wanyu/IteraTeR_v2 huggingface dataset:
Original:  Another limitation is that information about the context is stored  in the same element-wise representations.
Revised:  Another limitation is that information about the context is stored mostly in the same element-wise representations.
Edit intent: clarity
Original:  This makes the processing of properties related to the sequence as a whole more difficult.
Revised:  This might limit the processing of properties related to the sequence as a whole more difficult.
Edit intent: clarity
Original:  In this work, we propose and study two extensions of the Transformer baseline (1) by adding memory tokens to store non-local representations, and (2) creating memory bottleneck for the global information  .
Revised:  In this work, we propose and study two extensions of the Transformer baseline (1) by adding memory tokens to store non-local representations, (2) creating memory bottleneck for the global information .
Edit intent: coherence
Original:  We evaluate these memory augmented Transformers on machine translation task and demonstrate that memory size positively correlates with the model performance .
Revised:  We evaluate these memory augmented Transformers and demonstrate that memory size positively correlates with the model performance .
Edit intent: clarity
Original:  We evaluate these memory augmented Transformers on machine translation task and demonstrate that memory size positively correlates with the model performance .
Revised:  We evaluate these memory augmented Transformers on machine translation task and demonstrate that presence of memory positively correlates with the model performance .
Edit intent: clarity
Original:  Our algorithms apply more generally to \Delta-regular graphs satisfying a small set expansion condition.
Revised:  Our algorithms apply more generally to \Delta-regular graphs satisfying a small-set expansion condition.
Edit intent: fluency
Original:  The equilibrium concept here is a Mean Field Equilibrium (MFE) , and algorithms for learning MFE in dynamic MFGs are unknown in general due to the non-stationary evolution of the belief distribution .
Revised:  The equilibrium concept here is a Mean Field Equilibrium (MFE) . Algorithms for learning MFE in dynamic MFGs are unknown in general due to the non-stationary evolution of the belief distribution .
Edit intent: coherence
Original:  The equilibrium concept here is a Mean Field Equilibrium (MFE) , and algorithms for learning MFE in dynamic MFGs are unknown in general due to the non-stationary evolution of the belief distribution .
Revised:  The equilibrium concept here is a Mean Field Equilibrium (MFE) , and algorithms for learning MFE in dynamic MFGs are unknown in general .
Edit intent: clarity
Original:  We introduce both a model-free and a model based approach to learning T-MFE under unknown transition probabilities, using the trembling-hand idea of enabling exploration.
Revised:  We also introduce a model-free and a model based approach to learning T-MFE under unknown transition probabilities, using the trembling-hand idea of enabling exploration.
Edit intent: clarity
Original:  We introduce both a model-free and a model based approach to learning T-MFE under unknown transition probabilities, using the trembling-hand idea of enabling exploration.
Revised:  We introduce both a model-free and a model-based approach to learning T-MFE under unknown transition probabilities, using the trembling-hand idea of enabling exploration.
Edit intent: fluency
Original:  We also develop a scheme on concurrently sampling the system with a large number of agents that negates the need for a simulator , even though the model is non-stationary .
Revised:  We also develop a scheme on concurrently sampling the system with a large number of agents that negates the need for a simulator .
Edit intent: clarity
Original:  more specifically , they are t \cdot 2 ^{ O(\sqrt{\log \log t }  -colorable.
Revised:  more specifically , they are t \cdot 2 ^{ O(\sqrt{\log \log t } ) -colorable.
Edit intent: fluency
Original:  Recently, a theoretical model study on the hippocampus applying temporal difference (TD) learning , one of reinforcement learning algorithms, has been published.
Revised:  Recently, a theoretical model of the hippocampus based on temporal difference (TD) learning , one of reinforcement learning algorithms, has been published.
Edit intent: clarity
Original:  Recently, a theoretical model study on the hippocampus applying temporal difference (TD) learning , one of reinforcement learning algorithms, has been published.
Revised:  Recently, a theoretical model study on the hippocampus applying temporal difference (TD) learning has been published.
Edit intent: clarity
Original:  The theory was inspired by the successor representation (SR) learning algorithms, which decompose value function of TD learning into reward and state transition : it argued that the probability of state transition is represented by the rate of firing of CA1 place cells in the hippocampus  .
Revised:  Inspired by the successor representation (SR) learning algorithms, which decompose value function of TD learning into reward and state transition : it argued that the probability of state transition is represented by the rate of firing of CA1 place cells in the hippocampus .
