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citesum

src stringlengths 100 132k	tgt stringlengths 10 710	paper_id stringlengths 3 9	title stringlengths 9 254 ⌀	discipline dict
Abstract-With the advent of Cloud computing, large-scale virtualized compute and data centers are becoming common in the computing industry. These distributed systems leverage commodity server hardware in mass quantity, similar in theory to many of the fastest Supercomputers in existence today. However these systems ca...	In REF , they use technique of Dynamic Voltage Frequency Scaling (DVFS) to save energy consumption on CPU in cluster on scheduling.	12231480	Power-aware scheduling of virtual machines in DVFS-enabled clusters	{ "venue": "2009 IEEE International Conference on Cluster Computing and Workshops", "journal": "2009 IEEE International Conference on Cluster Computing and Workshops", "mag_field_of_study": [ "Computer Science" ] }
With the large volume of new information created every day, determining the validity of information in a knowledge graph and filling in its missing parts are crucial tasks for many researchers and practitioners. To address this challenge, a number of knowledge graph completion methods have been developed using low-dime...	ProjE REF uses a simple but effective shared variable neural network.	18367155	ProjE: Embedding Projection for Knowledge Graph Completion	{ "venue": "ArXiv", "journal": "ArXiv", "mag_field_of_study": [ "Computer Science", "Mathematics" ] }
The "Disaggregated Server" concept has been proposed for datacenters where the same type server resources are aggregated in their respective pools, for example a compute pool, memory pool, network pool, and a storage pool. Each server is constructed dynamically by allocating the right amount of resources from these poo...	The authors in REF studied the trade-off between cost and performance of building a disaggregated memory system; they constructed a simple cost model that compares the savings expected from a disaggregated memory system to the expected costs, such as latency and bandwidth costs, and then identified the level at which a...	7563532	Disaggregated and optically interconnected memory: when will it be cost effective?	{ "venue": "ArXiv", "journal": "ArXiv", "mag_field_of_study": [ "Computer Science" ] }
Influence maximization is a well-studied problem that asks for a small set of influential users from a social network, such that by targeting them as early adopters, the expected total adoption through influence cascades over the network is maximized. However, almost all prior work focuses on cascades of a single propa...	The related complementary opinion is extended by Lu et al. REF , who proposed the Comparative Independent Cascade (Com-IC) model consisting of edge-level information propagation and a Node-Level Automation (NLA) that ultimately makes adoption decisions based on a set of model parameters called Global Adoption Probabili...	3471972	From Competition to Complementarity: Comparative Influence Diffusion and Maximization	{ "venue": "ArXiv", "journal": "ArXiv", "mag_field_of_study": [ "Computer Science", "Physics" ] }
A graph has growth rate k if the number of nodes in any subgraph with diameter r is bounded by O(r k ). The communication graphs of wireless networks and peer-to-peer networks often have small growth rate. In this paper we study the tradeoff between two quality measures for routing in growth restricted graphs. The two ...	For instance, for growth-bounded wireless networks, Gao and Zhang REF show routing algorithms that simultaneously achieve a stretch factor of c and a load balancing ratio of O((n/c) 1−1/k ) where k is the growth rate.	207794	Tradeoffs between stretch factor and load balancing ratio in routing on growth restricted graphs	{ "venue": "PODC '04", "journal": null, "mag_field_of_study": [ "Computer Science", "Mathematics" ] }
This paper introduces new optimality-preserving operators on Q-functions. We first describe an operator for tabular representations, the consistent Bellman operator, which incorporates a notion of local policy consistency. We show that this local consistency leads to an increase in the action gap at each state; increas...	More recently, it was shown that the advantage learning algorithm is a gap-increasing operator REF .	1907310	Increasing the Action Gap: New Operators for Reinforcement Learning	{ "venue": "Bellemare, Marc G., Ostrovski, G., Guez, A., Thomas, Philip S., and Munos, Remi. Increasing the Action Gap: New Operators for Reinforcement Learning. Proceedings of the AAAI Conference on Artificial Intelligence, 2016", "journal": null, "mag_field_of_study": [ "Computer Science" ] }
Does phonological variation get transcribed into social media text? This paper investigates examples of the phonological variable of consonant cluster reduction in Twitter. Not only does this variable appear frequently, but it displays the same sensitivity to linguistic context as in spoken language. This suggests that...	REF analyzes phonological factors in social media writing.	2655326	Phonological Factors in Social Media Writing	{ "venue": "LASM", "journal": null, "mag_field_of_study": [ "Computer Science" ] }
This paper presents a statistical decision procedure for lexical ambiguity resolution. The algorithm exploits both local syntactic patterns and more distant collocational evidence, generating an efficient, effective, and highly perspicuous recipe for resolving a given ambiguity. By identifying and utilizing only the si...	REF presents a statistic procedure for lexical ambiguity resolution, based on decision lists, that achieved good results when applied to accent restoration in Spanish and French.	1580335	Decision Lists For Lexical Ambiguity Resolution: Application To Accent Restoration In Spanish And French	{ "venue": "Annual Meeting Of The Association For Computational Linguistics", "journal": null, "mag_field_of_study": [ "Computer Science" ] }
Online content exhibits rich temporal dynamics, and diverse realtime user generated content further intensifies this process. However, temporal patterns by which online content grows and fades over time, and by which different pieces of content compete for attention remain largely unexplored. We study temporal patterns...	Yang and Leskovec REF describe six classes of temporal shapes of attention.	1412278	Patterns of temporal variation in online media	{ "venue": "WSDM '11", "journal": null, "mag_field_of_study": [ "Computer Science" ] }
Land use classification is a fundamental task of information extraction from remote sensing imagery. Semantic segmentation based on deep convolutional neural networks (DCNNs) has shown outstanding performance in this task. However, these methods are still affected by the loss of spatial features. In this study, we prop...	Yao et al. REF proposed the dense-coordconv network (DCCN) to reduce the loss of spatial features and strengthen object boundaries.	195357122	Land Use Classification of the Deep Convolutional Neural Network Method Reducing the Loss of Spatial Features	{ "venue": "Sensors (Basel, Switzerland)", "journal": "Sensors (Basel, Switzerland)", "mag_field_of_study": [ "Engineering", "Medicine", "Computer Science" ] }
