wanyu/IteraTeR_v2 huggingface dataset:
Original:  In this paper, we propose a unified model MTMLF that uses a multi-task training procedure to capture the transferable knowledge across tasks and a pretrain finetune procedure to distill the transferable meta knowledge across DBs.
Revised:  In this paper, we propose a unified model MTMLF that uses a multi-task training procedure to capture the transferable knowledge across tasks and a pre-train fine-tune procedure to distill the transferable meta knowledge across DBs.
Edit intent: fluency
Original:  To further improve the voice quality  , we introduce a \textbf{shallow diffusion mechanism to make better use of the prior knowledge learned by the simple loss.
Revised:  To further improve the voice quality , we introduce a \textbf{shallow diffusion mechanism to make better use of the prior knowledge learned by the simple loss.
Edit intent: fluency
Original:  The evaluations conducted on the Chinese singing dataset demonstrate that DiffSinger outperforms state-of-the-art SVS work with a notable margin (0.11 MOS gains) .
Revised:  The evaluations conducted on the Chinese singing dataset demonstrate that DiffSinger outperforms state-of-the-art SVS work .
Edit intent: clarity
Original: We present the novel idea of inference delivery networks (IDN  ), networks of computing nodes that coordinate to satisfy  inference requests achieving the best trade-off between latency and accuracy.
Revised: We present the novel idea of inference delivery networks ), networks of computing nodes that coordinate to satisfy inference requests achieving the best trade-off between latency and accuracy.
Edit intent: clarity
Original:  We propose a distributed dynamic policy for ML model allocation in an IDN by which each node periodically updates its local set of inference models based on requests observed during the recent past plus limited information exchange with its neighbor nodes.
Revised:  We propose a distributed dynamic policy for ML model allocation in an IDN by which each node dynamically updates its local set of inference models based on requests observed during the recent past plus limited information exchange with its neighbor nodes.
Edit intent: clarity
Original:  We propose a distributed dynamic policy for ML model allocation in an IDN by which each node periodically updates its local set of inference models based on requests observed during the recent past plus limited information exchange with its neighbor nodes.
Revised:  We propose a distributed dynamic policy for ML model allocation in an IDN by which each node periodically updates its local set of inference models based on requests observed during the recent past plus limited information exchange with its neighboring nodes.
Edit intent: fluency
Original: We present a bounded equivalence verification technique for higher-order programs with local state that combines fully abstract symbolic environmental bisimulations similar to symbolic game models , novel up-to techniques which are effective in practice even when terms diverge , and lightweight  invariant annotations.
Revised: We present a bounded equivalence verification technique for higher-order programs with local state . This technique combines fully abstract symbolic environmental bisimulations similar to symbolic game models , novel up-to techniques which are effective in practice even when terms diverge , and lightweight invariant annotations.
Edit intent: clarity
Original: We present a bounded equivalence verification technique for higher-order programs with local state that combines fully abstract symbolic environmental bisimulations similar to symbolic game models , novel up-to techniques which are effective in practice even when terms diverge , and lightweight  invariant annotations.
Revised: We present a bounded equivalence verification technique for higher-order programs with local state that combines fully abstract symbolic environmental bisimulations similar to symbolic game semantics , novel up-to techniques which are effective in practice even when terms diverge , and lightweight invariant annotations.
Edit intent: clarity
Original: We present a bounded equivalence verification technique for higher-order programs with local state that combines fully abstract symbolic environmental bisimulations similar to symbolic game models , novel up-to techniques which are effective in practice even when terms diverge , and lightweight  invariant annotations.
Revised: We present a bounded equivalence verification technique for higher-order programs with local state that combines fully abstract symbolic environmental bisimulations similar to symbolic game models , novel up-to techniques , and lightweight invariant annotations.
Edit intent: coherence
Original: We present a bounded equivalence verification technique for higher-order programs with local state that combines fully abstract symbolic environmental bisimulations similar to symbolic game models , novel up-to techniques which are effective in practice even when terms diverge , and lightweight  invariant annotations.