Edit intent: clarity
Original:  The theory was inspired by the successor representation (SR) learning algorithms, which decompose value function of TD learning into reward and state transition : it argued that the probability of state transition is represented by the rate of firing of CA1 place cells in the hippocampus  .
Revised:  The theory was inspired by the successor representation (SR) learning algorithms, which decompose value function of TD learning into reward and state transition , they argued that the probability of state transition is represented by the rate of firing of CA1 place cells in the hippocampus .
Edit intent: coherence
Original:  The theory was inspired by the successor representation (SR) learning algorithms, which decompose value function of TD learning into reward and state transition : it argued that the probability of state transition is represented by the rate of firing of CA1 place cells in the hippocampus  .
Revised:  The theory was inspired by the successor representation (SR) learning algorithms, which decompose value function of TD learning into reward and state transition : it argued that the rate of firing of CA1 place cells in the hippocampus .
Edit intent: clarity
Original:  The theory was inspired by the successor representation (SR) learning algorithms, which decompose value function of TD learning into reward and state transition : it argued that the probability of state transition is represented by the rate of firing of CA1 place cells in the hippocampus  .
Revised:  The theory was inspired by the successor representation (SR) learning algorithms, which decompose value function of TD learning into reward and state transition : it argued that the probability of state transition is represented by the rate of firing of CA1 place cells in the hippocampus represents the probability of state transition .
Edit intent: coherence
Original:  I tried to add biological implications to the predictive map theory by modifying the SR learning algorithm .
Revised:  Modifying the SR learning algorithm added biological implications to the predictive map theory by modifying the SR learning algorithm .
Edit intent: coherence
Original:  I tried to add biological implications to the predictive map theory by modifying the SR learning algorithm .
Revised:  I tried to add biological implications to the predictive map theory .
Edit intent: clarity
Original:  Similar with the simultaneous needs of information of the current and future state in the SR learning algorithm, the CA1 pyramidal neurons receive two inputs from CA3 and entorhinal cortex.
Revised:  Similar with the simultaneous needs of information of the current and future state in the SR learning algorithm, the CA1 place cells receive two inputs from CA3 and entorhinal cortex.
Edit intent: clarity
Original:  Then I discussed papers that reported heterosynaptic plasticity phenomena in CA1 ;
Revised:  The heterosynaptic plasticity phenomena in CA1 ;
Edit intent: clarity
Original:  This study provides answers to what is the neurobiological mechanisms of the TD algorithms invented in reinforcement learning, which can be a cornerstone for further researches in neuroscience and artificial intelligence fields .
Revised:  This study attempted to interpret the TD algorithm as the neurobiological mechanism occurring in place learning, and to integrate the neuroscience and artificial intelligence fields .
Edit intent: clarity
Original:  This study provides answers to what is the neurobiological mechanisms of the TD algorithms invented in reinforcement learning, which can be a cornerstone for further researches in neuroscience and artificial intelligence fields .
Revised:  This study provides answers to what is the neurobiological mechanisms of the TD algorithms invented in reinforcement learning, which can be a cornerstone for further researches in neuroscience and artificial intelligence approaches in the field .
Edit intent: clarity
Original: Smart Contracts and transactions allow users to implement elaborate constructions on cryptocurrency blockchains like Bitcoin , Ethereum, and Libra .
Revised: Smart Contracts and transactions allow users to implement elaborate constructions on cryptocurrency blockchains like Bitcoin and Ethereum .
Edit intent: coherence
Original:  Many of these  , including operational payment channels  , use a building block called Hashed Time-Locked Contract (HTLC).
Revised:  Many of these constructions , including operational payment channels , use a building block called Hashed Time-Locked Contract (HTLC).
Edit intent: clarity
Original:  In this work, we distill from HTLC a specification ( HTLCSpec ), and present an implementation called Mutual-Assured-Destruction Hashed Time-Locked Contract (MAD-HTLC).
Revised:  In this work, we distill from HTLC a specification ( HTLC-Spec ), and present an implementation called Mutual-Assured-Destruction Hashed Time-Locked Contract (MAD-HTLC).
Edit intent: fluency
Original:  MADHTLC employs a novel approach of utilizing the existing blockchain operators, called miners, as part of the design.
Revised:  MAD-HTLC employs a novel approach of utilizing the existing blockchain operators, called miners, as part of the design.
