wanyu/IteraTeR_v2 huggingface dataset:
Original:  For example, given a dataset of n points for which an unknown subset of \alpha n points are drawn from a distribution of interest, and no assumptions are made about the remaining (1-\alpha)n points, is it possible to return a list of poly (1/\alpha) answers, one of which is correct?
Revised:  For example, given a dataset of n points for which an unknown subset of \alpha n points are drawn from a distribution of interest, and no assumptions are made about the remaining (1-\alpha)n points, is it possible to return a list of (1/\alpha) answers, one of which is correct?
Edit intent: fluency
Original:  The second framework, which we term the semi-verified learning model  considers the extent to which a small dataset of trusted data (drawn from the distribution in question) can be leveraged to enable the accurate extraction of information from a much larger but untrusted dataset (of which only an \alpha-fraction is drawn from the distribution).
Revised:  The second framework, which we term the semi-verified learning model , considers the extent to which a small dataset of trusted data (drawn from the distribution in question) can be leveraged to enable the accurate extraction of information from a much larger but untrusted dataset (of which only an \alpha-fraction is drawn from the distribution).
Edit intent: fluency
Original:  Starting form a random initial pattern, we use the modified BFGS algorithm to reach a local minimum pattern.
Revised:  Starting form a random initial layout, we apply the local BFGS algorithm to reach a local minimum pattern.
Edit intent: clarity
Original:  The modified BFGS algorithm fully utilizes the neighborhood information and considerably speeds up the running time of the gradient descent process, and the efficiency is more apparent for larger scale instances.
Revised:  The modified BFGS algorithm fully utilizes the neighborhood information and considerably speeds up the running time of the gradient descent process, and the efficiency is very apparent for large scale instances.
Edit intent: clarity
Original:  The new basin-hopping strategy is to shrink the container size when yielding a local minimum pattern . Experimental results indicate that the new basin-hopping strategy is very efficient, especially for a type of pattern with comparatively dense packing in the center and  sparse packing around the bounding .
Revised:  When yielding a local minimum layout, the new basin-hopping strategy is to shrink the container size when yielding a local minimum pattern . Experimental results indicate that the new basin-hopping strategy is very efficient, especially for a type of pattern with comparatively dense packing in the center and sparse packing around the bounding .
Edit intent: clarity
Original:  The new basin-hopping strategy is to shrink the container size when yielding a local minimum pattern . Experimental results indicate that the new basin-hopping strategy is very efficient, especially for a type of pattern with comparatively dense packing in the center and  sparse packing around the bounding .
Revised:  The new basin-hopping strategy is to shrink the container size when yielding a local minimum pattern . Experimental results indicate that the new basin-hopping strategy is very efficient, especially for a type of layout with comparatively dense packing in the center and sparse packing around the bounding .
Edit intent: clarity
Original:  The new basin-hopping strategy is to shrink the container size when yielding a local minimum pattern . Experimental results indicate that the new basin-hopping strategy is very efficient, especially for a type of pattern with comparatively dense packing in the center and  sparse packing around the bounding .
Revised:  The new basin-hopping strategy is to shrink the container size when yielding a local minimum pattern . Experimental results indicate that the new basin-hopping strategy is very efficient, especially for a type of pattern with comparatively dense packing in the center and comparatively sparse packing around the bounding .
Edit intent: fluency
Original:  The new basin-hopping strategy is to shrink the container size when yielding a local minimum pattern . Experimental results indicate that the new basin-hopping strategy is very efficient, especially for a type of pattern with comparatively dense packing in the center and  sparse packing around the bounding .
Revised:  The new basin-hopping strategy is to shrink the container size when yielding a local minimum pattern . Experimental results indicate that the new basin-hopping strategy is very efficient, especially for a type of pattern with comparatively dense packing in the center and sparse packing around the boundary of the container .
Edit intent: clarity
Original:  We test EQPA on the instances of n = 1,2, \cdots ,320, and obtain 66 new patterns which have smaller container sizes than the current best-known results reported in literature.
