Split (2)

train · 433k rows

id stringlengths 9 16	title stringlengths 4 278	abstract stringlengths 3 4.08k	cs.HC bool 2 classes	cs.CE bool 2 classes	cs.SD bool 2 classes	cs.SI bool 2 classes	cs.AI bool 2 classes	cs.IR bool 2 classes	cs.LG bool 2 classes	cs.RO bool 2 classes	cs.CL bool 2 classes	cs.IT bool 2 classes	cs.SY bool 2 classes	cs.CV bool 2 classes	cs.CR bool 2 classes	cs.CY bool 2 classes	cs.MA bool 2 classes	cs.NE bool 2 classes	cs.DB bool 2 classes	Other bool 2 classes	__index_level_0__ int64 0 541k
2410.20579	Toward Conditional Distribution Calibration in Survival Prediction	Survival prediction often involves estimating the time-to-event distribution from censored datasets. Previous approaches have focused on enhancing discrimination and marginal calibration. In this paper, we highlight the significance of conditional calibration for real-world applications -- especially its role in indivi...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	502,870
2310.13627	Deep-Learning-based Change Detection with Spaceborne Hyperspectral PRISMA data	Change detection (CD) methods have been applied to optical data for decades, while the use of hyperspectral data with a fine spectral resolution has been rarely explored. CD is applied in several sectors, such as environmental monitoring and disaster management. Thanks to the PRecursore IperSpettrale della Missione ope...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	401,519
2207.09054	Towards a Low-SWaP 1024-beam Digital Array: A 32-beam Sub-system at 5.8 GHz	Millimeter wave communications require multibeam beamforming in order to utilize wireless channels that suffer from obstructions, path loss, and multi-path effects. Digital multibeam beamforming has maximum degrees of freedom compared to analog phased arrays. However, circuit complexity and power consumption are import...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	308,771
1505.05561	Why Regularized Auto-Encoders learn Sparse Representation?	While the authors of Batch Normalization (BN) identify and address an important problem involved in training deep networks-- \textit{Internal Covariate Shift}-- the current solution has certain drawbacks. For instance, BN depends on batch statistics for layerwise input normalization during training which makes the esti...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	43,315
2502.10492	Multi-view 3D surface reconstruction from SAR images by inverse rendering	3D reconstruction of a scene from Synthetic Aperture Radar (SAR) images mainly relies on interferometric measurements, which involve strict constraints on the acquisition process. These last years, progress in deep learning has significantly advanced 3D reconstruction from multiple views in optical imaging, mainly thro...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	533,917
1905.13388	Design Light-weight 3D Convolutional Networks for Video Recognition Temporal Residual, Fully Separable Block, and Fast Algorithm	Deep 3-dimensional (3D) Convolutional Network (ConvNet) has shown promising performance on video recognition tasks because of its powerful spatio-temporal information fusion ability. However, the extremely intensive requirements on memory access and computing power prohibit it from being used in resource-constrained sc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	133,107
2410.04386	Data Distribution Valuation	Data valuation is a class of techniques for quantitatively assessing the value of data for applications like pricing in data marketplaces. Existing data valuation methods define a value for a discrete dataset. However, in many use cases, users are interested in not only the value of the dataset, but that of the distrib...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	495,262
2311.12437	Learning Site-specific Styles for Multi-institutional Unsupervised Cross-modality Domain Adaptation	Unsupervised cross-modality domain adaptation is a challenging task in medical image analysis, and it becomes more challenging when source and target domain data are collected from multiple institutions. In this paper, we present our solution to tackle the multi-institutional unsupervised domain adaptation for the cros...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	409,336
2207.00735	Can Language Models Make Fun? A Case Study in Chinese Comical Crosstalk	Language is the principal tool for human communication, in which humor is one of the most attractive parts. Producing natural language like humans using computers, a.k.a, Natural Language Generation (NLG), has been widely used for dialogue systems, chatbots, machine translation, as well as computer-aid creation e.g., i...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	305,868
2011.01060	Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps	A multi-hop question answering (QA) dataset aims to test reasoning and inference skills by requiring a model to read multiple paragraphs to answer a given question. However, current datasets do not provide a complete explanation for the reasoning process from the question to the answer. Further, previous studies reveal...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	204,470
2106.13066	Shallow Representation is Deep: Learning Uncertainty-aware and Worst-case Random Feature Dynamics	Random features is a powerful universal function approximator that inherits the theoretical rigor of kernel methods and can scale up to modern learning tasks. This paper views uncertain system models as unknown or uncertain smooth functions in universal reproducing kernel Hilbert spaces. By directly approximating the o...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	242,951
2102.07350	Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigm	Prevailing methods for mapping large generative language models to supervised tasks may fail to sufficiently probe models' novel capabilities. Using GPT-3 as a case study, we show that 0-shot prompts can significantly outperform few-shot prompts. We suggest that the function of few-shot examples in these cases is bette...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	220,079
