wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We also prove that Martingale Fishmonger has   an MVP of around 1.63 , and conjecture this to be an information-theoretic lower bound on the problem, independent of update time.
Revised:  We also prove that Martingale Fishmonger has an MVP of H_0/2 \approx 1.63 , and conjecture this to be an information-theoretic lower bound on the problem, independent of update time.
Edit intent: meaning-changed
Original:  To this end, it revises the grammar with respect to comprehensiveness, flexibility, and specificity by offering multiple levels of expressiveness (IG Core, IG Extended, IG Logico) , and further introduces encoding of constitutive institutional statements, in addition to the encoding of regulative statements .
Revised:  To this end, it revises the grammar with respect to comprehensiveness, flexibility, and specificity by offering multiple levels of expressiveness (IG Core, IG Extended, IG Logico) . In addition to the encoding of regulative statements, it further introduces the encoding of constitutive institutional statements, in addition to the encoding of regulative statements .
Edit intent: coherence
Original:  To this end, it revises the grammar with respect to comprehensiveness, flexibility, and specificity by offering multiple levels of expressiveness (IG Core, IG Extended, IG Logico) , and further introduces encoding of constitutive institutional statements, in addition to the encoding of regulative statements . The codebook covers fundamental concepts of IG 2.0, before providing an overview of pre-coding steps relevant for document preparation.
Revised:  To this end, it revises the grammar with respect to comprehensiveness, flexibility, and specificity by offering multiple levels of expressiveness (IG Core, IG Extended, IG Logico) , and further introduces encoding of constitutive institutional statements, as well as statements that exhibit both constitutive and regulative characteristics. Introducing those aspects, the codebook initially covers fundamental concepts of IG 2.0, before providing an overview of pre-coding steps relevant for document preparation.
Edit intent: clarity
Original: The fundamental result of Li, Long, and Srinivasan on approximations of set systems has become a key tool across several communities such as learning theory, algorithms,  combinatorics and data analysis (described as `the pinnacle of a long sequence of papers') .
Revised: The fundamental result of Li, Long, and Srinivasan on approximations of set systems has become a key tool across several communities such as learning theory, algorithms, computational geometry, combinatorics and data analysis (described as `the pinnacle of a long sequence of papers') .
Edit intent: meaning-changed
Original: The fundamental result of Li, Long, and Srinivasan on approximations of set systems has become a key tool across several communities such as learning theory, algorithms,  combinatorics and data analysis (described as `the pinnacle of a long sequence of papers') .
Revised: The fundamental result of Li, Long, and Srinivasan on approximations of set systems has become a key tool across several communities such as learning theory, algorithms, combinatorics and data analysis .
Edit intent: coherence
Original: Knowledge graphs (KGs) are relevant to many NLP tasks, but building a reliable domain-specific KG is time-consuming and expensive . A number of methods for constructing KGs with minimized human interventionhave been proposed, but still require a process to align into the human-annotated knowledge base .
Revised: Knowledge graphs (KGs) are relevant to many NLP tasks, but building a reliable domain-specific KG is time-consuming and expensive as it requires human intervention .
Edit intent: clarity
Original:  To overcome this issue, we propose a novel method to automatically construct a KG from unstructured documents that does not require external alignment and explore its use to extract desired information. To summarize our approach, we first extract knowledge tuples in their surface form from unstructured documents , encode them using a pre-trained language model, and link the surface-entities via the encoding to form the graph structure.
Revised:  To overcome this issue, we propose a novel method to automatically construct a KG from unstructured documents that does not require external alignment . We first extract surface-form knowledge tuples from unstructured documents , encode them using a pre-trained language model, and link the surface-entities via the encoding to form the graph structure.
Edit intent: coherence
Original:  To summarize our approach, we first extract knowledge tuples in their surface form from unstructured documents , encode them using a pre-trained language model, and link the surface-entities via the encoding to form the graph structure.
Revised:  To summarize our approach, we first extract knowledge tuples in their surface form from unstructured documents and encode them with contextual information. Entities with similar context semantics are then linked through internal alignment to form a graph structure.
