wanyu/IteraTeR_v2 huggingface dataset:
Original:  Our proposed SNN is seamlessly integrated into Intel's Loihi neuromorphic processor, a non-Von Neumann hardware that mimics the brain's computing paradigms.
Revised:  We integrated our neuromorphic algorithm to Intel's Loihi neuromorphic processor, a non-Von Neumann hardware that mimics the brain's computing paradigms.
Edit intent: clarity
Original:  We performed comparative analyses for accuracy and energy-efficiency between our method and the GMapping algorithm, which is widely used in small environments.
Revised:  We performed comparative analyses for accuracy and energy-efficiency between our neuromorphic approach and the GMapping algorithm, which is widely used in small environments.
Edit intent: clarity
Original:  These results pave the way for extending our approach towards an energy-efficient SLAM that is applicable to Loihi-controlled mobile robots.
Revised:  These results pave the way for scaling our approach towards an energy-efficient SLAM that is applicable to Loihi-controlled mobile robots.
Edit intent: clarity
Original:  These results pave the way for extending our approach towards an energy-efficient SLAM that is applicable to Loihi-controlled mobile robots.
Revised:  These results pave the way for extending our approach towards active-SLAM alternative solutions for Loihi-controlled mobile robots.
Edit intent: clarity
Original:  These results pave the way for extending our approach towards an energy-efficient SLAM that is applicable to Loihi-controlled mobile robots.
Revised:  These results pave the way for extending our approach towards an energy-efficient SLAM that is applicable to Loihi-controlled autonomous robots.
Edit intent: clarity
Original: We present FAST NAVIGATOR , a general framework for action decoding, which yields state-of-the-art results on the recent Room-to-Room (R2R) Vision-and-Language navigation challenge of Anderson et. al. (2018).
Revised: We present FAST NAVIGATOR , a general framework for action decoding, that achieves state-of-the-art results on the recent Room-to-Room (R2R) Vision-and-Language navigation challenge of Anderson et. al. (2018).
Edit intent: clarity
Original: We present FAST NAVIGATOR , a general framework for action decoding, which yields state-of-the-art results on the recent Room-to-Room (R2R) Vision-and-Language navigation challenge of Anderson et. al. (2018).
Revised: We present FAST NAVIGATOR , a general framework for action decoding, which yields state-of-the-art results on the Room-to-Room (R2R) Vision-and-Language navigation challenge of Anderson et. al. (2018).
Edit intent: clarity
Original:  Given a natural language instruction and photo-realistic image views of a previously unseen environment, the agent must navigate from a source to a target location as quickly as possible.
Revised:  Given a natural language instruction and photo-realistic image views of a previously unseen environment, the agent was tasked with navigating from source to target location as quickly as possible.
Edit intent: clarity
Original:  While all of current approaches make local action decisions or score entire trajectories with beam search, our framework seamlessly balances local and global signals when exploring the environment.
Revised:  While all current approaches make local action decisions or score entire trajectories with beam search, our framework seamlessly balances local and global signals when exploring the environment.
Edit intent: clarity
Original:  While all of current approaches make local action decisions or score entire trajectories with beam search, our framework seamlessly balances local and global signals when exploring the environment.
Revised:  While all of current approaches make local action decisions or score entire trajectories using beam search, our framework seamlessly balances local and global signals when exploring the environment.
Edit intent: fluency
Original:  While all of current approaches make local action decisions or score entire trajectories with beam search, our framework seamlessly balances local and global signals when exploring the environment.
Revised:  While all of current approaches make local action decisions or score entire trajectories with beam search, ours balances local and global signals when exploring the environment.
Edit intent: clarity
Original:  While all of current approaches make local action decisions or score entire trajectories with beam search, our framework seamlessly balances local and global signals when exploring the environment.
Revised:  While all of current approaches make local action decisions or score entire trajectories with beam search, our framework seamlessly balances local and global signals when exploring an unobserved environment.