2302.03375	Transfer learning for process design with reinforcement learning	Process design is a creative task that is currently performed manually by engineers. Artificial intelligence provides new potential to facilitate process design. Specifically, reinforcement learning (RL) has shown some success in automating process design by integrating data-driven models that learn to build process fl...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	344,318
2401.03536	Clique counts for network similarity	Counts of small subgraphs, or graphlet counts, are widely applicable to measure graph similarity. Computing graphlet counts can be computationally expensive and may pose obstacles in network analysis. We study the role of cliques in graphlet counts as a method for graph similarity in social networks. Higher-order clust...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	420,141
2407.01571	Interpretable DRL-based Maneuver Decision of UCAV Dogfight	This paper proposes a three-layer unmanned combat aerial vehicle (UCAV) dogfight frame where Deep reinforcement learning (DRL) is responsible for high-level maneuver decision. A four-channel low-level control law is firstly constructed, followed by a library containing eight basic flight maneuvers (BFMs). Double deep Q...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	469,363
2108.08887	Risk Bounds and Calibration for a Smart Predict-then-Optimize Method	The predict-then-optimize framework is fundamental in practical stochastic decision-making problems: first predict unknown parameters of an optimization model, then solve the problem using the predicted values. A natural loss function in this setting is defined by measuring the decision error induced by the predicted p...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	251,420
2004.06803	Probabilistic Evolution of Stochastic Dynamical Systems: A Meso-scale Perspective	Stochastic dynamical systems arise naturally across nearly all areas of science and engineering. Typically, a dynamical system model is based on some prior knowledge about the underlying dynamics of interest in which probabilistic features are used to quantify and propagate uncertainties associated with the initial con...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	172,606
2205.05126	A Meta-Analysis of the Utility of Explainable Artificial Intelligence in Human-AI Decision-Making	Research in artificial intelligence (AI)-assisted decision-making is experiencing tremendous growth with a constantly rising number of studies evaluating the effect of AI with and without techniques from the field of explainable AI (XAI) on human decision-making performance. However, as tasks and experimental setups va...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	295,845
2403.12920	Semantic Layering in Room Segmentation via LLMs	In this paper, we introduce Semantic Layering in Room Segmentation via LLMs (SeLRoS), an advanced method for semantic room segmentation by integrating Large Language Models (LLMs) with traditional 2D map-based segmentation. Unlike previous approaches that solely focus on the geometric segmentation of indoor environment...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	439,388
1312.1760	Towards Normalizing the Edit Distance Using a Genetic Algorithms Based Scheme	The normalized edit distance is one of the distances derived from the edit distance. It is useful in some applications because it takes into account the lengths of the two strings compared. The normalized edit distance is not defined in terms of edit operations but rather in terms of the edit path. In this paper we pro...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	28,887
2403.13466	An AI-Assisted Skincare Routine Recommendation System in XR	In recent years, there has been an increasing interest in the use of artificial intelligence (AI) and extended reality (XR) in the beauty industry. In this paper, we present an AI-assisted skin care recommendation system integrated into an XR platform. The system uses a convolutional neural network (CNN) to analyse an ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	439,645
1911.12275	Fooling with facts: Quantifying anchoring bias through a large-scale online experiment	Living in the 'Information Age' means that not only access to information has become easier but also that the distribution of information is more dynamic than ever. Through a large-scale online field experiment, we provide new empirical evidence for the presence of the anchoring bias in people's judgment due to irratio...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	155,355
2106.15893	Fast whole-slide cartography in colon cancer histology using superpixels and CNN classification	Automatic outlining of different tissue types in digitized histological specimen provides a basis for follow-up analyses and can potentially guide subsequent medical decisions. The immense size of whole-slide-images (WSI), however, poses a challenge in terms of computation time. In this regard, the analysis of non-over...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	243,907
1608.00859	Temporal Segment Networks: Towards Good Practices for Deep Action Recognition	Deep convolutional networks have achieved great success for visual recognition in still images. However, for action recognition in videos, the advantage over traditional methods is not so evident. This paper aims to discover the principles to design effective ConvNet architectures for action recognition in videos and l...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	59,353