Revised:  We test EQPA on the instances of n = 1,2, ... ,320, and obtain 66 new patterns which have smaller container sizes than the current best-known results reported in literature.
Edit intent: clarity
Original:  We test EQPA on the instances of n = 1,2, \cdots ,320, and obtain 66 new patterns which have smaller container sizes than the current best-known results reported in literature.
Revised:  We test EQPA on the instances of n = 1,2, \cdots ,320, and obtain 66 new layouts which have smaller container sizes than the current best-known results reported in literature.
Edit intent: clarity
Original:  \in (0, 1 if every matchingM of size at most k contains   an induced matching of size at least \alpha(k)|M|. Assuming |A|=|B|=n, we prove that there are graphs of average degree d, such that \alpha(k)>0 is independent of d and k approaches n/d.
Revised:  \in (0, 1 if every matchingM of size at most k containsneed an induced matching of size at least \alpha(k)|M|. Assuming |A|=|B|=n, we prove that there are graphs of average degree d, such that \alpha(k)>0 is independent of d and k approaches n/d.
Edit intent: fluency
Original:  \in (0, 1 if every matchingM of size at most k contains   an induced matching of size at least \alpha(k)|M|. Assuming |A|=|B|=n, we prove that there are graphs of average degree d, such that \alpha(k)>0 is independent of d and k approaches n/d.
Revised:  \in (0, 1 if every matchingM of size at most k contains can an induced matching of size at least \alpha(k)|M|. Assuming |A|=|B|=n, we prove that there are graphs of average degree d, such that \alpha(k)>0 is independent of d and k approaches n/d.
Edit intent: fluency
Original:  We present a novel synthesis approach which automatically computes correct network configurations that comply with the operator's requirements.
Revised:  We present a novel synthesis approach that automatically computes correct network configurations that comply with the operator's requirements.
Edit intent: fluency
Original:  Using stratified Datalog, we capture the behavior of existing routers along with the distributed protocols they run  .
Revised:  We capture the behavior of existing routers along with the distributed protocols they run .
Edit intent: clarity
Original:  Using stratified Datalog, we capture the behavior of existing routers along with the distributed protocols they run  .
Revised:  Using stratified Datalog, we capture the behavior of existing routers along with the distributed protocols they run in stratified Datalog .
Edit intent: clarity
Original:  Our key insight is to reduce the problem of finding correct input configurations to the task of synthesizing inputs for a program expressed in stratified Datalog .
Revised:  Our key insight is to reduce the problem of finding correct input configurations to the task of synthesizing inputs for a stratified Datalog program .
Edit intent: clarity
Original:  To solve the synthesis task, we introduce a new iterative algorithm for stratified Datalog programs.
Revised:  To solve this synthesis task, we introduce a new iterative algorithm for stratified Datalog programs.
Edit intent: fluency
Original:  To solve the synthesis task, we introduce a new iterative algorithm for stratified Datalog programs.
Revised:  To solve the synthesis task, we introduce a new algorithm that synthesizes inputs for stratified Datalog programs.
Edit intent: clarity
Original:  We demonstrate the performance of this scheme on synthetic data, MNIST and SVHN, showing that the obtained clusters are distinct, interpretable and result in achieving higher performance on unsupervised clustering classification than previous approaches .
Revised:  We demonstrate the performance of our model on synthetic data, MNIST and SVHN, showing that the obtained clusters are distinct, interpretable and result in achieving higher performance on unsupervised clustering classification than previous approaches .
Edit intent: clarity
Original:  We demonstrate the performance of this scheme on synthetic data, MNIST and SVHN, showing that the obtained clusters are distinct, interpretable and result in achieving higher performance on unsupervised clustering classification than previous approaches .
Revised:  We demonstrate the performance of this scheme on synthetic data, MNIST and SVHN, showing that the obtained clusters are distinct, interpretable and result in achieving competitive performance on unsupervised clustering classification than previous approaches .