Edit intent: meaning-changed
Original: A bipartite graph G=(A,B,E) is {\cal H}-convex, for some family of graphs {\cal H}, if there exists a graph H\in {\cal H} with V(H)=A such that the set of neighbours in A of each b\in B induces a connected subgraph of H. A variety of well-known NP-complete problems, including Dominating Set ,Feedback Vertex Set ,Induced Matching andList k-Colouring , become polynomial-time solvable for {\mathcal H}-convex graphs when {\mathcal H} is the set of paths.
Revised: A bipartite graph G=(A,B,E) is {\cal H}-convex, for some family of graphs {\cal H}, if there exists a graph H\in {\cal H} with V(H)=A such that the set of neighbours in A of each b\in B induces a connected subgraph of H. Many NP-complete problems, including Dominating Set ,Feedback Vertex Set ,Induced Matching andList k-Colouring , become polynomial-time solvable for {\mathcal H}-convex graphs when {\mathcal H} is the set of paths.
Edit intent: clarity
Original: A bipartite graph G=(A,B,E) is {\cal H}-convex, for some family of graphs {\cal H}, if there exists a graph H\in {\cal H} with V(H)=A such that the set of neighbours in A of each b\in B induces a connected subgraph of H. A variety of well-known NP-complete problems, including Dominating Set ,Feedback Vertex Set ,Induced Matching andList k-Colouring , become polynomial-time solvable for {\mathcal H}-convex graphs when {\mathcal H} is the set of paths.
Revised: A bipartite graph G=(A,B,E) is {\cal H}-convex, for some family of graphs {\cal H}, if there exists a graph H\in {\cal H} with V(H)=A such that the set of neighbours in A of each b\in B induces a connected subgraph of H. A variety of well-known NP-complete problems, including ,Feedback Vertex Set ,Induced Matching andList k-Colouring , become polynomial-time solvable for {\mathcal H}-convex graphs when {\mathcal H} is the set of paths.
Edit intent: fluency
Original: A bipartite graph G=(A,B,E) is {\cal H}-convex, for some family of graphs {\cal H}, if there exists a graph H\in {\cal H} with V(H)=A such that the set of neighbours in A of each b\in B induces a connected subgraph of H. A variety of well-known NP-complete problems, including Dominating Set ,Feedback Vertex Set ,Induced Matching andList k-Colouring , become polynomial-time solvable for {\mathcal H}-convex graphs when {\mathcal H} is the set of paths.
Revised: A bipartite graph G=(A,B,E) is {\cal H}-convex, for some family of graphs {\cal H}, if there exists a graph H\in {\cal H} with V(H)=A such that the set of neighbours in A of each b\in B induces a connected subgraph of H. A variety of well-known NP-complete problems, including Dominating Set Feedback Vertex Set ,Induced Matching andList k-Colouring , become polynomial-time solvable for {\mathcal H}-convex graphs when {\mathcal H} is the set of paths.
Edit intent: fluency
Original: A bipartite graph G=(A,B,E) is {\cal H}-convex, for some family of graphs {\cal H}, if there exists a graph H\in {\cal H} with V(H)=A such that the set of neighbours in A of each b\in B induces a connected subgraph of H. A variety of well-known NP-complete problems, including Dominating Set ,Feedback Vertex Set ,Induced Matching andList k-Colouring , become polynomial-time solvable for {\mathcal H}-convex graphs when {\mathcal H} is the set of paths.
Revised: A bipartite graph G=(A,B,E) is {\cal H}-convex, for some family of graphs {\cal H}, if there exists a graph H\in {\cal H} with V(H)=A such that the set of neighbours in A of each b\in B induces a connected subgraph of H. A variety of well-known NP-complete problems, including Dominating Set , ,Induced Matching andList k-Colouring , become polynomial-time solvable for {\mathcal H}-convex graphs when {\mathcal H} is the set of paths.
Edit intent: meaning-changed
Original: A bipartite graph G=(A,B,E) is {\cal H}-convex, for some family of graphs {\cal H}, if there exists a graph H\in {\cal H} with V(H)=A such that the set of neighbours in A of each b\in B induces a connected subgraph of H. A variety of well-known NP-complete problems, including Dominating Set ,Feedback Vertex Set ,Induced Matching andList k-Colouring , become polynomial-time solvable for {\mathcal H}-convex graphs when {\mathcal H} is the set of paths.
