wanyu/IteraTeR_v2 huggingface dataset:
Original:  The agent hears multiple audio sources simultaneously (e.g., a person speaking down the hall in a noisy household) and  must use its eyes and ears to automatically separate out the sounds originating from the target object within a limited time budget.
Revised:  The agent hears multiple audio sources simultaneously (e.g., a person speaking down the hall in a noisy household) and it must use its eyes and ears to automatically separate out the sounds originating from the target object within a limited time budget.
Edit intent: fluency
Original:  The agent hears multiple audio sources simultaneously (e.g., a person speaking down the hall in a noisy household) and  must use its eyes and ears to automatically separate out the sounds originating from the target object within a limited time budget.
Revised:  The agent hears multiple audio sources simultaneously (e.g., a person speaking down the hall in a noisy household) and must use its eyes and ears to automatically separate out the sounds originating from a target object within a limited time budget.
Edit intent: fluency
Original:  The neural tree architecture does not perform message passing on the input graph  but on a tree-structured graph, called the H-tree, that is constructed from the input graph.
Revised:  The neural tree architecture does not perform message passing on the input graph , but on a tree-structured graph, called the H-tree, that is constructed from the input graph.
Edit intent: fluency
Original:  Nodes in the H-tree correspond to subgraphs in the input graph, and they are reorganized in a hierarchical manner such that a parent-node of a node in the H-tree always corresponds to a larger subgraph in the input graph.
Revised:  Nodes in the H-tree correspond to subgraphs in the input graph, and they are reorganized in a hierarchical manner such that the parent of a node in the H-tree always corresponds to a larger subgraph in the input graph.
Edit intent: fluency
Original:  We show that the neural tree architecture can approximate any smooth probability distribution function over an undirected graph , as well as emulate the junction tree algorithm .
Revised:  We show that the neural tree architecture can approximate any smooth probability distribution function over an undirected graph .
Edit intent: coherence
Original: Offline reinforcement learning (RL) enables learning policies using pre-collected datasets without environment interaction, which provides a promising direction to make RL useable in real-world systems.
Revised: Offline reinforcement learning (RL) enables learning policies using pre-collected datasets without environment interaction, which provides a promising direction to make RL usable in real-world systems.
Edit intent: clarity
Original:  Experimental results show that MOPP provides competitive performance compared with existing model-based offline planning and RL approaches , and allows easy adaptation to varying objectives and extra constraints .
Revised:  Experimental results show that MOPP provides competitive performance compared with existing model-based offline planning and RL approaches .
Edit intent: coherence
Original:  The information contains the environment channel response between the transmitter and the receiver, so that the people/objects and their movement in between can be detected by analyzing CSI. CSI is the channel estimation result in the receiver based on the pre-known training field of the transmitted  signal.
Revised:  The information contains the environment channel response between the transmitter and the receiver, so the people/objects and their movement in between can be detected by analyzing CSI. CSI is the channel estimation result in the receiver based on the pre-known training field of the transmitted signal.
Edit intent: coherence
Original:  The information contains the environment channel response between the transmitter and the receiver, so that the people/objects and their movement in between can be detected by analyzing CSI. CSI is the channel estimation result in the receiver based on the pre-known training field of the transmitted  signal.
Revised:  The information contains the environment channel response between the transmitter and the receiver, so that the people/objects and their movement in between can be sensed. To get CSI, the receiver performs channel estimation based on the pre-known training field of the transmitted signal.
Edit intent: clarity
Original:  CSI information is useful in many cases, but it also brings concerns on privacy and security.
Revised:  CSI related technology is useful in many cases, but it also brings concerns on privacy and security.
Edit intent: clarity
Original:  The CSI fuzzer imposes an artificial channel response to the signal before it leaves the transmitter , so the CSI extracted at the receiver will indicate the actual channel response combined with the artificial response.
Revised:  The CSI fuzzer imposes an artificial channel response to the signal before it is transmitted , so the CSI extracted at the receiver will indicate the actual channel response combined with the artificial response.