Edit intent: clarity
Original:  Importantly, this allows us to act greedily , but use global signals to backtrack when necessary.
Revised:  Importantly, this lets us act greedily but use global signals to backtrack when necessary.
Edit intent: fluency
Original:  Our FAST framework , applied to existing models, yielded a 17\% relative gain over the previous state-of-the-art , an absolute 6\% gain on success rate weighted by path length (SPL).
Revised:  Applying FAST framework to existing state-of-the-art models achieved a 17\% relative gain over the previous state-of-the-art , an absolute 6\% gain on success rate weighted by path length (SPL).
Edit intent: clarity
Original:  Our FAST framework , applied to existing models, yielded a 17\% relative gain over the previous state-of-the-art , an absolute 6\% gain on success rate weighted by path length (SPL).
Revised:  Our FAST framework , applied to existing models, yielded a 17\% relative gain , an absolute 6\% gain on success rate weighted by path length (SPL).
Edit intent: clarity
Original:  Our FAST framework , applied to existing models, yielded a 17\% relative gain over the previous state-of-the-art , an absolute 6\% gain on success rate weighted by path length (SPL).
Revised:  Our FAST framework , applied to existing models, yielded a 17\% relative gain over the previous state-of-the-art , an absolute 6\% gain on Success rate weighted by path length (SPL).
Edit intent: fluency
Original:  Our FAST framework , applied to existing models, yielded a 17\% relative gain over the previous state-of-the-art , an absolute 6\% gain on success rate weighted by path length (SPL).
Revised:  Our FAST framework , applied to existing models, yielded a 17\% relative gain over the previous state-of-the-art , an absolute 6\% gain on success rate weighted by Path Length (SPL).
Edit intent: fluency
Original: The olfactory system uses the responses of a small number of broadly sensitive receptors to combinatorially encode a vast number of odors.
Revised: The olfactory system uses responses of a small number of broadly sensitive receptors to combinatorially encode a vast number of odors.
Edit intent: fluency
Original:  So a response below threshold signals the absence of all such odorants.
Revised:  So a response below threshold signals absence of all such odorants.
Edit intent: fluency
Original:  We give a simple neural network realization of our algorithm which resembles the known circuit architecture of the piriform cortex .
Revised:  We give a simple neural network realization of our algorithm resembling the circuit architecture in piriform cortex, and propose experimental tests .
Edit intent: clarity
Original: The olfactory system uses responses of a small number of broadly sensitive receptors to combinatorially encode a vast number of odors.
Revised: Olfactory systems use a small number of broadly sensitive receptors to combinatorially encode a vast number of odors.
Edit intent: clarity
Original:  Here, we propose a method for decoding such a distributed representation.
Revised:  We propose a method for decoding such a distributed representation.
Edit intent: coherence
Original:  Our main idea is that a receptor that does not respond to an odor carries more information than a receptor that does, because a typical receptor binds to many odorants.
Revised:  Our main idea is that a receptor that does not respond to an odor carry more information than a receptor that does, because a typical receptor binds to many odorants.
Edit intent: fluency
Original:  We demonstrate that, for biologically realistic numbers of receptors, response functions, and odor mixture complexity, this remarkably simple method of elimination turns an underdetermined decoding problem into an overdetermined one, allowing accurate determination of odorants in a mixture and their concentrations.
Revised:  For realistic numbers of receptors, response functions, and odor mixture complexity, this remarkably simple method of elimination turns an underdetermined decoding problem into an overdetermined one, allowing accurate determination of odorants in a mixture and their concentrations.
Edit intent: coherence
Original:  We demonstrate that, for biologically realistic numbers of receptors, response functions, and odor mixture complexity, this remarkably simple method of elimination turns an underdetermined decoding problem into an overdetermined one, allowing accurate determination of odorants in a mixture and their concentrations.
Revised:  We demonstrate that, for biologically realistic numbers of receptors, response functions, and odor complexity, this remarkably simple method of elimination turns an underdetermined decoding problem into an overdetermined one, allowing accurate determination of odorants in a mixture and their concentrations.