We describe a method for incorporating syntactic information in statistical machine translation systems. The first step of the method is to parse the source language string that is being translated. The second step is to apply a series of transformations to the parse tree, effectively reordering the surface string on t...	For example, REF parse the sentences of the source language and restructure the word order, such that it matches the target language word order more closely.	11142668	Clause Restructuring For Statistical Machine Translation	{ "venue": "Annual Meeting Of The Association For Computational Linguistics", "journal": null, "mag_field_of_study": [ "Computer Science" ] }
Abstract. Given an undirected graph G = (V, E), the density of a subgraph on vertex set S is defined as d(S) = , where E(S) is the set of edges in the subgraph induced by nodes in S. Finding subgraphs of maximum density is a very well studied problem. One can also generalize this notion to directed graphs. For a direct...	In REF , they also consider the density versions of the problems in directed graphs.	1774289	On finding dense subgraphs	{ "venue": "In ICALP ’09", "journal": null, "mag_field_of_study": [ "Mathematics", "Computer Science" ] }
Well distributed point sets play an important role in a variety of computer graphics contexts, such as anti-aliasing, global illumination, halftoning, non-photorealistic rendering, point-based modeling and rendering, and geometry processing. In this paper, we introduce a novel technique for rapidly generating large poi...	The technique of REF generates non-periodic point sets that can be used for tiling, allowing viewers to interactively resize the stipple image.	11007853	Recursive Wang tiles for real-time blue noise	{ "venue": "SIGGRAPH '06", "journal": null, "mag_field_of_study": [ "Computer Science" ] }
Abstract-Content-centric networking (CCN) is a promising framework to rebuild the Internet's forwarding substrate around the concept of content. CCN advocates ubiquitous in-network caching to enhance content delivery, and thus each router has storage space to cache frequently requested content. In this work, we focus o...	Wang et al. REF address the distribution of the cache capacity across routers under a constrained total storage budget for the network.	12943609	Design and Evaluation of the Optimal Cache Allocation for Content-Centric Networking	{ "venue": "IEEE Transactions on Computers", "journal": "IEEE Transactions on Computers", "mag_field_of_study": [ "Computer Science" ] }
Sequence to sequence learning models still require several days to reach state of the art performance on large benchmark datasets using a single machine. This paper shows that reduced precision and large batch training can speedup training by nearly 5x on a single 8-GPU machine with careful tuning and implementation. 1...	Other work shows that training on 128 GPUs can significantly boost the experimental results and shorten the training time REF .	44131019	Scaling Neural Machine Translation	{ "venue": "ArXiv", "journal": "ArXiv", "mag_field_of_study": [ "Computer Science" ] }
Emojis have evolved as complementary sources for expressing emotion in social-media platforms where posts are mostly composed of texts and images. In order to increase the expressiveness of the social media posts, users associate relevant emojis with their posts. Incorporating domain knowledge has improved machine unde...	Emojinet has also improved the accuracies of emoji prediction in case of images REF .	52096100	Which Emoji Talks Best for My Picture?	{ "venue": "2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI)", "journal": "2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI)", "mag_field_of_study": [ "Computer Science" ] }
It has been several years since Massive Open Online Courses (MOOC) have entered the higher education environment and many forms have emerged from this new way of acquiring knowledge. Teachers have been incorporating MOOCs with more or less success in a traditional classroom setting to support various learning preferenc...	In REF , Bralić and Divjak proposed a blended learning model that integrates Massive Open Online Course (MOOC) into a traditional classroom.	20647488	Integrating MOOCs in traditionally taught courses: achieving learning outcomes with blended learning	{ "venue": "International Journal of Educational Technology in Higher Education", "journal": "International Journal of Educational Technology in Higher Education", "mag_field_of_study": [ "Sociology" ] }
This paper advocates expansion of the role of Bayesian statistical inference when formally quantifying uncertainty in computer models defined by systems of ordinary or partial differential equations. We adopt the perspective that implicitly defined infinite dimensional functions representing model states are objects to...	A similar approach is followed in REF , yielding a nonparametric posterior rather than a Gaussian approximation.	14077995	Bayesian Solution Uncertainty Quantification for Differential Equations	{ "venue": null, "journal": "arXiv: Methodology", "mag_field_of_study": [ "Mathematics" ] }
Standard artificial neural networks suffer from the well-known issue of catastrophic forgetting, making continual or lifelong learning problematic. Recently, numerous methods have been proposed for continual learning, but due to differences in evaluation protocols it is difficult to directly compare their performance. ...	More recently, this idea has been made more efficient by integrating the generative model into the training procedure REF .	52880246	Generative replay with feedback connections as a general strategy for continual learning	{ "venue": "ArXiv", "journal": "ArXiv", "mag_field_of_study": [ "Computer Science", "Mathematics" ] }
The production environment for analytical data management applications is rapidly changing. Many enterprises are shifting away from deploying their analytical databases on high-end proprietary machines, and moving towards cheaper, lower-end, commodity hardware, typically arranged in a shared-nothing MPP architecture, o...	HadoopDB REF proposes a hybrid system combining a Hadoop deployment and a parallel database system to simultaneously leverage the resilience and scalability of MapReduce together with the performance and efficiency of parallel databases.	2717398	HadoopDB: An Architectural Hybrid of MapReduce and DBMS Technologies for Analytical Workloads	{ "venue": "PVLDB", "journal": "PVLDB", "mag_field_of_study": [ "Computer Science" ] }
In this paper, we bring techniques from operations research to bear on the problem of choosing optimal actions in partially observable stochastic domains. We begin by introducing the theory of Markov decision processes (mdps) and partially observable mdps (pomdps). We then outline a novel algorithm for solving pomdps o...	A partially observable Markov decision process (POMDP) REF defines the optimal policy for a sequential decision making problem while taking into account uncertain state transitions and partially observable states.	5613003	Planning and Acting in Partially Observable Stochastic Domains	{ "venue": "Artif. Intell.", "journal": null, "mag_field_of_study": [ "Mathematics", "Computer Science" ] }