Edit intent: clarity
Original:  The CSI fuzzer imposes an artificial channel response to the signal before it leaves the transmitter , so the CSI extracted at the receiver will indicate the actual channel response combined with the artificial response.
Revised:  The CSI fuzzer imposes an artificial channel response to the signal before it leaves the transmitter , so the CSI seen by the receiver will indicate the actual channel response combined with the artificial response.
Edit intent: clarity
Original:  Relationship between agents such as their spatial proximity and functional similarities could play a crucial role in cooperation between agents.
Revised:  Relationships between agents such as their spatial proximity and functional similarities could play a crucial role in cooperation between agents.
Edit intent: fluency
Original:  Time-energy trade-off: For any k \geq \log \log N, we show that a leader among at most n devices can be elected deterministically in O(  n^{1+\epsilon}) + O(k \cdot N^{1/k}) time and O(k) energy if each device can simultaneously transmit and listen, where \epsilon > 0 is any small constant.
Revised:  Time-energy trade-off: For any k \geq \log \log N, we show that a leader among at most n devices can be elected deterministically in O( k \cdot n^{1+\epsilon}) + O(k \cdot N^{1/k}) time and O(k) energy if each device can simultaneously transmit and listen, where \epsilon > 0 is any small constant.
Edit intent: fluency
Original: In this document, some general results from approximation theory and matrix analysis with applications to the approximate sparse identification of time series models and nonlinear discrete-time dynamical systems are presented.
Revised: In this document, some general results in approximation theory and matrix analysis with applications to the approximate sparse identification of time series models and nonlinear discrete-time dynamical systems are presented.
Edit intent: fluency
Original: In this document, some general results from approximation theory and matrix analysis with applications to the approximate sparse identification of time series models and nonlinear discrete-time dynamical systems are presented.
Revised: In this document, some general results from approximation theory and matrix analysis with applications to sparse identification of time series models and nonlinear discrete-time dynamical systems are presented.
Edit intent: coherence
Original:  The aforementioned theoretical methods are translated into predictive algorithms that can be used to approximately simulate the behavior of a given dynamical system , based on some structured data measured from the system .
Revised:  The aforementioned theoretical methods are translated into algorithms that can be used to approximately simulate the behavior of a given dynamical system , based on some structured data measured from the system .
Edit intent: clarity
Original:  The aforementioned theoretical methods are translated into predictive algorithms that can be used to approximately simulate the behavior of a given dynamical system , based on some structured data measured from the system .
Revised:  The aforementioned theoretical methods are translated into predictive algorithms that can be used to approximately simulate the behavior of a given dynamical system , based on structured data measured from the system .
Edit intent: clarity
Original:  The aforementioned theoretical methods are translated into predictive algorithms that can be used to approximately simulate the behavior of a given dynamical system , based on some structured data measured from the system .
Revised:  The aforementioned theoretical methods are translated into predictive algorithms that can be used to approximately simulate the behavior of a given dynamical system , based on some structured data measured from the systems .
Edit intent: clarity
Original:  The results of the experiment show that the mean opinion scores (MOS) of It\text{o}TTS and It\text{o}Wave can exceed the current state-of-the-art methods,  reached 3.925\pm0.
Revised:  The results of the experiment show that the mean opinion scores (MOS) of It\text{o}TTS and It\text{o}Wave can exceed the current state-of-the-art methods, and reached 3.925\pm0.
Edit intent: coherence
Original:  However, since these features contain rich multimodal patterns and most of them are irrelevant to the recommendation purpose  , excessive reliance on these features will make the model  difficult to generalize.
Revised:  However, since these features contain rich multimodal information, and most of them are irrelevant to the recommendation purpose , excessive reliance on these features will make the model difficult to generalize.
Edit intent: clarity
Original:  However, since these features contain rich multimodal patterns and most of them are irrelevant to the recommendation purpose  , excessive reliance on these features will make the model  difficult to generalize.
