wanyu/IteraTeR_full_sent huggingface dataset:
Original:  Finally, we apply our theory to a  model of Escherichia coli chemotaxis and show that, from this abstract point of view, adaptation or homeostasis in this model is caused by a mechanism that we called input counterweight.
Revised:  Finally, we apply our theory to a specific model of Escherichia coli chemotaxis and show that, from this abstract point of view, adaptation or homeostasis in this model is caused by a mechanism that we called input counterweight.
Edit intent: clarity
Original:  Finally, we apply our theory to a  model of Escherichia coli chemotaxis and show that, from this abstract point of view, adaptation or homeostasis in this model is caused by a mechanism that we called input counterweight.
Revised:  Finally, we apply our theory to a model of Escherichia coli chemotaxis and show that, from our abstract point of view, adaptation or homeostasis in this model is caused by a mechanism that we called input counterweight.
Edit intent: fluency
Original:  Finally, we apply our theory to a  model of Escherichia coli chemotaxis and show that, from this abstract point of view, adaptation or homeostasis in this model is caused by a mechanism that we called input counterweight.
Revised:  Finally, we apply our theory to a model of Escherichia coli chemotaxis and show that, from this abstract point of view, adaptation or homeostasis in the model is caused by a mechanism that we called input counterweight.
Edit intent: coherence
Original:  While this underlying involution proposal structure suggests a scope which includes Hamiltonian-type kernel structures , we demonstrate that our result also recovers a broad range of kernels encompassed by a previous general state space approach in [Tierney, Annals of Applied Probability, 1998]  . Altogether, the theoretical unity and reach of our main result provides a basis for deriving novel sampling algorithms while laying bare important relationships between existing methods.
Revised:  Note that, while this underlying proposal structure suggests a scope which includes Hamiltonian-type kernel structures , we demonstrate that our result also recovers a broad range of kernels encompassed by a previous general state space approach in [Tierney, Annals of Applied Probability, 1998] . Altogether, the theoretical unity and reach of our main result provides a basis for deriving novel sampling algorithms while laying bare important relationships between existing methods.
Edit intent: clarity
Original:  While this underlying involution proposal structure suggests a scope which includes Hamiltonian-type kernel structures , we demonstrate that our result also recovers a broad range of kernels encompassed by a previous general state space approach in [Tierney, Annals of Applied Probability, 1998]  . Altogether, the theoretical unity and reach of our main result provides a basis for deriving novel sampling algorithms while laying bare important relationships between existing methods.
Revised:  While this underlying involution proposal structure suggests a scope which includes Hamiltonian-type kernels , we demonstrate that our result also recovers a broad range of kernels encompassed by a previous general state space approach in [Tierney, Annals of Applied Probability, 1998] . Altogether, the theoretical unity and reach of our main result provides a basis for deriving novel sampling algorithms while laying bare important relationships between existing methods.
Edit intent: clarity
Original:  While this underlying involution proposal structure suggests a scope which includes Hamiltonian-type kernel structures , we demonstrate that our result also recovers a broad range of kernels encompassed by a previous general state space approach in [Tierney, Annals of Applied Probability, 1998]  . Altogether, the theoretical unity and reach of our main result provides a basis for deriving novel sampling algorithms while laying bare important relationships between existing methods.
Revised:  While this underlying involution proposal structure suggests a scope which includes Hamiltonian-type kernel structures , we demonstrate that our abstract result is, in an appropriate sense, equivalent to an earlier general state space approach in [Tierney, Annals of Applied Probability, 1998] . Altogether, the theoretical unity and reach of our main result provides a basis for deriving novel sampling algorithms while laying bare important relationships between existing methods.
Edit intent: meaning-changed
Original:  While this underlying involution proposal structure suggests a scope which includes Hamiltonian-type kernel structures , we demonstrate that our result also recovers a broad range of kernels encompassed by a previous general state space approach in [Tierney, Annals of Applied Probability, 1998]  . Altogether, the theoretical unity and reach of our main result provides a basis for deriving novel sampling algorithms while laying bare important relationships between existing methods.
Revised:  While this underlying involution proposal structure suggests a scope which includes Hamiltonian-type kernel structures , we demonstrate that our result also recovers a broad range of kernels encompassed by a previous general state space setting developed in [Tierney, Annals of Applied Probability, 1998] . Altogether, the theoretical unity and reach of our main result provides a basis for deriving novel sampling algorithms while laying bare important relationships between existing methods.
Edit intent: clarity
Original:  While this underlying involution proposal structure suggests a scope which includes Hamiltonian-type kernel structures , we demonstrate that our result also recovers a broad range of kernels encompassed by a previous general state space approach in [Tierney, Annals of Applied Probability, 1998]  . Altogether, the theoretical unity and reach of our main result provides a basis for deriving novel sampling algorithms while laying bare important relationships between existing methods.
