wanyu/IteraTeR_full_sent huggingface dataset:
Original:  The only requisite information about unseen types is the name of their labels. We propose a Parasitic Neural Network (PNN), and it can learn a mapping between the general feature representations of text samples and the distributions of unseen types in a shared semantic space. Experiment results show that our model significantly outperforms others on the unseen relation extraction task and achieves effect improvement more than 20\%, when there are not any manual annotations or additional resources .
Revised:  The only requisite information about unseen types is the methods for English are not compatible with that for Chinese. The diversities between Chinese and English linguistics are mainly reflected in morphology and syntax .
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Original:  This paper focuses on the translation system and improves performance by utilizing Transformer networks. We report a wide range of experimental results for various Transformer setups and introduce the use of Spatial-Temporal Multi-Cue (STMC) networks in an end-to-end SLT system with Transformer. We perform experiments on RWTH-PHOENIX-Weather 2014T, a challenging SLT benchmark dataset of German sign language, and ASLG-PC12, a dataset involving American Sign Language (ASL) recently used in gloss-to-text translation. Our methodology improves on the current state-of-the-art by over 5 and 7 points respectively in BLEU-4 score on ground truth glosses and by using an STMC network to predict glosses of the RWTH-PHOENIX-Weather 2014T dataset.
Revised:  This paper focuses on the translation system and introduces the STMC-Transformer which improves on the current state-of-the-art by over 5 and 7 points respectively in BLEU-4 score on ground truth glosses and by using an STMC network to predict glosses of the RWTH-PHOENIX-Weather 2014T dataset.
Edit intent: clarity
Original:  Our methodology improves on the current state-of-the-art by over 5 and 7 points respectively in BLEU-4 score on ground truth glosses and by using an STMC network to predict glosses of the RWTH-PHOENIX-Weather 2014T dataset.
Revised:  Our methodology improves on the current state-of-the-art by over 5 and 7 BLEU respectively on gloss-to-text and video-to-text translation of the PHOENIX-Weather 2014T dataset.
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Original:  On the ASLG-PC12 corpus, we report an improvement of over 16 points in BLEU-4. Our findings also demonstrate that end-to-end translation on predicted glosses provides even better performance than translation on ground truth glosses.
Revised:  On the ASLG-PC12 corpus, we report an improvement of over 16 BLEU. We also demonstrate the problem in current methods that rely on gloss supervision. The video-to-text translation of our STMC-Transformer outperforms translation of GT glosses.
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Original:  This shows potential for further improvement in SLT by either jointly training the SLR and translation systems or by revising the gloss annotation system .
Revised:  This contradicts previous claims that GT gloss translation acts as an upper bound for SLT performance and reveals that glosses are an inefficient representation of sign language. For future SLT research, we therefore suggest an end-to-end training of the recognition and translation models, or using a different sign language annotation scheme .
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Original:  We introduce a new concept of pareto optimality, and study the generalized version of the problem from the perspective of Parameterized Complexity .
Revised:  We introduce the concept of global optimality, which extends the notion of pareto optimality to the multi-layered setting, and we focus on the problem of deciding whether a globally optimal assignment exists. We study this problem from the perspective of Parameterized Complexity .
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Original:  We introduce a new concept of pareto optimality, and study the generalized version of the problem from the perspective of Parameterized Complexity . Here, we consider several natural parameters such as the number of layers,  number of agents,  number of items, and maximal length of a preference list ;
Revised:  We introduce a new concept of pareto optimality, and study the generalized version of the problem from the perspective of Parameterized Complexity : we consider several natural parameters such as the number of layers, number of agents, number of items, and maximal length of a preference list ;
Edit intent: coherence
Original:  Here, we consider several natural parameters such as the number of layers,  number of agents,  number of items, and maximal length of a preference list ; we present a comprehensive picture of the parameterized complexity of the problem with respect to these parameters.
Revised:  Here, we consider several natural parameters such as the number of layers, number of agents, number of items, and maximal length of a preference list . We present a comprehensive picture of the parameterized complexity of the problem with respect to these parameters.
Edit intent: fluency
Original:  The study reveals that very close to the critical point, the critical slowing-down  phenomenon, introduced by the theory of critical phenomena, emerges ; additionally, a behavior of the epidemic obeying to a second order phase transition  occurs.
Revised:  The study reveals that very close to the critical point, the critical slowing-down phenomenon, introduced by the theory of critical phenomena, emerges , leading to a tremendous increase of both the percentage of active carriers and the duration of the epidemic. A behavior of the epidemic obeying to a second order phase transition occurs.
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Original:  All these results, together with an investigation of the effectiveness of authorities intervention, as in the case of applying contact restriction measures, documents scientifically their worthiness  .