Revised:  However, since these features contain rich multimodal patterns and most of them are irrelevant to the recommendation purpose . Therefore , excessive reliance on these features will make the model difficult to generalize.
Edit intent: coherence
Original:  To address the above two challenges , we propose a VBAE for recommendation.
Revised:  In this article , we propose a VBAE for recommendation.
Edit intent: clarity
Original:  Furthermore, VBAE establishes an information regulation mechanism by introducing a user-dependent channel variable where the bandwidth is determined by the information already contained in the observed ratings to dynamically control the amount of information allowed to be accessed from the corresponding user features.
Revised:  Furthermore, VBAE establishes an information regulation mechanism by introducing a user-dependent channel to dynamically control the amount of information allowed to be accessed from the corresponding user features.
Edit intent: coherence
Original:  Furthermore, VBAE establishes an information regulation mechanism by introducing a user-dependent channel variable where the bandwidth is determined by the information already contained in the observed ratings to dynamically control the amount of information allowed to be accessed from the corresponding user features.
Revised:  Furthermore, VBAE establishes an information regulation mechanism by introducing a user-dependent channel variable where the bandwidth is determined by the information already contained in the observed ratings to dynamically control the information allowed to be accessed from the corresponding user features.
Edit intent: clarity
Original:  Due to both the non-convex objective and the BATS code-related variables, the algorithms developed for the existing flow optimization problems can not be directed applied to solve our NUM problem.
Revised:  Due to both the probably nonconcave objective and the BATS code-related variables, the algorithms developed for the existing flow optimization problems can not be directed applied to solve our NUM problem.
Edit intent: clarity
Original:  Due to both the non-convex objective and the BATS code-related variables, the algorithms developed for the existing flow optimization problems can not be directed applied to solve our NUM problem.
Revised:  Due to both the non-convex objective and the BATS code-related variables, the algorithms developed for the existing flow optimization problems cannot be applied directly to solve our NUM problem.
Edit intent: fluency
Original:  We introduce a two-step algorithm for solving the NUM problem, where the first step solves the problem with nonadaptive recoding schemes, and the second step optimizes adaptive recoding hop-by-hop from upstream to downstream in each flow.
Revised:  We introduce a two-step algorithm to solve our NUM problem, where the first step solves the problem with nonadaptive recoding schemes, and the second step optimizes adaptive recoding hop-by-hop from upstream to downstream in each flow.
Edit intent: clarity
Original: Batched network coding (BNC) is a low-complexity solution to network transmission in feedbackless multi-hop packet networks with packet loss.
Revised: Batched network coding (BNC) is a low-complexity solution to network transmission in multi-hop packet networks with packet loss.
Edit intent: clarity
Original:  In order to adapt  random fluctuations in the number of erasures in individual batches, it is not optimal to recode and transmit the same number of packets for all batches.
Revised:  In order to adapt to random fluctuations in the number of erasures in individual batches, it is not optimal to recode and transmit the same number of packets for all batches.
Edit intent: fluency
Original:  We show that the expected rank functions are concave when the packet loss pattern is a stationary stochastic process regardless of the field size , which covers but not limited to independent packet loss and burst packet loss .
Revised:  We show that the expected rank functions are concave when the packet loss pattern is a stationary stochastic process , which covers but not limited to independent packet loss and burst packet loss .
Edit intent: clarity
Original:  To obtain such an optimal solution, we propose tuning schemes that can turn any feasible solution into a desired optimal solution.
Revised:  We provide an algorithm to obtain such an optimal solution, we propose tuning schemes that can turn any feasible solution into a desired optimal solution.
Edit intent: clarity
Original:  To obtain such an optimal solution, we propose tuning schemes that can turn any feasible solution into a desired optimal solution.
Revised:  To obtain such an optimal optimal solution, and propose tuning schemes that can turn any feasible solution into a desired optimal solution.
Edit intent: coherence
Original: We propose a deterministic Kaczmarz method for solving linear systems A\x=\b with A nonsingular.
Revised: We propose a deterministic Kaczmarz algorithm for solving linear systems A\x=\b with A nonsingular.