Revised:  While this underlying involution proposal structure suggests a scope which includes Hamiltonian-type kernel structures , we demonstrate that our result also recovers a broad range of kernels encompassed by a previous general state space approach in [Tierney, Annals of Applied Probability, 1998] where the connection to Hamiltonian methods was more obscure . Altogether, the theoretical unity and reach of our main result provides a basis for deriving novel sampling algorithms while laying bare important relationships between existing methods.
Edit intent: meaning-changed
Original:   In this paper, we  propose a method utilizing named entity recognition (NER) and part-of-speech (POS) as auxiliary sequence labeling (SL) tasks for disfluency detection.
Revised:  Existing works for disfluency detection have focused on designing a single objective only for disfluency detection, while auxiliary objectives utilizing linguistic information of a word such as named entity or part-of-speech information can be effective. In this paper, we propose a method utilizing named entity recognition (NER) and part-of-speech (POS) as auxiliary sequence labeling (SL) tasks for disfluency detection.
Edit intent: meaning-changed
Original:   In this paper, we  propose a method utilizing named entity recognition (NER) and part-of-speech (POS) as auxiliary sequence labeling (SL) tasks for disfluency detection.
Revised:  In this paper, we focus on detecting disfluencies on spoken transcripts and propose a method utilizing named entity recognition (NER) and part-of-speech (POS) as auxiliary sequence labeling (SL) tasks for disfluency detection.
Edit intent: meaning-changed
Original:  First  , we show that training a disfluency detection model with auxiliary SL tasks can improve its F-score in disfluency detection.
Revised:  First , we investigate cases that utilizing linguistic information of a word can prevent mispredicting important words and can be helpful for the correct detection of disfluencies. Second , we show that training a disfluency detection model with auxiliary SL tasks can improve its F-score in disfluency detection.
Edit intent: meaning-changed
Original:  In particular, through this structure, we obtain the first constant-factor approximation for the Balanced Connected Partition (BCP) problem, where the task is to partition a vertex-weighted graph into k connected components of approximately equal weight.
Revised:  In particular, through this structure, we obtain the first constant-factor approximation for the Balanced Connected Partition (BCP) problem, where the task is to partition a vertex-weighted graph into k connected components of approximately equal weight.
Edit intent: fluency
Original:  We derive a 3-approximation for the two most commonly used objectives of maximizing the weight of the lightest component or minimizing the weight of the heaviest component . Further, we show how to compute our balanced crown decomposition very efficiently which as an intermediate result yields an improved running time in O(|V||E|) for the well-known (Weighted) q-Expansion Lemma .
Revised:  We derive a 3-approximation for the two most commonly used objectives of maximizing the weight of the lightest component or minimizing the weight of the heaviest component .
Edit intent: coherence
Original:  We give the first randomized algorithms for this problem running in time ( \text{nnz  + \text{nnz  + c^2) \cdot k/\varepsilon^{1.
Revised:  We give the first randomized algorithms for this problem running in time ( nnz + \text{nnz + c^2) \cdot k/\varepsilon^{1.
Edit intent: fluency
Original:  We give the first randomized algorithms for this problem running in time ( \text{nnz  + \text{nnz  + c^2) \cdot k/\varepsilon^{1.
Revised:  We give the first randomized algorithms for this problem running in time ( \text{nnz (A) + \text{nnz + c^2) \cdot k/\varepsilon^{1.
Edit intent: meaning-changed
Original:  We give the first randomized algorithms for this problem running in time ( \text{nnz  + \text{nnz  + c^2) \cdot k/\varepsilon^{1.
Revised:  We give the first randomized algorithms for this problem running in time ( \text{nnz + nnz + c^2) \cdot k/\varepsilon^{1.
Edit intent: meaning-changed
Original:  We give the first randomized algorithms for this problem running in time ( \text{nnz  + \text{nnz  + c^2) \cdot k/\varepsilon^{1.
Revised:  We give the first randomized algorithms for this problem running in time ( \text{nnz + \text{nnz (B) + c^2) \cdot k/\varepsilon^{1.
Edit intent: meaning-changed
Original:  As both (1) spectral low rank approximation (A = B) and (2) linear system solving ( m = n and d = 1) are special cases, our time cannot be improved by more than a 1/\varepsilon factor (up to polylogarithmic factors) without a major breakthrough in linear algebra.
Revised:  As both (1) spectral low rank approximation (A = B) and (2) linear system solving ( n = c and d = 1) are special cases, our time cannot be improved by more than a 1/\varepsilon factor (up to polylogarithmic factors) without a major breakthrough in linear algebra.
Edit intent: meaning-changed
Original:  These applications raised the interest of the community for theoretical properties of this type of codes, such as the hardness of decoding in rank metric or better decoding algorithms . Among classical problems associated to codes for a given metric, the notion of code equivalence  has always been of the greatest interest  .