Edit intent: clarity
Original:  Our methodintializes the encoder and decoder of the seq2seq model with the trained weights of two language models , and then all weights are jointly fine-tuned with labeled data.
Revised:  Our methodintializes the encoder and decoder of a seq2seq model with the trained weights of two language models , and then all weights are jointly fine-tuned with labeled data.
Edit intent: fluency
Original:  Our methodintializes the encoder and decoder of the seq2seq model with the trained weights of two language models , and then all weights are jointly fine-tuned with labeled data.
Revised:  Our methodintializes the encoder and decoder of the seq2seq model with the trained weights of two language models and then fine-tuned with labeled data.
Edit intent: clarity
Original:  An additional language modeling loss can be used to regularize the model during fine-tuning.
Edit intent: coherence
Original:  We apply this method to low-resource tasks in machine translation and abstractive summarization and find that it significantly improves the subsequent supervised models.
Revised:  We apply this method to challenging benchmarks in machine translation and abstractive summarization and find that it significantly improves the subsequent supervised models.
Edit intent: clarity
Original:  Our main finding is that the pretraining accelerates training and improves generalization of seq2seq models , achieving state-of-the-art results on the WMT English\rightarrowGerman task .
Revised:  Our main result is that pretraining improves the generalization of seq2seq models , achieving state-of-the-art results on the WMT English\rightarrowGerman task .
Edit intent: clarity
Original:  Our main finding is that the pretraining accelerates training and improves generalization of seq2seq models , achieving state-of-the-art results on the WMT English\rightarrowGerman task .
Revised:  Our main finding is that the pretraining accelerates training and improves generalization of seq2seq models . We achieve state-of-the art results on the WMT English\rightarrowGerman task .
Edit intent: coherence
Original: Affiliation, or two-mode, networks, such as actor-movie, document-keyword, or user-product are prevalent in a lot of applications.
Revised: Affiliation, or two-mode, networks, such as actor-movie, document-keyword, and user-product are prevalent in a lot of applications.
Edit intent: fluency
Original:  Our peeling algorithms are based on the butterfly subgraphs (2, 2-bicliques) .
Revised:  Our peeling algorithms are based on the butterfly motif (2, 2-bicliques) .
Edit intent: clarity
Original:  An in-depth analysis on the author-paper network of the top database conferences highlights the richer structure that can be identified by working on bipartite graphs, which is otherwise lost in a co-occurrence network .
Revised:  Analysis of the author-paper network of the top database conferences highlights the richer structure that can be identified by working on bipartite graphs, which is otherwise lost in a co-occurrence network .
Edit intent: clarity
Original:  An in-depth analysis on the author-paper network of the top database conferences highlights the richer structure that can be identified by working on bipartite graphs, which is otherwise lost in a co-occurrence network .
Revised:  An in-depth analysis on the author-paper network of the top database conferences highlights the richer structure that can be identified by working on bipartite graphs, which is otherwise lost in a co-occurrence graph .
Edit intent: fluency
Original: Bipartite graphs are the natural way to model affiliation networks, such as actor-movie, document-keyword, and user-product networks.
Edit intent: coherence
Original:  Finding dense bipartite subgraphs and detecting the relations among them is an important problem for affiliation networks that arise in a range of domains, such as social network analysis, word-document clustering,  internet advertising, and bioinformatics , to name a few . However, most dense subgraph discovery algorithms are designed for classic, unipartite graphs.
Revised:  Finding dense bipartite subgraphs and detecting the relations among them is an important problem for affiliation networks that arise in a range of domains, such as social network analysis, word-document clustering, internet advertising, and bioinformatics . However, most dense subgraph discovery algorithms are designed for classic, unipartite graphs.
Edit intent: coherence
Original:  Subsequently, studies on affiliation networks are conducted on the co-occurrence graphs (e.g., co-authors and co-purchase networks) , which projects the bipartite structure to a unipartite structure by connecting two entities if they share an affiliation.