Revised:  All these results, together with an investigation of the effectiveness of authorities intervention, as in the case of applying contact restriction measures, documents scientifically their worthiness , while they also demonstrate the limits for which herd immunity holds safely. Finally, the model has been compared against real epidemic data in the case of Greece, which imposed restrictive measures consistently and in time .
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Original:  In addition to county-level time-series data from the JHU CSSE COVID-19 Dashboard, our dataset contains more than 300 variables that summarize population estimates, demographics, ethnicity, housing, education, employment and in come , climate, transit scores, and healthcare system-related metrics.
Revised:  In addition to county-level time-series data from the JHU CSSE COVID-19 Dashboard, our dataset contains more than 300 variables that summarize population estimates, demographics, ethnicity, housing, education, employment and income , climate, transit scores, and healthcare system-related metrics.
Edit intent: fluency
Original:  Furthermore, we present aggregated out-of-home activity information for various points of interest for each county, including grocery stores and hospitals, summarizing data from SafeGraph . By collecting these data, as well as providing tools to read them, we hope to aid researchers investigating how the disease spreads and which communities are best able to accommodate stay-at-home mitigation efforts .
Revised:  Furthermore, we present aggregated out-of-home activity information for various points of interest for each county, including grocery stores and hospitals, summarizing data from SafeGraph and Google mobility reports. We compile information from IHME, state and county-level government, and newspapers for dates of the enactment and reversal of non-pharmaceutical interventions. By collecting these data, as well as providing tools to read them, we hope to aid researchers investigating how the disease spreads and which communities are best able to accommodate stay-at-home mitigation efforts .
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Original:  Furthermore, we present aggregated out-of-home activity information for various points of interest for each county, including grocery stores and hospitals, summarizing data from SafeGraph . By collecting these data, as well as providing tools to read them, we hope to aid researchers investigating how the disease spreads and which communities are best able to accommodate stay-at-home mitigation efforts .
Revised:  Furthermore, we present aggregated out-of-home activity information for various points of interest for each county, including grocery stores and hospitals, summarizing data from SafeGraph . By collecting these data, as well as providing tools to read them, we hope to accelerate research that investigates how the disease spreads and which communities are best able to accommodate stay-at-home mitigation efforts .
Edit intent: clarity
Original:  Furthermore, we present aggregated out-of-home activity information for various points of interest for each county, including grocery stores and hospitals, summarizing data from SafeGraph . By collecting these data, as well as providing tools to read them, we hope to aid researchers investigating how the disease spreads and which communities are best able to accommodate stay-at-home mitigation efforts .
Revised:  Furthermore, we present aggregated out-of-home activity information for various points of interest for each county, including grocery stores and hospitals, summarizing data from SafeGraph . By collecting these data, as well as providing tools to read them, we hope to aid researchers investigating how the disease spreads and why spread may be different across regions .
Edit intent: clarity
Original:  On the one hand, at a temporary level, our perspective is rather similar to that of the aforementioned model. On the other hand, all players in the model will impact the asset's public price, yielding an aggregate permanent price impact. We propose to analyze two different settings .
Revised:  Moreover, information is asymmetric among the traders, with mild assumptions. For constant market parameters, we provide specialized results. Each player selects her parameters based not only on her informational level but also on her particular preferences .
Edit intent: meaning-changed
Original:  The first one comprises the case where there is no hierarchy among players, and there is a symmetry of information. In this setting, we obtain closed-form formulas to the Nash equilibrium in the most general setting, i.e., when players' preferences are completely heterogeneous. Particularizing to the case of homogeneous parameters, we show that the average optimal inventory of the finite population converges to its mean-field counterpart, uniformly over a fixed trading horizon , as the population size grows to infinity .
Revised:  The first part of the work is where we examine the unconstrained problem, in which traders do not necessarily have to reach the end of the case of homogeneous parameters, we show that the average optimal inventory of the finite population converges to its mean-field counterpart, uniformly over a fixed trading horizon , as the population size grows to infinity .
Edit intent: clarity
Original:  In the second framework, we consider a major player, also called a leader, with the first move advantage, and a population of minor players, also known as followers, thought of as high-frequency traders, which trade on informational advantage against the leader. This leads to a model of McKean-Vlasov type for the dynamics of the asset's midprice.
Revised:  In the sequel, we proceed to analyze the constrained situation as an asymptotic limit of the previous one.
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Original:  We prove the existence and uniqueness of the Stackelberg-Nash equilibrium for a reasonable set of model parameters. We also characterize it as the solution of an abstract vector forward-backward stochastic differential equation system .
Revised:  We prove the existence and uniqueness of a Nash equilibrium in both frameworks, alongside a characterization, under suitable weak interaction assumptions. We conclude the paper by presenting an extension of the basic model to a hierarchical market, for which we establish the existence, uniqueness, and characterization of a Stackelberg-Nash equilibrium .