Private information retrieval (PIR) enables a user to retrieve a data item from a database, replicated among one or more servers, while hiding the identity of the retrieved item. This problem was suggested by Chor, Goldreich, Kushilevitz, and Sudan in 1995, and since then efficient protocols with sub-linear communicati...	Theoretical work proves that the collective work required by the servers to answer a client's request scales at least linearly with the size of the database REF .	12258286	Reducing the servers' computation in private information retrieval: Pir with preprocessing	{ "venue": "In CRYPTO 2000", "journal": null, "mag_field_of_study": [ "Computer Science" ] }
Abstract We prove that with high probability a skip graph contains a 4-regular expander as a subgraph and estimate the quality of the expansion via simulations. As a consequence, skip graphs contain a large connected component even after an adversarial deletion of nodes. We show how the expansion property can be used t...	It was shown in REF that skip graphs contain expanders as subgraphs w.h.p., which can be used as a randomized expander construction.	5986866	The expansion and mixing time of skip graphs with applications	{ "venue": "Distributed Computing", "journal": "Distributed Computing", "mag_field_of_study": [ "Computer Science", "Engineering" ] }
Abstract. Honest but curious cloud servers can make inferences about the stored encrypted documents and the profile of a user once it knows the keywords queried by her and the keywords contained in the documents. We propose two progressively refined privacy-preserving conjunctive symmetric searchable encryption (PCSSE)...	Later, Moataz et al. REF proposed the Conjunctive Symmetric Searchable Encryption scheme that allows conjunctive keyword search on encrypted documents with different privacy assurances.	6510158	Privacy-Preserving Multiple Keyword Search on Outsourced Data in the Clouds	{ "venue": "DBSec", "journal": null, "mag_field_of_study": [ "Computer Science" ] }
Abstract-For robots to be a part of our daily life, they need to be able to navigate among crowds not only safely but also in a socially compliant fashion. This is a challenging problem because humans tend to navigate by implicitly cooperating with one another to avoid collisions, while heading toward their respective ...	In REF future trajectories of all interacting agents are modeled by learning social interactions from real data using a Gaussian Process model.	1491148	Modeling cooperative navigation in dense human crowds	{ "venue": "2017 IEEE International Conference on Robotics and Automation (ICRA)", "journal": "2017 IEEE International Conference on Robotics and Automation (ICRA)", "mag_field_of_study": [ "Engineering", "Computer Science" ] }
Many significant challenges exist for the mental health field, but one in particular is a lack of data available to guide research. Language provides a natural lens for studying mental health -much existing work and therapy have strong linguistic components, so the creation of a large, varied, language-centric dataset ...	Coppersmith et al. REF examined a broad range of mental health conditions in Twitter data by identifying self-reported statements of diagnosis, and they took the experimental results as evidence that examining mental health through the lens of language was fertile ground for advances in mental health.	96824	From ADHD to SAD: Analyzing the Language of Mental Health on Twitter through Self-Reported Diagnoses	{ "venue": "CLPsych@HLT-NAACL", "journal": null, "mag_field_of_study": [ "Computer Science" ] }
Abstract-We present a novel domain adaptation approach for solving cross-domain pattern recognition problems, i.e., the data or features to be processed and recognized are collected from different domains of interest. Inspired by canonical correlation analysis (CCA), we utilize the derived correlation subspace as a joi...	Inspired by the Canonical Correlation Analysis (CCA), the authors of REF utilize a correlation subspace as a joint representation for associating the data across different domains.	13828880	Heterogeneous Domain Adaptation and Classification by Exploiting the Correlation Subspace	{ "venue": "IEEE Transactions on Image Processing", "journal": "IEEE Transactions on Image Processing", "mag_field_of_study": [ "Mathematics", "Medicine", "Computer Science" ] }
We present techniques for speeding up the test-time evaluation of large convolutional networks, designed for object recognition tasks. These models deliver impressive accuracy, but each image evaluation requires millions of floating point operations, making their deployment on smartphones and Internet-scale clusters pr...	Inspired by this technique, a low rank approximation for the convolution layers achieves twice the speed while staying within 1% of the original model in terms of accuracy REF .	7340116	Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation	{ "venue": "ArXiv", "journal": "ArXiv", "mag_field_of_study": [ "Computer Science" ] }
We study the problem of verifiable delegation of computation over outsourced data, whereby a powerful worker maintains a large data structure for a weak client in a verifiable way. Compared to the well-studied problem of verifiable computation, this setting imposes additional difficulties since the verifier also needs ...	Canetti et al. extended it by allowing data updates and monolithic verification of hierarchical set operations REF .	8750990	Verifiable Set Operations over Outsourced Databases	{ "venue": "Public Key Cryptography", "journal": null, "mag_field_of_study": [ "Computer Science" ] }
Abstract. We introduce a shape detection framework called Contour Context Selection for detecting objects in cluttered images using only one exemplar. Shape based detection is invariant to changes of object appearance, and can reason with geometrical abstraction of the object. Our approach uses salient contours as inte...	In REF , Zhu et al. formulate the shape matching of contour in clutter as a set to set matching problem, and present an approximate solution to the hard combinatorial problem by using a voting scheme.	9878393	Contour Context Selection for Object Detection : A Set-to-Set Contour Matching Approach	{ "venue": "ICPR (3)", "journal": null, "mag_field_of_study": [ "Computer Science" ] }
Researchers studying daily life mobility patterns have recently shown that humans are typically highly predictable in their movements. However, no existing work has examined the boundaries of this predictability, where human behaviour transitions temporarily from routine patterns to highly unpredictable states. To addr...	A recent study REF proposes methods to identify and predict departures from routine in individual mobility using information-theoretic metrics, such as the instantaneous entropy, and developing a Bayesian framework that explicitly models the tendency of individuals to break from routine.	624605	Breaking the habit: Measuring and predicting departures from routine in individual human mobility	{ "venue": "Pervasive Mob. Comput.", "journal": "Pervasive Mob. Comput.", "mag_field_of_study": [ "Computer Science" ] }