Revised: We present a bounded equivalence verification technique for higher-order programs with local state that combines fully abstract symbolic environmental bisimulations similar to symbolic game models , novel up-to techniques which are effective in practice even when terms diverge , and lightweight state invariant annotations.
Edit intent: clarity
Original:  The combination yields an equivalence checking technique with no false positives or negatives where all inequivalences can be automatically detected , and many equivalences can be automatically or semi-automatically proved, including all classical Meyer and Sieber equivalences .
Revised:  This yields an equivalence checking technique with no false positives or negatives where all inequivalences can be automatically detected , and many equivalences can be automatically or semi-automatically proved, including all classical Meyer and Sieber equivalences .
Edit intent: clarity
Original:  The combination yields an equivalence checking technique with no false positives or negatives where all inequivalences can be automatically detected , and many equivalences can be automatically or semi-automatically proved, including all classical Meyer and Sieber equivalences .
Revised:  The combination yields an equivalence verification technique with no false positives or negatives where all inequivalences can be automatically detected , and many equivalences can be automatically or semi-automatically proved, including all classical Meyer and Sieber equivalences .
Edit intent: clarity
Original: Linked text representation is critical for many intelligent web applications, such as online advertisement and recommender systems . Recent breakthroughs on pretrained language models and graph neural networks facilitate the development of corresponding techniques.
Revised: Linked text representation is critical for many intelligent web applications, such as online advertisement and recommender systems . Recent breakthroughs on pretrained language models and graph neural networks push forward the development of corresponding techniques.
Edit intent: clarity
Original:  However, the existing works mainly rely on cascaded model structures: the texts are independently encoded by language models at first , and the textual embeddings are further aggregated by graph neural networks  .
Revised:  The existing works mainly rely on cascaded model structures: the texts are independently encoded by language models at first , and the textual embeddings are further aggregated by graph neural networks .
Edit intent: coherence
Original:  However, the existing works mainly rely on cascaded model structures: the texts are independently encoded by language models at first , and the textual embeddings are further aggregated by graph neural networks  .
Revised:  However, the existing works mainly rely on cascaded model structures: the texts are independently encoded by language models at first ; the textual embeddings are further aggregated by graph neural networks .
Edit intent: coherence
Original:  However, the existing works mainly rely on cascaded model structures: the texts are independently encoded by language models at first , and the textual embeddings are further aggregated by graph neural networks  .
Revised:  However, the existing works mainly rely on cascaded model structures: the texts are independently encoded by language models at first , and the textual embeddings are aggregated by graph neural networks .
Edit intent: clarity
Original:  We argue that the neighbourhood information is insufficiently utilized within the above process, which restricts the representation quality.
Edit intent: coherence
Original:  In this work, we propose GraphFormers, where graph neural networks are nested alongside each transformer layer of the language models.
Revised:  In this work, we propose GraphFormers, where graph neural networks are nested alongside the transformer blocks of language models.
Edit intent: clarity
Original:  On top of the above architecture, the linked texts will iteratively extract neighbourhood information for the enhancement of their own semantics.
Revised:  With the proposed architecture, the linked texts will iteratively extract neighbourhood information for the enhancement of their own semantics.
Edit intent: clarity
Original:  We generalize Noether's theorem known in physics to explicitly take into account this kinetic asymmetry and derive the resulting motion of the Noether charge  .
Revised:  We generalize Noether's theorem known in physics to take into account this kinetic asymmetry and derive the resulting motion of the Noether charge .
Edit intent: clarity
Original:  We generalize Noether's theorem known in physics to explicitly take into account this kinetic asymmetry and derive the resulting motion of the Noether charge  .
Revised:  We generalize Noether's theorem known in physics to explicitly take into account KSB and derive the resulting motion of the Noether charge .
Edit intent: clarity
Original:  Finally, we apply our theory to modern deep networks with normalization layers and reveal  a mechanism of  implicit adaptive optimization induced by the kinetic symmetry breaking .