2202.03670	How to Understand Masked Autoencoders	"Masked Autoencoders (MAE) Are Scalable Vision Learners" revolutionizes the self-supervised learning method in that it not only achieves the state-of-the-art for image pre-training, but is also a milestone that bridges the gap between visual and linguistic masked autoencoding (BERT-style) pre-trainings. However, to our...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	279,297
2105.06086	HINet: Half Instance Normalization Network for Image Restoration	In this paper, we explore the role of Instance Normalization in low-level vision tasks. Specifically, we present a novel block: Half Instance Normalization Block (HIN Block), to boost the performance of image restoration networks. Based on HIN Block, we design a simple and powerful multi-stage network named HINet, whic...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	235,018
1709.05168	Crowdsourcing Paper Screening in Systematic Literature Reviews	Literature reviews allow scientists to stand on the shoulders of giants, showing promising directions, summarizing progress, and pointing out existing challenges in research. At the same time conducting a systematic literature review is a laborious and consequently expensive process. In the last decade, there have a fe...	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	80,799
1909.10772	Technical report on Conversational Question Answering	Conversational Question Answering is a challenging task since it requires understanding of conversational history. In this project, we propose a new system RoBERTa + AT +KD, which involves rationale tagging multi-task, adversarial training, knowledge distillation and a linguistic post-process strategy. Our single model...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	146,626
1907.09328	A Conceptual Framework for Evaluating Fairness in Search	While search efficacy has been evaluated traditionally on the basis of result relevance, fairness of search has attracted recent attention. In this work, we define a notion of distributional fairness and provide a conceptual framework for evaluating search results based on it. As part of this, we formulate a set of axi...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	139,334
2403.17774	Towards Over-Canopy Autonomous Navigation: Crop-Agnostic LiDAR-Based Crop-Row Detection in Arable Fields	Autonomous navigation is crucial for various robotics applications in agriculture. However, many existing methods depend on RTK-GPS devices, which can be susceptible to loss of radio signal or intermittent reception of corrections from the internet. Consequently, research has increasingly focused on using RGB cameras f...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	441,618
2104.07423	The Role of Context in Detecting Previously Fact-Checked Claims	Recent years have seen the proliferation of disinformation and fake news online. Traditional approaches to mitigate these issues is to use manual or automatic fact-checking. Recently, another approach has emerged: checking whether the input claim has previously been fact-checked, which can be done automatically, and th...	false	false	false	false	true	true	true	false	true	false	false	false	false	false	false	true	false	false	230,413
1911.04227	Cumulo: A Dataset for Learning Cloud Classes	One of the greatest sources of uncertainty in future climate projections comes from limitations in modelling clouds and in understanding how different cloud types interact with the climate system. A key first step in reducing this uncertainty is to accurately classify cloud types at high spatial and temporal resolution...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	152,931
1912.10561	A Survey of NOMA: Current Status and Open Research Challenges	Non-orthogonal multiple access (NOMA) has been considered as a study-item in 3GPP for 5G new radio (NR). However, it was decided not to continue with it as a work-item, and to leave it for possible use in beyond 5G. In this paper, we first review the discussions that ended in such decision. Particularly, we present sim...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	158,352
2305.10928	Multilingual Event Extraction from Historical Newspaper Adverts	NLP methods can aid historians in analyzing textual materials in greater volumes than manually feasible. Developing such methods poses substantial challenges though. First, acquiring large, annotated historical datasets is difficult, as only domain experts can reliably label them. Second, most available off-the-shelf N...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	365,296
2312.09082	Learned Fusion: 3D Object Detection using Calibration-Free Transformer Feature Fusion	The state of the art in 3D object detection using sensor fusion heavily relies on calibration quality, which is difficult to maintain in large scale deployment outside a lab environment. We present the first calibration-free approach for 3D object detection. Thus, eliminating the need for complex and costly calibration...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	415,596
2211.09295	Testing for context-dependent changes in neural encoding in naturalistic experiments	We propose a decoding-based approach to detect context effects on neural codes in longitudinal neural recording data. The approach is agnostic to how information is encoded in neural activity, and can control for a variety of possible confounding factors present in the data. We demonstrate our approach by determining w...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	330,927
2301.03826	CDA: Contrastive-adversarial Domain Adaptation	Recent advances in domain adaptation reveal that adversarial learning on deep neural networks can learn domain invariant features to reduce the shift between source and target domains. While such adversarial approaches achieve domain-level alignment, they ignore the class (label) shift. When class-conditional data dist...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	339,899