Revised: A bipartite graph G=(A,B,E) is {\cal H}-convex, for some family of graphs {\cal H}, if there exists a graph H\in {\cal H} with V(H)=A such that the set of neighbours in A of each b\in B induces a connected subgraph of H. A variety of well-known NP-complete problems, including Dominating Set ,Feedback Vertex Set Induced Matching andList k-Colouring , become polynomial-time solvable for {\mathcal H}-convex graphs when {\mathcal H} is the set of paths.
Edit intent: fluency
Original: A bipartite graph G=(A,B,E) is {\cal H}-convex, for some family of graphs {\cal H}, if there exists a graph H\in {\cal H} with V(H)=A such that the set of neighbours in A of each b\in B induces a connected subgraph of H. A variety of well-known NP-complete problems, including Dominating Set ,Feedback Vertex Set ,Induced Matching andList k-Colouring , become polynomial-time solvable for {\mathcal H}-convex graphs when {\mathcal H} is the set of paths.
Revised: A bipartite graph G=(A,B,E) is {\cal H}-convex, for some family of graphs {\cal H}, if there exists a graph H\in {\cal H} with V(H)=A such that the set of neighbours in A of each b\in B induces a connected subgraph of H. A variety of well-known NP-complete problems, including Dominating Set ,Feedback Vertex Set , andList k-Colouring , become polynomial-time solvable for {\mathcal H}-convex graphs when {\mathcal H} is the set of paths.
Edit intent: coherence
Original: A bipartite graph G=(A,B,E) is {\cal H}-convex, for some family of graphs {\cal H}, if there exists a graph H\in {\cal H} with V(H)=A such that the set of neighbours in A of each b\in B induces a connected subgraph of H. A variety of well-known NP-complete problems, including Dominating Set ,Feedback Vertex Set ,Induced Matching andList k-Colouring , become polynomial-time solvable for {\mathcal H}-convex graphs when {\mathcal H} is the set of paths.
Revised: A bipartite graph G=(A,B,E) is {\cal H}-convex, for some family of graphs {\cal H}, if there exists a graph H\in {\cal H} with V(H)=A such that the set of neighbours in A of each b\in B induces a connected subgraph of H. A variety of well-known NP-complete problems, including Dominating Set ,Feedback Vertex Set ,Induced Matching List k-Colouring , become polynomial-time solvable for {\mathcal H}-convex graphs when {\mathcal H} is the set of paths.
Edit intent: fluency
Original: A bipartite graph G=(A,B,E) is {\cal H}-convex, for some family of graphs {\cal H}, if there exists a graph H\in {\cal H} with V(H)=A such that the set of neighbours in A of each b\in B induces a connected subgraph of H. A variety of well-known NP-complete problems, including Dominating Set ,Feedback Vertex Set ,Induced Matching andList k-Colouring , become polynomial-time solvable for {\mathcal H}-convex graphs when {\mathcal H} is the set of paths.
Revised: A bipartite graph G=(A,B,E) is {\cal H}-convex, for some family of graphs {\cal H}, if there exists a graph H\in {\cal H} with V(H)=A such that the set of neighbours in A of each b\in B induces a connected subgraph of H. A variety of well-known NP-complete problems, including Dominating Set ,Feedback Vertex Set ,Induced Matching andproblems such as Dominating Set, Feedback Vertex Set, Induced Matching and List k-Colouring , become polynomial-time solvable for {\mathcal H}-convex graphs when {\mathcal H} is the set of paths.
Edit intent: coherence
Original:  To complement result (ii), we show that the mim-width of {\mathcal H}-convex graphs is unbounded if {\mathcal H} is the set of trees with arbitrarily large maximum degree or  arbitrarily large number of vertices of degree at least 3.
Revised:  To complement result (ii), we show that the mim-width of {\mathcal H}-convex graphs is unbounded if {\mathcal H} is the set of trees with arbitrarily large maximum degree or an arbitrarily large number of vertices of degree at least 3.
Edit intent: fluency
Original:  The energy potential and equilibrium equations are first expressed in terms of deformation and polarization, and then rewritten in terms of deformation and electric potential, yielding an unconstrained system of fourth order partial differential equations ( PDE ).