Revised:  Subsequently, studies on affiliation networks are conducted on the co-occurrence graphs (e.g., co-author and co-purchase networks) , which projects the bipartite structure to a unipartite structure by connecting two entities if they share an affiliation.
Edit intent: fluency
Original:  Subsequently, studies on affiliation networks are conducted on the co-occurrence graphs (e.g., co-authors and co-purchase networks) , which projects the bipartite structure to a unipartite structure by connecting two entities if they share an affiliation.
Revised:  Subsequently, studies on affiliation networks are conducted on the co-occurrence graphs (e.g., co-authors and co-purchase ) that project the bipartite structure to a unipartite structure by connecting two entities if they share an affiliation.
Edit intent: coherence
Original:  Despite their convenience, co-occurrence networks come at a cost of loss of information and an explosion in graph sizes, which limit the quality and  efficiency of solutions.
Revised:  Despite their convenience, co-occurrence networks come at a cost of loss of information and an explosion in graph sizes, which limit the quality and the efficiency of solutions.
Edit intent: fluency
Original:  In this paper, we study the dense subgraph discovery problem on bipartite graphs.
Revised:  We study the dense subgraph discovery problem on bipartite graphs.
Edit intent: clarity
Original:  Experiments show that we can identify much denser structures compared to the state-of-the-art techniques on co-occurrence graphs .
Revised:  We can identify denser structures compared to the state-of-the-art techniques on co-occurrence graphs .
Edit intent: clarity
Original:  Experiments show that we can identify much denser structures compared to the state-of-the-art techniques on co-occurrence graphs .
Revised:  Experiments show that we can identify much denser structures compared to the state-of-the-art algorithms on co-occurrence graphs .
Edit intent: clarity
Original: The original concept of physical-layer network coding (PNC) was first proposed in a MobiCom challenge paper in 2006 as a new paradigm to boost the throughput of wireless relay networks.
Revised: Physical-layer network coding (PNC) was first proposed in a MobiCom challenge paper in 2006 as a new paradigm to boost the throughput of wireless relay networks.
Edit intent: coherence
Original: The original concept of physical-layer network coding (PNC) was first proposed in a MobiCom challenge paper in 2006 as a new paradigm to boost the throughput of wireless relay networks.
Revised: The original concept of physical-layer network coding (PNC) is a communications paradigm that exploits overlapped transmissions to boost the throughput of wireless relay networks.
Edit intent: clarity
Original:  Since then, PNC has attracted a wide following within the research community.
Edit intent: coherence
Original:  A high point of PNC research was a theoretical proof that the use of nested lattice codes in PNC could achieve the capacity of a two-way relay network to within half bit.
Revised:  A high point of PNC research was a theoretical proof that PNC that makes use of lattice codes could approach the information-theoretic capacity of a two-way relay network to within half bit.
Edit intent: clarity
Original:  Our contributions are twofold: 1) we design and demonstrate a low-overhead channel precoding scheme that can accurately align the channels of distributed nodes driven by independent low-cost temperature-compensated oscillators ( TCXO);
Revised:  Our contributions are twofold: 1) we design and implement a low-overhead channel precoding scheme that can accurately align the channels of distributed nodes driven by independent low-cost temperature-compensated oscillators ( TCXO);
Edit intent: clarity
Original:  Our contributions are twofold: 1) we design and demonstrate a low-overhead channel precoding scheme that can accurately align the channels of distributed nodes driven by independent low-cost temperature-compensated oscillators ( TCXO);
Revised:  Our contributions are twofold: 1) we design and demonstrate a low-overhead channel precoding system that accurately aligns the channels of distributed nodes driven by independent low-cost temperature-compensated oscillators ( TCXO);
Edit intent: clarity
Original:  Our contributions are twofold: 1) we design and demonstrate a low-overhead channel precoding scheme that can accurately align the channels of distributed nodes driven by independent low-cost temperature-compensated oscillators ( TCXO);
Revised:  Our contributions are twofold: 1) we design and demonstrate a low-overhead channel precoding scheme that can accurately align the channels of distributed nodes driven by independent low-cost temperature-compensated oscillators ( 
Edit intent: clarity
Original:  2)  we adapt the low-density lattice code (LDLC) for use in practical PNC systems.