2306.04099	NTKCPL: Active Learning on Top of Self-Supervised Model by Estimating True Coverage	High annotation cost for training machine learning classifiers has driven extensive research in active learning and self-supervised learning. Recent research has shown that in the context of supervised learning different active learning strategies need to be applied at various stages of the training process to ensure i...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	371,603
1910.03090	Instagram Fake and Automated Account Detection	Fake engagement is one of the significant problems in Online Social Networks (OSNs) which is used to increase the popularity of an account in an inorganic manner. The detection of fake engagement is crucial because it leads to loss of money for businesses, wrong audience targeting in advertising, wrong product predicti...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	148,408
1909.01716	ScisummNet: A Large Annotated Corpus and Content-Impact Models for Scientific Paper Summarization with Citation Networks	Scientific article summarization is challenging: large, annotated corpora are not available, and the summary should ideally include the article's impacts on research community. This paper provides novel solutions to these two challenges. We 1) develop and release the first large-scale manually-annotated corpus for scie...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	143,979
2211.10583	An Information-State Based Approach to Linear Time Varying System Identification and Control	This paper considers the problem of system identification for linear time varying systems. We propose a new system realization approach that uses an "information-state" as the state vector, where the "information-state" is composed of a finite number of past inputs and outputs. The system identification algorithm uses ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	331,355
2109.11690	Discovering and Validating AI Errors With Crowdsourced Failure Reports	AI systems can fail to learn important behaviors, leading to real-world issues like safety concerns and biases. Discovering these systematic failures often requires significant developer attention, from hypothesizing potential edge cases to collecting evidence and validating patterns. To scale and streamline this proce...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	257,023
1602.07362	The Possibilities and Limitations of Private Prediction Markets	We consider the design of private prediction markets, financial markets designed to elicit predictions about uncertain events without revealing too much information about market participants' actions or beliefs. Our goal is to design market mechanisms in which participants' trades or wagers influence the market's behav...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	52,499
2310.05597	Can language models learn analogical reasoning? Investigating training objectives and comparisons to human performance	While analogies are a common way to evaluate word embeddings in NLP, it is also of interest to investigate whether or not analogical reasoning is a task in itself that can be learned. In this paper, we test several ways to learn basic analogical reasoning, specifically focusing on analogies that are more typical of wha...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	398,216
2212.01215	Olive Branch Learning: A Topology-Aware Federated Learning Framework for Space-Air-Ground Integrated Network	The space-air-ground integrated network (SAGIN), one of the key technologies for next-generation mobile communication systems, can facilitate data transmission for users all over the world, especially in some remote areas where vast amounts of informative data are collected by Internet of remote things (IoRT) devices t...	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	true	334,348
1901.00461	A CNN adapted to time series for the classification of Supernovae	Cosmologists are facing the problem of the analysis of a huge quantity of data when observing the sky. The methods used in cosmology are, for the most of them, relying on astrophysical models, and thus, for the classification, they usually use a machine learning approach in two-steps, which consists in, first, extracti...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	117,782
2303.08319	FAQ: Feature Aggregated Queries for Transformer-based Video Object Detectors	Video object detection needs to solve feature degradation situations that rarely happen in the image domain. One solution is to use the temporal information and fuse the features from the neighboring frames. With Transformerbased object detectors getting a better performance on the image domain tasks, recent works bega...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	351,595
2303.06637	Integrated Communication and Receiver Sensing with Security Constraints on Message and State	We study the state-dependent wiretap channel with non-causal channel state informations at the encoder in an integrated sensing and communications (ISAC) scenario. In this scenario, the transmitter communicates a message and a state sequence to a legitimate receiver while keeping the message and state-information secre...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	350,933
2010.13515	Syllabification of the Divine Comedy	We provide a syllabification algorithm for the Divine Comedy using techniques from probabilistic and constraint programming. We particularly focus on the synalephe, addressed in terms of the "propensity" of a word to take part in a synalephe with adjacent words. We jointly provide an online vocabulary containing, for e...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	203,161