Twitter, a microblogging service less than three years old, commands more than 41 million users as of July 2009 and is growing fast. Twitter users tweet about any topic within the 140-character limit and follow others to receive their tweets. The goal of this paper is to study the topological characteristics of Twitter...	In REF , the authors analysed the entire Twitter graph in order to assess its topological characteristics.	207178765	What is Twitter, a social network or a news media?	{ "venue": "WWW '10", "journal": null, "mag_field_of_study": [ "Computer Science", "Political Science" ] }
We apply a general deep learning framework to address the non-factoid question answering task. Our approach does not rely on any linguistic tools and can be applied to different languages or domains. Various architectures are presented and compared. We create and release a QA corpus and setup a new QA task in the insur...	These representation learning based methods do not rely on any linguistic tools and can be applied to different languages or domains REF .	3477924	Applying deep learning to answer selection: A study and an open task	{ "venue": "2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU)", "journal": "2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU)", "mag_field_of_study": [ "Computer Science" ] }
Abstract -As web is expanding day by day and people generally rely on web for communication so e-mails are the fastest way to send information from one place to another. Now a day's all the transactions all the communication whether general or of business taking place through e-mails. E-mail is an effective tool for co...	Megha Rathi and Vikas Pareek(2013) performed an analysis on spam email detection through Data Mining by performing analysis on classifiers by selecting and without selecting the features REF .	35670502	Spam Mail Detection through Data Mining – A Comparative Performance Analysis	{ "venue": null, "journal": "International Journal of Modern Education and Computer Science", "mag_field_of_study": [ "Computer Science" ] }
In this paper, we consider a two-user mobile-edge computing (MEC) network, where each wireless device (WD) has a sequence of tasks to execute. In particular, we consider task dependency between the two WDs, where the input of a task at one WD requires the final task output at the other WD. Under the considered task-dep...	When the computing tasks at different MUs have inputoutput dependency, REF studies the optimal binary offloading strategy and resource allocation that minimizes the computation delay and energy consumption.	53082484	Optimal Offloading and Resource Allocation in Mobile-Edge Computing with Inter-User Task Dependency	{ "venue": "2018 IEEE Global Communications Conference (GLOBECOM)", "journal": "2018 IEEE Global Communications Conference (GLOBECOM)", "mag_field_of_study": [ "Computer Science" ] }
We introduce a model for information spreading among a population of N agents diffusing on a square L × L lattice, starting from an informed agent (Source). Information passing from informed to unaware agents occurs whenever the relative distance is ≤ 1. Numerical simulations show that the time required for the informa...	Agliari et al. studied information spreading in a population of diffusing agents REF .	17928479	Efficiency of information spreading in a population of diffusing agents	{ "venue": "Physical review. E, Statistical, nonlinear, and soft matter physics", "journal": "Physical review. E, Statistical, nonlinear, and soft matter physics", "mag_field_of_study": [ "Medicine", "Physics" ] }
The combined advances of open mobile platforms and online social networking applications (SNAs) are driving pervasive computing to the real-world users, as the mobile SNAs are expected to revolutionize wireless application industry. While sharing location through mobile SNAs is useful for information access and user in...	Research in REF studies the privacy of mobile social network application design.	2250582	Analyzing Privacy Designs of Mobile Social Networking Applications	{ "venue": "2008 IEEE/IFIP International Conference on Embedded and Ubiquitous Computing", "journal": "2008 IEEE/IFIP International Conference on Embedded and Ubiquitous Computing", "mag_field_of_study": [ "Computer Science" ] }
ABSTRACT In this paper, we study radio frequency energy harvesting (EH) in a wireless sensor network in the presence of multiple eavesdroppers (EAVs). Specifically, the sensor source and multiple sensor relays harvest energy from multiple power transfer stations (PTSs), and then, the source uses this harvested energy t...	The results indicated that the proposed scheme outperformed both the best-relayand-random-jammer scheme and the random-relay-and-bestjammer scheme in terms of secrecy performance REF .	21709243	Secrecy Outage Performance Analysis for Energy Harvesting Sensor Networks With a Jammer Using Relay Selection Strategy	{ "venue": "IEEE Access", "journal": "IEEE Access", "mag_field_of_study": [ "Computer Science" ] }
QoS-aware dynamic binding of composite services provides the capability of binding each service invocation in a composition to a service chosen among a set of functionally equivalent ones to achieve a QoS goal, for example minimizing the response time while limiting the price under a maximum value. This paper proposes ...	REF have proposed an approach based on genetic algorithms.	181777	A Framework for QoS-Aware Binding and Re-Binding of Composite Web Services	{ "venue": "J. Syst. Softw.", "journal": "J. Syst. Softw.", "mag_field_of_study": [ "Computer Science" ] }
Abstract-Fog computing is seen as a promising approach to perform distributed, low-latency computation for supporting Internet of Things applications. However, due to the unpredictable arrival of available neighboring fog nodes, the dynamic formation of a fog network can be challenging. In essence, a given fog node mus...	To provide fog computing services, the formation of fog networks is studied in REF .	15363899	An online secretary framework for fog network formation with minimal latency	{ "venue": "2017 IEEE International Conference on Communications (ICC)", "journal": "2017 IEEE International Conference on Communications (ICC)", "mag_field_of_study": [ "Mathematics", "Computer Science" ] }
Abstract-With the introduction of network function virtualization technology, migrating entire enterprise data centers into the cloud has become a possibility. However, for a cloud service provider (CSP) to offer such services, several research problems still need to be addressed. In previous work, we have introduced a...	Rankothge et al. REF have presented a resource allocation algorithm for VNFs based on Generic algorithms (GAs).	28867567	Optimizing Resource Allocation for Virtualized Network Functions in a Cloud Center Using Genetic Algorithms	{ "venue": "IEEE Transactions on Network and Service Management", "journal": "IEEE Transactions on Network and Service Management", "mag_field_of_study": [ "Computer Science" ] }
Abstract-We introduce a weakly supervised approach for learning human actions modeled as interactions between humans and objects. Our approach is human-centric: We first localize a human in the image and then determine the object relevant for the action and its spatial relation with the human. The model is learned auto...	A humancentric approach is proposed by REF that works by first localizing a human and then finding an object and its relationship to it.	1819788	Weakly Supervised Learning of Interactions between Humans and Objects	{ "venue": "IEEE Transactions on Pattern Analysis and Machine Intelligence", "journal": "IEEE Transactions on Pattern Analysis and Machine Intelligence", "mag_field_of_study": [ "Computer Science", "Medicine" ] }
