wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We prove that every girth-reducible graph of average degree (1-o(1) )q \ln q is efficiently q-colorable and that the threshold for girth reducibility of random graphs coincides with the algorithmic barrier. Thus, we link the tractability of graph coloring up to the algorithmic barrier to a single structural property. Our main theorem actually extends to coloring k-uniform hypergraphs. As such, we believe that it is an important first step towards discovering the structural properties behind the tractability of arbitrary k-CSPs for constraint densities up to the algorithmic barrier. Our main technical contribution is to prove that, for every k \ge 2, every k-uniform hypergaph of degree \Delta and girth at least 5 is efficiently (1+o(1) )(k-1) (\Delta / \ln \Delta )^{ 1/(k-1) } -list colorable via a deterministic algorithm , which is a result of independent interest .
Revised:  We prove that every k \ge 2, every k-uniform hypergaph of degree \Delta and girth at least 5 is efficiently (1+o(1) )(k-1) (\Delta / \ln \Delta )^{ 1/(k-1) } -list colorable via a deterministic algorithm , which is a result of independent interest .
Edit intent: coherence
Original:  Our main technical contribution is to prove that, for every k \ge 2, every k-uniform hypergaph of degree \Delta and girth at least 5 is efficiently (1+o(1) )(k-1) (\Delta / \ln \Delta )^{ 1/(k-1) } -list colorable via a deterministic algorithm , which is a result of independent interest .
Revised:  Our main technical contribution is to prove that, for every k \ge 2, every k-uniform hypergaph of degree \Delta and girth at least 5 is efficiently (1+o(1) )(k-1) (\Delta / \ln \Delta )^{ 1/(k-1) } -list colorable . As an application we obtain the currently best deterministic algorithm for list-coloring random hypergraphs of bounded average degree .
Edit intent: meaning-changed
Original:  In this model, we say a policy leads to zero (asymptotic) queueing delay if the job delay under the policy approaches the delay given by the max of service times of its tasks , as if tasks entered service right upon arrival.
Revised:  Under this model, we say a policy leads to zero (asymptotic) queueing delay if the job delay under the policy approaches the delay given by the max of service times of its tasks , as if tasks entered service right upon arrival.
Edit intent: fluency
Original:  In this model, we say a policy leads to zero (asymptotic) queueing delay if the job delay under the policy approaches the delay given by the max of service times of its tasks , as if tasks entered service right upon arrival.
Revised:  In this model, we propose a new notion of zero (asymptotic) queueing delay if the job delay under the policy approaches the delay given by the max of service times of its tasks , as if tasks entered service right upon arrival.
Edit intent: clarity
Original:  In this model, we say a policy leads to zero (asymptotic) queueing delay if the job delay under the policy approaches the delay given by the max of service times of its tasks , as if tasks entered service right upon arrival.
Revised:  In this model, we say a policy leads to zero (asymptotic) queueing delay that requires the job delay under the policy approaches the delay given by the max of service times of its tasks , as if tasks entered service right upon arrival.
Edit intent: meaning-changed
Original:  In this model, we say a policy leads to zero (asymptotic) queueing delay if the job delay under the policy approaches the delay given by the max of service times of its tasks , as if tasks entered service right upon arrival.
Revised:  In this model, we say a policy leads to zero (asymptotic) queueing delay if the job delay under a policy to approach the job delay given by the max of service times of its tasks , as if tasks entered service right upon arrival.
Edit intent: clarity
Original:  In this model, we say a policy leads to zero (asymptotic) queueing delay if the job delay under the policy approaches the delay given by the max of service times of its tasks , as if tasks entered service right upon arrival.
Revised:  In this model, we say a policy leads to zero (asymptotic) queueing delay if the job delay under the policy approaches the delay given by the max of its tasks' service times, i.e., the job delay assuming its tasks entered service right upon arrival.
Edit intent: clarity
Original:   We show that zero queueing delay for such parallel jobs can be achieved using  a variant of the %DIFDELCMD < \pod%%% \ policy, the batch-filling policy, with a probe overhead d = \omega\left(\frac{1}{(1-\lambda)\log k}\right)  , where k is the number of tasks in each job  .