Revised:  Finally, we apply NLD to neural networks with normalization layers and reveal a mechanism of implicit adaptive optimization induced by the kinetic symmetry breaking .
Edit intent: clarity
Original:  Finally, we apply our theory to modern deep networks with normalization layers and reveal  a mechanism of  implicit adaptive optimization induced by the kinetic symmetry breaking .
Revised:  Finally, we apply our theory to modern deep networks with normalization layers and reveal a mechanism of " implicit adaptive optimization induced by the kinetic symmetry breaking .
Edit intent: fluency
Original: Genetic association data from national biobanks and large-scale association studies has provided new prospects for understanding the genetic evolution of complex traits and diseases  .
Revised: Genetic association data from national biobanks and large-scale association studies have provided new prospects for understanding the genetic evolution of complex traits and diseases .
Edit intent: fluency
Original: Genetic association data from national biobanks and large-scale association studies has provided new prospects for understanding the genetic evolution of complex traits and diseases  .
Revised: Genetic association data from national biobanks and large-scale association studies has provided new prospects for understanding the genetic evolution of complex traits and diseases in humans .
Edit intent: clarity
Original:  In turn, genomes from ancient  archaeological remains are now easier than ever to obtain, and provide a direct window into changes in frequencies of trait-associated alleles in the past.
Revised:  In turn, genomes from ancient human archaeological remains are now easier than ever to obtain, and provide a direct window into changes in frequencies of trait-associated alleles in the past.
Edit intent: clarity
Original:  This has generated a new wave of studies aiming to analyze the genetic component of traits in historic and prehistoric times using ancient DNA, and to determine whether any such traits were subject to natural selection.
Revised:  This has generated a new wave of studies aiming to analyse the genetic component of traits in historic and prehistoric times using ancient DNA, and to determine whether any such traits were subject to natural selection.
Edit intent: fluency
Original:  Experimental results suggest that the proposed methods are promising in identifying critical higher-order interactions.
Revised:  Experimental results suggest that the proposed method is promising in identifying critical higher-order interactions.
Edit intent: fluency
Original:  For FIE being RGAS, our only assumption is that the system is time-discounted incrementally input-output-to-state-stable (i-IOSS) . Hence , we show that this condition is sufficient for the existence of RGAS observers.
Revised:  For FIE being RGAS, our only assumptions are that the system is time-discounted incrementally input-output-to-state-stable (i-IOSS) . Hence , we show that this condition is sufficient for the existence of RGAS observers.
Edit intent: fluency
Original:  For FIE being RGAS, our only assumption is that the system is time-discounted incrementally input-output-to-state-stable (i-IOSS) . Hence , we show that this condition is sufficient for the existence of RGAS observers.
Revised:  For FIE being RGAS, our only assumption is that the system is time-discounted incrementally input-output-to-state-stable (i-IOSS) . Hence , we show that i-IOSS is sufficient for the existence of RGAS observers.
Edit intent: clarity
Original:  Uniswap V2 introduces new arbitrage opportunities : Traders are now able to trade cryptocurrencies cyclically: A trader can exchange currency A for B, then B for C, and finally C for A again through  different trading pools.
Revised:  Uniswap V2 introduces new arbitrage opportunities : Traders are able to trade cryptocurrencies cyclically: A trader can exchange currency A for B, then B for C, and finally C for A again through different trading pools.
Edit intent: clarity
Original:  Uniswap V2 introduces new arbitrage opportunities : Traders are now able to trade cryptocurrencies cyclically: A trader can exchange currency A for B, then B for C, and finally C for A again through  different trading pools.
Revised:  Uniswap V2 introduces new arbitrage opportunities : Traders are now able to trade cryptocurrencies cyclically: A trader can exchange currency A for B, then B for C, and finally C for A again through three different trading pools.
Edit intent: clarity
Original:  In this paper, we study cyclic arbitrages in Decentralized Exchanges (DEXes ) of cryptocurrencies with transaction-level data on Uniswap V2, observing 285,127 cyclic arbitrages over eight months.