2401.04631	Deep Reinforcement Multi-agent Learning framework for Information Gathering with Local Gaussian Processes for Water Monitoring	The conservation of hydrological resources involves continuously monitoring their contamination. A multi-agent system composed of autonomous surface vehicles is proposed in this paper to efficiently monitor the water quality. To achieve a safe control of the fleet, the fleet policy should be able to act based on measur...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	420,489
2203.17002	Conditional Autoregressors are Interpretable Classifiers	We explore the use of class-conditional autoregressive (CA) models to perform image classification on MNIST-10. Autoregressive models assign probability to an entire input by combining probabilities from each individual feature; hence classification decisions made by a CA can be readily decomposed into contributions fr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	289,006
1904.13216	Signal2Image Modules in Deep Neural Networks for EEG Classification	Deep learning has revolutionized computer vision utilizing the increased availability of big data and the power of parallel computational units such as graphical processing units. The vast majority of deep learning research is conducted using images as training data, however the biomedical domain is rich in physiologic...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	129,327
2412.09784	Semi-IIN: Semi-supervised Intra-inter modal Interaction Learning Network for Multimodal Sentiment Analysis	Despite multimodal sentiment analysis being a fertile research ground that merits further investigation, current approaches take up high annotation cost and suffer from label ambiguity, non-amicable to high-quality labeled data acquisition. Furthermore, choosing the right interactions is essential because the significa...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	516,641
1203.3621	Robustness of correlated networks against propagating attacks	We investigate robustness of correlated networks against propagating attacks modeled by a susceptible-infected-removed model. By Monte-Carlo simulations, we numerically determine the first critical infection rate, above which a global outbreak of disease occurs, and the second critical infection rate, above which disea...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	14,990
2012.03763	Using previous acoustic context to improve Text-to-Speech synthesis	Many speech synthesis datasets, especially those derived from audiobooks, naturally comprise sequences of utterances. Nevertheless, such data are commonly treated as individual, unordered utterances both when training a model and at inference time. This discards important prosodic phenomena above the utterance level. I...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	210,244
2102.06112	A Metamodel and Framework for Artificial General Intelligence From Theory to Practice	This paper introduces a new metamodel-based knowledge representation that significantly improves autonomous learning and adaptation. While interest in hybrid machine learning / symbolic AI systems leveraging, for example, reasoning and knowledge graphs, is gaining popularity, we find there remains a need for both a cle...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	219,643
2112.13637	Self-normalized Classification of Parkinson's Disease DaTscan Images	Classifying SPECT images requires a preprocessing step which normalizes the images using a normalization region. The choice of the normalization region is not standard, and using different normalization regions introduces normalization region-dependent variability. This paper mathematically analyzes the effect of the n...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	273,314
1705.09993	Deep Learning for User Comment Moderation	Experimenting with a new dataset of 1.6M user comments from a Greek news portal and existing datasets of English Wikipedia comments, we show that an RNN outperforms the previous state of the art in moderation. A deep, classification-specific attention mechanism improves further the overall performance of the RNN. We al...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	74,319
2210.16985	Space-time design for deep joint source channel coding of images Over MIMO channels	We propose novel deep joint source-channel coding (DeepJSCC) algorithms for wireless image transmission over multi-input multi-output (MIMO) Rayleigh fading channels, when channel state information (CSI) is available only at the receiver. We consider two different schemes; one exploiting the spatial diversity and the o...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	327,526
1712.09520	Tensor Regression Networks with various Low-Rank Tensor Approximations	Tensor regression networks achieve high compression rate of neural networks while having slight impact on performances. They do so by imposing low tensor rank structure on the weight matrices of fully connected layers. In recent years, tensor regression networks have been investigated from the perspective of their comp...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	87,367
2401.08878	A Survey on Hypergraph Mining: Patterns, Tools, and Generators	Hypergraphs, which belong to the family of higher-order networks, are a natural and powerful choice for modeling group interactions in the real world. For example, when modeling collaboration networks, which may involve not just two but three or more people, the use of hypergraphs allows us to explore beyond pairwise (...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	false	422,058
2404.03159	HandDiff: 3D Hand Pose Estimation with Diffusion on Image-Point Cloud	Extracting keypoint locations from input hand frames, known as 3D hand pose estimation, is a critical task in various human-computer interaction applications. Essentially, the 3D hand pose estimation can be regarded as a 3D point subset generative problem conditioned on input frames. Thanks to the recent significant pr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	444,140