Revised:  These applications raised the interest of the community for theoretical properties of this type of codes, such as the hardness of decoding in rank metric . Among classical problems associated to codes for a given metric, the notion of code equivalence has always been of the greatest interest .
Edit intent: clarity
Original:  These applications raised the interest of the community for theoretical properties of this type of codes, such as the hardness of decoding in rank metric or better decoding algorithms . Among classical problems associated to codes for a given metric, the notion of code equivalence  has always been of the greatest interest  .
Revised:  These applications raised the interest of the community for theoretical properties of this type of codes, such as the hardness of decoding in rank metric or better decoding algorithms . Among classical problems associated to codes for a given metric, the notion of code equivalence (to decide if two codes are isometric) has always been of the greatest interest .
Edit intent: meaning-changed
Original:  These applications raised the interest of the community for theoretical properties of this type of codes, such as the hardness of decoding in rank metric or better decoding algorithms . Among classical problems associated to codes for a given metric, the notion of code equivalence  has always been of the greatest interest  .
Revised:  These applications raised the interest of the community for theoretical properties of this type of codes, such as the hardness of decoding in rank metric or better decoding algorithms . Among classical problems associated to codes for a given metric, the notion of code equivalence has always been of the greatest interest , for its cryptographic applications or its deep connexions to the graph isomorphism problem .
Edit intent: meaning-changed
Original:  Inspired by May's analysis of the stability of random ecological communities, we analyze the threshold for reaction-diffusion systems whose linearized dynamics near a homogeneous fixed point are given by a random matrix .
Revised:  Inspired by May's analysis of the stability of random ecological communities, we analyze the probability distribution of the diffusive threshold in reaction-diffusion systems whose linearized dynamics near a homogeneous fixed point are given by a random matrix .
Edit intent: meaning-changed
Original:  Inspired by May's analysis of the stability of random ecological communities, we analyze the threshold for reaction-diffusion systems whose linearized dynamics near a homogeneous fixed point are given by a random matrix .
Revised:  Inspired by May's analysis of the stability of random ecological communities, we analyze the threshold for reaction-diffusion systems defined by random matrices describing linearized dynamics near a homogeneous fixed point are given by a random matrix .
Edit intent: clarity
Original:  In the numerically tractable cases of N\leqslant 6, we find that the diffusive threshold generically decreases as N increases and that  these many-species instabilities generally require all species to be diffusing .
Revised:  In the numerically tractable cases N\leqslant 6, we find that the diffusive threshold generically decreases as N increases and that these many-species instabilities generally require all species to be diffusing .
Edit intent: clarity
Original:  In the numerically tractable cases of N\leqslant 6, we find that the diffusive threshold generically decreases as N increases and that  these many-species instabilities generally require all species to be diffusing .
Revised:  In the numerically tractable cases of N\leqslant 6, we find that the diffusive threshold becomes more likely to be smaller and physical as N increases and that these many-species instabilities generally require all species to be diffusing .
Edit intent: meaning-changed
Original:  In the numerically tractable cases of N\leqslant 6, we find that the diffusive threshold generically decreases as N increases and that  these many-species instabilities generally require all species to be diffusing .
Revised:  In the numerically tractable cases of N\leqslant 6, we find that the diffusive threshold generically decreases as N increases and that most of these many-species instabilities generally require all species to be diffusing .
Edit intent: clarity
Original:  In the numerically tractable cases of N\leqslant 6, we find that the diffusive threshold generically decreases as N increases and that  these many-species instabilities generally require all species to be diffusing .
Revised:  In the numerically tractable cases of N\leqslant 6, we find that the diffusive threshold generically decreases as N increases and that these many-species instabilities cannot be described by reduced models with fewer species .
Edit intent: meaning-changed
Original:  Since validating drug combinations via direct screening is prohibitively expensive due to combinatorial explosion, recent approaches have applied machine learning to identify synergistic combinations for cancer . However, these approaches is not readily applicable to many diseases with limited combination data.
Revised:  Since validating drug combinations via direct screening is prohibitively expensive due to combinatorial explosion, recent approaches have applied machine learning to identify synergistic combinations for cancer , but they are not applicable to new diseases with limited combination data.
Edit intent: clarity
Original:  Our model is trained and evaluated on two SARS-CoV-2 drug combination screens and achieves 0.777 test AUC , which is 10\% higher than the model trained without drug-target interaction  .
Revised:  Our model is trained and evaluated on two SARS-CoV-2 drug combination screens and achieves 0.777 test AUC , which is 10\% higher than the model trained without drug-target interactionexplain .
Edit intent: meaning-changed
Original:  Our model is trained and evaluated on two SARS-CoV-2 drug combination screens and achieves 0.777 test AUC , which is 10\% higher than the model trained without drug-target interaction  .