Revised:  This notion quantifies the effect of queueing on a job level for jobs consisting of multiple tasks, and thus deviates from the conventional zero queueing delay for single-task jobs in the literature. We show that zero queueing delay for such parallel jobs can be achieved using a variant of the %DIFDELCMD < \pod%%% \ policy, the batch-filling policy, with a probe overhead d = \omega\left(\frac{1}{(1-\lambda)\log k}\right) , where k is the number of tasks in each job .
Edit intent: meaning-changed
Original:   We show that zero queueing delay for such parallel jobs can be achieved using  a variant of the %DIFDELCMD < \pod%%% \ policy, the batch-filling policy, with a probe overhead d = \omega\left(\frac{1}{(1-\lambda)\log k}\right)  , where k is the number of tasks in each job  .
Revised:  We show that zero queueing delay for parallel jobs can be achieved using a variant of the %DIFDELCMD < \pod%%% \ policy, the batch-filling policy, with a probe overhead d = \omega\left(\frac{1}{(1-\lambda)\log k}\right) , where k is the number of tasks in each job .
Edit intent: clarity
Original:   We show that zero queueing delay for such parallel jobs can be achieved using  a variant of the %DIFDELCMD < \pod%%% \ policy, the batch-filling policy, with a probe overhead d = \omega\left(\frac{1}{(1-\lambda)\log k}\right)  , where k is the number of tasks in each job  .
Revised:  We show that zero queueing delay for such parallel jobs can be achieved using the batch-filling policy ( a variant of the %DIFDELCMD < \pod%%% \ policy, the batch-filling policy, with a probe overhead d = \omega\left(\frac{1}{(1-\lambda)\log k}\right) , where k is the number of tasks in each job .
Edit intent: fluency
Original:   We show that zero queueing delay for such parallel jobs can be achieved using  a variant of the %DIFDELCMD < \pod%%% \ policy, the batch-filling policy, with a probe overhead d = \omega\left(\frac{1}{(1-\lambda)\log k}\right)  , where k is the number of tasks in each job  .
Revised:  We show that zero queueing delay for such parallel jobs can be achieved using a variant of the %DIFDELCMD < \pod%%% celebrated pod policy) with a probe overhead d = \omega\left(\frac{1}{(1-\lambda)\log k}\right) , where k is the number of tasks in each job .
Edit intent: clarity
Original:   We show that zero queueing delay for such parallel jobs can be achieved using  a variant of the %DIFDELCMD < \pod%%% \ policy, the batch-filling policy, with a probe overhead d = \omega\left(\frac{1}{(1-\lambda)\log k}\right)  , where k is the number of tasks in each job  .
Revised:  We show that zero queueing delay for such parallel jobs can be achieved using a variant of the %DIFDELCMD < \pod%%% \ policy, the batch-filling policy, with a probe overhead d = \omega\left(\frac{1}{(1-\lambda)\log k}\right) in the sub-Halfin-Whitt heavy-traffic regime , where k is the number of tasks in each job .
Edit intent: meaning-changed
Original:   We show that zero queueing delay for such parallel jobs can be achieved using  a variant of the %DIFDELCMD < \pod%%% \ policy, the batch-filling policy, with a probe overhead d = \omega\left(\frac{1}{(1-\lambda)\log k}\right)  , where k is the number of tasks in each job  .
Revised:  We show that zero queueing delay for such parallel jobs can be achieved using a variant of the %DIFDELCMD < \pod%%% \ policy, the batch-filling policy, with a probe overhead d = \omega\left(\frac{1}{(1-\lambda)\log k}\right) , where k is the number of tasks in each job and k properly scales with N (the number of servers) .
Edit intent: meaning-changed
Original:  We also establish a lower bound on the minimum d needed : we show that zero queueing delay cannot be achieved if d = e^{o\left(\frac{\log N}{\log k}\right)}.
Revised:  We also establish an impossibility result : we show that zero queueing delay cannot be achieved if d = e^{o\left(\frac{\log N}{\log k}\right)}.