Users organize themselves into communities on web platforms. These communities can interact with one another, often leading to conflicts and toxic interactions. However, little is known about the mechanisms of interactions between communities and how they impact users. Here we study intercommunity interactions across 3...	Kumar et al. REF introduced a method that employs graph embeddings, where the graph captures user interactions on Reddit 1 , in conjunction with user, community, and text features to predict potential conflict and subsequent community mobilization.	3854959	Community Interaction and Conflict on the Web	{ "venue": "ArXiv", "journal": "ArXiv", "mag_field_of_study": [ "Computer Science" ] }
This paper continues the rather recent line of research on the dynamics of non-monotonic formalisms. In particular, we consider semantic changes in Dung's abstract argumentation formalism. One of the most studied problems in this context is the so-called enforcing problem which is concerned with manipulating argumentat...	Quite recently, in REF ) the so-called extension removal problem was studied.	54053953	Extension Removal in Abstract Argumentation -- An Axiomatic Approach	{ "venue": "AAAI", "journal": null, "mag_field_of_study": [ "Computer Science" ] }
We introduce a deep memory network for aspect level sentiment classification. Unlike feature-based SVM and sequential neural models such as LSTM, this approach explicitly captures the importance of each context word when inferring the sentiment polarity of an aspect. Such importance degree and text representation are c...	REF introduced an end-to-end memory network for aspect level sentiment classification, which employs an attention mechanism over an external memory to capture the importance of each context word.	359042	Aspect Level Sentiment Classification with Deep Memory Network	{ "venue": "ArXiv", "journal": "ArXiv", "mag_field_of_study": [ "Computer Science" ] }
Multi-dimensional Bayesian network classifiers (MBCs) are probabilistic graphical models recently proposed to deal with multi-dimensional classification problems, where each instance in the data set has to be assigned to more than one class variable. In this paper, we propose a Markov blanket-based approach for learnin...	Borchani et al. REF further propose a Markov blanket-based approach to train the MBCs from multioutput data.	205713058	Markov blanket-based approach for learning multi-dimensional Bayesian network classifiers : An application to predict the European Quality of Life-5 Dimensions ( EQ-5 D ) from the 39-item Parkinson ’ s Disease Questionnaire ( PDQ-39 )	{ "venue": "Journal of biomedical informatics", "journal": "Journal of biomedical informatics", "mag_field_of_study": [ "Computer Science", "Medicine" ] }
Background: Cloud computing is a unique paradigm that is aggregating resources available from cloud service providers for use by customers on demand and pay per use basis. There is a Cloud federation that integrates the four primary Cloud models and the Cloud aggregator that integrates multiple computing services. A sy...	REF is cloud design and deployment models: a systematic mapping study.	198134639	Cloud designs and deployment models: a systematic mapping study	{ "venue": "BMC Research Notes", "journal": "BMC Research Notes", "mag_field_of_study": [ "Medicine" ] }
To accurately match records it is often necessary to utilize the semantics of the data. Functional dependencies (FDs) have proven useful in identifying tuples in a clean relation, based on the semantics of the data. For all the reasons that FDs and their inference are needed, it is also important to develop dependencie...	Reasoning mechanism for deducing MDs from a set of given MDs is studied in REF .	2690556	Reasoning about Record Matching Rules	{ "venue": "PVLDB", "journal": "PVLDB", "mag_field_of_study": [ "Computer Science" ] }
The existing watermarking schemes were designed to embed the watermark information into the original images, which are vulnerable to unauthorized access. In this paper, we have proposed a novel and feasible watermarking algorithm in the encrypted domain. First, we encrypted both original medical image and watermark ima...	Dong et al. proposed a novel and feasible watermarking algorithm in the encrypted domain by using DCT REF .	27562386	A Robust Watermarking Algorithm for Encrypted Medical Images Based on DCT Encrypted Domain	{ "venue": "Proceedings of the 2015 International Conference on Electronic Science and Automation Control", "journal": "Proceedings of the 2015 International Conference on Electronic Science and Automation Control", "mag_field_of_study": [ "Computer Science" ] }
We describe an algorithm, IsoRank, for global alignment of two protein-protein interaction (PPI) networks. IsoRank aims to maximize the overall match between the two networks; in contrast, much of previous work has focused on the local alignment problem-identifying many possible alignments, each corresponding to a loca...	In REF , Singh et al. present IsoRank, an algorithm for pairwise global alignment of PPI networks aiming at finding a correspondence between nodes and edges of the input networks that maximizes the overall match between the two networks.	6304597	Pairwise global alignment of protein interaction networks by matching neighborhood topology	{ "venue": "RECOMB", "journal": null, "mag_field_of_study": [ "Mathematics", "Computer Science" ] }
Research has shown that computers are notoriously bad at supporting the management of parallel activities and interruptions, and that mobility increases the severity and scope of these problems. This paper presents activity-based computing (ABC) which supplements the prevalent data-and application-oriented computing pa...	Another group, based at the University of Aarhus in Denmark REF , has trialled an extension to the Windows XP operating system for Activity Based Computing (ABC).	9648288	Support for activity-based computing in a personal computing operating system	{ "venue": "CHI", "journal": null, "mag_field_of_study": [ "Computer Science" ] }
Abstract-In this paper, fault tolerance in a multi-radio network is discussed. Fault tolerance is achieved using the BeeHive routing algorithm. The paper discusses faults added to the system as random fluctuations in hardware radio operation. The multi-radio nodes are designed using WiMAX and WiFi Radios that work in c...	Kiran K et al (2014) REF discusses fault tolerance in a multi-radio network.	22260439	Fault tolerant BeeHive routing in mobile ad-hoc multi-radio network	{ "venue": "2014 IEEE REGION 10 SYMPOSIUM", "journal": "2014 IEEE REGION 10 SYMPOSIUM", "mag_field_of_study": [ "Engineering" ] }