Revised:  Our model is trained and evaluated on two SARS-CoV-2 drug combination screens and achieves 0.777 test AUC , which is 10\% higher than the model trained without drug-target interaction how a biological target affects drug synergy. By utilizing additional biological information, our model achieves 0.78 test AUC in drug synergy prediction using only 90 COVID drug combinations for training. We experimentally tested the model predictions in the U.S. National Center for Advancing Translational Sciences (NCATS) facilities and discovered two novel drug combinations (Remdesivir + Reserpine and Remdesivir + IQ-1S) with strong synergy in vitro .
Edit intent: meaning-changed
Original:  More precisely, we inject the ego 's cost function with an adversarial phase, a time interval during which other agents are assumed to be temporarily distracted, to robustify the ego agent's trajectory against other agents' potentially dangerous behavior during this time.
Revised:  More precisely, we prepend an adversarial phase to the ego agent 's cost function with an adversarial phase, a time interval during which other agents are assumed to be temporarily distracted, to robustify the ego agent's trajectory against other agents' potentially dangerous behavior during this time.
Edit intent: clarity
Original:  More precisely, we inject the ego 's cost function with an adversarial phase, a time interval during which other agents are assumed to be temporarily distracted, to robustify the ego agent's trajectory against other agents' potentially dangerous behavior during this time.
Revised:  More precisely, we inject the ego 's cost function . That is, we prepend a time interval during which other agents are assumed to be temporarily distracted, to robustify the ego agent's trajectory against other agents' potentially dangerous behavior during this time.
Edit intent: meaning-changed
Original:  More precisely, we inject the ego 's cost function with an adversarial phase, a time interval during which other agents are assumed to be temporarily distracted, to robustify the ego agent's trajectory against other agents' potentially dangerous behavior during this time.
Revised:  More precisely, we inject the ego 's cost function with an adversarial phase, a time interval during which other agents are assumed to be temporarily distracted, in order to render the ego agent's trajectory against other agents' potentially dangerous behavior during this time.
Edit intent: coherence
Original:  More precisely, we inject the ego 's cost function with an adversarial phase, a time interval during which other agents are assumed to be temporarily distracted, to robustify the ego agent's trajectory against other agents' potentially dangerous behavior during this time.
Revised:  More precisely, we inject the ego 's cost function with an adversarial phase, a time interval during which other agents are assumed to be temporarily distracted, to robustify the ego agent's equilibrium trajectory robust against other agents' potentially dangerous behavior during this time.
Edit intent: meaning-changed
Original: The  search for objects of interest in an unknown environment by making data-collection decisions (i.e., active search or active sensing) has robotics applications in many fields, including the search and rescue of human survivors following disasters , detecting gas leaks or locating and preventing animal poachers.
Revised: The active search for objects of interest in an unknown environment by making data-collection decisions (i.e., active search or active sensing) has robotics applications in many fields, including the search and rescue of human survivors following disasters , detecting gas leaks or locating and preventing animal poachers.
Edit intent: fluency
Original: The  search for objects of interest in an unknown environment by making data-collection decisions (i.e., active search or active sensing) has robotics applications in many fields, including the search and rescue of human survivors following disasters , detecting gas leaks or locating and preventing animal poachers.
Revised: The search for objects of interest in an unknown environment has many robotics applications including search and rescue of human survivors following disasters , detecting gas leaks or locating and preventing animal poachers.
Edit intent: clarity
Original: The  search for objects of interest in an unknown environment by making data-collection decisions (i.e., active search or active sensing) has robotics applications in many fields, including the search and rescue of human survivors following disasters , detecting gas leaks or locating and preventing animal poachers.
Revised: The search for objects of interest in an unknown environment by making data-collection decisions (i.e., active search or active sensing) has robotics applications in many fields, including the search and rescue , detecting gas leaks or locating and preventing animal poachers.
Edit intent: clarity
Original: The  search for objects of interest in an unknown environment by making data-collection decisions (i.e., active search or active sensing) has robotics applications in many fields, including the search and rescue of human survivors following disasters , detecting gas leaks or locating and preventing animal poachers.
Revised: The search for objects of interest in an unknown environment by making data-collection decisions (i.e., active search or active sensing) has robotics applications in many fields, including the search and rescue of human survivors following disasters , detecting gas leaks or locating animal poachers.
Edit intent: coherence
Original:  We present an algorithm called Noise-Aware Thompson Sampling (NATS) that addresses these issues for multiple ground-based robot agents performing active search considering two sources of sensory information from monocular optical imagery and sonar tracking.
Revised:  We present an algorithm called Noise-Aware Thompson Sampling (NATS) that addresses these issues for multiple ground-based robots performing active search considering two sources of sensory information from monocular optical imagery and sonar tracking.
Edit intent: clarity