveals that our meta-learned LAs learn qualitatively different from gradient descent .
Edit intent: clarity
Original:  Using a Reinforcement Learning framework in the game of Go, we develop a simple measure of human adaptation to AI and test its usefulness in two case studies.
Revised:  We develop a simple measure of human adaptation to AI and test its usefulness in two case studies.
Edit intent: coherence
Original:  In Case Study 2, we use our measure to detect a negative form of adaptation to AI , cheating by getting help from AIin a professional match between human experts .
Revised:  In Case Study 2, we test whether our measure is sensitive enough to capture a negative form of adaptation to AI , cheating by getting help from AIin a professional match between human experts .
Edit intent: clarity
Original:  In Case Study 2, we use our measure to detect a negative form of adaptation to AI , cheating by getting help from AIin a professional match between human experts .
Revised:  In Case Study 2, we use our measure to detect a negative form of adaptation to AI (cheating aided by AI), which occurred in a match between professional Go players .
Edit intent: clarity
Original: Across a growing number of domains, human experts are expected to learn from and adapt to AI with superior decision-making abilities.
Revised: Across a growing number of domains, human experts are expected to learn from and adapt to AI with superior decision making abilities.
Edit intent: fluency
Original:  In Case Study 2, we test whether our measure is sensitive enough to capture a negative form of adaptation to AI (cheating aided by AI), which occurred in a match between professional Go players.
Revised:  In Case Study 2, we test whether our measure is sufficiently sensitive to capture a negative form of adaptation to AI (cheating aided by AI), which occurred in a match between professional Go players.
Edit intent: clarity