Edit intent: clarity
Original:  Instead of using orthogonal projections , we use reflections in the original Kaczmarz iterative method .
Revised:  Instead of using orthogonal projections , we use reflections in each step of the iteration .
Edit intent: clarity
Original:  This generates a series of points on an n-sphere \S centered at the solution%DIFDELCMD < \x%%% _*=A^{-1\b.
Revised:  This generates a series of points %DIFDELCMD < \x%%% _*=A^{-1\b.
Edit intent: clarity
Original:  We will show how to choose these points efficiently.
Revised:  We will show how to select these points efficiently.
Edit intent: fluency
Original:  The numerical testsshow that in practice this deterministic scheme converges much faster than we expected and can beat the (block) randomized Kaczmarz methodsA }\x  \b, where W is the low-triangular matrix such that W+W^T=2AA^T.
Revised:  From the numerical tests, our Kaczmarz algorithm usually converges more quickly than the (block) randomized Kaczmarz methodsA }\x \b, where W is the low-triangular matrix such that W+W^T=2AA^T.
Edit intent: clarity
Original: This paper introduces a general framework for explicitly constructing universal deep neural models with inputs from a complete, separable, and locally-compact metric space X and outputs in the Wasserstein-1  P_1( \mathcal{Y .
Revised: We introduce a general framework for explicitly constructing universal deep neural models with inputs from a complete, separable, and locally-compact metric space X and outputs in the Wasserstein-1 P_1( \mathcal{Y .
Edit intent: clarity
Original: This paper introduces a general framework for explicitly constructing universal deep neural models with inputs from a complete, separable, and locally-compact metric space X and outputs in the Wasserstein-1  P_1( \mathcal{Y .
Revised: This paper introduces a general framework for explicitly constructing universal deep neural models with inputs from a complete, separable, and locally-compact metric space X and outputs in the Wasserstein-1 space P_1( \mathcal{Y .
Edit intent: clarity
Original:  We find that any model built using the proposed framework is dense in the space C(X,P_1(Y)) of continuous functions from \mathcal{X to P_1( \mathcal{Y .
Revised:  We find that the models built using our framework can approximate any continuous functions from \mathcal{X to P_1( \mathcal{Y .
Edit intent: clarity
Original:  We identify two methods in which the curse of dimensionality can be broken.
Revised:  We identify two methods for avoiding the " curse of dimensionality can be broken.
Edit intent: clarity
Original:  The proposed }  framework is used to derive an affirmative answer to the open conjecture of Bishop (1994);
Revised:  The proposed } Our framework is used to derive an affirmative answer to the open conjecture of Bishop (1994);
Edit intent: clarity
Original:  The proposed }  framework is used to derive an affirmative answer to the open conjecture of Bishop (1994);
Revised:  The proposed } framework is used to obtain an affirmative answer to the open conjecture of Bishop (1994);
Edit intent: clarity
Original:  namely: mixture density networks are generic regular conditional distributions.
Revised:  namely: mixture density networks are universal regular conditional distributions.
Edit intent: clarity
Original:  Numerical experiments are performed in the contexts of extreme learning machines, randomized DNNs , and heteroscedastic regression  .
Revised:  The predictive performance of the proposed models is evaluated against comparable learning models on various probabilistic predictions tasks in the context of ELMs, model uncertainty , and heteroscedastic regression .
Edit intent: clarity
Original:  For general n, and t%DIFDELCMD < \le %%% n/2, we give a  linear programming lower bound involving Charlier polynomials.
Revised:  For general n, %DIFDELCMD < \le %%% n/2, we give a linear programming lower bound involving Charlier polynomials.
Edit intent: coherence
Original:  For general n, and t%DIFDELCMD < \le %%% n/2, we give a  linear programming lower bound involving Charlier polynomials.
Revised:  For general n, and t%DIFDELCMD < \le %%% n/2, we give a \% linear programming lower bound involving Charlier polynomials.