Revised:  The energy potential and equilibrium equations are first expressed in terms of deformation and polarization, and then rewritten in terms of deformation and electric potential, yielding an unconstrained system of fourth order partial differential equations ( PDEs ).
Edit intent: clarity
Original:  We further develop a theory of geometrically nonlinear extensible flexoelectric rods under open and closed circuit conditions, with which we examine  cantilever bending and buckling under mechanical and electrical actuation.
Revised:  We further develop a theory of geometrically nonlinear extensible flexoelectric rods under open and closed circuit conditions, with which we examine analytically cantilever bending and buckling under mechanical and electrical actuation.
Edit intent: meaning-changed
Original: We derive analytic formulae which link \alpha, \nu and \rho parameters in Andreasen-Huge style SABR model to the ATM price and option prices at four equally spaced strikes on the sides of ATM. We give two applications. First, we give a characterisation for the SABR parameters in terms of  the swap rate forward probability density function.
Revised: We derive analytic formulae which link \alpha, \nu and \rho parameters in Andreasen-Huge style SABR model to the ATM price and option prices at four strikes close to ATM. Based on these formulae we give a characterisation for the SABR parameters in terms of the swap rate forward probability density function.
Edit intent: clarity
Original:  In this paper, we pretrain a T5 model on the BrWac corpus, an extensive collection of web pages in Portuguese, and evaluate its performance against other Portuguese pretrained models and multilingual models on the sentence similarity and sentence entailment tasks.
Revised:  In this paper, we pretrain a T5 model on the BrWac corpus, an extensive collection of web pages in Portuguese, and evaluate its performance against other Portuguese pretrained models and multilingual models on three different tasks.
Edit intent: clarity
Original:  We argue that sentence-level approaches are ill-suited to the task and introduce a generative transformer-based encoder-decoder framework  that is designed to model context at the document level: it can make extraction decisions across sentence boundaries;
Revised:  We argue that sentence-level approaches are ill-suited to the task and introduce a generative transformer-based encoder-decoder framework (GRIT) that is designed to model context at the document level: it can make extraction decisions across sentence boundaries;
Edit intent: meaning-changed
Original:  Existing edge detection and tracking methods are proposed to create suitable autonomy for mobile robots, however  many of them face overconfidence and large computations at the entrance to scenarios with an immense number of landmarks.
Revised:  Existing edge detection and tracking methods are proposed to create suitable autonomy for mobile robots, however , many of them face overconfidence and large computations at the entrance to scenarios with an immense number of landmarks.
Edit intent: fluency
Original:  Even though few datasets are available, they suffer from many shortcomings: a) they contain few languages and small amounts of labeled data for other languages b ) they are based on the simple intent and slot detection paradigm for non-compositional queries.
Revised:  Available datasets suffer from several shortcomings: a) they contain few languages and small amounts of labeled data for other languages b ) they are based on the simple intent and slot detection paradigm for non-compositional queries.
Edit intent: clarity
Original:  Even though few datasets are available, they suffer from many shortcomings: a) they contain few languages and small amounts of labeled data for other languages b ) they are based on the simple intent and slot detection paradigm for non-compositional queries.
Revised:  Even though few datasets are available, they suffer from many shortcomings: a) they contain few languages b) they contain small amounts of labeled data for other languages b ) they are based on the simple intent and slot detection paradigm for non-compositional queries.
Edit intent: coherence
Original:  Even though few datasets are available, they suffer from many shortcomings: a) they contain few languages and small amounts of labeled data for other languages b ) they are based on the simple intent and slot detection paradigm for non-compositional queries.
Revised:  Even though few datasets are available, they suffer from many shortcomings: a) they contain few languages and small amounts of labeled examples per language c ) they are based on the simple intent and slot detection paradigm for non-compositional queries.
Edit intent: clarity
Original:  Furthermore, we also demonstrate strong zero-shot performance using pre-trained models combined with automatic translation and alignment, and a proposed distant supervision method to reduce the noise in slot label projection.abstract 
Revised:  Furthermore, we also demonstrate strong zero-shot performance using pre-trained models combined with automatic translation and alignment, and a proposed distant supervision method to reduce the noise in slot label projection.abstract points on Slot F1 for the two existing multilingual datasets, over best results reported in their experiments. Furthermore, we demonstrate strong zero-shot performance using pre-trained models combined with automatic translation and alignment, and a proposed distant supervision method to reduce the noise in slot label projection.