Edit intent: fluency
Original:  We prove that MAD-HTLC satisfies HTLC-Spec with game-theoretic analysis and instantiate it on Bitcoin's operational blockchain . Notably, current miner software makes only little effort to optimize revenue, since the advantage is relatively small.
Revised:  We prove MAD-HTLC satisfies HTLC-Spec with game-theoretic analysis and instantiate it on Bitcoin's operational blockchain . Notably, current miner software makes only little effort to optimize revenue, since the advantage is relatively small.
Edit intent: fluency
Original:  Finally, we show how vulnerable HTLC is to bribery attacks.
Revised:  Finally, we extend previous results regarding HTLC vulnerability to bribery attacks.
Edit intent: clarity
Original:  We demonstrate this  can be easily implemented by patching the Bitcoin client, and use game theoretic tools to qualitatively tighten the known cost bound of such bribery attacks \2 \25K .
Revised:  We demonstrate this attack can be easily implemented by patching the Bitcoin client, and use game theoretic tools to qualitatively tighten the known cost bound of such bribery attacks \2 \25K .
Edit intent: clarity
Original:  We demonstrate this  can be easily implemented by patching the Bitcoin client, and use game theoretic tools to qualitatively tighten the known cost bound of such bribery attacks \2 \25K .
Revised:  We demonstrate this can be easily implemented by patching the Bitcoin client, and use game-theoretic tools to qualitatively tighten the known cost bound of such bribery attacks \2 \25K .
Edit intent: fluency
Original:  We demonstrate this  can be easily implemented by patching the Bitcoin client, and use game theoretic tools to qualitatively tighten the known cost bound of such bribery attacks \2 \25K .
Revised:  We demonstrate this can be easily implemented by patching the Bitcoin client, and use game theoretic tools to qualitatively tighten the known cost bound of such bribery attacks \2 for over\25K .
Edit intent: clarity
Original:  We demonstrate this  can be easily implemented by patching the Bitcoin client, and use game theoretic tools to qualitatively tighten the known cost bound of such bribery attacks \2 \25K .
Revised:  We demonstrate this can be easily implemented by patching the Bitcoin client, and use game theoretic tools to qualitatively tighten the known cost bound of such bribery attacks \2 \25K) .
Edit intent: fluency
Original:  By patching the standard Bitcoin client, we demonstrate such an optimization is easy to implement, making the miners natural enforcers of MAD-HTLC.
Revised:  By patching the standard Bitcoin client, we demonstrate such optimization is easy to implement, making the miners natural enforcers of MAD-HTLC.
Edit intent: fluency
Original:  In addition, multiple decision makers that affect each others expected congestion, call for non-cooperative game theoretic analysis of this strategic interaction.
Revised:  In addition, multiple decision makers that affect each other's expected congestion, call for non-cooperative game theoretic analysis of this strategic interaction.
Edit intent: fluency
Original:  This common daily scenario has prompted a research stream pioneered by the ?/M/1 model of Glazer and Hassin ( 1983 ) that first characterized an arrival process to a queue as a Nash equilibrium solution of a game.
Revised:  This common daily scenario has prompted a research stream pioneered by the ?/M/1 model of Glazer and Hassin ( GH1983 ) that first characterized an arrival process to a queue as a Nash equilibrium solution of a game.
Edit intent: clarity
Original: Although quantum computing is expected to outperform universal classical computing, an unconditional proof of this assertion seems to be hard because an unconditional separation between%DIFDELCMD < {\sf %%% BQP and%DIFDELCMD < {\sf %%% BPP implies%DIFDELCMD < {\sf %DIFDELCMD < %%% P \neq{\sf PSPACE ground states of any local Hamiltonians  in quantum polynomial time.
Revised: %DIFDELCMD < {\sf %%% BQP and%DIFDELCMD < {\sf %%% BPP implies%DIFDELCMD < {\sf %DIFDELCMD < %%% P \neq{\sf PSPACE ground states of any local Hamiltonians in quantum polynomial time.
Edit intent: coherence
Original: Although quantum computing is expected to outperform universal classical computing, an unconditional proof of this assertion seems to be hard because an unconditional separation between%DIFDELCMD < {\sf %%% BQP and%DIFDELCMD < {\sf %%% BPP implies%DIFDELCMD < {\sf %DIFDELCMD < %%% P \neq{\sf PSPACE ground states of any local Hamiltonians  in quantum polynomial time.