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Original:  We are able to explain the origin of this scaling behavior by the superposition of two concurrent processes : the large-scale spread of the virus between countries and the small-scale accumulation of case numbers within each country.
Revised:  We are able to explain the origin of this scaling behavior as a dual-scale process : the large-scale spread of the virus between countries and the small-scale accumulation of case numbers within each country.
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Original:  Our theory gives a mechanistic explanation why most COVID-19 cases occurred within a few epicenters, at least in the initial phase of the pandemic. By combining real world data, modeling, and numerical simulations we make the case that that the distribution of epidemic prevalence, and possibly that of spreading processes in general, might follow universal rules .
Revised:  Our theory gives a mechanistic explanation why most COVID-19 cases occurred within a few epicenters, at least in the initial phase of the outbreak. Assessing how well a simple dual-scale model predicts the early spread of epidemics, despite the huge contrasts between countries, could help identify critical temporal and spatial scales of response in which to mitigate future epidemic threats .
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Original:  Despite the contribution, we critiqued that there are not only mathematical errors in Mark's model but also limitations in applying it to other hierarchical structures. We present a more generalized model by introducing a novel hierarchy measure to interpolate the cooperativeness of group members in any hierarchy structure of interest.
Revised:  Despite the contribution, we critiqued that there are not only mathematical errors in Mark's model that makes it less realistic than it could in explaining real-world experiences. Consequently, we present a more generalized model by introducing a novel hierarchy measure to interpolate the cooperativeness of group members in any hierarchy structure of interest.
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Original:  We present a more generalized model by introducing a novel hierarchy measure to interpolate the cooperativeness of group members in any hierarchy structure of interest. We derive the conditions under which cooperation can emerge and verify our analytical predictions by agent-based computer simulation.
Revised:  We present a more generalized modified framework in which his model is a special case, by developing and introducing a new hierarchy measure into the model to estimate the cooperation level in a set of hierarchical structures omitted in Mark's work yet common in everyday life--those with multiple leaders. We derived the conditions under which cooperation can emerge and verify our analytical predictions by agent-based computer simulation.
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Original:  We derive the conditions under which cooperation can emerge and verify our analytical predictions by agent-based computer simulation. In general, our evolutionary model provides stronger evidence than Mark's original model with respect to how status behavior can facilitate the emergence of social cooperation .
Revised:  We derive the conditions under which cooperation can emerge and verify our analytical predictions by agent-based computer simulations. In so doing, not only does our model elaborate on its predecessor and support Mark's original model with respect to how status behavior can facilitate the emergence of social cooperation .
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Original:  In general, our evolutionary model provides stronger evidence than Mark's original model with respect to how status behavior can facilitate the emergence of social cooperation .
Revised:  In general, our evolutionary model provides stronger evidence than Mark's general prediction. For theory, our work further reveals two novel phenomena of group cooperation: Both the relative number of cooperators to defectors in groups and the assortativity among these different roles can backfire; they are not always the higher, the better for cooperation to thrive. For methodology, the hierarchy measure developed and our model using the measure may also be applied in future research on a wide range of related topics .
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Original:  In this article, we present a numerical study of the (stoquastic) adiabatic quantum algorithm applied to protein lattice folding. Using exact numerical modelling of small systems, we find that the time-to-solution metric scales exponentially with peptide length, even for small peptides. However, comparison with classical heuristics for optimisation indicates a potential limited quantum speedup .
Revised:  In this article, we present a numerical study of quantum annealing applied to a large number of small peptide folding problems, aiming to infer useful insights for near-term applications. We present two conclusions: that even naive quantum annealing, when applied to protein lattice folding, has the potential to outperform classical approaches, and that careful engineering of the Hamiltonians and schedules involved can deliver notable relative improvements for this problem .
Edit intent: clarity
Original:  In recent years , powerful compressed indexes have emerged . These are based on Entropy, the Lempel-Ziv factorization, the run-length Burrows-Wheeler Transform (BWT) , context-free grammars and, more recently, string attractors.
Revised:  In recent years , powerful compressed indexes have emerged ; these are based on Entropy, the Lempel-Ziv factorization, the run-length Burrows-Wheeler Transform (BWT) , context-free grammars and, more recently, string attractors.
Edit intent: fluency
Original:  These are based on Entropy, the Lempel-Ziv factorization, the run-length Burrows-Wheeler Transform (BWT) , context-free grammars and, more recently, string attractors.
Revised:  These are based on the Lempel-Ziv factorization, the run-length Burrows-Wheeler Transform (BWT) , context-free grammars and, more recently, string attractors.
Edit intent: meaning-changed
Original:  These are based on Entropy, the Lempel-Ziv factorization, the run-length Burrows-Wheeler Transform (BWT) , context-free grammars and, more recently, string attractors.