Current approaches for semantic parsing take a supervised approach requiring a considerable amount of training data which is expensive and difficult to obtain. This supervision bottleneck is one of the major difficulties in scaling up semantic parsing. We argue that a semantic parser can be trained effectively without ...	It is also possible to self-train a semantic parser without any labeled data REF .	9111381	Confidence Driven Unsupervised Semantic Parsing	{ "venue": "Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies", "journal": null, "mag_field_of_study": [ "Computer Science" ] }
Abstract. We present a novel method to generate accurate and realistic clothing deformation from real data capture. Previous methods for realistic cloth modeling mainly rely on intensive computation of physicsbased simulation (with numerous heuristic parameters), while models reconstructed from visual observations typi...	REF takes a hybrid approach combining a statistical model for pose-based global deformation with a conditional generative adversarial network for adding details on normal maps to produce finer wrinkles.	51967305	DeepWrinkles: Accurate and Realistic Clothing Modeling	{ "venue": "ArXiv", "journal": "ArXiv", "mag_field_of_study": [ "Computer Science" ] }
Patient genomes are interpretable only in the context of other genomes; however, genome sharing enables discrimination. Thousands of monogenic diseases have yielded definitive genomic diagnoses and potential gene therapy targets. Here we show how to provide such diagnoses while preserving participant privacy through th...	Another protocol was proposed to provide genomic diagnoses while preserving participant privacy REF .	206658219	Deriving genomic diagnoses without revealing patient genomes	{ "venue": "Science", "journal": "Science", "mag_field_of_study": [ "Medicine", "Biology" ] }
Abstract-Recently, a number of existing blockchain systems have witnessed major bugs and vulnerabilities within smart contracts. Although the literature features a number of proposals for securing smart contracts, these proposals mostly focus on proving the correctness or absence of a certain type of vulnerability with...	Another interesting example is the Sereum REF architecture, a hardened EVM which is able to protect deployed contracts against re-entrancy attacks in a backward compatible way by leveraging taint tracking to monitor runtime behaviors of smart contracts.	55701989	Sereum: Protecting Existing Smart Contracts Against Re-Entrancy Attacks	{ "venue": "ArXiv", "journal": "ArXiv", "mag_field_of_study": [ "Computer Science" ] }
Abstract. Motivated by the problem of avoiding duplication in storage systems, Bellare, Keelveedhi, and Ristenpart have recently put forward the notion of Message-Locked Encryption (MLE) schemes which subsumes convergent encryption and its variants. Such schemes do not rely on permanent secret keys, but rather encrypt ...	Then Abadi et al. REF designed a randomized scheme to avoid the ciphertext derived from the message.	1315646	Message-locked encryption for lock-dependent messages	{ "venue": "In Advances in Cryptology–CRYPTO 2013", "journal": null, "mag_field_of_study": [ "Computer Science" ] }
Virtual humans need to be persuasive in order to promote behaviour change in human users. While several studies have focused on understanding the numerous aspects that inluence the degree of persuasion, most of them are limited to dyadic interactions. In this paper, we present an evaluation study focused on understandi...	An early evaluation study REF was conducted to observe the influence of gender, status (authoritative and peer), and focus employed by the agent i. e., (i) user-directed: persuading by addressing the user directly, and (ii) vicarious: persuading the user indirectly by engaging another agent in the discussion.	53244506	Is Two Better than One?: Effects of Multiple Agents on User Persuasion	{ "venue": "IVA '18", "journal": null, "mag_field_of_study": [ "Computer Science" ] }
Abstract-Radio spectrum resource is of fundamental importance for wireless communication. Recent reports show that most available spectrum has been allocated. While some of the spectrum bands (e.g., unlicensed band, GSM band) have seen increasingly crowded usage, most of the other spectrum resources are underutilized. ...	In REF , the tradeoff between the spectrum access opportunity and spectrum sensing overhead in cognitive radio systems is formulated as a finite-horizon optimal stopping problem, which is solved using backward induction.	14939569	HC-MAC: A Hardware-Constrained Cognitive MAC for Efficient Spectrum Management	{ "venue": "IEEE Journal on Selected Areas in Communications", "journal": "IEEE Journal on Selected Areas in Communications", "mag_field_of_study": [ "Computer Science" ] }
Figure 1: Two agents in Gibson Environment for real-world perception. The agent is active, embodied, and subject to constraints of physics and space (a,b). It receives a constant stream of visual observations as if it had an on-board camera (c). It can also receive additional modalities, e.g. depth, semantic labels, or...	Gibson REF ) is a learning environment in which an agent is embodied and made subject to constraints of space and physics (using Bullet physics) and spawned in a virtualized real space (coming from real-world datasets such as Matterport or Stanford 2D-3D).	49358881	Gibson Env: Real-World Perception for Embodied Agents	{ "venue": "CVPR 2018", "journal": null, "mag_field_of_study": [ "Computer Science" ] }
The ubiquity of Online Social Networks (OSNs) is creating new sources for healthcare information, particularly in the context of pharmaceutical drugs. We aimed to examine the impact of a given OSN's characteristics on the content of pharmaceutical drug discussions from that OSN. We compared the effect of four distingui...	REF examined the characteristics of ten different online social networking sites to find impacts of these characteristics on the discussions of pharmaceutical drugs among the users and DailyStrength was one of these websites.	7022593	Pharmaceutical drugs chatter on Online Social Networks	{ "venue": "Journal of biomedical informatics", "journal": "Journal of biomedical informatics", "mag_field_of_study": [ "Computer Science", "Medicine" ] }
Abstract Exploiting the full computational power of current hierarchical multiprocessor machines requires a very careful distribution of threads and data among the underlying non-uniform architecture so as to avoid remote memory access penalties. Directive-based programming languages such as OpenMP, can greatly help to...	Broquedis et al. REF combined NUMA-aware memory manager with their runtime system to enable dynamic load distribution, utilizing the information from the application structure and hardware topology.	10528126	ForestGOMP: An Efficient OpenMP Environment for NUMA Architectures	{ "venue": "International Journal of Parallel Programming", "journal": "International Journal of Parallel Programming", "mag_field_of_study": [ "Computer Science" ] }
Many natural language processing tasks solely rely on sparse dependencies between a few tokens in a sentence. Soft attention mechanisms show promising performance in modeling local/global dependencies by soft probabilities between every two tokens, but they are not effective and efficient when applied to long sentences...	REF proposed reinforced selfattention network (ReSAN), which integrate both soft and hard attention into one context fusion with reinforced learning.	27764139	Reinforced Self-Attention Network: a Hybrid of Hard and Soft Attention for Sequence Modeling	{ "venue": "ArXiv", "journal": "ArXiv", "mag_field_of_study": [ "Computer Science" ] }