Edit intent: clarity
Original:  We demonstrate that, for biologically realistic numbers of receptors, response functions, and odor mixture complexity, this remarkably simple method of elimination turns an underdetermined decoding problem into an overdetermined one, allowing accurate determination of odorants in a mixture and their concentrations.
Revised:  We demonstrate that, for biologically realistic numbers of receptors, response functions, and odor mixture complexity, this method of elimination turns an underdetermined decoding problem into an overdetermined one, allowing accurate determination of odorants in a mixture and their concentrations.
Edit intent: clarity
Original:  We demonstrate that, for biologically realistic numbers of receptors, response functions, and odor mixture complexity, this remarkably simple method of elimination turns an underdetermined decoding problem into an overdetermined one, allowing accurate determination of odorants in a mixture and their concentrations.
Revised:  We demonstrate that, for biologically realistic numbers of receptors, response functions, and odor mixture complexity, this remarkably simple method of elimination turns an underconstrained decoding problem into an overdetermined one, allowing accurate determination of odorants in a mixture and their concentrations.
Edit intent: clarity
Original:  We demonstrate that, for biologically realistic numbers of receptors, response functions, and odor mixture complexity, this remarkably simple method of elimination turns an underdetermined decoding problem into an overdetermined one, allowing accurate determination of odorants in a mixture and their concentrations.
Revised:  We demonstrate that, for biologically realistic numbers of receptors, response functions, and odor mixture complexity, this remarkably simple method of elimination turns an underdetermined decoding problem into a solvable one, allowing accurate determination of odorants in a mixture and their concentrations.
Edit intent: clarity
Original:  We give a simple neural network realization of our algorithm resembling the circuit architecture in piriform cortex, and propose experimental tests .
Revised:  We construct a neural network realization of our algorithm resembling the circuit architecture in piriform cortex, and propose experimental tests .
Edit intent: clarity
Original:  We give a simple neural network realization of our algorithm resembling the circuit architecture in piriform cortex, and propose experimental tests .
Revised:  We give a simple neural network realization of our algorithm based on the structure of the olfactory pathway .
Edit intent: clarity
Original: We propose the ideal individual model and the behavior coordinate system . Based on the ideal individual model, the behavior coordinate system and the quantum probability, a toy quantum model of human psychology is presented here in a different way.
Revised: We propose the ideal individual model and the behavior coordinate system . Based on the ideal individual model, the behavior coordinate system and the quantum probability, a novel quantum theory of psychology is offered here in a different way.
Edit intent: clarity
Original:  The class of output-oblivious CRNs is fundamental, having appeared in several earlier studies of CRN computation, because it is precisely the class of CRNs that can be composed by simply renaming the output of the upstream CRN to match the input of the downstream CRN.
Revised:  The class of output-oblivious CRNs is fundamental, appearing in earlier studies of CRN computation, because it is precisely the class of CRNs that can be composed by simply renaming the output of the upstream CRN to match the input of the downstream CRN.
Edit intent: clarity
Original:  The key necessary condition is that f is eventually the minimum of a finite number of nondecreasing quilt-affine functions : essentially "nearly affine " functions, with a fixed (rational) linear slope and periodic offsets .
Revised:  The key necessary condition is that for sufficiently large inputs, f is the minimum of a finite number of nondecreasing quilt-affine functions : essentially "nearly affine " functions, with a fixed (rational) linear slope and periodic offsets .
Edit intent: clarity
Original:  The key necessary condition is that f is eventually the minimum of a finite number of nondecreasing quilt-affine functions : essentially "nearly affine " functions, with a fixed (rational) linear slope and periodic offsets .
Revised:  The key necessary condition is that f is eventually the minimum of a finite number of nondecreasing quilt-affine functions . (An affine function is linear with a constant offset; a quilt-affine function is linear with a periodic offset) .
Edit intent: clarity
Original:  Our key technique is to view the sketch as a randomized mirror projection , and perform mirror descent analysis on the expected projection .