Revised: Although quantum computing is expected to outperform universal classical computing, an unconditional proof of this assertion seems to be hard because an unconditional separation between%DIFDELCMD < {\sf %%% BQP %DIFDELCMD < {\sf %%% BPP implies%DIFDELCMD < {\sf %DIFDELCMD < %%% P \neq{\sf PSPACE ground states of any local Hamiltonians in quantum polynomial time.
Edit intent: clarity
Original: Although quantum computing is expected to outperform universal classical computing, an unconditional proof of this assertion seems to be hard because an unconditional separation between%DIFDELCMD < {\sf %%% BQP and%DIFDELCMD < {\sf %%% BPP implies%DIFDELCMD < {\sf %DIFDELCMD < %%% P \neq{\sf PSPACE ground states of any local Hamiltonians  in quantum polynomial time.
Revised: Although quantum computing is expected to outperform universal classical computing, an unconditional proof of this assertion seems to be hard because an unconditional separation between%DIFDELCMD < {\sf %%% BQP and%DIFDELCMD < {\sf %%% implies%DIFDELCMD < {\sf %DIFDELCMD < %%% P \neq{\sf PSPACE ground states of any local Hamiltonians in quantum polynomial time.
Edit intent: clarity
Original: Although quantum computing is expected to outperform universal classical computing, an unconditional proof of this assertion seems to be hard because an unconditional separation between%DIFDELCMD < {\sf %%% BQP and%DIFDELCMD < {\sf %%% BPP implies%DIFDELCMD < {\sf %DIFDELCMD < %%% P \neq{\sf PSPACE ground states of any local Hamiltonians  in quantum polynomial time.
Revised: Although quantum computing is expected to outperform universal classical computing, an unconditional proof of this assertion seems to be hard because an unconditional separation between%DIFDELCMD < {\sf %%% BQP and%DIFDELCMD < {\sf %%% BPP %DIFDELCMD < {\sf %DIFDELCMD < %%% P \neq{\sf PSPACE ground states of any local Hamiltonians in quantum polynomial time.
Edit intent: fluency
Original: Although quantum computing is expected to outperform universal classical computing, an unconditional proof of this assertion seems to be hard because an unconditional separation between%DIFDELCMD < {\sf %%% BQP and%DIFDELCMD < {\sf %%% BPP implies%DIFDELCMD < {\sf %DIFDELCMD < %%% P \neq{\sf PSPACE ground states of any local Hamiltonians  in quantum polynomial time.
Revised: Although quantum computing is expected to outperform universal classical computing, an unconditional proof of this assertion seems to be hard because an unconditional separation between%DIFDELCMD < {\sf %%% BQP and%DIFDELCMD < {\sf %%% BPP implies%DIFDELCMD < {\sf %DIFDELCMD < %%% \neq{\sf PSPACE ground states of any local Hamiltonians in quantum polynomial time.
Edit intent: coherence
Original: Although quantum computing is expected to outperform universal classical computing, an unconditional proof of this assertion seems to be hard because an unconditional separation between%DIFDELCMD < {\sf %%% BQP and%DIFDELCMD < {\sf %%% BPP implies%DIFDELCMD < {\sf %DIFDELCMD < %%% P \neq{\sf PSPACE ground states of any local Hamiltonians  in quantum polynomial time.
Revised: Although quantum computing is expected to outperform universal classical computing, an unconditional proof of this assertion seems to be hard because an unconditional separation between%DIFDELCMD < {\sf %%% BQP and%DIFDELCMD < {\sf %%% BPP implies%DIFDELCMD < {\sf %DIFDELCMD < %%% P \neq{\sf PSPACE ground states of any local Hamiltonians seems to be impossible in quantum polynomial time.
Edit intent: clarity
Original:  In this paper, we give evidence for this impossibility by applying an argument used in the quantum-computational-supremacy approach.
Revised:  In this paper, we give evidence for the impossibility by applying an argument used in the quantum-computational-supremacy approach.
Edit intent: fluency
Original:  Our evidence {\sf  {\sf   is superior to the existing findings in the sense that we reduce the impossibility to an unlikely relation between classical complexity classes.
Revised:  Our evidence {\sf PP {\sf is superior to the existing findings in the sense that we reduce the impossibility to an unlikely relation between classical complexity classes.
Edit intent: fluency
Original:  Our evidence {\sf  {\sf   is superior to the existing findings in the sense that we reduce the impossibility to an unlikely relation between classical complexity classes.