Edit intent: meaning-changed
Original:  We also establish an impossibility result: we show that zero queueing delay cannot be achieved if d = e^{o\left(\frac{\log N{\log k}\right)}} \left({\left({\log k}}\right)}\right) .
Revised:  We also establish an impossibility result: we show that zero queueing delay cannot be achieved if d = {\log k}\right)}} \left({\left({\log k}}\right)}\right) .
Edit intent: meaning-changed
Original:  We also establish an impossibility result: we show that zero queueing delay cannot be achieved if d = e^{o\left(\frac{\log N{\log k}\right)}} \left({\left({\log k}}\right)}\right) .
Revised:  We also establish an impossibility result: we show that zero queueing delay cannot be achieved if d = e^{o\left(\frac{\log N{\log k}\right)}} \exp\left({\left({\log k}}\right)}\right) .
Edit intent: meaning-changed
Original:  We also establish an impossibility result: we show that zero queueing delay cannot be achieved if d = e^{o\left(\frac{\log N{\log k}\right)}} \left({\left({\log k}}\right)}\right) .
Revised:  We also establish an impossibility result: we show that zero queueing delay cannot be achieved if d = e^{o\left(\frac{\log N{\log k}\right)}} \left({o\left({\log k}}\right)}\right) .
Edit intent: meaning-changed
Original:  We also establish an impossibility result: we show that zero queueing delay cannot be achieved if d = e^{o\left(\frac{\log N{\log k}\right)}} \left({\left({\log k}}\right)}\right) .
Revised:  We also establish an impossibility result: we show that zero queueing delay cannot be achieved if d = e^{o\left(\frac{\log N{\log k}\right)}} \left({\left(\frac{\log N{\log k}}\right)}\right) .
Edit intent: fluency
Original: Neurodegeneration and cancer may share a common pathomechanism of defective cell-cycle control as a consequence of age-dependent accumulation of DNA damage. The response to DNA damage is controlled by the tumor suppressor P53 that coordinates a complex network of cellular pathways.
Revised: Cells are constantly exposed to DNA damaging insults. To protect URLanism, cells developed a complex molecular response coordinated by P53 that coordinates a complex network of cellular pathways.
Edit intent: clarity
Original:  The response to DNA damage is controlled by the tumor suppressor P53 that coordinates a complex network of cellular pathways. We investigated whether the protein Tau changes the response of cells exposed to acute DNA damage .
Revised:  The response to DNA damage is controlled by the tumor suppressor P53 , the master regulator of DNA repair, cell division and cell fate. DNA damage accumulation and abnormal cell fate decision may represent a pathomechanism shared by aging-associated disorders such as cancer and neurodegeneration. Here, we examined this hypothesis in the context of tauopathies, a neurodegenerative disorder group characterized by Tau protein deposition. For this, the response to an acute DNA damage .
Edit intent: meaning-changed
Original:  We investigated whether the protein Tau changes the response of cells exposed to acute DNA damage . We report that Tau depletion in neuroblastoma cells severely dysregulate P53 activity and leads to reduced cell death counterbalanced by increased cell senescence.
Revised:  We investigated whether the protein Tau changes the response of cells exposed to acute DNA damage was studied in neuroblastoma cells severely dysregulate P53 activity and leads to reduced cell death counterbalanced by increased cell senescence.
Edit intent: coherence
Original:  We report that Tau depletion in neuroblastoma cells severely dysregulate P53 activity and leads to reduced cell death counterbalanced by increased cell senescence.
Revised:  We report that Tau depletion in neuroblastoma cells with depleted Tau, as a model of loss-of-function. Under these conditions, altered P53 activity and leads to reduced cell death counterbalanced by increased cell senescence.
Edit intent: meaning-changed
Original:  As a consequence of DNA damage, abnormal modifications of both P53 and  MDM2 were detected in Tau-KO cells suggesting an important role of Tau in the regulation of P53 modification, stability and activity .
Revised:  This newly discovered function of Tau involves abnormal modification of P53 and MDM2 were detected in Tau-KO cells suggesting an important role of Tau in the regulation of P53 modification, stability and activity .
Edit intent: meaning-changed
Original:  As a consequence of DNA damage, abnormal modifications of both P53 and  MDM2 were detected in Tau-KO cells suggesting an important role of Tau in the regulation of P53 modification, stability and activity .