Revised:  Our key technique is to view the sketch as a randomized mirror projection , and perform mirror descent analysis on the expected projection .
Edit intent: fluency
Original:  We also apply this sketch to a simple no-regret scheme for semidefinite programming in saddle-point form, where it matches the best known guarantees .
Revised:  We also apply this sketch to semidefinite programming in saddle-point form, where it matches the best known guarantees .
Edit intent: clarity
Original:  While many previous investigations assumed that all users have the same preference  , this may not be true in practice.
Revised:  Many studies assume that all users have the same preference , this may not be true in practice.
Edit intent: clarity
Original:  This work investigates whether and how the information about individual preferences can benefit such cache-aided D2D networks.
Revised:  This work investigates whether and how the information about individual preferences can benefit cache-aided D2D networks.
Edit intent: clarity
Original:  Considering a clustered network , we derive a network utility that considers both the user distribution and channel fading effects , and formulate a utility optimization problem .
Revised:  We examine a clustered network , we derive a network utility that considers both the user distribution and channel fading effects , and formulate a utility optimization problem .
Edit intent: clarity
Original:  Considering a clustered network , we derive a network utility that considers both the user distribution and channel fading effects , and formulate a utility optimization problem .
Revised:  Considering a clustered network and derive a network utility that considers both the user distribution and channel fading effects , and formulate a utility optimization problem .
Edit intent: clarity
Original:  Considering a clustered network , we derive a network utility that considers both the user distribution and channel fading effects , and formulate a utility optimization problem .
Revised:  Considering a clustered network , we derive a network utility that considers both the user distribution and channel fading effects into the analysis. We also formulate a utility optimization problem .
Edit intent: clarity
Original:  This formulation can be used to optimize several important quantities, including throughput, energy efficiency (EE),  and hit-rate, and  solve different tradeoff problems.
Revised:  This formulation can be used to optimize several important quantities, including throughput, energy efficiency (EE), and hit-rate, and to solve different tradeoff problems.
Edit intent: fluency
Original:  We provide designs of caching policies that solve the utility maximization problem with and without coordination between the devices, and prove that the coordinated design can obtain the stationary point under a mild assumption.
Revised:  We provide a general approach that can solve the proposed problem under the assumption that users coordinate, then prove that the coordinated design can obtain the stationary point under a mild assumption.
Edit intent: clarity
Original:  We provide designs of caching policies that solve the utility maximization problem with and without coordination between the devices, and prove that the coordinated design can obtain the stationary point under a mild assumption.
Revised:  We provide designs of caching policies that solve the utility maximization problem with and without coordination between the devices, and prove that the proposed approach can obtain the stationary point under a mild assumption.
Edit intent: clarity
Original:  Besides, different types of tradeoffs exist between different performance metrics , and they can be managed by means of proper caching policy and cooperation distance design .
Revised:  Besides, different types of tradeoffs exist between different performance metrics and that they can be managed by means of proper caching policy and cooperation distance design .
Edit intent: coherence
Original:  Besides, different types of tradeoffs exist between different performance metrics , and they can be managed by means of proper caching policy and cooperation distance design .
Revised:  Besides, different types of tradeoffs exist between different performance metrics , and they can be managed through caching policy and cooperation distance design .
Edit intent: clarity
Original:  Besides, different types of tradeoffs exist between different performance metrics , and they can be managed by means of proper caching policy and cooperation distance design .
Revised:  Besides, different types of tradeoffs exist between different performance metrics , and they can be managed by means of proper caching policy and cooperation distance designs .
Edit intent: fluency
Original:  Vehicular clouds, formed by a collection of vehicles allowing jobs to be offloaded among vehicles, can substantially alleviate heavy on-board workloads and enable on-demand provisioning of computational resources.
Revised:  Vehicular clouds, formed by a collection of vehicles , which allows jobs to be offloaded among vehicles, can substantially alleviate heavy on-board workloads and enable on-demand provisioning of computational resources.