Revised:  These are based on Entropy, the Lempel-Ziv factorization, the run-length BWT , context-free grammars and, more recently, string attractors.
Edit intent: clarity
Original:  We show that the number r \leq n of XBWT-runs upper-bounds the size of the smallest tree attractor and lower-bounds the trie's high-order worst-case entropy \mathcal H^{wc index able to \emph{locate in pre-order nodes reached by a path labeled with a given pattern.
Revised:  We show that the number r \leq n of XBWT-runs upper-bounds the size of the smallest tree attractor and lower-bounds the trie's high-order worst-case entropy H. We finally present the first trie index able to \emph{locate in pre-order nodes reached by a path labeled with a given pattern.
Edit intent: meaning-changed
Original:  We show that the number r \leq n of XBWT-runs upper-bounds the size of the smallest tree attractor and lower-bounds the trie's high-order worst-case entropy \mathcal H^{wc index able to \emph{locate in pre-order nodes reached by a path labeled with a given pattern.
Revised:  We show that the number r \leq n of XBWT-runs upper-bounds the size of the smallest tree attractor and lower-bounds the trie's high-order worst-case entropy \mathcal H^{wc index able to \emph{locate in pre-order nodes reached by a path labeled with a given pattern.
Edit intent: fluency
Original:  Our index locates path occurrences in constant time each and takes 2n + o(n) + O(r \log n) \leq 2n + o(n) + O( \mathcal H ^{wc_k\log }  n) bits of space: the reporting time is optimal and the locate machinery fits within compressed space on top of the tree's topology.
Revised:  Our index locates path occurrences in constant time each and takes 2n + o(n) + O(r log n) \leq 2n + o(n) + O( \mathcal H ^{wc_k\log } n) bits of space: the reporting time is optimal and the locate machinery fits within compressed space on top of the tree's topology.
Edit intent: fluency
Original:  Our index locates path occurrences in constant time each and takes 2n + o(n) + O(r \log n) \leq 2n + o(n) + O( \mathcal H ^{wc_k\log }  n) bits of space: the reporting time is optimal and the locate machinery fits within compressed space on top of the tree's topology.
Revised:  Our index locates path occurrences in constant time each and takes 2n + o(n) + O(r \log n) \leq 2n + o(n) + O( _k\log } n) bits of space: the reporting time is optimal and the locate machinery fits within compressed space on top of the tree's topology.
Edit intent: meaning-changed
Original:  Our index locates path occurrences in constant time each and takes 2n + o(n) + O(r \log n) \leq 2n + o(n) + O( \mathcal H ^{wc_k\log }  n) bits of space: the reporting time is optimal and the locate machinery fits within compressed space on top of the tree's topology.
Revised:  Our index locates path occurrences in constant time each and takes 2n + o(n) + O(r \log n) \leq 2n + o(n) + O( \mathcal H ^{wc_k\log } H log n) bits of space: the reporting time is optimal and the locate machinery fits within compressed space on top of the tree's topology.
Edit intent: fluency
Original:  Our index locates path occurrences in constant time each and takes 2n + o(n) + O(r \log n) \leq 2n + o(n) + O( \mathcal H ^{wc_k\log }  n) bits of space: the reporting time is optimal and the locate machinery fits within compressed space on top of the tree's topology.
Revised:  Our index locates path occurrences in constant time each and takes 2n + o(n) + O(r \log n) \leq 2n + o(n) + O( \mathcal H ^{wc_k\log } n) bits of space: the reporting time is optimal and the locate machinery fits within compressed space on top of the succinct topology.
Edit intent: clarity
Original:  Here, we introduce PEtab,  which facilitates the specification of parameter estimation problems using Systems Biology Markup Language (SBML) models and a set of tab-separated value files describing the observation model and experimental data as well as parameters to be estimated.
Revised:  Here, we introduce PEtab, a format which facilitates the specification of parameter estimation problems using Systems Biology Markup Language (SBML) models and a set of tab-separated value files describing the observation model and experimental data as well as parameters to be estimated.
Edit intent: clarity
Original:  Availability and Implementation: Specifications of PEtab, the PEtab Python library, as well as links to examples, and all supporting software  are available at URL a snapshot is available at URL All original content is available under permissive licenses.
Revised:  Specifications of PEtab, the PEtab Python library, as well as links to examples, and all supporting software are available at URL a snapshot is available at URL All original content is available under permissive licenses.
Edit intent: coherence
Original:  Availability and Implementation: Specifications of PEtab, the PEtab Python library, as well as links to examples, and all supporting software  are available at URL a snapshot is available at URL All original content is available under permissive licenses.
Revised:  Availability and Implementation: Specifications of PEtab, the PEtab Python library, as well as links to examples, and all supporting software tools are available at URL a snapshot is available at URL All original content is available under permissive licenses.
Edit intent: clarity