Revised:  2) we adapt the low-density lattice code for use in practical PNC systems.
Edit intent: clarity
Original: Recent work has demonstrated the effectiveness of employing explicit external memory structures in conjunction with deep neural models for algorithmic learning (Graves et al. 2014 ;
Revised: External neural memory structures have recently become a popular tool for algorithmic deep learning (Graves et al. 2014 ;
Edit intent: clarity
Original: Recent work has demonstrated the effectiveness of employing explicit external memory structures in conjunction with deep neural models for algorithmic learning (Graves et al. 2014 ;
Revised: Recent work has demonstrated the effectiveness of employing explicit external memory structures in conjunction with deep neural models for algorithmic learning (Graves et al. 2014 ,
Edit intent: fluency
Original:  These models  utilize differentiable versions of traditional discrete memory-access structures (random access, stacks, tapes) to provide the variable-length storage necessary for computational tasks.
Revised:  These models generally utilize differentiable versions of traditional discrete memory-access structures (random access, stacks, tapes) to provide the variable-length storage necessary for computational tasks.
Edit intent: clarity
Original:  These models  utilize differentiable versions of traditional discrete memory-access structures (random access, stacks, tapes) to provide the variable-length storage necessary for computational tasks.
Revised:  These models utilize differentiable versions of traditional discrete memory-access structures (random access, stacks, tapes) to provide the storage necessary for computational tasks.
Edit intent: clarity
Original:  The head is moved via Lie group actions, such as shifts or rotations, generated by a controller, and soft memory access is performed by considering the distance to keys associated with each memory .
Revised:  The head is moved via Lie group actions, such as shifts or rotations, generated by a controller, and memory access is performed by considering the distance to keys associated with each memory .
Edit intent: clarity
Original:  We argue that Lie groups provide a natural generalization of discrete memory structures, such as Turing machines, as they provide inverse and identity operators while maintain differentiability.
Revised:  We argue that Lie groups provide a natural generalization of discrete memory structures, such as Turing machines, as they provide inverse and identity operators while maintaining differentiability.
Edit intent: fluency
Original:  To experiment with this approach, we implement several simplified Lie-access neural Turing machine (LANTM) with different Lie groups.
Revised:  To experiment with this approach, we implement a simplified Lie-access neural Turing machine (LANTM) with different Lie groups.
Edit intent: clarity
Original:  This result is tight in several aspects, as the minimum multicut problem is for example both APX-hard and W[1]-hard (parameterized by the number of terminals), even on planar graphs (equivalently, when g=0).
Revised:  This result is tight in several aspects, as the minimum multicut problem is both APX-hard and W[1]-hard (parameterized by the number of terminals), even on planar graphs (equivalently, when g=0).
Edit intent: clarity
Original: Given a  network of experts, we tackle the problem of finding a team of experts that covers a set of required skills in order to complete a project.
Revised: Given a network of experts, we address the problem of finding a team of experts that covers a set of required skills in order to complete a project.
Edit intent: fluency
Original: Given a  network of experts, we tackle the problem of finding a team of experts that covers a set of required skills in order to complete a project.
Revised: Given a network of experts, we tackle the problem of discovering a team of experts that covers a set of required skills in order to complete a project.
Edit intent: fluency
Original: Given a  network of experts, we tackle the problem of finding a team of experts that covers a set of required skills in order to complete a project.
Revised: Given a network of experts, we tackle the problem of finding a team of experts that collectively holds a set of required skills in order to complete a project.
Edit intent: clarity
Original: Given a  network of experts, we tackle the problem of finding a team of experts that covers a set of required skills in order to complete a project.
Revised: Given a network of experts, we tackle the problem of finding a team of experts that covers a set of skills required to complete a project.
Edit intent: coherence