Edit intent: coherence
Original:  In this article , we present a novel framework for vehicular clouds that maps components of graph jobs to service providers via opportunistic vehicle-to-vehicle communication.
Revised:  In this paper , we present a novel framework for vehicular clouds that maps components of graph jobs to service providers via opportunistic vehicle-to-vehicle communication.
Edit intent: fluency
Original:  Then, graph job allocation over vehicular clouds is formulated as a form of non-linear integer programming with respect to vehicles' contact duration and available resources, aiming to minimize job completion time and data exchange cost.
Revised:  Then, graph job allocation over vehicular clouds is formulated as a non-linear integer programming with respect to vehicles' contact duration and available resources, aiming to minimize job completion time and data exchange cost.
Edit intent: clarity
Original:  The problem is approached from two scenarios: low-traffic and rush-hours.
Revised:  The problem is addressed for two scenarios: low-traffic and rush-hours.
Edit intent: clarity
Original:  In the latter case, given  intractable computations for deriving feasible allocations, we propose a novel low-complexity randomized algorithm.
Revised:  In the latter case, given the intractable computations for deriving feasible allocations, we propose a novel low-complexity randomized algorithm.
Edit intent: fluency
Original: It was conjectured by Gupta et . al. [Combinatorica04] that every planar graph can be embedded into \ell_1 with constant distortion.
Revised: It was conjectured by Gupta et al. [Combinatorica04] that every planar graph can be embedded into \ell_1 with constant distortion.
Edit intent: fluency
Original:  However, given an n-vertex weighted planar graph, the best upper bound  is only O(\log n)  by Rao [SoCG99].
Revised:  However, given an n-vertex weighted planar graph, the best upper bound is only O(\log n) , by Rao [SoCG99].
Edit intent: fluency
Original:  In this paper we study the terminated case , where there is a set K of terminals, and the goal is to embed only the terminals into \ell_1 with low distortion.
Revised:  In this paper we study the case where there is a set K of terminals, and the goal is to embed only the terminals into \ell_1 with low distortion.
Edit intent: clarity
Original:  More generally, suppose that the terminals could be covered by \gamma faces .
Revised:  The more general case, where the set of terminals can be covered by \gamma faces .
Edit intent: clarity
Original: Theory13].  ] Our contribution is a further improvement of the upper bound to O(\log\gamma).
Revised: Theory13]. ]. Our contribution is a further improvement of the upper bound to O(\log\gamma).
Edit intent: fluency
Original: Theory13].  ] Our contribution is a further improvement of the upper bound to O(\log\gamma).
Revised: Theory13]. ] Our contribution is a further improvement on the upper bound to O(\log\gamma).
Edit intent: fluency
Original:  Note that since every planar graph has at most O(n) faces, any further improvement of this result, will imply an improvement upon Rao's long standing upper bound.
Revised:  Since every planar graph has at most O(n) faces, any further improvement of this result, will imply an improvement upon Rao's long standing upper bound.
Edit intent: coherence
Original:  Note that since every planar graph has at most O(n) faces, any further improvement of this result, will imply an improvement upon Rao's long standing upper bound.
Revised:  Note that since every planar graph has at most O(n) faces, any further improvement on this result, will imply an improvement upon Rao's long standing upper bound.
Edit intent: clarity
Original:  It is well known that the flow-cut gap equals to the distortion of the best embedding into \ell_1.
Revised:  Moreover, it is well known that the flow-cut gap equals to the distortion of the best embedding into \ell_1.
Edit intent: coherence
Original:  Hence the solution recovered is sometimes either over-fitted or over-smoothed, especially in the presence of discontinuities .
Revised:  An attractive alternative is iterative regularization, where one minimizes an associated functional in a regularized fashion (i.e., stopping at an appropriate iteration). However, in most of the regularization methods the associated minimizing functional contains the noisy data directly, and hence, the recovery gets affected .
Edit intent: coherence