Revised:  In this paper, we study cyclic arbitrages in DEXes of cryptocurrencies with transaction-level data on Uniswap V2, observing 285,127 cyclic arbitrages over eight months.
Edit intent: clarity
Original:  In this paper, we study cyclic arbitrages in Decentralized Exchanges (DEXes ) of cryptocurrencies with transaction-level data on Uniswap V2, observing 285,127 cyclic arbitrages over eight months.
Revised:  In this paper, we study cyclic arbitrages in Decentralized Exchanges (DEXes ) of cryptocurrencies with transaction-level data on Uniswap , measuring 285,127 cyclic arbitrages over eight months.
Edit intent: clarity
Original:  We study the market size (the revenue and the cost) of cyclic arbitrages, how cyclic arbitrageschange market prices, how cyclic arbitrageurs influence other participants , and the implementations of cyclic arbitrages.
Revised:  We study the market size (the revenue and the cost) of cyclic arbitrages, the influence of cyclic arbitrages , and the implementations of cyclic arbitrages.
Edit intent: clarity
Original:  To this end, we analysed the stimulation responses in 131 stimulation sessions across 66 patients with focal epilepsy recorded through intracranial EEG (iEEG).
Revised:  To this end, we analyzed the stimulation responses in 131 stimulation sessions across 66 patients with focal epilepsy recorded through intracranial EEG (iEEG).
Edit intent: fluency
Original: This paper considers the problem of retrieving an object from a set of tightly packed objects by using a combination of robotic pushing and grasping actions.
Revised: This paper considers the problem of retrieving an object from many tightly packed objects by using a combination of robotic pushing and grasping actions.
Edit intent: clarity
Original: This paper considers the problem of retrieving an object from a set of tightly packed objects by using a combination of robotic pushing and grasping actions.
Revised: This paper considers the problem of retrieving an object from a set of tightly packed objects using a combination of robotic pushing and grasping actions.
Edit intent: fluency
Original:  Object retrieval from confined spaces that contain clutter is an important skill for robots in order to effectively operate in households and everyday environments  .
Revised:  Object retrieval in dense clutter is an important skill for robots in order to effectively operate in households and everyday environments .
Edit intent: clarity
Original:  Object retrieval from confined spaces that contain clutter is an important skill for robots in order to effectively operate in households and everyday environments  .
Revised:  Object retrieval from confined spaces that contain clutter is an important skill for robots to operate in households and everyday environments .
Edit intent: clarity
Original:  Object retrieval from confined spaces that contain clutter is an important skill for robots in order to effectively operate in households and everyday environments  .
Revised:  Object retrieval from confined spaces that contain clutter is an important skill for robots in order to effectively operate in households and everyday environments effectively .
Edit intent: clarity
Original:  The proposed solution, Visual Foresight Tree (VFT), cleverly rearranges the clutter surrounding the target object so that it can be grasped easily.
Revised:  The proposed solution, Visual Foresight Tree (VFT), intelligently rearranges the clutter surrounding the target object so that it can be grasped easily.
Edit intent: clarity
Original:  The proposed solution, Visual Foresight Tree (VFT), cleverly rearranges the clutter surrounding the target object so that it can be grasped easily.
Revised:  The proposed solution, Visual Foresight Tree (VFT), cleverly rearranges the clutter surrounding a target object so that it can be grasped easily.
Edit intent: fluency
Original:  Rearrangement with nested non-prehensile actions is challenging as it requires predicting complex object interactions in a combinatorially large configuration space of multiple objects.
Revised:  Rearrangement with nested nonprehensile actions is challenging as it requires predicting complex object interactions in a combinatorially large configuration space of multiple objects.
Edit intent: fluency
Original:  The tree search returns a sequence of consecutive push actions that result in the best arrangement of the clutter for grasping the target object.
Revised:  The tree search returns a sequence of consecutive push actions yielding the best arrangement of the clutter for grasping the target object.