2101.07994	Distributed Motion Coordination Using Convex Feasible Set Based Model Predictive Control	The implementation of optimization-based motion coordination approaches in real world multi-agent systems remains challenging due to their high computational complexity and potential deadlocks. This paper presents a distributed model predictive control (MPC) approach based on convex feasible set (CFS) algorithm for mul...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	216,197
1506.04356	The Artists who Forged Themselves: Detecting Creativity in Art	Creativity and the understanding of cognitive processes involved in the creative process are relevant to all of human activities. Comprehension of creativity in the arts is of special interest due to the involvement of many scientific and non scientific disciplines. Using digital representation of paintings, we show th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	44,158
2303.06586	Proactive Prioritization of App Issues via Contrastive Learning	Mobile app stores produce a tremendous amount of data in the form of user reviews, which is a huge source of user requirements and sentiments; such reviews allow app developers to proactively address issues in their apps. However, only a small number of reviews capture common issues and sentiments which creates a need ...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	true	350,912
2302.04664	Algebraic characterizations of least model and uniform equivalence of propositional Krom logic programs	This research note provides algebraic characterizations of the least model, subsumption, and uniform equivalence of propositional Krom logic programs.	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	344,776
2310.03147	Context-Based Tweet Engagement Prediction	Twitter is currently one of the biggest social media platforms. Its users may share, read, and engage with short posts called tweets. For the ACM Recommender Systems Conference 2020, Twitter published a dataset around 70 GB in size for the annual RecSys Challenge. In 2020, the RecSys Challenge invited participating tea...	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	false	397,152
1908.03477	Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings	We address the problem of cross-modal fine-grained action retrieval between text and video. Cross-modal retrieval is commonly achieved through learning a shared embedding space, that can indifferently embed modalities. In this paper, we propose to enrich the embedding by disentangling parts-of-speech (PoS) in the accom...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	141,248
2211.08112	An Efficient Active Learning Pipeline for Legal Text Classification	Active Learning (AL) is a powerful tool for learning with less labeled data, in particular, for specialized domains, like legal documents, where unlabeled data is abundant, but the annotation requires domain expertise and is thus expensive. Recent works have shown the effectiveness of AL strategies for pre-trained lang...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	330,484
2412.15101	Review-Then-Refine: A Dynamic Framework for Multi-Hop Question Answering with Temporal Adaptability	Retrieve-augmented generation (RAG) frameworks have emerged as a promising solution to multi-hop question answering(QA) tasks since it enables large language models (LLMs) to incorporate external knowledge and mitigate their inherent knowledge deficiencies. Despite this progress, existing RAG frameworks, which usually ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	518,943
2305.11046	Difference of Submodular Minimization via DC Programming	Minimizing the difference of two submodular (DS) functions is a problem that naturally occurs in various machine learning problems. Although it is well known that a DS problem can be equivalently formulated as the minimization of the difference of two convex (DC) functions, existing algorithms do not fully exploit this...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	365,356
2112.03407	Causal Analysis and Classification of Traffic Crash Injury Severity Using Machine Learning Algorithms	Causal analysis and classification of injury severity applying non-parametric methods for traffic crashes has received limited attention. This study presents a methodological framework for causal inference, using Granger causality analysis, and injury severity classification of traffic crashes, occurring on interstates...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	270,187
1909.00986	Certified Robustness to Adversarial Word Substitutions	State-of-the-art NLP models can often be fooled by adversaries that apply seemingly innocuous label-preserving transformations (e.g., paraphrasing) to input text. The number of possible transformations scales exponentially with text length, so data augmentation cannot cover all transformations of an input. This paper c...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	143,775
2403.09355	Mitigating Data Consistency Induced Discrepancy in Cascaded Diffusion Models for Sparse-view CT Reconstruction	Sparse-view Computed Tomography (CT) image reconstruction is a promising approach to reduce radiation exposure, but it inevitably leads to image degradation. Although diffusion model-based approaches are computationally expensive and suffer from the training-sampling discrepancy, they provide a potential solution to th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	437,734
1702.06334	Synthesizing Imperative Programs from Examples Guided by Static Analysis	We present a novel algorithm that synthesizes imperative programs for introductory programming courses. Given a set of input-output examples and a partial program, our algorithm generates a complete program that is consistent with every example. Our key idea is to combine enumerative program synthesis and static analys...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	68,582