Edit intent: fluency
Original:  In general, based on numerical evidence, we conjecture that t-designs have size n(n-1)\dots (n-t+1), or larger .
Revised:  In general, based on numerical evidence, we conjecture that t-designs of n(n-1)\dots (n-t+1), or larger .
Edit intent: clarity
Original:  Although we use low-cost and low-power contact microphones to detect the vibrations, our results show that learning from multi-modal data enables us to transform cheap acoustic sensorsinto rich visual sensors . Due to the ubiquity of containers, we believe integrating perception capabilities into them will enable new applications in human-computer interaction and robotics.
Revised:  Although we use low-cost and low-power contact microphones to detect the vibrations, our results show that learning from multimodal data enables state estimation from affordable audio sensors . Due to the ubiquity of containers, we believe integrating perception capabilities into them will enable new applications in human-computer interaction and robotics.
Edit intent: clarity
Original:  Although we use low-cost and low-power contact microphones to detect the vibrations, our results show that learning from multi-modal data enables us to transform cheap acoustic sensorsinto rich visual sensors . Due to the ubiquity of containers, we believe integrating perception capabilities into them will enable new applications in human-computer interaction and robotics.
Revised:  Although we use low-cost and low-power contact microphones to detect the vibrations, our results show that learning from multi-modal data enables us to transform cheap acoustic sensorsinto rich visual sensors . Due to the ubiquity of containers, we believe the box will have a number of applications in robotics.
Edit intent: clarity
Original:  With the help of the rear sentinel instead of the traditional header node, we avoid additional check steps in the pop operation .
Revised:  With the help of the rear sentinel instead of the usual header node, we avoid additional check steps in the pop operation .
Edit intent: fluency
Original:  The essence of this representation is the half-opened pointer interval  , which can guarantee the uniform treatment even in the empty queue case.
Revised:  The essence of our representation is the half-opened pointer interval , which can guarantee the uniform treatment even in the empty queue case.
Edit intent: fluency
Original:  The simplification of queue implementations cuts off unnecessary steps, and it minimizes the number of steps in the dequeue operation with the time limitation of enqueue operation, which could contribute to the the performance of the real-time systems.
Revised:  The simplification of queue implementations cuts off unnecessary steps, and it minimizes the number of steps in the dequeue operation with the time limitation of enqueue operation, which could contribute to the performance of the real-time systems.
Edit intent: fluency
Original: Deep data types are those that are defined in terms of other such data types, including, possibly, themselves.
Revised: Deep data types are those that are constructed from other data types, including, possibly, themselves.
Edit intent: clarity
Original:  In that case, they are said to be truly nested.
Revised:  In this case, they are said to be truly nested.
Edit intent: coherence
Original:  In this paper we show how to extend deep induction to deep GADTs that are not truly nested .
Revised:  In this paper we show how to extend deep induction to GADTs that are not truly nested .
Edit intent: clarity
Original:  We also show that deep induction cannot be extended to truly nested GADTs  .
Revised:  We also show that the techniques developed in this paper do not suffice for extending deep induction to truly nested GADTs .
Edit intent: clarity
Original:  However, as occlusions limit the vehicle's perception ability, reasoning about potential hazards beyond the field-of-view is one of the most challenging issues in developing autonomous driving systems.
Revised:  However, as occlusions limit the vehicle's perception ability, reasoning about potential hazards beyond the field of view is one of the most challenging issues in developing autonomous driving systems.
Edit intent: fluency
Original:  However, those studies are mainly based on the statistical correlation or bayesian causality inference, lacking of physical and neuroscience level interpretability.
Revised:  However, those studies are mainly based on the statistical correlation or bayesian causality inference, lacking physical and neuroscience level interpretability.
Edit intent: coherence
Original:  Here, we propose a Kuramoto model physical based framework to investigate oxytocin effects on the phase dynamical neural coupling in DMN and FPN.
Revised:  Here, we propose a Kuramoto model physical-based framework to investigate oxytocin effects on the phase dynamical neural coupling in DMN and FPN.
Edit intent: fluency