Edit intent: clarity
Original:  A video introducing VFT, with robot experiments, is accessible at URL Full source code will also be made available upon publication of this manuscript.
Revised:  A video introducing VFT, with robot experiments, is accessible at URL The full source code is available at URL
Edit intent: clarity
Original: Roboticists frequently turn to Imitation learning (IL) for data efficient policy learning.
Revised:  Imitation learning (IL) for data efficient policy learning.
Edit intent: clarity
Original: Roboticists frequently turn to Imitation learning (IL) for data efficient policy learning.
Revised: Roboticists frequently turn to Imitation learning (IL) is a frequently used approach for data-efficient policy learning.
Edit intent: clarity
Original:  Many IL methods, canonicalized by the seminal work on Dataset Aggregation (DAgger), combat distributional shift issues with older Behavior Cloning (BC) methods by introducing oracle experts.
Revised:  Many IL methods, such as Dataset Aggregation (DAgger), combat distributional shift issues with older Behavior Cloning (BC) methods by introducing oracle experts.
Edit intent: clarity
Original:  Many IL methods, canonicalized by the seminal work on Dataset Aggregation (DAgger), combat distributional shift issues with older Behavior Cloning (BC) methods by introducing oracle experts.
Revised:  Many IL methods, canonicalized by the seminal work on Dataset Aggregation (DAgger), combat challenges like distributional shift by interacting with oracular experts.
Edit intent: clarity
Original:  Unfortunately, access to oracle experts is often unrealistic in practice;
Revised:  Unfortunately, assuming access to oracular experts is often unrealistic in practice;
Edit intent: clarity
Original:  data  frequently comes from manual offline methods such as lead-through or teleoperation.
Revised:  data frequently comes from offline processes such as lead-through or teleoperation.
Edit intent: clarity
Original:  We present a data-efficient imitation learning technique called Collocation for Demonstration Encoding (CoDE) that operates on only a fixed set of trajectory demonstrations by modeling learning as empirical risk minimization .
Revised:  We present a data-efficient imitation learning technique called Collocation for Demonstration Encoding (CoDE) that operates on only a fixed set of trajectory demonstrations .
Edit intent: coherence
Original:  We circumvent problematic back-propagation through time problems by introducing an auxiliary trajectory network taking inspiration from collocation techniques in optimal control.
Revised:  We circumvent challenges with methods like back-propagation-through-time by introducing an auxiliary trajectory network taking inspiration from collocation techniques in optimal control.
Edit intent: clarity
Original:  We circumvent problematic back-propagation through time problems by introducing an auxiliary trajectory network taking inspiration from collocation techniques in optimal control.
Revised:  We circumvent problematic back-propagation through time problems by introducing an auxiliary trajectory network , which takes inspiration from collocation techniques in optimal control.
Edit intent: coherence
Original:  Our method generalizes well and is much more data efficient than standard BC methods.
Revised:  Our method generalizes well and more accurately reproduces the demonstrated behavior with fewer guiding trajectories when compared to standard behavioral cloning methods.
Edit intent: clarity
Original:  We present experiments on a 7-degree-of-freedom (DoF) robotic manipulator learning behavior shaping policies for efficient tabletop operation .
Revised:  We present simulation results on a 7-degree-of-freedom (DoF) robotic manipulator learning behavior shaping policies for efficient tabletop operation .
Edit intent: clarity
Original:  The other way around , general spider algebras can be characterized as pregroup unions .
Revised:  The other way around preordered spider algebras in general can be characterized as pregroup unions .
Edit intent: clarity
Original:  The other way around , general spider algebras can be characterized as pregroup unions .
Revised:  The other way around , general spider algebras can be characterized as unions of pregroups .
Edit intent: clarity
Original:  This extends the characterization of spider algebras over sets and relations as disjoint unions of abelian groups.
Revised:  This extends the characterization of relational spider algebras as disjoint unions of abelian groups.
Edit intent: clarity