2108.10617	Image-free single-pixel segmentation	The existing segmentation techniques require high-fidelity images as input to perform semantic segmentation. Since the segmentation results contain most of edge information that is much less than the acquired images, the throughput gap leads to both hardware and software waste. In this letter, we report an image-free s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	251,953
2404.08558	Safe Start Regions for Medical Steerable Needle Automation	Steerable needles are minimally invasive devices that enable novel medical procedures by following curved paths to avoid critical anatomical obstacles. Planning algorithms can be used to find a steerable needle motion plan to a target. Deployment typically consists of a physician manually inserting the steerable needle...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	446,288
2306.09916	Calculation of the transient response of lossless transmission lines	We present an analytical calculation of the transient response of ideal (i.e. lossless) transmission lines. The calculation presented considers a length of transmission line connected to a signal generator with output impedance $Z_\mathrm{g}$ and terminated with a load impedance $Z_\mathrm{L}$. The approach taken is to...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	374,016
2010.01251	UCP: Uniform Channel Pruning for Deep Convolutional Neural Networks Compression and Acceleration	To apply deep CNNs to mobile terminals and portable devices, many scholars have recently worked on the compressing and accelerating deep convolutional neural networks. Based on this, we propose a novel uniform channel pruning (UCP) method to prune deep CNN, and the modified squeeze-and-excitation blocks (MSEB) is used ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	198,579
2209.14743	Dataset Complexity Assessment Based on Cumulative Maximum Scaled Area Under Laplacian Spectrum	Dataset complexity assessment aims to predict classification performance on a dataset with complexity calculation before training a classifier, which can also be used for classifier selection and dataset reduction. The training process of deep convolutional neural networks (DCNNs) is iterative and time-consuming becaus...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	320,338
2308.00008	Interpolation-Split: a data-centric deep learning approach with big interpolated data to boost airway segmentation performance	The morphology and distribution of airway tree abnormalities enables diagnosis and disease characterisation across a variety of chronic respiratory conditions. In this regard, airway segmentation plays a critical role in the production of the outline of the entire airway tree to enable estimation of disease extent and ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	382,784
2405.03995	Deep Event-based Object Detection in Autonomous Driving: A Survey	Object detection plays a critical role in autonomous driving, where accurately and efficiently detecting objects in fast-moving scenes is crucial. Traditional frame-based cameras face challenges in balancing latency and bandwidth, necessitating the need for innovative solutions. Event cameras have emerged as promising ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	452,400
1503.00075	Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks	Because of their superior ability to preserve sequence information over time, Long Short-Term Memory (LSTM) networks, a type of recurrent neural network with a more complex computational unit, have obtained strong results on a variety of sequence modeling tasks. The only underlying LSTM structure that has been explored...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	40,658
1801.02832	Biomedical Question Answering via Weighted Neural Network Passage Retrieval	The amount of publicly available biomedical literature has been growing rapidly in recent years, yet question answering systems still struggle to exploit the full potential of this source of data. In a preliminary processing step, many question answering systems rely on retrieval models for identifying relevant documen...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	87,995
2204.04611	Decay No More: A Persistent Twitter Dataset for Learning Social Meaning	With the proliferation of social media, many studies resort to social media to construct datasets for developing social meaning understanding systems. For the popular case of Twitter, most researchers distribute tweet IDs without the actual text contents due to the data distribution policy of the platform. One issue is...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	290,714
2406.19320	Efficient World Models with Context-Aware Tokenization	Scaling up deep Reinforcement Learning (RL) methods presents a significant challenge. Following developments in generative modelling, model-based RL positions itself as a strong contender. Recent advances in sequence modelling have led to effective transformer-based world models, albeit at the price of heavy computatio...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	468,380
1812.02690	Provably Efficient Maximum Entropy Exploration	Suppose an agent is in a (possibly unknown) Markov Decision Process in the absence of a reward signal, what might we hope that an agent can efficiently learn to do? This work studies a broad class of objectives that are defined solely as functions of the state-visitation frequencies that are induced by how the agent be...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	115,827
2002.03140	HHH: An Online Medical Chatbot System based on Knowledge Graph and Hierarchical Bi-Directional Attention	This paper proposes a chatbot framework that adopts a hybrid model which consists of a knowledge graph and a text similarity model. Based on this chatbot framework, we build HHH, an online question-and-answer (QA) Healthcare Helper system for answering complex medical questions. HHH maintains a knowledge graph construc...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	163,148