Abstract-In this work, we propose a Programmable Vector Memory Controller (PVMC), which boosts noncontiguous vector data accesses by integrating descriptors of memory patterns, a specialized local memory, a memory manager in hardware, and multiple DRAM controllers. We implemented and validated the proposed system on an...	Hussain et al. proposed a vector architecture called programmable vector memory controller (PVMC) REF and its implementation on an Altera Stratix IV 230 FPGA device.	15805857	PVMC: Programmable Vector Memory Controller	{ "venue": "2014 IEEE 25th International Conference on Application-Specific Systems, Architectures and Processors", "journal": "2014 IEEE 25th International Conference on Application-Specific Systems, Architectures and Processors", "mag_field_of_study": [ "Computer Science" ] }
Abstract-Monitoring network traffic and classifying applications are essential functions for network administrators. In this paper, we consider the use of Traffic Dispersion Graphs (TDGs) to classify network traffic. Given a set of flows, a TDG is a graph with an edge between any two IP addresses that communicate; thus...	REF developed a graph-based framework for classifying P2P traffic.	6109492	Graph-Based P2P Traffic Classification at the Internet Backbone	{ "venue": "IEEE INFOCOM Workshops 2009", "journal": "IEEE INFOCOM Workshops 2009", "mag_field_of_study": [ "Computer Science" ] }
Background: Since Swanson proposed the Undiscovered Public Knowledge (UPK) model, there have been many approaches to uncover UPK by mining the biomedical literature. These earlier works, however, required substantial manual intervention to reduce the number of possible connections and are mainly applied to disease-effe...	Ijaz, Song, and Lee REF proposed the MKE (Multi-Level Knowledge Emergence) model.	9720218	MKEM: a Multi-level Knowledge Emergence Model for mining undiscovered public knowledge	{ "venue": "BMC Bioinformatics", "journal": "BMC Bioinformatics", "mag_field_of_study": [ "Medicine", "Computer Science" ] }
Abstract-Human face detection and tracking is an important research area having wide application in human machine interface, content-based image retrieval, video coding, gesture recognition, crowd surveillance and face recognition. Human face detection is extremely important and simultaneously a difficult problem in co...	Shivesh Bajpai, et. al., REF discussed the gradient vector flow and silhouettes algorithms.	56205479	An Experimental Comparison of Face Detection Algorithms	{ "venue": null, "journal": "International Journal of Computer Theory and Engineering", "mag_field_of_study": [ "Computer Science" ] }
Robust and accurate visual tracking is one of the most challenging computer vision problems. Due to the inherent lack of training data, a robust approach for constructing a target appearance model is crucial. Recently, discriminatively learned correlation filters (DCF) have been successfully applied to address this pro...	Spatially Regularized Discriminative Correlation Filter (SRDCF) REF utilizes spatial regularization by introducing a spatial regularization component, which can penalize the correlation filter coefficients during learning and lead to not only alleviating the unwanted boundary effects but also allowing the CF to be lear...	206770621	Learning Spatially Regularized Correlation Filters for Visual Tracking	{ "venue": "2015 IEEE International Conference on Computer Vision (ICCV)", "journal": "2015 IEEE International Conference on Computer Vision (ICCV)", "mag_field_of_study": [ "Computer Science" ] }
We introduce the value iteration network (VIN): a fully differentiable neural network with a 'planning module' embedded within. VINs can learn to plan, and are suitable for predicting outcomes that involve planning-based reasoning, such as policies for reinforcement learning. Key to our approach is a novel differentiab...	iteration algorithm was introduced that is capable of predicting outcomes that involve planning-based reasoning REF .	11374605	Value Iteration Networks	{ "venue": "Advances in Neural Information Processing Systems 29 pages 2154--2162, 2016", "journal": null, "mag_field_of_study": [ "Computer Science", "Mathematics" ] }
The United States spends more than $250 million each year on the American Community Survey (ACS), a labor-intensive door-todoor study that measures statistics relating to race, gender, education, occupation, unemployment, and other demographic factors. Although a comprehensive source of data, the lag between demographi...	Gebru et al. REF extracted car types, years, and make from 50 million Google Street View images to correlate with socio-economic factors such as income and geographic demographic types across different cities in the United States.	37969305	Using deep learning and Google Street View to estimate the demographic makeup of neighborhoods across the United States	{ "venue": "Proceedings of the National Academy of Sciences of the United States of America", "journal": "Proceedings of the National Academy of Sciences of the United States of America", "mag_field_of_study": [ "Computer Science", "Medicine", "Geography" ] }
Abstract-We propose a system that is capable of detailed analysis of eye region images in terms of the position of the iris, degree of eyelid opening, and the shape, complexity, and texture of the eyelids. The system uses a generative eye region model that parameterizes the fine structure and motion of an eye. The stru...	In REF , a system was proposed that is capable of a detailed analysis of the eye region images in terms of the position of the iris, degree of the eyelid opening, and the shape, the complexity, and the texture of the eyelids.	9732534	Meticulously detailed eye region model and its application to analysis of facial images	{ "venue": "IEEE Transactions on Pattern Analysis and Machine Intelligence", "journal": "IEEE Transactions on Pattern Analysis and Machine Intelligence", "mag_field_of_study": [ "Computer Science", "Medicine" ] }
Abstract. Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific skills are needed for participating. At the moment, however, the information retrieval support ...	FolkRank REF leverages the structure of folksonomy and finds the communities to restructure search results.	2204253	Information retrieval in folksonomies: Search and ranking	{ "venue": "The Semantic Web: Research and Applications, volume 4011 of LNAI", "journal": null, "mag_field_of_study": [ "Computer Science" ] }
Abstract-The packet pair technique estimates the capacity of a path (bottleneck bandwidth) from the dispersion (spacing) experienced by two back-to-back packets [1][2][3]. We demonstrate that the dispersion of packet pairs in loaded paths follows a multimodal distribution, and discuss the queueing effects that cause th...	The work in REF mentions a technique for estimating the available bandwidth based on the asymptotic dispersion rate (ADR) method.	352687	What do packet dispersion techniques measure?	{ "venue": "Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213)", "journal": "Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Co...