Revised:  Our evidence {\sf {\sf . Our result is superior to the existing findings in the sense that we reduce the impossibility to an unlikely relation between classical complexity classes.
Edit intent: clarity
Original:  Furthermore, our argument can be used to give evidence that at least one 3-local Hamiltonian exists such that its ground state cannot be represented by a polynomial number of bits, which may be related to a gap between%DIFDELCMD < {\sf %%% QMA and%DIFDELCMD < {\sf %%% QCMA .
Revised:  %DIFDELCMD < {\sf %%% QMA and%DIFDELCMD < {\sf %%% QCMA .
Edit intent: coherence
Original:  Furthermore, our argument can be used to give evidence that at least one 3-local Hamiltonian exists such that its ground state cannot be represented by a polynomial number of bits, which may be related to a gap between%DIFDELCMD < {\sf %%% QMA and%DIFDELCMD < {\sf %%% QCMA .
Revised:  Furthermore, our argument can be used to give evidence that at least one 3-local Hamiltonian exists such that its ground state cannot be represented by a polynomial number of bits, which may be related to a gap between%DIFDELCMD < {\sf %%% and%DIFDELCMD < {\sf %%% QCMA .
Edit intent: fluency
Original:  Furthermore, our argument can be used to give evidence that at least one 3-local Hamiltonian exists such that its ground state cannot be represented by a polynomial number of bits, which may be related to a gap between%DIFDELCMD < {\sf %%% QMA and%DIFDELCMD < {\sf %%% QCMA .
Revised:  Furthermore, our argument can be used to give evidence that at least one 3-local Hamiltonian exists such that its ground state cannot be represented by a polynomial number of bits, which may be related to a gap between%DIFDELCMD < {\sf %%% QMA %DIFDELCMD < {\sf %%% QCMA .
Edit intent: coherence
Original: Very recently, a deep Neural Cellular Automata (NCA) 1 has been proposed to simulate the complex morphogenesis process with deep networks.
Revised: Very recently, the Neural Cellular Automata (NCA) 1 has been proposed to simulate the complex morphogenesis process with deep networks.
Edit intent: clarity
Original: Very recently, a deep Neural Cellular Automata (NCA) 1 has been proposed to simulate the complex morphogenesis process with deep networks.
Revised: Very recently, a deep Neural Cellular Automata (NCA) 1 has been proposed to simulate the morphogenesis process with deep networks.
Edit intent: clarity
Original:  This model learns to grow an image starting from a fixed single pixel.
Revised:  NCA learns to grow an image starting from a fixed single pixel.
Edit intent: clarity
Original:  We accomplish this by introducing dynamic convolutions inside an Auto-Encoder architecture, for the first time used to join two different sources of information, the encoding and cell's environment information.
Revised:  We accomplish this by introducing dynamic convolutions inside an Auto-Encoder architecture, for the first time used to join two different sources of information, the encoding and cells environment information.
Edit intent: fluency
Original:  We thoroughly evaluate our approach in a dataset of synthetic emojis and also in real images of CIFAR-10 . Our model introduces a general-purpose network, which can be used in a broad range of problems beyond image generation.
Revised:  We thoroughly evaluate our approach in a dataset of synthetic emojis and also in real images of CIFAR10 . Our model introduces a general-purpose network, which can be used in a broad range of problems beyond image generation.
Edit intent: fluency
Original: For many tasks -- including guideline development for medical doctors and systematic reviews for research fields -- the scientific literature needs to be checked systematically.
Revised: For many tasks - including but not limited to systematic reviews for research fields -- the scientific literature needs to be checked systematically.
Edit intent: clarity
Original: For many tasks -- including guideline development for medical doctors and systematic reviews for research fields -- the scientific literature needs to be checked systematically.
Revised: For many tasks -- including guideline development for medical doctors and systematic reviews for research fields - the scientific literature needs to be checked systematically.
Edit intent: fluency
Original:  The current practice is that scholars and practitioners  screen thousands of studies by hand to find which studies to include in their review.
Revised:  Currently, scholars and practitioners screen thousands of studies by hand to find which studies to include in their review.
Edit intent: clarity
Original:  The current practice is that scholars and practitioners  screen thousands of studies by hand to find which studies to include in their review.
Revised:  The current practice is that scholars and practitioners might screen thousands of studies by hand to find which studies to include in their review.
Edit intent: clarity