2304.02931	Mask Detection and Classification in Thermal Face Images	Face masks are recommended to reduce the transmission of many viruses, especially SARS-CoV-2. Therefore, the automatic detection of whether there is a mask on the face, what type of mask is worn, and how it is worn is an important research topic. In this work, the use of thermal imaging was considered to analyze the po...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	356,611
2207.14336	Data centers with quantum random access memory and quantum networks	In this paper, we propose the Quantum Data Center (QDC), an architecture combining Quantum Random Access Memory (QRAM) and quantum networks. We give a precise definition of QDC, and discuss its possible realizations and extensions. We discuss applications of QDC in quantum computation, quantum communication, and quantu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	310,546
2410.09086	AI in Archival Science -- A Systematic Review	The rapid expansion of records creates significant challenges in management, including retention and disposition, appraisal, and organization. Our study underscores the benefits of integrating artificial intelligence (AI) within the broad realm of archival science. In this work, we start by performing a thorough analys...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	497,425
2312.09402	CERN for AI: A Theoretical Framework for Autonomous Simulation-Based Artificial Intelligence Testing and Alignment	This paper explores the potential of a multidisciplinary approach to testing and aligning artificial intelligence (AI), specifically focusing on large language models (LLMs). Due to the rapid development and wide application of LLMs, challenges such as ethical alignment, controllability, and predictability of these mod...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	true	415,699
2311.11756	LSTM-CNN: An efficient diagnostic network for Parkinson's disease utilizing dynamic handwriting analysis	Background and objectives: Dynamic handwriting analysis, due to its non-invasive and readily accessible nature, has recently emerged as a vital adjunctive method for the early diagnosis of Parkinson's disease. In this study, we design a compact and efficient network architecture to analyse the distinctive handwriting p...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	409,062
2306.16285	Generalizing Surgical Instruments Segmentation to Unseen Domains with One-to-Many Synthesis	Despite their impressive performance in various surgical scene understanding tasks, deep learning-based methods are frequently hindered from deploying to real-world surgical applications for various causes. Particularly, data collection, annotation, and domain shift in-between sites and patients are the most common obs...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	376,330
2409.12817	Automated Linear Disturbance Mapping via Semantic Segmentation of Sentinel-2 Imagery	In Canada's northern regions, linear disturbances such as roads, seismic exploration lines, and pipelines pose a significant threat to the boreal woodland caribou population (Rangifer tarandus). To address the critical need for management of these disturbances, there is a strong emphasis on developing mapping approache...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	489,733
2204.06815	deep-significance - Easy and Meaningful Statistical Significance Testing in the Age of Neural Networks	A lot of Machine Learning (ML) and Deep Learning (DL) research is of an empirical nature. Nevertheless, statistical significance testing (SST) is still not widely used. This endangers true progress, as seeming improvements over a baseline might be statistical flukes, leading follow-up research astray while wasting huma...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	291,456
2404.00548	Modeling State Shifting via Local-Global Distillation for Event-Frame Gaze Tracking	This paper tackles the problem of passive gaze estimation using both event and frame data. Considering the inherently different physiological structures, it is intractable to accurately estimate gaze purely based on a given state. Thus, we reformulate gaze estimation as the quantification of the state shifting from the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	442,985
2304.03483	RED-PSM: Regularization by Denoising of Factorized Low Rank Models for Dynamic Imaging	Dynamic imaging addresses the recovery of a time-varying 2D or 3D object at each time instant using its undersampled measurements. In particular, in the case of dynamic tomography, only a single projection at a single view angle may be available at a time, making the problem severely ill-posed. We propose an approach, ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	356,826
1701.04350	An Object-oriented approach to Robotic planning using Taxi domain	This paper aims to implement Object-Oriented Markov Decision Process (OO-MDPs) for goal planning and navigation of robot in an indoor environment. We use the OO-MDP representation of the environment which is a natural way of modeling the environment based on objects and their interactions. The paper aims to extend the ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	66,846
2411.02710	Full Field Digital Mammography Dataset from a Population Screening Program	Breast cancer presents the second largest cancer risk in the world to women. Early detection of cancer has been shown to be effective in reducing mortality. Population screening programs schedule regular mammography imaging for participants, promoting early detection. Currently, such screening programs require manual r...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	505,626

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