Revised:  As a consequence of DNA damage, abnormal modifications of both P53 and its E3 ubiquitin ligase MDM2 were detected in Tau-KO cells suggesting an important role of Tau in the regulation of P53 modification, stability and activity .
Edit intent: meaning-changed
Original: The COVID-19 pandemic has highlighted the need for control measures that reduce the epidemic peak ("flattening the curve").
Revised: In the absence of drugs and vaccines, policymakers use non-pharmaceutical interventions such as social distancing to decrease rates of disease-causing contact, with the aim of reducing or delaying the epidemic peak. These measures carry social and economic costs, so societies may be unable to maintain them for more than a short period of time. Intervention policy design often relies on numerical simulations of epidemic models, but comparing policies and assessing their robustness demands clear principles that apply across strategies.
Edit intent: meaning-changed
Original:  However, none of these strategies are robust to implementation errors: mistiming the start of the intervention by even a single week can be enormously costly, for realistic epidemic parameters. Sustained control measures, though less efficient than optimal and near-optimal time-limited interventions, can be used in combination with time-limited strategies to mitigate the catastrophic risks of mistiming .
Revised:  However, none of these strategies are robust to implementation error: small errors in timing the intervention produce large increases in peak prevalence. Our results reveal fundamental principles of non-pharmaceutical disease control and expose their potential fragility. For robust control, an intervention must be strong, early, and ideally sustained .
Edit intent: meaning-changed
Original:  Initially, we solve this problem for two given points s, t and a query point q. Then, the proposed solution would be extended to a general case for three arbitrary query points s, t and q. In the former, we propose an algorithm with O(n) preprocessing time.
Revised:  Initially, we solve this problem for two given points s, t and a query point q. Then, the proposed solution is extended to a general case for three arbitrary query points s, t and q. In the former, we propose an algorithm with O(n) preprocessing time.
Edit intent: clarity
Original:  The link distance  between s, t with visibility q, and its path are provided in time O(\log n) and O(k+\log n)  for the above two cases, where k is the number of links.
Revised:  The link distance of a q-visible path between s, t with visibility q, and its path are provided in time O(\log n) and O(k+\log n) for the above two cases, where k is the number of links.
Edit intent: meaning-changed
Original:  The link distance  between s, t with visibility q, and its path are provided in time O(\log n) and O(k+\log n)  for the above two cases, where k is the number of links.
Revised:  The link distance between s, t as well as the path are provided in time O(\log n) and O(k+\log n) for the above two cases, where k is the number of links.
Edit intent: clarity
Original:  The link distance  between s, t with visibility q, and its path are provided in time O(\log n) and O(k+\log n)  for the above two cases, where k is the number of links.
Revised:  The link distance between s, t with visibility q, and its path are provided in time O(\log n) and O(k+\log n) , respectively, for the above two cases, where k is the number of links.
Edit intent: meaning-changed
Original:  In this paper, we show that  in some cases it is possible to improve this compatibility-accuracy trade-off relative to a specific user by employing new error functions for the AI updates that personalize the weight updates to be compatible with the user's history of interaction with the system and present experimental results indicating that this approach provides major improvements to certain users .
Revised:  In this paper, we show that by personalizing the loss function to specific users, in some cases it is possible to improve this compatibility-accuracy trade-off relative to a specific user by employing new error functions for the AI updates that personalize the weight updates to be compatible with the user's history of interaction with the system and present experimental results indicating that this approach provides major improvements to certain users .
Edit intent: meaning-changed
Original:  In this paper, we show that  in some cases it is possible to improve this compatibility-accuracy trade-off relative to a specific user by employing new error functions for the AI updates that personalize the weight updates to be compatible with the user's history of interaction with the system and present experimental results indicating that this approach provides major improvements to certain users .
Revised:  In this paper, we show that in some cases it is possible to improve the compatibility-accuracy trade-off relative to a specific user by employing new error functions for the AI updates that personalize the weight updates to be compatible with the user's history of interaction with the system and present experimental results indicating that this approach provides major improvements to certain users .