Edit intent: meaning-changed
Original:  Furthermore,  , we perform an extensive quantitative evaluation of the impact of different pipeline stages on desirable properties of the generated maps, such as octolinearity, monotonicity, and edge uniformity.
Revised:  Furthermore, using several real-world datasets , we perform an extensive quantitative evaluation of the impact of different pipeline stages on desirable properties of the generated maps, such as octolinearity, monotonicity, and edge uniformity.
Edit intent: meaning-changed
Original: Many NLP models follow the embed-contextualize-predict paradigm, in which each sequence token is represented as a dense vector via an embedding matrix, and fed into a contextualization component that aggregates the information from the entire sequence in order to make a prediction. Could NLP models work without the embedding component? To that end, we omit the input and output embeddings from a standard machine translation model, and represent text as a sequence of bytes via UTF-8 encoding, using a constant 256-dimension one-hot representation for each byte.
Revised: Many NLP models operate over sequences of subword tokens produced by hand-crafted tokenization rules and heuristic subword induction algorithms. A simple universal alternative is to represent every computerized text as a sequence of bytes via UTF-8 encoding, using a constant 256-dimension one-hot representation for each byte.
Edit intent: clarity
Original:  To that end, we omit the input and output embeddings from a standard machine translation model, and represent text as a sequence of bytes via UTF-8 encoding, using a constant 256-dimension one-hot representation for each byte.
Revised:  To that end, we omit the input and output embeddings from a standard machine translation model, and represent text as a sequence of bytes via UTF-8 , obviating the need for an embedding layer since there are fewer token types (256) than dimensions. Surprisingly, replacing the ubiquitous embedding layer with one-hot representation for each byte.
Edit intent: meaning-changed
Original:  To that end, we omit the input and output embeddings from a standard machine translation model, and represent text as a sequence of bytes via UTF-8 encoding, using a constant 256-dimension one-hot representation for each byte. Experiments on 10 language pairs show that removing the embedding matrix consistently improves the performance of byte-to-byte models , often outperforms character-to-character models , and sometimes even produces better translations than standard subword models .
Revised:  To that end, we omit the input and output embeddings from a standard machine translation model, and represent text as a sequence of bytes via UTF-8 encoding, using a constant 256-dimension one-hot representations of each byte does not hurt performance; experiments on byte-to-byte machine translation from English to 10 language pairs show that removing the embedding matrix consistently improves the performance of byte-to-byte models , often outperforms character-to-character models , and sometimes even produces better translations than standard subword models .
Edit intent: coherence
Original:  Experiments on 10 language pairs show that removing the embedding matrix consistently improves the performance of byte-to-byte models , often outperforms character-to-character models , and sometimes even produces better translations than standard subword models .
Revised:  Experiments on 10 different languages show a consistent improvement in BLEU, rivaling character-level and even standard subword-level models. A deeper investigation reveals that the combination of embeddingless models with decoder-input dropout amounts to token dropout, which benefits byte-to-byte models , often outperforms character-to-character models , and sometimes even produces better translations than standard subword models .
Edit intent: meaning-changed
Original: We give the first ANN-data structure for time series under the continuous Fr\'echet distance , where ANN stands for approximate near neighbor . Given a parameter \epsilon \in (0,1], the data structure can be used to preprocess n curves in Euclidean R (aka time series), each of complexity m, to answer queries with a curve of complexity k by either returning a curve that lies within Fr\'echet distance 2+\epsilon, or answering that there exists no curve in the input within distance 1.
Revised: We give the first approximate-near-neighbor data structure for time series under the continuous Fr\'echet distance , where ANN stands for approximate near neighbor . Given a parameter \epsilon \in (0,1], the data structure can be used to preprocess n curves in Euclidean R (aka time series), each of complexity m, to answer queries with a curve of complexity k by either returning a curve that lies within Fr\'echet distance 2+\epsilon, or answering that there exists no curve in the input within distance 1.
Edit intent: clarity