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CiteSum

Description

CiteSum: Citation Text-guided Scientific Extreme Summarization and Low-resource Domain Adaptation.

CiteSum contains TLDR summaries for scientific papers from their citation texts without human annotation, making it around 30 times larger than the previous human-curated dataset SciTLDR.

Homepage

https://github.com/morningmoni/CiteSum

Paper

https://arxiv.org/abs/2205.06207

Authors

Yuning Mao, Ming Zhong, Jiawei Han

University of Illinois Urbana-Champaign

{yuningm2, mingz5, hanj}@illinois.edu

Dataset size

Train: 83304
Validation: 4721
Test: 4921

Data details

src (string): source text. long description of paper
tgt (string): target text. tldr of paper
paper_id (string): unique id for the paper
title (string): title of the paper
discipline (dict):
- venue (string): Where the paper was published (conference)
- journal (string): Journal in which the paper was published
- mag_field_of_study (list[str]): scientific fields that the paper falls under.

Example:

{
    'src': 'We describe a convolutional neural network that learns feature representations for short textual posts using hashtags as a supervised signal. The proposed approach is trained on up to 5.5 billion words predicting 100,000 possible hashtags. As well as strong performance on the hashtag prediction task itself, we show that its learned representation of text (ignoring the hashtag labels) is useful for other tasks as well. To that end, we present results on a document recommendation task, where it also outperforms a number of baselines.',

    'tgt': 'A convolutional neural network model for predicting hashtags was proposed in REF .',

    'paper_id': '14697143',

    'title': '#TagSpace: Semantic Embeddings from Hashtags',

    'discipline': {
        'venue': 'EMNLP',
        'journal': None,
        'mag_field_of_study': ['Computer Science']
        }
}

Using the dataset

from datasets import load_dataset

ds = load_dataset("yuningm/citesum")

Data location

https://drive.google.com/file/d/1ndHCREXGSPnDUNllladh9qCtayqbXAfJ/view

Downloads last month: 12

Size of downloaded dataset files:

60.9 MB

Size of the auto-converted Parquet files:

99.7 MB

Number of rows:

92,946

Models trained or fine-tuned on yuningm/citesum

Paper for yuningm/citesum

CiteSum: Citation Text-guided Scientific Extreme Summarization and Domain Adaptation with Limited Supervision

Paper • 2205.06207 • Published May 12, 2022 • 1