Edit intent: fluency
Original:  In this paper, we show that  in some cases it is possible to improve this compatibility-accuracy trade-off relative to a specific user by employing new error functions for the AI updates that personalize the weight updates to be compatible with the user's history of interaction with the system and present experimental results indicating that this approach provides major improvements to certain users .
Revised:  In this paper, we show that in some cases it is possible to improve this compatibility-accuracy trade-off with respect to these users (increase the compatibility of the model while sacrificing less accuracy). We present experimental results indicating that this approach provides major improvements to certain users .
Edit intent: clarity
Original:  In this paper, we show that  in some cases it is possible to improve this compatibility-accuracy trade-off relative to a specific user by employing new error functions for the AI updates that personalize the weight updates to be compatible with the user's history of interaction with the system and present experimental results indicating that this approach provides major improvements to certain users .
Revised:  In this paper, we show that in some cases it is possible to improve this compatibility-accuracy trade-off relative to a specific user by employing new error functions for the AI updates that personalize the weight updates to be compatible with the user's history of interaction with the system and present experimental results indicating that this approach provides moderate improvements on average (around 20\%) but large improvements for certain users (up to 300\%) .
Edit intent: meaning-changed
Original:  More formally, a tandem duplication can be thought of as an operation that converts a string S = AXB into a string T = AXXB , and is denoted by S \Rightarrow T . As they appear to be involved in genetic disorders, tandem duplications are widely studied in computational biology.
Revised:  More formally, a tandem duplication can be thought of as an operation that converts a string S = AXB into a string T = AXXB . As they appear to be involved in genetic disorders, tandem duplications are widely studied in computational biology.
Edit intent: coherence
Original:  The problem of determining the complexity of computing the tandem duplication distance between two given strings was proposed by [Leupold et al., 2004] and, very recently, it was shown to be NP-hard for the case of unbounded alphabets [Lafond et al., 2019 ].
Revised:  The problem of determining the complexity of computing the tandem duplication distance between two given strings was proposed by [Leupold et al., 2004] and, very recently, it was shown to be NP-hard for the case of unbounded alphabets [Lafond et al., STACS2020 ].
Edit intent: meaning-changed
Original:  A polynomial time algorithm that solves this (existence ) problem was only known for the case of the binary alphabet . We focus on a special class of strings---here referred to as "purely alternating"---that generalize the special structure of binary strings to larger alphabets. We show that for the case of purely alternating strings from an alphabet of size \leq 5, the existence problem can be solved in linear time .
Revised:  A polynomial time algorithm that solves this (existence ) problem was only known for the case of the binary alphabet .
Edit intent: coherence
Original:  Split Cycle belongs to the small family of known voting methods  satisfying independence of clones and the Pareto principle. Unlike other methods in this family,  Split Cycle satisfies a new criterion we call immunity to spoilers, which concerns adding candidates to elections, as well as the known criteria of positive involvement and negative involvement, which concern adding voters to elections.
Revised:  Split Cycle belongs to the small family of known voting methods satisfying independence of clones . In this family, Split Cycle satisfies a new criterion we call immunity to spoilers, which concerns adding candidates to elections, as well as the known criteria of positive involvement and negative involvement, which concern adding voters to elections.
Edit intent: clarity
Original:  Unlike other methods in this family,  Split Cycle satisfies a new criterion we call immunity to spoilers, which concerns adding candidates to elections, as well as the known criteria of positive involvement and negative involvement, which concern adding voters to elections.
Revised:  Unlike other methods in this family, only Split Cycle satisfies a new criterion we call immunity to spoilers, which concerns adding candidates to elections, as well as the known criteria of positive involvement and negative involvement, which concern adding voters to elections.
Edit intent: coherence
Original:  While similar, these two concepts are equivalent only when the topology satisfies the following universal property: for each continuous mapping from preferences to outcomes there is a unique mapping from utilities to outcomes that is faithful to the preference map and is continuous.
Revised:  While similar, these two concepts are equivalent only when the topology satisfies the following universal property: for each continuous mapping from preferences to model's outputs there is a unique mapping from utilities to outcomes that is faithful to the preference map and is continuous.
Edit intent: clarity